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USING TIME-LAPSE SEISMIC MEASUREMENTS TO

IMPROVE FLOW MODELING OF CO2 INJECTION

IN THE WEYBURN FIELD: A NATURALLY

FRACTURED, LAYERED RESERVOIR

by

Hirofumi Yamamoto

A thesis submitted to the Faculty and the Board of Trustees of the Colorado

School of Mines in partial fulfillment of the requirements for the degree of Doctor of

Philosophy (Petroleum Engineering).

Golden, Colorado

Date _______________

Signed: ________________________ Hirofumi Yamamoto

Approved: _________________________ Dr. John R. Fanchi Thesis Advisor

Golden, Colorado

Date _______________

________________________________

Dr. Craig W. Van Kirk Professor and Head Department of Petroleum Engineering

ii

ABSTRACT

The Reservoir Characterization Project, RCP, has conducted a time-lapse seismic

survey in a section of the Weyburn Field, Saskatchewan, Canada, which is operated by

EnCana. The section is being subjected to an enhanced oil recovery process that began in

October 2000. Weyburn has two major reservoir units; the upper unit is the Marly

dolomite with high porosity and low permeability, and the lower unit is the Vuggy

limestone with low porosity and high permeability. Both units are naturally fractured,

but the Vuggy is more fractured than Marly.

The EOR process in the RCP section of the Weyburn Field uses CO2 and water

injection to displace oil that is remaining after waterflood. The first 3-D, 9C seismic

survey was shot before the start of the EOR project. The second and third seismic

surveys were conducted one year and two years later, respectively. The latter seismic

surveys provide information about the location of injected fluids, particularly CO2.

Time lapse seismic monitoring has motivated changes to the reservoir description

in a flow model. Field history was originally matched in a compositional model up to the

beginning of CO2 injection. Changes to the P-impedance between the first baseline

survey and the first monitoring survey indicated the location of the CO2 front. The P-

impedance was used as a history match constraint. Using properties from the

compositional simulation model, the P-impedance was calculated using Gassmann’s

theory with appropriate modifications to make the theory suitable for the area of interest.

The calculated P-impedance was then compared to the observed P-impedance.

Adjustments were made to the reservoir description to minimize the difference between

calculated and observed P-impedance values while simultaneously matching the entire

production history. The production history in this case includes primary depletion,

iii

waterflooding, and the first year of the EOR process. This thesis describes the results of

this integrated study.

A new waterflood history match was built by matching the timing of water

breakthrough in the on-trend and off-trend wells in the South and East patterns. Then,

the simulation was extended to the CO2 injection period. The conceptual model study

showed that the high vertical permeability associated with existing vertical fractures

plays a significant role in the CO2 injection process. The P-impedance was calculated

based on the simulation results from the CO2 injection period and compared to the

observed P-impedance changes, which clearly showed the movement of injected CO2.

The time-lapse P-impedance data helped identify details of fluid movement, such as

vertical distribution of CO2 and possible injection intervals beside the branches of

horizontal wells.

An objective function (OF) was calculated to measure the proximity of the

observed and calculated P-impedance values. The OF in the Marly formation was

reduced relative to the EnCana model performance in both the South and East patterns.

For the Vuggy formation, the OF increased slightly. The relative OF that includes both

the P-impedance and production data was calculated by using EnCana’s case as a base

case. The relative OF shows the overall improvement of the flow simulation model.

This research successfully demonstrated that time-lapse P-impedance data helped

improve the existing flow model and provided valuable information that other data did

not.

iv

TABLE OF CONTENTS

ABSTRACT....................................................................................................................... iii

LIST OF FIGURES ............................................................................................................ x

LIST OF TABLES......................................................................................................... xviii

ACKNOWLEDGEMENTS............................................................................................. xix

Chapter 1 INTRODUCTION.............................................................................................. 1

1.1 Introduction............................................................................................................. 1

1.2 Geologic Overview and Reservoir Properties ........................................................ 2

1.3 Field Development and Production History ........................................................... 7

1.4 Seismic Surveys in Weyburn Field......................................................................... 8

1.5 The Objective of this Research Within RCP ........................................................ 11

Chapter 2 LITERATURE REVIEW................................................................................. 13

2.1 Introduction........................................................................................................... 13

2.2 Reservoir Characterization Using Seismic Data................................................... 13

2.3 Natural Fractures................................................................................................... 16

2.3.1 Core and Log Studies of Midale Formation for Natural Fractures.............. 16

2.3.2 Engineering and Laboratory Studies for Natural Fractures ......................... 18

2.4 Streamline Simulation........................................................................................... 20

2.4.1 Limitations of Streamline Simulation.......................................................... 20

2.5 CO2 for Enhanced Oil Recovery Process ............................................................. 21

Chapter 3 WEYBURN ENHANCED OIL RECOVERY PROJECT............................... 27

3.1 Introduction........................................................................................................... 27

3.2 Summary of Pattern Response.............................................................................. 27

v

3.3 Injection Design in Weyburn Field....................................................................... 28

3.4 CO2 Source ........................................................................................................... 31

3.5 CO2 Sequestration................................................................................................. 31

3.6 CO2 Injection and Production Response............................................................... 32

3.6.1 The South Pattern......................................................................................... 34

3.6.2 The East Pattern ........................................................................................... 37

3.6.3 The West Pattern.......................................................................................... 40

3.6.4 The North Pattern......................................................................................... 41

Chapter 4 ENCANA RESERVOIR SIMULATION MODEL OF WEYBURN.............. 43

4.1 Introduction........................................................................................................... 43

4.2 Summary............................................................................................................... 44

4.3 Reservoir Simulation Model by EnCana .............................................................. 45

4.4 Natural Fractures................................................................................................... 47

4.5 Weyburn Equation of State (EOS) Model ............................................................ 48

4.5.1 Water Density Calculation........................................................................... 49

4.6 Relative Permeability Curves and Endpoints ....................................................... 49

4.7 History Match by EnCana..................................................................................... 51

4.7.1 Waterflood History Match ........................................................................... 53

4.7.1.1 The South Pattern............................................................................. 55

4.7.1.2 The East Pattern ............................................................................... 61

4.7.1.3 The West and North Pattern............................................................. 64

4.7.2 Horizontal Wells History Match.................................................................. 65

4.7.2.1 The South Pattern............................................................................. 65

4.7.2.2 The East Pattern ............................................................................... 68

4.8 Forecast Results of EnCana’s Simulation Model ................................................. 72

4.8.1 The South Pattern......................................................................................... 72

4.8.1.1 Placement of CO2 in the South Pattern ............................................ 72

vi

4.8.2 The East Pattern ........................................................................................... 75

4.8.2.1 Placement of CO2 in the East Pattern .............................................. 75

4.9 Cumulative Production ......................................................................................... 78

Chapter 5 FORWARD MODELING AND P-IMPEDANCE DATA.............................. 81

5.1 Introduction........................................................................................................... 81

5.2 Summary............................................................................................................... 81

5.3 Rock Physics Modeling for Weyburn Field ......................................................... 82

5.4 Computer Program to Calculate P-Impedance from Simulation Results ............. 86

5.5 P-Impedance Value within Simulation Grid Block .............................................. 87

5.6 P-Impedance Change due to CO2 Injection .......................................................... 90

5.7 P-Impedance Data................................................................................................. 92

5.7.1 P-Impedance Change in Marly .................................................................... 93

5.7.2 P-Impedance Change in Vuggy ................................................................... 94

5.8 Objective Function................................................................................................ 96

5.9 P-Impedance calculation....................................................................................... 98

Chapter 6 MECHANISMS AFFECTING THE MOVEMENT OF CO2 IN RESERVOIRS......................................................................................................................................... 101

6.1 Introduction......................................................................................................... 101

6.2 Summary............................................................................................................. 102

6.3 Simulation of Flow Barrier Based on Flow Unit Analysis................................. 102

6.4 Understanding CO2 Movement in the Reservoir ................................................ 110

6.4.1 Is CO2 heavier than oil at reservoir conditions? ........................................ 110

6.4.2 Why would CO2 migrate down into the Vuggy? ....................................... 110

6.4.3 Why would CO2 stay in the Vuggy zone? ................................................. 111

6.5 Vertical Displacement Efficiency....................................................................... 114

Chapter 7 EFFECTS OF NATURAL FRACTURES IN FLUID FLOW....................... 121

vii

7.1 Introduction......................................................................................................... 121

7.2 Summary............................................................................................................. 121

7.3 Dual Continuum Model ...................................................................................... 122

7.4 Dual Porosity Model........................................................................................... 126

7.4.1 Dual Porosity Model with Low Vertical Fracture Permeability................ 127

7.4.2 Dual Porosity Model with Flow Barrier between Marly and Vuggy......... 130

7.4.3 Dual Porosity Model with High Vertical Fracture Permeability ............... 133

Chapter 8 HISTORY MATCHING USING TIME-LAPSE SEISMIC DATA.............. 137

8.1 Introduction......................................................................................................... 137

8.2 Summary............................................................................................................. 137

8.3 Waterflood History Matching............................................................................. 138

8.3.1 On-Trend and Off-Trend Wells ................................................................. 139

8.3.2 Corner Wells .............................................................................................. 144

8.3.3 Relative Permeability Curve for Water...................................................... 145

8.3.4 Horizontal Wells ........................................................................................ 152

8.3.5 Reservoir Pressure ..................................................................................... 154

8.4 Waterflood History Matching to CO2 flood History Matching .......................... 154

8.5 History Matching using 4-D seismic Data.......................................................... 156

8.5.1 The South Pattern....................................................................................... 157

8.5.1.1 Production Match Results .............................................................. 162

8.5.1.2 Objective Function......................................................................... 165

8.5.1.3 Cumulative Production of the South Pattern ................................. 170

8.5.2 East Pattern ................................................................................................ 171

8.5.2.1 Production Match Results .............................................................. 174

8.5.2.2 Objective Function......................................................................... 176

8.5.2.3 Cumulative Production .................................................................. 176

8.5.3 Total Objective Function and Relative Objective Function ...................... 180

viii

Chapter 9 CONCLUSIONS AND RECOMMENDATIONS......................................... 185

9.1 Introduction......................................................................................................... 185

9.1.1 Time-Lapse P-Impedance Data.................................................................. 185

9.1.2 Forward Modeling and Optimization......................................................... 186

9.1.3 Natural Fracture Characterization and Simulation Model ......................... 187

9.1.4 Horizontal CO2 Injectors............................................................................ 188

REFERENCES ............................................................................................................... 191

APPENDIX..................................................................................................................... 197

ix

LIST OF FIGURES

Figure 1.1: Location of Weyburn Field in Saskatchewan, Canada..................................... 3

Figure 1.2: Stratigraphic column for Weyburn Field. Left side is after Dietrich and Magnusson (1998). Right side is after Wegelin (1984). ............................................ 4

Figure 1.3: Weyburn production history (EnCana) ............................................................ 8

Figure 1.4: EOR infrastructure at RCP 4-D 9-C seismic survey area ................................ 9

Figure 1.5: The workflow of integrating time-lapse seismic data into a flow simulation model......................................................................................................................... 12

Figure 2.1: Sketch of the Midale fracture system (Beliveau 1991). ................................. 17

Figure 2.2: Miscible displacement in a quarter of a five-spot pattern at mobility ratios > 1.0, viscous fingering (Habermann 1960). At Weyburn condition, oil-CO2 mobility ratio is about 40......................................................................................................... 23

Figure 2.3: Minimum miscibility pressure versus temperature (Cronquist 1978)............ 24

Figure 2.4: Density of CO2 (Green and Willhite 1998) .................................................... 24

Figure 2.5: Comparison of two-phase envelopes of methane/hydrocarbon and CO2/hydrocarbon systems (Green and Willhite 1998). ............................................ 25

Figure 3.1: CO2 injection and RCP survey areas.............................................................. 29

Figure 3.2: The horizontal wells that are indicated by the ellipses have responded to CO injection with increased oil recovery.

2....................................................................... 29

Figure 3.3: Two SSWG Injection Patterns; Top View .................................................... 30

Figure 3.4: SSWG injection patterns, Side View (EnCana) ............................................. 30

Figure 3.5 Pattern name assignment ................................................................................ 33

Figure 3.6: Cumulative CO2 injection volume up to the second survey in 2001.............. 33

Figure 3.7: Horizontal Well locations of the South Pattern.............................................. 35

Figure 3.8: Injection rate and wellhead pressure of CO2 injector, CD-10H12 in the South pattern ....................................................................................................................... 36

Figure 3.9: Production history of well OP-09HB12 ......................................................... 36

Figure 3.10: Production history of well OP-01H13.......................................................... 37

Figure 3.11: Well locations of horizontal wells in the East pattern.................................. 38

x

Figure 3.12: Injection rate and wellhead pressure of CO2 injector, CD-10H18 in the East pattern ....................................................................................................................... 39

Figure 3.13: Production history of the well OP-08H18.................................................... 39

Figure 3.14: Production history of the well OP-15H18.................................................... 40

Figure 3.15: Injection rate and wellhead pressure of CO2 injector, CD-04H13 in the West pattern ....................................................................................................................... 41

Figure 3.16: Injection rate and wellhead pressure of CO2 injector, CD-04H19 in the North pattern. ...................................................................................................................... 42

Figure 4.1 Simulation Area and RCP Survey Area ......................................................... 46

Figure 4.2: Relative permeability curves of the Marly formation .................................... 50

Figure 4.3: Relative permeability curves of the Vuggy formation ................................... 51

Figure 4.4: Shaded areas indicate the locations of permeability and porosity modifications in Marly. Color filled cells in red, green, and blue represent CO2 injectors, producers, and water injectors, respectively ............................................................. 52

Figure 4.5: Shaded areas indicate the locations of permeability and porosity modifications in Vuggy. Color filled cells represent well locations............................................... 53

Figure 4.6: Location of wells in the RCP survey area and natural fracture trends ........... 54

Figure 4.7: Location vertical wells in the South pattern................................................... 55

Figure 4.8: Production plot of well OP-04-18 .................................................................. 57

Figure 4.9: Production plot of well OP-10-12 .................................................................. 57

Figure 4.10: Production plot of well OP-02-13 ................................................................ 58


Figure 4.12: Production plot of well OP-08-13)............................................................... 59




Figure 4.16: Location of vertical wells in the East pattern ............................................... 61





xi


Figure 4.22: Location of horizontal injector and producers in the South Pattern............. 66

Figure 4.23: Production plot of well OP-01H13............................................................... 66



Figure 4.26: Production plot of well OP-09HB12............................................................ 68

Figure 4.27: Well locations of horizontal wells in the East pattern.................................. 69




Figure 4.31: Pressure (barsa) at the end of history match in M3_A layer ........................ 71

Figure 4.32: Production match of well OP-01H13 ........................................................... 73

Figure 4.33: Production match of well OP-09HB12 ........................................................ 73

Figure 4.34: The South pattern, liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right).............................................................................................................. 74

Figure 4.35: Cross section of the South pattern showing CO2 mole fraction in liquid phase. Notice that all horizontal wells are positioned in the Marly zone ................ 74



Figure 4.38: The East pattern, liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right).............................................................................................................. 77

Figure 4.39: Cross section of the East pattern showing CO2 mole fraction in liquid phase. Notice that all horizontal wells are positioned in the Marly zone ............................ 77

Figure 4.40: Cumulative production volume of the South pattern. .................................. 79

Figure 4.41: Cumulative production volume of East pattern............................................ 79

Figure 5.1: Location of P-impedance values and the simulation grids. The red rectangle is the area for comparison. ........................................................................................ 88

Figure 5.2 Close up view of the location of P-impedance values and the simulation grids................................................................................................................................... 89

Figure 5.3: Averaged P-impedance data in Marly ............................................................ 89

Figure 5.4: Averaged P-impedance data in Vuggy........................................................... 90

xii

Figure 5.5 Variation of Marly P-wave impedance with fluid saturation and pressure at constant crack density (Brown 2002). ...................................................................... 91

Figure 5.6 Variation of Vuggy P-wave impedance with fluid saturation and pressure at constant crack density (Brown 2002). ...................................................................... 92

Figure 5.7: P-impedance differences map using the sparse-spike inversion for the Marly formation (Herawati 2002). ...................................................................................... 94

Figure 5.8: P-impedance differences map using the sparse-spike inversion for the Vuggy formation (Herawati 2002). ...................................................................................... 95

Figure 5.9: Calculated time-lapse P-impedance of EnCana’s history matched model..... 99

Figure 6.1: Flow unit study of Well OP-02-13 (Pantoja 2000) ..................................... 103

Figure 6.2: Flow unit study of Well OP 04-18 (Pantoja 2000)....................................... 104

Figure 6.3: Production match of well OP-01H13 with flow barrier ............................... 106

Figure 6.4: Production match of well OP-09HB12 with flow barrier ............................ 106




Figure 6.8: Pressure (barsa) at the end of history match in M3_A layer with flow barrier. Notice that the pressure at horizontal producers are low. ....................................... 108

Figure 6.9: Cross section of the South pattern showing CO2 mole fraction in liquid phase.................................................................................................................................. 109

Figure 6.10: Cross section of the East pattern showing CO2 mole fraction in liquid phase. CO2 in the Vuggy is from WG-10-18. .................................................................... 109

Figure 6.11: CO2 mole fraction in liquid phase, isotropic model ................................... 112

Figure 6.12: CO2 mole fraction in liquid phase, simple Weyburn case with low vertical permeability ............................................................................................................ 113

Figure 6.13: CO2 mole fraction in liquid phase, simple Weyburn case with high vertical permeability ............................................................................................................ 113

Figure 6.14: Plot of vertical displacement efficiency as a function of viscous/gravity ratio(Craig 1957)..................................................................................................... 116

Figure 6.15: Plot of volumetric displacement efficiency as a function of viscous/gravity ratio ......................................................................................................................... 116

Figure 6.16: Flow regimes in miscible displacement of unfavorable mobility ratio (Stalkup 1983)......................................................................................................... 117

xiii

Figure 6.17: Side view of the reservoir showing movement of fluids during CO2 injection process..................................................................................................................... 119

Figure 7.1: Dual continuum model with non-connected fracture set (top view). Solid black lines indicate fractures................................................................................... 123

Figure 7.2: Dual continuum model with connected fracture set (top view). Solid black lines indicate fractures. ........................................................................................... 123

Figure 7.3: CO2 mole fraction in the non-fractured model............................................. 124

Figure 7.4: CO2 mole fraction in the non-connected fracture model.............................. 125

Figure 7.5: CO2 mole fraction in the connected fracture model ..................................... 125

Figure 7.6: Oil saturation of matrix after 300 days of water injection into Vuggy. Black dots represent completed formation........................................................................ 128

Figure 7.7: Oil saturation of fracture after 300 days of water injection into Vuggy. Black dots represent completed formation........................................................................ 129

Figure 7.8: CO2 mole fraction in liquid phase in matrix after 30 days of injection into Marly. Black dots represent completed formation................................................. 129

Figure 7.9: CO2 mole fraction in liquid phase in fracture after 30 days of injection into Marly. Black dots represent completed formation................................................. 130


Figure 7.11: Oil saturation of fracture after 300 days of water injection into Vuggy. Black dots represent completed formation.............................................................. 132




Figure 7.15: Oil saturation of fracture after 300 days of water injection into Vuggy. Black dots represent completed formation.............................................................. 135



xiv

Figure 8.1: Production match of on-trend well OP-04-18 (South pattern) ..................... 141

Figure 8.2: Production match of on-trend well OP-10-12 (South pattern) ..................... 141

Figure 8.3: Production match of off-trend well OP-12-07 (South pattern) .................... 142

Figure 8.4: Production match of off-trend well OP-02-13 (South pattern) .................... 142

Figure 8.5: Production match of off-trend well OP-02-18 (East pattern)....................... 143



Figure 8.8: Five-point and Nine-point finite difference stencils..................................... 145

Figure 8.9: Relative permeability of Marly .................................................................... 146

Figure 8.10: Relative permeability of Vuggy ................................................................. 147

Figure 8.11: Production plots of OP-08-13 (South pattern). Notice better water production match at water breakthrough. ............................................................... 149

Figure 8.12: Production plots of OP-14-12 (South pattern). Notice better water production match at water breakthrough. ............................................................... 149

Figure 8.13: Production match of off-trend well OP-08-12 (South pattern) .................. 150

Figure 8.14: Production match of corner well OP-14-07 (South pattern) ...................... 150

Figure 8.15: Production match of corner well OP-14-18 (East pattern)......................... 151

Figure 8.16: Production match of corner well OP-08-18 (East pattern)......................... 151

Figure 8.17: Production plots of OP-09HB12. Notice improved oil production rate after the modification of water relative permeability curve. ........................................... 153

Figure 8.18: Production match of corner well OP-04H18.............................................. 153

Figure 8.19: Measured and calculated pressure.............................................................. 155

Figure 8.20: History match flow..................................................................................... 156

Figure 8.21: Marly P-impedance change of the South pattern indicating the channels and the equal spread of the anomaly from the southern leg .......................................... 159

Figure 8.22: Vuggy P-impedance changes in the South pattern..................................... 159

Figure 8.23: Completion changes in injection well CD-10H12 ..................................... 160

Figure 8.24: The South pattern liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right)............................................................................................................ 160

Figure 8.25: Cross section of the South pattern showing CO2 mole fraction in liquid phase. ...................................................................................................................... 161

xv

Figure 8.26: The image of the calculated P-impedance.................................................. 161

Figure 8.27: Production match of OP-09HB12 .............................................................. 163

Figure 8.28: Production match of OP-01H13................................................................. 164

Figure 8.29: The location of local permeability modification in Marly. The shaded area is the area of the modification. ................................................................................... 164

Figure 8.30: The location of local permeability modification in Vuggy. The shaded area is the area of the modification................................................................................. 165

Figure 8.31: Objective function history of the P-impedance in the South pattern ......... 166

Figure 8.32: Objective function history of the production in the South pattern ............. 167

Figure 8.33: Objective function history of the production (oil and water rates) of only horizontal wells in the South pattern ...................................................................... 167

Figure 8.34: Objective function history of the production (GOR) of only horizontal wells in the South and East patterns ................................................................................. 168

Figure 8.35: Objective function history of the 2-year production in the South pattern.. 169

Figure 8.36: Objective function history of the 2-year production of horizontal well only in the South pattern ..................................................................................................... 169

Figure 8.37: Cumulative production of South pattern .................................................... 170

Figure 8.38: Vuggy P-impedance change indicating no injection sections of the horizontal legs and possible channels toward horizontal producers. ....................................... 172

Figure 8.39: Completion change of CD-10H18.............................................................. 172

Figure 8.40: The East pattern liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right)............................................................................................................ 173

Figure 8.41: Cross section of the East pattern showing CO2 mole fraction in liquid phase.................................................................................................................................. 173



Figure 8.44: Objective function history of the P-impedance in the South pattern (2% cut-off)........................................................................................................................... 177

Figure 8.45: Objective function history of the production in the East pattern ............... 177

Figure 8.46: Objective function history of the production (oil and water rates) of only horizontal wells in the East pattern ......................................................................... 178

Figure 8.47: Objective function history of the 2-year production in the East pattern .... 178

xvi

Figure 8.48: Objective function history of the 2-year production of horizontal wells only in the East pattern.................................................................................................... 179

Figure 8.49: Cumulative production of East pattern....................................................... 179

Figure 8.50: Objective function history of overall production in the South pattern....... 181

Figure 8.51: Objective function history of overall production in the East pattern ......... 181

Figure 8.52: Objective function of pressure match......................................................... 182

Figure 8.53: Relative objective function without OF of pressure................................... 182

Figure 8.54: Relative objective function with OF of pressure........................................ 183

xvii

LIST OF TABLES

Table 1.1: Summary of Weyburn Reservoir Properties (Churcher and Edmonds 1994). .. 6

Table 1.2: Parameters for receivers in the survey (RCP 2000)......................................... 10

Table 1.3: Parameters for sources in the survey (RCP 2000) ........................................... 10

Table 2.1: Properties of Carbon Dioxide .......................................................................... 23

Table 3.1: The list of designated letters in order to classify wells.................................... 34

Table 4.1 Layer Assignment of Encana’s Simulation Model .......................................... 47

Table 4.2: List of attributes in production plots................................................................ 54

Table 6.1: Values used to calculate viscous/gravity ratio for Weyburn ......................... 115

Table 6.2: Cumulative oil production at the time of breakthrough................................. 118

Table 7.1: Dual porosity model parameters.................................................................... 127



Table 8.1: Permeability multiplier for global horizontal permeability modification...... 140

Table 8.2: Permeability multiplier for global vertical permeability modification.......... 140

xviii

ACKNOWLEDGEMENTS

The author wishes to thank my advisors, Dr. John Fanchi and Dr. Tom Davis, for

their technical and financial support to complete this research. The Reservoir

Characterization Project has funded my education and research since the Fall of 2000,

and without the support, it was not attainable to meet the goal of this research. I would

also like to thank Mr. Dan Stright and Dr. Richard Christiansen for their ideas and

suggestions to approach various problems in different aspects. I am also thankful for the

members of the consortium for their continuing interest and support.

I would like to acknowledge the support from my fellow student members of the

project: Marty Terrell, Leo Brown, Ida Herawati, Tagir Galikeev, Nicole Pendrigh,

Rodorigo Fuck, Reynaldo Cardona, Robb Bunge and David Pantoja.

I would also like to show my immense appreciation to Mr. Sandy Graham and

Mr. Ryan Adair, engineers at EnCana, who have helped me with the reservoir data and

shared their insights of Weyburn Field. Despite being busy with other responsibilities,

they have taken time to communicate with me through emails and phone calls.

Finally, I would like to thank my parents for their everlasting support to

accomplish my education thus far. The long distance separated my parents and me, but

their encouragement kept me pursuing this degree.

xix

For Yuki

xx

1

Chapter 1

INTRODUCTION

1.1 Introduction

The successful implementation of a CO2 miscible injection project depends on

how knowledgeable geoscientists and engineers are about the petroleum reservoir. Since

such projects involve millions of dollars in capital investment, the understanding of the

reservoir is crucial. Geological data such as cores and electrical logs provide excellent

information for analyzing reservoir stratigraphy; however, the understanding of areal

geologic variation is rather limited due to horizontal discontinuities among geologic and

petrophysical properties. Production and injection history are available as dynamic data

to analyze reservoirs, but the conclusions from such data are often ambiguous.

Geoscientists and engineers try their best to characterize reservoirs with static and

dynamic data; however, uncertainties can be significant when the reservoir is

heterogeneous.

The questions that CO2 miscible injection projects must address concerning

heterogeneity are: (1) Which areas have been contacted by CO2? (2) Which areas have

not been contacted? (3) If there are areas that have not been contacted, why were they not

contacted? It is the contention of many in the oil and gas industry that these questions

can be answered with the aid of time-lapse seismic surveys since these surveys provide

information about the interwell region of the reservoir. The purpose of this thesis is to

investigate how time-lapse seismic survey data can help improve a reservoir flow

simulation model of CO2 injection into layered reservoirs.

The research presented in this thesis was sponsored by the Reservoir

Characterization Project (RCP), directed by Dr. Tom Davis in the Geophysics

2

Department at Colorado School of Mines. The RCP is an industry-sponsored consortium

that applies geophysical practices to actual reservoirs to find new techniques and

interpretation methods from geophysical data. The RCP is currently in the final stage of

Phase IX, which was continued from Phase VIII. Phase VIII began in 1999. The

objectives of these Phases are to monitor the CO2 miscible injection process using 9-

component, 4-D seismic surveys, to characterize the reservoir using time-lapse seismic

data, and to build a flow model that integrates information from the time-lapse seismic

surveys. Weyburn Field, a carbonate reservoir located in Saskatchewan, Canada, is the

focus of this research. This is the first time that time-lapse seismic data has been

integrated into a flow model of a CO2 miscible injection process using horizontal

injection wells.

This introductory chapter presents an overview of Weyburn Field, including its

geology and production history, in Sections 1.2 and 1.3, respectively. A unique enhanced

oil recovery (EOR) injection scheme developed by EnCana (formerly PanCanadian), the

operator of Weyburn Field, is introduced in Section 1.4. Section 1.5 discusses the RCP

objectives in Phase IX.

1.2 Geologic Overview and Reservoir Properties

Weyburn Field is located just north of the U.S.-Canadian border in the

southeastern part of Saskatchewan, Canada, as shown in Figure 1.1. A stratigraphic

column representative of Weyburn Field is shown in Figure 1.2. A geologic study for the

reservoir characterization of Weyburn Field was conducted by several geologists based

on microscanner logs, repeat formation testing and open hole wireline logs. Furthermore,

12,000 meters of core acquired from more than 600 vertical wells and two horizontal

wells were studied. Churcher and Edmunds (1994), Bunge (2000), and Reasnor (2001)

have presented a detailed geology of Weyburn Field. The following geologic description

3

and reservoir data are from the EnCana report entitled “Weyburn Unit CO2 Miscible

Flood EOR Application (1997)”.

Medium gravity crude oil, ranging from 22 to 35 °API, is produced from the

Midale Beds of the Mississippian Charles Formation. The oil pool is an undersaturated

reservoir with no associated gas cap. These sediments were deposited on a shallow

carbonate shelf in the Williston Basin. The distribution of the reservoir’s porosity and

permeability is controlled by a combination of depositional and secondary diagenetic

events. The time sequencing of these various events relative to the initial deposition of

the sediments and the emplacement of the hydrocarbon charge is very important in

predicting the ultimate reservoir quality and reservoir performance.

Figure 1.1: Location of Weyburn Field in Saskatchewan, Canada

4

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Age Formation Lithology Mississippian Strata

Mad

ison

Gro

up Cha

rles

Form

atio

nM

issi

on C

anyo

nFo

rmat

ion

LodgepoleFormation

Big GroupJurassic Watrous Formation

Kibbey FormationPoplar Beds

RatcliffeBeds

MidaleBeds

Frobisher Beds

Kisbey SandstoneAlida Beds

Tilston Beds

Souris Valley Beds

Bakken Formation

Quengre Evap.

Midale Evap.

Hastings Evap.Frobisher Evap.

Winlaw Evap.

Gainsborough Evap.

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Jurassic

Mississippian

Dev

onia

n Upp

erM

iddl

e

Silurian

Ordovician

Cambrian

PreCambrian

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Charles

Bakken

Birdbear

Winnipegosis

Stony Mtn.

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood

Watrous

Mission Canyon

Lodgepole

Three Forks

Duperow

Souris River

Dawson BayPrairie

Evaporite

AshernElk

P oin

t

InterlakeStonewall

Red River

WinnipegDeadwood


Mad

ison

Gro

up Cha

rles

Form

atio

nM

issi

on C

anyo

nFo

rmat

ion

LodgepoleFormation



RatcliffeBeds

MidaleBeds

Frobisher Beds


Tilston Beds

Souris Valley Beds

Bakken Formation

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.


Mad

ison

Gro

up Cha

rles

Form

atio

nM

issi

on C

anyo

nFo

rmat

ion

LodgepoleFormation



RatcliffeBeds

MidaleBeds

Frobisher Beds


Tilston Beds

Souris Valley Beds

Bakken Formation

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.

Quengre Evap.

Midale Evap.


Winlaw Evap.

Gainsborough Evap.

Figure 1.2: Stratigraphic column for Weyburn Field. Left side is after Dietrich and Magnusson (1998). Right side is after Wegelin (1984).

The different depositional environments affecting the reservoir have resulted in

the development of three distinct porosity types, namely the Marly dolostones, the Vuggy

shoal, and the Vuggy intershoal. The reservoir horizons in the Marly zone are comprised

of chalky, microcrystalline dolostone and dolomitic limestone, which are often separated

by a tighter, fractured limestone interbed. In areas where Marly tidal channels are found,

the normally continuous Marly beds are partially replaced by heterogeneous channel-fill

sequence consisting of Marly mudstones, occasional grainstones, and dark argillaceous

dolomitic muds. This channel fill sequence occasionally contains some reservoir quality

rock. In other areas of the field, the channel-fill consists of mainly reservoir quality

Marly dolostones. Marly total net pay ranges from 0.1 m to 9.8 m, with the average net

5

pay thickness being 4.3 m. Net porosity in the Marly dolostones ranges from 16% to

38%, averaging 26% across the Weyburn Unit. Marly matrix air permeability values

(from unstressed core) range from 1 md to over 100 md, averaging 10 md.

Two distinct rock types are present within the Vuggy zone, each having unique

petrophysical and petrological properties. Higher energy, coarser grained carbonate

sands accumulate locally to form high porosity (12% to 20%, averaging 15%) and high

permeability (10 to 500-plus md, averaging 50 md) deposits called shoals. The thickest

and most permeable shoal development occurs in the west end of the pool (the west

shoal) and corresponds to the area of highest vertical well productivity and the region of

best waterflood pressure support. Shoal development does occur in the southern portion

of the pool (the south shoal); however, lower quality and thinner shoals are present.

Vertical well productivity in the area is correspondingly lower than in the west shoal.

Lower energy, muddier sediments accumulate in regions between the shoals and

dominate deposition in the east end of the pool. These deposits are termed the intershoal

and range in porosity from a few percent to 12%, with an average of 10%. Matrix air

permeability ranges from less than 0.1 md to 25 md, averaging 3 md. Fracturing in the

Vuggy is more pronounced than within the Marly, particularly in the tighter intershoal

rock. Overall the Vuggy net pay ranges from 0.1 m to 18.6 m, averaging 6.0 m. Net

porosity values within the Vuggy reservoir range from 8% to 20%, averaging 11 %

across the Weyburn Unit, with Vuggy matrix air permeabilities ranging from 0.3 md to

over 500 md, averaging 15 md. Table 1.1 summarizes the reservoir properties mentioned

above.

The reservoir is overlain by a tight, interbedded, evaporitic dolomite and shale

sequence, which forms the top seal on the reservoir. The hydrocarbons are trapped

laterally by hydrodynamic forces. These beds are in turn capped by the Midale

Evaporite. Above the Midale Evaporite lie the Ratcliffe and Poplar Beds, representing a

series of relatively thin, shallowing upward sequences that alternate between carbonate

6

and evaporitic carbonate deposition. The Ratcliffe and Poplar Beds are progressively

eroded off to the north along the Mississippian unconformity. In the northern part of the

unit these beds are absent.

The reservoir is underlain by the Frobisher Beds. This sequence consists of

Frobisher Vuggy, Marly and Evaporite zones that are lithologically and depositionally

similar to the overlying Midale Beds. The Frobisher Evaporite is not present in the

southern half of the Unit. The original oil-water contact for the Unit is in the upper part

of the Frobisher Vuggy. Chapter Two discusses natural fractures in the Midale formation

in more details.

Table 1.1: Summary of Weyburn Reservoir Properties (Churcher and Edmonds 1994).

Marly Dolostones Vuggy Shoal Vuggy Intershoal

Texture Mudstone-

wackestone Packstone-grainstone Mudstone-packstone

Porosity Type

microsucrosic

some pinpoint

vuggy

open vuggy

pinpoint vuggy

intercrystalline

intercrystalline

pinpoint vuggy

Porosity

(Average)

16 – 38 %

(26 %)

12 – 20 %

(15 %)

2 – 12 %

(10 %)

Matrix

Permeability

(Average)

1 – 100 md

(10 md)

10 – 500+ md

(50 md)

0.1 – 25 md

(3 md)

Thickness

(Average)

0.1 – 9.8 m

(4.3 m)

0.1 – 18.6 m

(6 m)

7

1.3 Field Development and Production History

Weyburn Field was discovered as an oil field in 1954, and was initially drilled on

32-ha (79-acre) spacing. Original Oil in Place (OOIP) was estimated to be 1.3 billon

barrels. The production was started with depletion drive until 1964, when waterflood

was implemented. The waterflood program was initiated in 32-ha spacing with inverted

nine-spot injection patterns. The maximum production from the water flood was 7,300

m3/day (≈ 46,000 barrels/day). In 1984, some of the vertical producers were converted to

water injectors to create “Line-Drive” waterflood patterns. Simultaneously, the infill-

drilling program was started to offset lost production due to the conversion of producers

to injectors. A total of 75 new producers was drilled in the infill-drilling program, and

the production was increased from 1,400 m3/day to 2,500 m3/day. The operator believed

that past production due to the waterflood was coming mainly from the Vuggy formation

since the formation was more permeable and fractured than the Marly formation.

Therefore, a horizontal drilling program was begun in 1991 and was designed to recover

bypassed oil in the Marly formation. Horizontal well completions were selected for the

tight Marly formation because they had higher productivity than vertical well

completions. The program increased the production from 2,100 m3/day to 3,800 m3/day.

After 46 years of production, 25% of OOIP had been recovered. The production history

and forecast due to the CO2 flood in the Weyburn Field are shown in Figure 1.3.

8

Base Waterflood

Horizontal Infill

Miscible Flood

0

1000

2000

3000

4000

5000

6000

7000

8000

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025

Year

Prod

uctio

n (m

³/d)

Base Waterflood

Horizontal Infill

Miscible Flood

0

1000

2000

3000

4000

5000

6000

7000

8000

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025

Year

Prod

uctio

n (m

³/d)

Figure 1.3: Weyburn production history (EnCana)

1.4 Seismic Surveys in Weyburn Field

Seismic surveys can see underground reservoirs indirectly by detecting waves

reflected by the geologic formations. The wave source is created by the explosion of

dynamite or the vibration created by special equipment. The generated waves propagate

from the source on the ground to subsurface reflectors, and then the reflected waves

propagate back to the surface where they are detected and recorded by arrays of seismic

detectors (geophones). There are two kinds of seismic waves, the compressional wave,

referred to as P-wave, and the shear wave or S-wave. The P-wave is the displacement of

particles that is parallel to the direction of P-wave propagation, while the S-wave is the

displacement of particles perpendicular to the direction of S-wave propagation. The

9

number of seismic wave detectors on the ground affects the areal resolution of the

seismic survey.

The RCP has shot three 9-component, 3D seismic surveys in Phase VIII and

Phase IX. The survey area, which is approximately 9 km2, covers four injection patterns

that each consist of one CO2 injector, a few horizontal producers, and many vertical

wells (Figure 1.4). The details of the injection pattern are discussed in the later chapter.

The first survey was conducted in October 2000 before the commencement of CO2

injection. Then, a year later in October 2001, the first monitor survey was shot in the

same area. Two years into the CO2 injection project, the second and final monitor survey

was shot. Solid State Geophysical conducted the actual surveys, and the data was

processed by Veritas DGC. The parameters of the P-wave seismic survey are listed in

Table 1.2 and Table 1.3.

Figure 1.4: EOR infrastructure at RCP 4-D 9-C seismic survey area

10

Table 1.2: Parameters for receivers in the survey (RCP 2000).

Receivers Model Oyo

# per group 3 (bunched) Record length (sec) 14

Line spacing (m) 140 Group spacing (m) 80

Groups per line 60 Lines 20

Total receivers live 1200 Total channels live 3600

Table 1.3: Parameters for sources in the survey (RCP 2000)

Sources

Source Mertz 18 (first survey) TRIAX (second survey)

Sweep frequency. (hz) 9-180, non-linear, 3db/oct boost Number of sweeps 3 Sweep length (sec) 10 Line spacing (m) 80 Source spacing 40 or 80 Sources per line or 33 66

Lines 28 Nu s mber of source point 1386

11

1.5 The arch Objective of this Rese Within RCP

Th udy within the Reservoir Characterization Project is to

characterize the area of interest in the Weyburn Field by integrating static and dynamic

data in a flo al is to use the time-lapse seismic data to enhance reservoir

characterization, and to create a better reservoir flow el. The 4-D seismic surveys at

Weybu monitor the CO2 enhanced oil recovery. The research

described herein will contribute to creating a more effective flow model by integrating

time-lapse seismic data into the history matching process. In addition, results of this

work will improve our understanding of the reservoir from an engineering perspective;

i.e. in terms of production/injection performance and flow model forecasting. The

procedures developed during this research and documented in this thesis should be

applicable to other CO2 injection projects in geologically complex reservoirs.

Figure 1.5 depicts the workflow of integrating time-lapse seismic data, e.g. P-

odel. The LHS and RHS of the

workfl of

, a

he P-

l fluid

influence

of natu

e objective of this st

w model. My go

mod

rn involved an attempt to

impedance data, into a flow model to calibrate the m

ow are the simulation workflow and seismic workflow, respectively. At the end

each workflow, the P-impedance is calculated and compared. The agreement between

the two P-impedance results is analyzed, and adjustments are made as needed to the flow

model.

In this dissertation, the history of the Weyburn Field production and injection

performance is first presented. The history of the field is followed by a discussion of a

history match of primary and waterflood performance prepared by the operator. Then

procedure for quantitatively integrating the P-impedance data into the history matching

process (i.e. the LHS of the workflow in Figure 1.5, including the interpretation of t

impedance data) is presented. Conceptual models are presented that examine severa

flow mechanisms, including the behavior of CO2 in a layered reservoir and the

ral fractures. Finally, the integrated history match process and results are

presented.

12

Figure 1.5: The workflow of integrating time-lapse seismic data into a flow simulation model.

Reservoir Simulation (Baseline and Repeat)

Rock and Fluid Physics Modeling

9-C Seismic Survey (Baseline and Repeat)

Interpretation

Output:So, Sw, Sg, P, φ, ρo,ρw, ρg, cw, cg, co, cr

Output:DZ

Synthetic Seismic Response

Inversion

Output:DZ

Wavelet

Weyburn Workflow

13

Chapter 2

LITERATURE REVIEW

2.1 Introduction

The literature contains many papers describing attempts to integrate time-lapse

seismic measurements into reservoir flow modeling. Section 2.2 discusses published

studies that are related to the topic of this thesis: integration of seismic data into reservoir

flow modeling of CO2 injection into a layered system. We show that there are no

published studies that discuss the integration of multicomponent, time-lapse seismic

measurements into the flow model of CO2 injection into a layered reservoir.

Previous research of natural fractures in the Midale formation is summarized in

Section 2.3. We also considered using streamline simulation in this study. In Section 2.4,

the limitations of streamline simulation that were encountered within the context of this

study are discussed.

2.2 Reservoir Characterization Using Seismic Data

Static three-dimensional (3-D) seismic survey data, in conjunction with log and

core data are often used in building the initial flow model. Seismic survey data help

define horizons of geological formations since its areal resolution is superior compared to

well log data. It is also used in reservoir modeling with geostatistics, which uses the

survey data as one of the constraints to build static models. Geostatistical modeling can

build high-resolution reservoir models consisting of millions of grid cells. The detailed

model can emulate the geologic heterogeneity of a reservoir; however, such models

would be unacceptable if fluid flow cannot be simulated in a reasonable time period.

14

Also, without good dynamic data, i.e. s that represent fluid flow within the

reservoir, the model will have ngineering tool.

King et al. (1993) used seismic data to estimate lithologic components, porosity,

and thickness variations laterally and vertically. The results were consistent with

erens et al.(1996) incorporated seismic data and well log data in 3-D

reservoir modeling with sequential Gaussian simulation with block Kriging (SGSBK),

which tre

f the

reservoir at a single point in time. Time-lapse (4-D) seismic surveys can provide us

dynami

odeling should improve the realism of reservoir models and

increase their accuracy of fluid flow forecasts. Several researchers have investigated the

eservoir modeling and history

matchi

fy

g

permeabilitie

limited utility as a reservoir e

borehole data. Beh

ats the seismic data as a soft estimate of the average reservoir properties.

Weinbrandt (1998) used their 3-D seismic data to define a porosity model of the

Grayburg reservoir. The model was confirmed by the history match, than used for the

redevelopment of the waterflood of the field.

The data from a 3-D seismic survey is static data: it gives us a picture o

c data: pictures of the reservoir at more than one point in time. Even though

seismic data in general has limited vertical resolution, it can provide an image of

saturation and pressure changes within a reservoir. Therefore, incorporating 4-D seismic

data into reservoir flow m

potential of using time-lapse seismic survey data in the r

ng process

Huang and Kelker (1996) integrated production data and seismic data to modi

their reservoir model using the simulated annealing optimization algorism. They applied

forward modeling approach using Gassmann’s equation for both synthetic and Frio

sandstone dry gas reservoir in South Texas. The details of forward modeling are

described in a later chapter.

Huang et al. (1997) later applied the forward modeling approach incorporatin

production data to a turbadite sheet sand oil reservoir in Gulf of Mexico.

15

Landa and Horne (1997) have also used 4-D seismic to estimate permeability and

porosity distributions within a reservoir using different mathematical optimiz

ation

techniq r

e

ld in

), which

or

ve function was reduced from 91.4 to a

low of the

ing

changes

s.

hich is geologically realistic and heterogeneous.

be

istory

ynamic model (in addition to conventional well production

data). -

ues. Production history was incorporated as well in their approach; however, thei

approach was tested on a synthetic reservoir model only.

Waggoner et al. (2002) used 4-D seismic data to improve their reservoir

simulation model. They prepared a compositional simulation model of a gas-condensat

reservoir in the Gulf of Mexico. Two 3-D seismic surveys were acquired in their fie

1993 and 1996. Their approach was to perform Seismic History Matching (SHM

is to match acoustic impedance using a rock physics model in conjunction with simulat

output results. After 317 iterations, the objecti

66.2. Further iteration improved the match in acoustic impedance but lowered

match in production data.

Kretz et al. (2002) used 4-D seismic data in their integration approach, assum

seismic variations are only a result of saturation changes. The effects of pressure

on seismic attributes were ignored. They used the Gradual Deformation Method to

perturb petrophysical properties in order to maintain special variability of the propertie

An objective function is introduced with weighting factors, which are estimated by

putting more emphasis on non-fitted data. The model they used in their study is a

synthetic model, w

Staples et al. (2002) with Shell UK Exploration and Production used 4-D seismic

data collected in one of their mature fields in the North Sea to optimize production by

workovers and an infill drilling program. They stated that a reservoir model needs to

updated as new data becomes available: “The 4D data provides strong additional h

matching constraints on the d

The more accurately a dynamic model matches the distributions at the time of a 4

D seismic survey, the more reliable it is likely to be in the future”

16

Fanchi (2003) has developed an integrated flow model that calculates seismic

attributes based on an algorithm that is an extension of Gassmann’s theory. The

petrophysical algorithm is coded directly into the simulator. The simulator significantly

reduces the time to analyze and compare the simulation results with the actual seismic

data. It also enables engineers and geophysicists to forecast what kind of seismic data

they should expect in future surveys.

2.3 Natural Fractures

Understanding natural fractures in petroleum reservoirs is critical since the

fractures can have a significant effect on reservoir performance. Fractures could enhance

the performance, or could bring devastating outcomes. In naturally fractured reservoirs,

reservoir storage is predominantly in the matrix. The matrix is much less permeable than

the frac

udies

tures. Thus, the fractures that are open and connected become conduits, which

create a network for fluid flow. In this section, previous geological and engineering

studies that discuss natural fractures in the Midale formation are presented. These st

show that the Weyburn Field is a fractured reservoir system.

2.3.1 Core and Log Studies of Midale Formation for Natural Fractures

ll

and it could occur in both pay and non-pay zones. The sketch of the Midale fracture

The existence of natural fractures in the Midale formation has been studied

previously by EnCana and Shell Canada geoscientists . Beliveau et al (1991) with She

Canada have studied 100 vertical cores and 180 ft of horizontal cores from three wells.

The study revealed that the natural fracture system exists primarily in the Vuggy

formation, and the Vuggy formation can be fractured two to five times more than the

Marly formation. The cores show vertical fractures separated by about 1 ft, and their

heights range from a few inches to a few feet. The fracture is not continuous vertically,

17

system

gs for fractures in the

Midale formation. He found the fracture spacing was lithology dependent, and the

Vuggy tends to be more fractured than the Marly. He also found that the fracture density

ks are more

fractur uggy

ists at

e.

a

is shown in Figure 2.1. Notice that the upper layer (Marl) is less fractured than

the lower layer (Vuggy).

Figure 2.1: Sketch of the Midale fracture system (Beliveau 1991).

Fischer (1994) studied 48 vertical cores and 3 FMS lo

(the inverse of fracture spacing) seems to be related to porosity, and tight roc

ed. The fracture density was calculated to be 2 to 4 fractures/meter for the V

formation and 0.5 fractures/meter for Marly. The average fracture height in the Marly

and Vuggy formations was 28 cm and 47 cm, respectively. Those fractures tend to be

short and remain in the same layer. The most significant vertical discontinuity ex

the Marly/Vuggy interface since most of the fractures end above or below the interfac

The report prepared by Eddy (1998), an engineer of EnCana, states that there is

fracture trend in the NE-SW direction, which creates an anisotropic reservoir. He also

18

mentioned the term “on trend”, which means the direction parallel to the NE-SW fractur

trend. The “off trend“ ref

e

ers to the direction perpendicular to the NE-SW trend. He

concluded that the fractures in directions other than the NE-SW direction, if they exist,

have minimal effect on the flow. One of the reasons is that the core study done by

Edm

. He also found

the Vuggy form orientations are NE

and NNW trending.

ted by the open

fracture sets. but the population of

2.3.2

onds showed that there are no open fractures in the “off trend” direction in 600 cores

Bunge (2000) also studied the Weyburn cores and EMI data. He found three

fracture sets and the average height of those fractures was about 30 cm

ation is more fractured than the Marly. The fracture

trending, which has the highest fracture density, WNW trending,

Two healed fracture sets were observed; however, they are intercep

He found a vertical fracture as long as 2.7 meters,

vertical fractures that are more than one meter long is only 5%. He concluded that 7% of

the vertical fractures are long enough to connect flow units, but the vertical fractures that

link the Marly and Vuggy formations were not found.

Engineering and Laboratory Studies for Natural Fractures

In addition to core studies, Beliveau et al. (1991) studied the Midale formatio

with comprehensive interwell pressure transient tests prior to their CO

n

l

anisotro

2 injection pilot

program. The test area consists of five wells in the arrangement of a five-spot injection

pattern. Those wells are located much closer to each other compared to regular interwell

distances so that the pressure transient data could be obtained within a reasonable time.

The purpose of the study was to characterize the reservoir by determining existence and

anisotropy of the natural fracture system within the reservoir. They found that the natura

fracture system is oriented N45˚E, and the vertical fractures create average permeability

py of about 25 to 30. Communication between the Marly and the Vuggy

19

formations was observed in the interference tests. The test results agree with the

existence of the vertical fractures observed in the cores.

Beliveau et al. (1991) built a dual porosity flow simulation model to analyze the

reservoir numerically. The simulation model was history matched for the waterfloo

the CO

d and

recover ve.

are vertical or subvertical, and

oriented at N45˚E. Some fractures are open, but some others are filled with anhydrite

cement. Estimated effective fracture spacing for the Marly and Vuggy formations is 3

odel

based o

as

l

approximately 0.1, which is much lower than the value that Beliveau, et al. had used.

2 injection periods. From the simulations, they found that the main waterflood

y mechanisms in the Midale formation are capillary imbibition and viscous dri

Gravity drainage plays a minor role in the thin Midale reservoir. In the case of the CO2

flood, gravity segregation enhanced by vertical fractures allowed injected CO2 to contact

the bypassed oil in the Marly formation. In their simulation model, it was necessary to

increase the effective vertical/horizontal permeability ratio (kv/kh) to as high as 2.5.

Elsayed et al. (1993) studied the Weyburn Field, located west of the field that

Shell Canada had studied. Weyburn has the Marly and Vuggy formations, and is

naturally fractured as well. The study included 150 vertical cores, five horizontal cores,

and FMS logs. From cores and FMS logs, the fractures

meter and 0.3 meters, respectively. They created a single porosity flow simulation m

n their studies. Then, the primary and secondary recovery periods were history

matched. During the history match, a horizontal permeability anisotropy ratio of 3:1 w

used in the Marly formation, and a horizontal permeability anisotropy ratio of 10:1 was

used in the Vuggy formation. They also investigated a permeability barrier and created a

map based on Horner-extrapolated RFT pressure data, core observations, and porosity

logs. The mapped flow barrier revealed that barriers in any given layer have limited area

extent (less than 48 ha). Also, the barriers rarely exist in all layers in a single well. In the

simulation study, using the data from the observation well log in Shell’s CO2 pilot

program, the vertical/horizontal permeability ratio (kv/kh) was determined to be

20

2.4 Streamline Simulation

Streamline simulation has become a popular simulation tool, especially in ranking

many g

,

ng

eostatistically derived multimillion cell flow simulation models. That is because

the streamline simulator can take large time steps, which results in a short simulation run-

time when compared to conventional finite difference simulation programs. Another

major advantage of the streamline simulator is that the fluid flow path can be visualized

between injectors and producers. This helps to identify linkages between wells and to

specify fluid allocation factors. Viewing the fluid flow path can also facilitate application

of the history matching process in a technique called assisted history matching (Milliken

Emanuel et al. 2000).

An attempt was made to incorporate streamline simulation into the history

matching phase of this research. The idea was to apply the assisted history matchi

process in the CO2 injection period. However, while proceeding with the research, some

limitations with the simulator were recognized.

2.4.1 Limitations of Streamline Simulation

Carbon dioxide (CO ) injection in the Weyburn Field is a miscible process.

Miscible flooding can involve complicated phase behavior such as the multi-contact

miscible process (Green and Willhite 1998). The streamline simulator that was used in

this research is capable of handling only first-contact miscible processes. In addition, the

PVT model in the streamline simulator is a pseudo-compositional model, which uses

mixing parameters to control how much CO is dissolved in the liquid phase (Todd and

Longstaff 1972). Since the mixing parameters need to be specified by the user, the

results depend on the mixing parameters that are “massaged” by the user as part of

history matching process.

2

2

the

21

In the streamline simulation, the recovery process needs to be in the steady state,

i.e., the

e

oblems. Streamline simulators are stable for very large time steps,

but if fluids are not moved correctly, the material balance errors can occur and be

significan

luid into Frobisher (this will be

discussed in later chapters). The need to include the aquifer in the system or the loss of

lation problem.

in

rch

injection volume needs to be in balance with the production volume. Thus,

modeling flow of a highly compressible fluid such as CO2 is not the most appropriate

application of the streamline simulator. Another problem with applying the streamline

simulator to this miscible injection process is the material balance error. The streamlin

simulation is fundamentally not mass conservative. This is because the mass balance

equation is not computed along the underlying Cartesian grid, but instead is applied as

multiple one-dimensional solutions along streamlines. For the compressible fluid case,

the added coupling of pressure to saturation can result in larger material balance errors

than incompressible pr

t. In one attempt, the material balance error became so large (on the order of

15%) that the simulation run was halted. Moreover, the Weyburn Field is thought to

have weak aquifer support from the Frobisher formation underlying the Vuggy formation.

Other evidence also shows possible leakage of injected f

injected fluid further complicates the flow simu

In conclusion, streamline simulation is a very useful tool if it is used under

appropriate reservoir, fluid, and recovery conditions. Generally, it is a powerful tool

analyzing incompressible systems such as waterflood processes, and it can be used to

assign allocation factors that illustrate the injector and producer relationships. It is also

good for simulating tracer problems. Incorporating streamline simulation in this resea

was halted because of the reasons discussed above.

2.5 CO2 for Enhanced Oil Recovery Process

Carbon dioxide injection has been used for EOR projects in many places around

the world, although other gases, such as methane, nitrogen, or mixtures of light gases can

22

be used

t

,

a

of

injection process,

miscibi ssion

e

nce CO2 dissolves in the oil, the viscosity of the oil-CO2 mixture is reduced and

, the residual oil saturation can be

reduced, which leads to additional recovery of oil from the reservoir. These are some of

instead of CO2. CO2 is preferred to other gases because of high solubility in oil

and its low cost. Unlike water, CO2 is a low viscosity fluid (0.045cp at Weyburn

condition) that is an effective displacing agent. When a low viscosity fluid is injected

into a reservoir to replace a more viscous fluid, e.g. oil, it can result in viscous fingering

and early breakthrough of the injected fluid due to unfavorable mobility ratio (Figure

2.2). This is a reason why many CO2 injection wells are designed with Water-

Alternating-Gas injection (WAG). One goal of the WAG scheme is to reduce the

possibility of viscous fingering.

Carbon dioxide produces an unfavorable mobility ratio that causes fingering, bu

many EOR projects still inject CO2 because of other advantages compared to other gases.

Under the most likely conditions of reservoir pressure and temperature at Weyburn

which are above the critical point of CO2 (listed in Table 2.1), the injected gas becomes

dense fluid with a density that has about 75% of the oil density (the plot of the density

CO2 at different temperatures and pressures is shown in Figure 2.4). This limits the

gravity segregation of CO2 relative to oil, but the gas density is much lower than water

density so that gravity segregation can occur when CO2 and water are the mobile,

resident fluids. Also, with CO2 as an injected fluid for a miscible

lity can be achieved at moderate pressures that does not require high compre

costs (Figure 2.3). At Weyburn condition, reservoir temperature of 63˚C (145.4˚F), the

MMP is about 14.5 MPa (2100 psi). By comparison, MMPs of methane or nitrogen ar

usually 3500 to 5500 psi (Stalkup 1983). From a phase behavior point of view, CO2 is

more efficient compared to methane since it can reach miscibility over a broader range of

compositions, as shown in Figure 2.5.

O

the volume of oil increases, or swells. Moreover

23

the reasons why CO2 was selected as the injection fluid. Another important reason was

the availability of CO2 from a gasification plant in the United States.

Table 2.1: Properties of Carbon Dioxide

Critical Pressure 1071 psia

Critical Temperature 87.91 ˚F

Figure 2.2: Miscible displacement in a q1.0, viscous fingering (Habermann 1960

uarter of a five-spot pattern at mobility ratios > ). At Weyburn condition, oil-CO2 mobility ratio

is about 40.

24

WeyburnWeyburn

Figure 2.3: Minimum erature (Cronquist 1978)

Figure 2.4: Density of CO2 (Green and Willhite 1998)

miscibility pressure versus temp

WeyburnWeyburn

25

Figure 2.5: Comparison of two-phase envelopes of methane/hydrocarbon and CO2/hydrocarbon systems (Green and Willhite 1998).

C1 or CO2

C7 + C2 to C6

C1 or CO2

C7 + C2 to C6

Chapter 3

26

27

WEYBURN ENHANCED OIL RECOVERY

PROJECT

3.1 Introduction

Enhanced oil recovery involves careful study of the reservoir and the properties of

fluids that are produced as well as injected. In addition, the relative location of producers

and injectors are important. EnCana has studied the feasibility of using CO2 for

enhanced oil recovery since the early 1990’s. In 2000, EnCana began its first phase of

the CO2 injection program to enhance oil production with 19 injection patterns in the

northwest part of the Weyburn Field (Figure 3.1).

Actual CO2 injection and production response in four different injection patterns

covered by the RCP survey is summarized in Section 3.2. Section 3.3 describes the

unique injection scheme employed at the Weyburn Field. Section 3.4 identifies the

source of CO2, and Section 3.5 briefly discusses CO2 sequestration. A more detailed

discussion of pattern response to CO2 injection is presented in Section 3.6.

3.2 Summary of Pattern Response

The unique injection scheme of “Simultaneous but Separate Water and Gas

(SSWG)” injection was designed by EnCana. The SSWG injection scheme is described

in Section 3.3. The RCP survey area covered four SSWG patterns to monitor the CO2

movement within the reservoir. These four patterns have responded quite differently to

CO2 injection. The South and East patterns have benefited most from CO2 injection

while the North and West patterns have not seen significant response at adjacent

producers. It is apparent that the producers in the North pattern have not seen any

response since the North pattern has injected the least amount of CO2 by far among the

four patterns of interest in the RCP study area. The East pattern, however, has not shown

28

any response at horiz ed gas. One

possible reason is that the majority of i as lost into another formation, most

likely the Frobisher formation beneath the Vuggy formation.

Figure 3.2 shows horizontal wells that have experienced an increase in oil

ng CO2 injection.

ontal producers despite the large volume of inject

njected CO2 w

production followi

3.3 Injection Design in Weyburn Field

In addition to those horizontal producers that were drilled into the Marly

formation, horizontal CO injectors have also been drilled into the same formation to

develop a unique injection scheme called the “Simultaneous

(SSWG)” injection pattern (Figure 3.3). CO is injected into the Marly form

2

but Separate Water and Gas

2 ation where

most o

tern

that

re 3.4)

hieved at reservoir conditions, since both reservoir

and inj at

f the bypassed oil is present, and the oil that was contacted by CO2 is produced in

the horizontal producers. Vertical producers from the original inverted nine-spot pat

are located at the edges of the SSWG pattern, and vertical water injectors are aligned

along the CO2 injectors. Vertical water injectors are completed in the Vuggy zone so

the injected water will keep the oil and CO2 mixture in the Marly zone (Figu

Miscibility is expected to be ac

ection pressures are greater than the minimum miscibility pressure (MMP) th

was obtained in the lab experiment using Weyburn oil samples. The measured MMP of

Weyburn Field is 14.5 MPa or 145 Bars. More details of the Weyburn PVT properties

are discussed in Chapter 4.

29

Figure 3.1: CO2 injection and RCP survey areas

Figure 3.2: The horizontal wells that are indicated by the ellipses have responded to CO2 injection with increased oil recovery.

R.14 R.13 R.12W2

T.7

T.6

T.5

RCP Survey area

CO2 Injection Area

R.14 R.13 R.12W2

T.7

T.6

T.5

RCP Survey area

CO2 Injection Area

30

Producers Water InjectorsCO2 Injectors

Producers Water InjectorsCO2 Injectors

Figure 3.3: Two SSWG Injection Patterns; Top View

ide View (EnCana) Figure 3.4: SSWG injection patterns, S

31

3.4 CO2 Source

In the U.S., CO2 gas is relatively easy to purchase through a pipeline network.

eyburn CO2 project, the gas needed for injection was delivered across the U.S.-

Canada border via a 325 km pipeline from a coal gasification plant in North Dakota. The

gas was a by-product of the coal gasification process. The CO2 gas was discharged

e atmosphere before the CO2 project was undertaken at Weyburn. Weyburn is

expected to receive a cumulative CO2 volume of 2.7 million cubic meters.

For the W

CO2

into th

3.5 CO2 Sequestration

The greenhouse effect that increases the global temperature of the earth has been

released into the atmosphere

prevents radiation from escaping back into space. Most scientists believe that the trapped

radiation causes the temperature of the atmosphere to increase. The main source of CO2

the burning of fossil fuels at stationary industrial sources such as power plants and

m

burn Field has attracted

debated in recent years. Scientists have found that CO2

is

natural gas processing plants. In the International UN climate conventions in Rio (1992),

Kyoto (1997), and Buenos Aires (1998), a goal among industrial countries was set to

reduce their greenhouse gas emission by approximately 5% compared with the 1990 level

(Lindeberg and Taber 2000). Since then, the sequestration of CO2 has been studied fro

engineering as well as environmental perspectives (Wigley, Richels et al. 1996;

Lindeberg and Taber 2000; Fanchi 2001; Ennis-King and Paterson 2002; Nguyen and

Allinson 2002; Moritis 2003).

In the petroleum industry, CO2 injection as an EOR method has been studied

since the 1950’s. In the U.S., especially in West Texas, many CO2 injection projects

have been implemented successfully. The CO2 gas is produced from the underground

reservoirs, and delivered through a pipeline network to wherever the demand for the gas

exists (Moritis 2003). The CO2 injection project at the Wey

32

attention from the petroleum industry because its CO2 source is an industrial coal

gasific

3.6

ation plant (Bachu and Shaw 2003; Fisher, Sloan et al. 2003; Moritis 2003). The

Weyburn CO2 injection project is important not only for its EOR performance, but also

because of its importance to environmental interests. The sequestration of CO2 in the

Weyburn Field is beyond the scope of this research, but it should be considered in future

studies.

CO2 Injection and Production Response

uish each injection pattern from the others, a name is assigned

to each

2 in

ist of the

ulation model will be used after that.

In order to disting

pattern as shown in Figure 3.5. Since the beginning of CO2 injection in October

2000, there has been a significant difference in the cumulative injection volume of CO

each pattern. Figure 3.6 shows the cumulative CO2 injection volume of each pattern up

to the second seismic survey in October 2001. The largest volume of CO2 has been

injected into the South pattern, and the least into the North. The East and the West

patterns have received comparable quantities of the gas.

In this section, the CO2 injection and production responses of each pattern are

discussed separately. In Weyburn Field, the actual well names are all numeral. This can

lead to confusion as to whether a well is a producer or an injector. Thus, EnCana has

designated the letters to classify wells in the simulation model. Table 3.1 is the l

letters and its meanings. The actual well names are listed at the beginning; then the

aliases using the letters in the sim

33

Figure 3.5 Pattern name assignment

Figure 3.6: Cumulative CO2 injection volume up to the second survey in 2001.

2.4 BCF

1.8 BCF

1.4 BCF

0.5 BCF

2.4 BCF

1.8 BCF

1.4 BCF

0.5 BCF

South

West East

North

South

West East

North

34

Table 3.1: Th

Lette

e list of designated letters in order to classify wells

rs Meanings

OP- Oil producers

WI- Water injectors

CD- CO2 injectors

WG- WAG injector

## H ## (# = numbers) Horizontal well

3.6.1 The South Pattern

of the CO2 injection well 191/10-12-006-14 (CD-

10H12) and horizontal producers (identified by the letters OP). As shown in Figure 3.6,

the South pattern was injected with the largest volume of CO2 of the four patterns.

/day

t to the injector

2

um rate of

100 m ay, which is approximately 900% increase. As the oil rate increased, the rate of

water production decreased. This is a typical production response of the EOR process.

Figure 3.7 shows the location

Figure 3.8 shows the injection and wellhead pressure history of the well CD-

10H12. The injection rate started at about 120 Mscm/day with the pressure at wellhead 7

MPa. After several months of shut-in period from the end of 2000 to the beginning of

2001, the rate increased to 200 Mscm/day, and it continued to increase to 260 Mscm

as the wellhead pressure also rose to 12 MPa in August 2001. Then, in October 2001, the

RCP shot its second seismic survey.

On the production side, both horizontal producers located adjacen

have responded to the CO2 injection nicely. Figure 3.9shows the production history of

well 192/09-12-006-14 (OP-09HB12), which is located south of the injector. The oil

production started to increase in April of 2001, after six months of CO injection. The oil

production rate continued to increase until August 2001 and reached the maxim3/d

35

Well 191/01-13-006-14 (OP-01H13) located north of the injector has shown

similar prod sponse (Figure 3 il rate increased sharply after nine

months of CO and the m of oil production was about 900%.

Compared to OP-09HB12, it took a couple of months longer for OP-01H13 to respond.

Notice that th ease of the oil jection in these producers is rather

dramatic.

of the South Pattern

13

uction re .10). The o

2 injection, aximum increase

e incr rate due to CO2 in

CD-10

Figure 3.7: Horizontal Well locations

OP-09H12OP-10H12

OP-09HB12

OP-01H

H12

OP-09H12OP-10H12

OP-09HB12

OP-01H13

CD-10H12

36

20

400

300

500

12

9

15

0

100

0

6

3

0

Inje

ct

Wel

lhea

d In

ject

io

ion

Rat

e (M

scm

/day

)

n Pr

essu

re (

Mpa

a)

Figure 3.8: Injection rate pattern

Figure 3.9: Production history of well OP-09HB12

and wellhead pressure of CO2 injector, CD-10H12 in the South

O il (m 3/day) W ate r (m 3/d ay) G as (M scm /day)O il (m 3/day) W ate r (m 3/d ay) G as (M scm /day)O il (m 3/day)O il (m 3/day) W ate r (m 3/d ay)W ate r (m 3/d ay) G as (M scm /day)G as (M scm /day)

2000 2001 2002 20032000 2001 2002 2003

0

100

0

6

3

0

20

400

300

500

12

9

15

Inje

ctio

n R

ate

(Msc

m/d

ay)

Inje

ct

Wel

lhea

d In

ject

io

ion

Rat

e (M

scm

/day

)

n Pr

essu

re (

Mpa

a)W

ellh

ead

Inje

ctio

n Pr

essu

re (

Mpa

a)

37

O il (m 3/d a y ) W a te r (m 3/d a y ) G a s (M scm /d a y )O il (m 3/d a y ) W a te r (m 3/d a y ) G a s (M scm /d a y )O il (m 3/d a y )O il (m 3/d a y ) W a te r (m 3/d a y )W a te r (m 3/d a y ) G a s (M scm /d a y )G a s (M scm /d a y )

Figure 3.10: Production history of well OP-01H13

3.6.2 The East Pattern

Compared to the response of the horizontal producers in the South pattern, the increase in

creases of the production rate in both

The CO2 injector, 191/10-18-006-13(CD-10H18 in Figure 3.11) in the East

pattern injected 1.4 BCF of CO2, the third largest volume of the gas. Its injection rate and

pressure history is shown in Figure 3.12. The initial injection rate was about 100

Mscm/day with wellhead pressure of 4 to 6 MPa. The injection was stopped for about

five months, and then was resumed with higher wellhead pressure. The maximum

injection rate was achieved at 200 Mscm/day, and the rate started to decline with

decreasing injection pressure. The pressure was increased in July of 2002; however, the

rate has continued to decline since the maximum production rate was recorded.

The horizontal producers in the pattern have responded to CO2 injection (Figure

3.13 and Figure 3.14). They have shown the typical response of the EOR process.

oil production was not dramatic but rather gradual in

38

wells. The maximum increase of oil production rate for OP-15H18 and OP-15H18 were

about 300% and 500%, respectively. As for their response time, the well 191/15-18-006-

13 (OP-15H18) has responded in six months, and it took nine months for the well 191/08-

18-006-13 (OP-15H18) to respond to CO2 injection.

Figure 3.11: Well locations of horizontal wells in the East pattern

OP-08H18

OP-15H18

CD-10H18

OP-04H18

OP-08H18

OP-15H18

CD-10H18

OP-08H18

OP-15H18

CD-10H18

OP-04H18

39

Figure 3.12: Injection rate pattern

Figure 3.13: Production history of the well OP-08H18

O il (m 3/d ay)

and wellhead pressure of CO2 injector, CD-10H18 in the East

W ate r (m 3/d a y) G as (M scm /da y)O il (m 3/d ay) W ate r (m 3/d a y) G as (M scm /da y)O il (m 3/d ay)O il (m 3/d ay) W ate r (m 3/d a y)W ate r (m 3/d a y) G as (M scm /da y)G as (M scm /da y)

20

200

100

0

0

6

3

0

12

9

400

500 15

30

Inje

ctio

n R

ate

(Msc

Wel

lhea

d In

ject

ion

Pres

sure

(M

m/d

ay) pa

a)

00 2001 2002 20032000 2001 2002 2003

200

100

0

0

6

3

0

12

9

400

500 15

30

Inje

ctio

n R

ate

(Msc

m/d

ay)

Inje

ctio

n R

ate

(Msc

Wel

lhea

d In

ject

ion

Pres

sure

(M

m/d

ay) pa

a)W

ellh

ead

Inje

ctio

n Pr

essu

re (

Mpa

a)

40

O il (m 3/d ay) W ate r (m 3/d a y) G as (M scm /daO il (m 3/d ay) W ate r (m 3/d a y) G as (M scm /daO il (m 3/d ay)O il (m 3/d ay) W ate r (m 3/d a y)W ate r (m 3/d a y) G as (M scm /daG as (M scm /da y)y )y )y )

Figure 3.14: Production history of the well OP-15H18

3.6.3 The West Pattern

The West pattern was injected with the second largest volume of CO2. Figure

3.15 is the injection rate and wellhead pressure history of well 191/04-13-006-14 (CD-

04-13). Unlike the previous two injection wells, the injection pressure was much higher

from the beginning, about 10 MPa. The maximum injection rate was about 200

Mscm/day in October 2001 with relatively high pressure. After the maximum rate was

set, it rapidly declined despite high injection pressure.

In spite of the high injection volume in the West pattern, none of the surrounding

producers has shown any significant response as of September 2003. One of the reasons

is that there was communication between the CO2 injector and the water injector located

between the branches of the bilateral CO2 injector. Due to the communication, it was

suspected that the gas was being injected into other formations through the water

41

injection well. EnCana acknowledged the problem and fixed it at the water injection

and wellhead pressure of CO2 injector, CD-04H13 in the West pattern

well. The evidence for this loss of CO2 is discussed more in Chapters 4 and 5.

Figure 3.15: Injection rate

3.6.4 The North Pattern

This pattern was injected with the least amount of CO by far. As shown

Figure 3.16, the injection rate of well 191/04-19-006-13 (CD-04H19) reached 100

Mscm/day only at the beginning of the injection period.

2 in

Notice that the injection

pressur

n

2000 2001 2002 2003

200

100

400

300

500

6

3

0

12

9

15

e is significantly higher from the beginning, and it has been maintaining the high

pressure. This well also had many operational problems, which was reflected in many

shut-in periods that contributed to the low injection volume. Not surprisingly, due to the

low injection volume, none of the adjacent producers has shown any sign of productio

increase.

0

Inje

ctio

n R

ate

(Msc

m/d

ay)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

2000 2001 2002 2003

200

100

400

300

500

6

3

0

12

9

15

0

Inje

ctio

n R

ate

(Msc

m/d

ay)

Inje

ctio

n R

ate

(Msc

m/d

ay)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

42

Figure 3.16: Injection rate and wellhead pressure of CO2 injector, CD-04H19 in the North pattern.

2000 2001 2002 2003

200

100

0

400

300

6

3

0

12

9

5500 1

Inje

ctio

n R

ate

(Msc

m/d

ay)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

2000 2001 2002 2003

200

100

0

300

6

3

0

12

9

5

400

500 1

Inje

ctio

n R

ate

(Msc

m/d

ay)

Inje

ctio

n R

ate

(Msc

m/d

ay)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

Wel

lhea

d In

ject

ion

Pres

sure

(M

paa)

43

Chapter 4

ENCANA RESERVOIR SIMULATION MODEL OF

WEYBURN

4.1 Introduction

Reservoir simulation has been used to characterize actual oil and gas reservoirs

since the 1960’s. The simulator is a useful tool to model fluid flow, to forecast the fu

ormance of wells, and to estimate the remaining life of the reservoir. With the aid of

powerful and fast personal computers, the reservoir simulator has become more

accessible to many engineers and geoscientists. In recent decades, reservoir models have

ture

perf

e models consist of millions of grid cells to model reservoirs today.

Reservoir models are built using well logs, core data, pressure transient test data,

and other data that can characterize the reservoir. Well logs and core data can define

geological properties in very fine scale, as small as inches, however, the area that is

drilled in a reservoir covers just a tiny fraction of the total reservoir area. Therefore,

creating a model based on such data becomes problematic. Pressure transient test data,

such as build-up and drawdown tests, can provide us reservoir properties, mainly

permeability, beyond the region near the wellbore. However, the obtained results are

average values, and cannot be used independently to create a fine-scaled model. In

addition, well tests are not always available for all wells in a field. With a limited

amount of data, geological properties throughout the reservoir need to be estimated using

available data points. Among the techniques that can be used for interpolating or

extrapolating data are deterministic and geostatistical approaches.

also become more detailed and complicated to improve their representation of real

reservoirs. Som

44

In addition to well logs, cores, t data, a 3-D seismic survey is a very

valuable measur odel.

Multiple 3-D seismic surveys in a 4-D is provide even more useful

information for verifying the accuracy of existing models.

and well tes

ement for improving the accuracy of the flow simulation m

seismic analys

4.2 Summary

Sandy Graham, an EnCana engineer, completed the history match of EnCana’s

simulation model up to the commencement of CO2 injection in October 2000. The

overall match is decent except in some horizontal producers and corner wells. However,

when the CO2 injection case was simulated using the matched model, the calcula

production of horizontal wells in the South pattern, especially simulated CO

ted gas

4.32

formati

results.

ction

ntal

igure

formation even

though the gas was injected into the Marly formation.

2

breakthrough, was significantly different from the actual gas production (see Figure

and Figure 4.33). Detailed analysis indicated that gas migrated down to the Vuggy

on and stayed there even though CO2 injectors were completed in the Marly

formation. The report author argued that CO2 reached adjacent producers through the

formation due to the high permeability of the Vuggy formation. This caused the CO2

breakthrough and resulted in the bypassing of targeted oil in the Marly formation (see

Figure 4.35).

The match of horizontal well production in the East pattern gave different

The horizontal wells had lower gas production rates than the wells in the South pattern

(see Figure 4.36 and Figure 4.37). History match modifications included the introdu

of a barrier in the model between Marly and Vuggy formations around these horizo

producers. The barrier prevented pressure support from Vuggy and caused an abnormal

low pressure zone (see Figure 4.31). The cross sectional view of the pattern (see F

4.35) revealed that most of the injected CO2 remained in the Vuggy

45

4.3 Reservoir Simulation Model by EnCana

Prior to the commencement of CO injection, a reservoir sim2 ulation model was

created by a group of engineers and geoscientists in EnCana. Phase I of the project was

to inject CO2 into nineteen patterns, of which nine injection patterns were covered in their

l. Since it is a CO2 injection project, a compositional PVT model was

needed

erived

ta

er

ation run-time. The X and Y grid sizes of the upscaled simulation model

are 60

ur

tterns in the southern area in the

simulation model (Figure 4.1).

simulation mode

to accurately simulate the enhanced oil recovery process.

The simulation model was created in the Stratamodel, which consists of a

stratigraphic and structural framework based on geologic formation and flow unit tops

derived from log and core analysis. The framework was than populated at each well with

the matrix petrophysical data, such as porosity, permeability, and saturations, d

from core analysis. Where core data was unavailable, statistical algorithms were used to

obtain the information needed between data points. This petrophysical data was then

used to deterministically populate the interwell space using interpolation between da

points.

This model is the source of EnCana’s original OOIP calculations within those

nine patterns, and used for pattern forecasts. It was then upscaled to coarse grids in ord

to reduce simul

meters by 60 meters, and are constant in the model. A corner-point gridding

scheme was necessary in building the model to honor the varying thicknesses of each

layer as well as occasional pinch-out layers. The simulation model includes the two

major geological units: Marly and Vuggy. Marly was divided into six layers, whereas

Vuggy comprised the bottom seven layers. Different relative permeability curves are

assigned to those rock types to account for their different flow characteristics. The

simulation covers nine injection patterns, while the RCP survey area includes only fo

injection patterns. The overlap of those areas is four pa

46

The boundary condition for the flow model is no-flow at the boundaries. Thus,

ned allocation factors by EnCana. The

allocation factors were essentially geometric: 0.5 was assigned for wells located in a

boundary grid block and 0.25 for wells located

le

wells located at the model boundaries were assig

in corner grid blocks of the model.

Figure 4.1 Simulation Area and RCP Survey Area

The number of grid cells in the model is 60 by 60 by 15, which includes Mida

Evaporite in layer 1 and Frobisher Beds in layer 15; therefore, the actual reservoir of

interest is from layer 2 down to layer 14. The layer assignment for each sub formation

with in the reservoir is shown in Table 4.1.

Simulation Area

RCP Survey Area

Simulation Area

RCP Survey Area

47

Table 4.1 Layer Assignment of Encana’s Simulation Model

Layers Sub-Formations

1 Midale Evaporite

2 M1 3 M2 4 M3_A 5 M3_B 6 M3_C

7 V1 8 V2_1 9 V2_2

10 V3 11 V4 12 V5 13 V6 14 V7

15 Frobisher

4.4 Natural Fractures

Natural fractures have high permeability values, often in the range of 1 darcy or

ince the permeability and porosity

distributions in the simulation model were derived from cores and well logs, the role of

existing

more if they are open to flow. In EnCana’s model, s

natural fractures was not considered in the permeability determination.

Therefore, the permeability values in the model were limited to the range of core

permeability values.

48

4.5 Weyburn Equation of State (EOS) Model

For this reason, a black-oil

PVT model was considered unsuitable to simulate the complicated phase behavior of the

CO2 miscible injection , an EOS was developed to simulate the

process. The EOS used in the EnCana Weyburn model is the Peng-Robinson EOS,

which is shown in the following equation:

The Weyburn project involves miscible CO2 injection.

process. Therefore

( ) ( )bVbbT

++VVbVRTP

−−

−= Equation 4.1

Here P is th ressure, T is the temperature, V is the volume, and R is the gas constant.

The aT is the temperature-dependent parameter that includes other internal variables, and

b is the critical-property-dependent parameter. Within the parameter aT, several variables

need to be modified to match the phase behavior of the actual hydrocarbon system.

The original Peng-Robinson EOS had a problem accurately estimating the

properties of ration. Thus, the volume shift parameter was

introdu d in the EOS to improve the estimation of liquid properties in the EnCana

model. Further details of the EOS can be found in the ECLIPSE Manual-Technical

Description (Schlumberger 2003).

ple was taken from well 191/12-18-006-13W2 and than

analyze

educed

ever, had an error in calculating oil viscosity below the fluid’s

a

e p

liquid, such as density and satu

ce

A reservoir fluid sam

d by three different laboratories: Hycal, SRC, and IFP. All three labs came up

with different PVT values. Each of the three laboratory measurements is considered

equally valid. The EOS model for the Weyburn was created by EnCana based on those

lab measurements. The initial PVT model had ten components, which was later r

to seven components to reduce computation time of the simulation runs. The 7-

component model, how

49

bubble point pressure. Also, the actual simulation run was greatly hindered when the

d.

CO2

an validated through simulations of slim tube

experiments to confirm that the minimum miscibility pressure (MMP) is consistent with

easured values through both rising-bubble and slim tube experiments (Adair 2003).

The measured MMP of Weyburn Field is 14.5

simulation of the CO2 injection process was starte

A new EOS was created by Ryan Adair at EnCana in 2002. For the EOS tuning,

it was matched to conventional PVT experiments such as differential liberation based on

the Hycal lab data, which was scaled down to be consistent with the SRC experiment.

Furthermore, the EOS was matched to the single and multi-contact experiments with

at 15.5 MPa. The tuned EOS model was th

m

MPa or 145 Bars.

4.5.1 Water Density Calculation

The original PVT data had specified water properties such as the formation

volume factor, viscosity, compressibility, and viscosibility. Since water density was not

specified externally, the simulation assumed the water density to be 999.014 kg/m3

interna alinity

ly 66

t in

density difference between water and CO2 is

pronou

lly. However, the Weyburn report (EnCana 1997) states that the observed s

of produced water in the field was 85,000 ppm total dissolved solids (TDS). Using a

chart shown in McCain (1990), the water density was determined to be approximate

lb/ft3, which is equivalent to 1057 kg/m3. This water density discrepancy is importan

the CO2 injection process since the

nced.

4.6 Relative Permeability Curves and Endpoints

The relative permeability curves are obtained from actual laboratory

measurements and scaled down to the new endpoints (Eddy, Edmunds et al. 1997).

Figure 4.2 and Figure 4.3 show the relative permeability curves of the Marly and Vuggy

50

formations. In EnCana’s history match, the relative permeability of water in the Marly

formation was scaled down to half of the original values throughout the saturation rang

which reduce the mobility of water in the formation co

e,

mpared to the mobility of oil.

Endpoints are measured from multiple cores before and after the core flood

experiments (Eddy, Edmunds et al. 1997). The residual oil saturations to waterflood

(Sorw) in Marly and Vuggy were determined to be 39% and 36%, respectively, and the

irreducible water saturations (Swr) were 36% for both formations.

Marly Relative Permeability Curves

0

0.1

0.2

0.3

0.4

0.5

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Sw

kr

0.6

0.8

0.9

1

0.7

kro

krw

Figure 4.2: Relative permeability curves of the Marly formation

51

Vuggy Relative Permeability Curves

0.8

0.9

1

0

0.1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Sw

0.2

0.3

0.4

0.5

0.6

0.7

kr

kro

krw

Figure 4.3: Relative permeability curves of the Vuggy formation

4.7 History Match by EnCana

Sandy Graham, an engineer at EnCana, was in charge of history matching the

lation model to the actual production history. The history match was perform

the beginning of oil production in 1956 up to 2000, prior to CO2 injection. The

of the model involved permeability, porosity, and some well comp

changes. Water relative permeability, krw, was also modified by using end-point s

which resulted in reducing the relative permeability in the Marly formation by half

simu ed

from

modification letion

caling,

throughout the saturation range.

he modification of permeability and porosity was done both globally as well as

locally. The global change was to reduce the vertical permeability of Marly and Vuggy

to one- the original values, and to multiply by 0.4 to the original value of

horizontal permeability in Marly.

T

tenth of

52

The local modifications surrounded the wells in order to match the production and

he locations of modifications in EnCana’s model are shown in Figure 4.4 and

Figure 4.5. These local modifications, especially of porosity, influenced the calcu

pedance values since they are a function of porosity in Gassmann’s theory (see

Chapter 5.3). The ECLIPSE data file that contains the modifications in the model is

attached in the Appendix.

injection. T

lated P-

im

ns Figure 4.4: Shaded areas indicate the locations of permeability and porosity modificatioin Marly. Color filled cells in red, green, and blue represent CO2 injectors, producers, and water injectors, respectively

53

Figure 4.5: Shaded areas indicate th odifications in Vuggy. Color filled cells rep

4.7.1

e locations of permeability and porosity mresent well locations.

Waterflood History Match

The waterflood started in 1964 with inverted

had responded differently depending on their loca

wells in the RCP survey area are shown in Figure 4.6. The area is

nine-spot patterns. Vertical wells

tions relative to water injection wells.

The locations of

Natural fracture sets are known to exist in the Weyburn Field. The fracture set

that is oriented N45˚E is the dominant natural fracture in the field (see Chapter 2). Thus,

vertical oil producers located on (parallel to) and off the fracture orientation responded

differently to the water injection in the field. The N45˚E orientation is called the “on-

trend” direction and fracture orientation other than the “on-trend” fracture set (usually

perpendicular to the “on-trend” fracture set) is called “off-trend” (Eddy 1998). Figure 4.6

also shows these trends on the map.

divided into four different patterns, and the history match result of each pattern is

discussed separately here.

54

Figure 4.6: Location of wells in the RCP survey area and natural fracture trends

he history match results are shown in the production plots of individual wells.

Each plot contains both calculated and actual production rates of oil, water, and gas.

colors: oil in green, gas in red, and water in blue.

Table 4

in production plots

On trend Off trendOn trend Off trend

T

They are represented by the following

.2 summarizes the attributes used in those plots. Theses attributes are used

throughout the thesis.

Table 4.2: List of attributes

Calculated History

Oil WOPR (well oil production rate)

WOPRH (well oil production rate history)

Gas WGPR (well gas production rate)

WGPRH (well gas production rate history)

Water WWPR (well water production rate)

WWPRH (well water production rate history)

55

4.7.1.1 The South Pattern

ttern are shown in Figure 4.7. In the

middle of the pattern, w I-16-12) was originally an oil

producer, wh the inverted nine spot

pattern. We and Well 101/10-12-006-14(OP-10-12) are

located NE and SW of th s of these wells,

relative to the water injec as the natural fracture set

trend in both Marly and Vuggy. W P-02-13) and 101/12-07-

006-13 (OP-12-07) are located NW

fracture set perpendicular to th , or “off-trend”.

Figure Location vert s in the South pattern

re 4 histo f oil,

water, and gas of wells OP-04-18 and OP-10-12, which are located in the on-trend

direction relati a ction

The vertical well locations of the South pa

ell 101/16-12 (OP-16-12 or W

ich was converted to a water injector in 1964 to form

ll 101/04-18-006-13 (OP-04-18)

e water injector, respectively. The location

tion well, are in the same orientation

ells 101/02-13-006-14 (O

and SE, which is the orientation of the natural

e direction of the other fracture set

WI-16-12

OP-04-18

OP-14-12

OP-02-13

OP-12-07

OP-14-07

OP-08-13

OP-10-12

OP-08-12

WI-16-12

OP-04-18

OP-14-12

OP-02-13

OP-12-07

OP-14-07

OP-08-13

OP-10-12

OP-08-12

4.7: ical well

Figu .8 and Figure 4.9 show the ry and calculated production rate o

ve to the injection well. The m tches of history and calculated produ

56 56

greement in both wells. The off-trend wells, OP-02-13 and

OP-12- e

h

3

water

4.4

and Figure 4.5. Since the calculated production rate was constrained by total liquid rate,

when the water production rate was calculated low, the oil production was calculated

response while dev ter.

production rate m

measuremen

the low econom was not as

valuable a comm

of oil and water are in close a

07 (Figure 4.10and Figure 4.11) also show reasonable history matches, except th

slightly early water breakthrough in the history of well OP-02-13. Figure 4.12 throug

Figure 4.15 are the plots for wells 101/08-13-006-14 (OP-08-13), 101/14-07-006-13 (OP-

14-07), 101/08-12-006-14 (OP-08-12), and 101/14-12-006-14 (OP-14-12). These wells

are located at the corners of the South pattern. The history matches of wells OP-08-1

(Figure 4.12) and OP-08-12 (Figure 4.14) are acceptable. However, the water production

of well OP-14-07 (Figure 4.13) and well OP-14-12 (Figure 4.15) during the waterflood

response period where water production starts to increase are lower than the actual

production, despite the modifications around those wells that can be seen in Figure

much higher than the actual rate. The same behavior was observed for the waterflood

eloping a new history match. This will be discussed in a later chap

Even though the oil and water production rates were matched reasonably well, gas

atches were always off. A possible reason for this is that the gas

t back in the early days of the production was not collected accurately due to

ic interest in gas production. Unlike in recent decades, gas

odity as oil; therefore, oil companies paid less attention to gas.

57

Figure 4.8: Production plot of well OP-04-18


58



59

Figure 4.12: Production plot of well OP-08-13)


60



61

4.7.1.2 The East Pattern

The vertical well locations of the East pattern are shown in Figure 4.16. Well

101/06-18- 006-13 (OP-06-18) was the oil producer, which, as noted earlier, was

converted into a water injector in 1964 in order to form the inverted nine spot pattern.

The well 101/10-18-006-13 (OP-10-18) is located in the on-trend direction, and wells

101/12-18- 006-13 (OP-12-18) and 101/02-18-006-13 (OP-02-18) are in the off-trend

direction. The corner wells are 101/14-18-006-13 (OP14-18) and 101/08-18-006-13 (OP-

08-18). Wells OP-04-18, OP-08-13, and OP-14-07, which are located in the border of

South and East patterns, were covered in the previous section.

Figure 4.17 through Figure 4.21 are the history match results of the vertical wells

in the East pattern. The matches of oil and water production are in close agreement in the

the

, the matches were excellent compared

atches of some corner wells in the South pattern. However, still the gas

production was much higher than the actual when the waterflood response started to

Figure 4.16: Location of vertical wells in the East pattern

on trend and off trend wells. As for corner wells

to the m

show.

OP-02-18

OP-10-18

OP-08-18

OP-14-18

OP-08-13

OP-04-18

OP-12-18

OP-14-07

WI-06-18

OP-02-18

OP-10-18

OP-08-18

OP-14-18

OP-08-13

OP-04-18

OP-12-18

OP-14-07

WI-06-18

62 62



63



64


4.7.1.3 The West and North Pattern

The time-lapse P-impedance data described in the previous chapter revealed tha

its apparent anomalies could be identified alongside of the CO2 injectors in the South and

East patterns. In the West pattern, the anomaly was concentrated around the water

tor, WI-06-13, despite the large volume of the injected gas. It is apparent that the

2 was not displacing the reservoir fluids; instead, the CO2 was lost into other

mations. This deters the application of the time-lapse P-impedance data toward the

reservoir modification. The same can be pointed out for the North pattern since the

pattern has received the least amount of CO2 by far, which resulted in no apparent

alies due to the CO2 injection. Thus, the idea of incorporating the time-lapse

ic data into the flow simulation to improve the existing flow simulation model was

t

injec

CO

for

anom

seism

applied only to the South and East patterns.

65

4.7.2 Horizontal Wells History Match

The horizontal well drilling program started in 1991 in order to recover the

bypassed oil in the Marly formation. Most of the horizontal wells, including CO2

injectors, were drilled parallel to the direction of the major fracture set, i.e., N45˚E.

Since the CO2 injection was started in 2000, there are nine years or fewer of the

production history, depending on the well, that needed to be matched. As in the previous

section, the result of the history matches are presented separately

4.7.2.1 The South Pattern

The well locations of the horizontal wells are shown in Figure 4.22. , well

191/10-12-006-14 (CD-10H12) is the CO2 injector with two horizontal legs, which is

located in the middle of the pattern. Well OP-01H13 is located on the northwest, and the

well OP-09HB12 is on the other side of the injector. Well OP-09H12 is located furthe

the injection well. Well OP-10H12 was drilled perpendicular to the direction of

jor fracture set. It is located at the southern boundary of the pattern.

Figure 4.23, Figure 4.24, and Figure 4.25 are the history match results of th

OP-01H13, OP-10H12, and OP-09H12, respectively. Their history match results are

good. The well OP-09HB12 was drill relatively late in the horizontal drilling program

Thus, there are only few data points to match (Figure 4.26). The calculated oil

production rate is much lower than the history, and the production rate of water is the

opposite.

r

SE of the

ma

e wells

.

66

OP-09H12OP-10H12

OP-01H13

OP-09HB12

CD-10H12

OP-09H12OP-10H12

OP-01H13

OP-09HB12

CD-10H12

Figure 4.22: Location of orizontal injector and producers in the South Pattern

Figure 4.23: Production plot of well OP-01H13

67



68

Figure 4.26: Production plot of well OP-09HB12

4.7.2.2 The East Pattern

The locations of horizontal wells are shown in Figure 4.27. Production rates of

the well OP-08H18 (Figure 4.28) were matched reasonably, but the matches of the well

OP-15H18 (Figure 4.29) were not as good as the others were. Even though these

tches were made, when the reservoir pressure at the end of history match was

ined, the pressures at these wells were abnormally lower than the other area (Fig

4.31). When the area of the low pressure and the area of the permeability modification

were put side by side, both areas were identical, indicating that the low pressure was most

ly due to the reservoir parameter modifications. The modification was to set the

vertical permeability in the lower Marly and whole Vuggy zones (layer 5 through 14

ma

exam ure

like

; see

ractically zero permeability in order to

gy. The effect of this establishment of

e flow barrier between the two formations will be discussed in later chapters.

Table 4.1) in the area of the wells to 0.001 md; p

prevent communication between Marly and Vug

th

69

Well 191/04-18-006-13 (OP-04H18) was drilled perpendicular to the direction of

the m

ma tch of

perm eability

OP-08H18

OP-15H18

Figure 4.27: Well locations of horizontal wells in the East pattern

CD-10H18

OP-04H18

OP-08H18

OP-15H18

CD-10H18

OP-08H18

OP-15H18

CD-10H18

OP-04H18

ajor fracture set. They are located at the boundary of the pattern. The history

tch of the well OP-04H18 is shown in Figure 4.30. Even though the history ma

the oil is reasonably close, the match is water is significantly off. The vertical

eability was set to 0.01 along the well trajectory. The effect of vertical perm

is discussed extensively in the later chapters.

70



71


Figure 4.31: Pressure (barsa) at the end of history match in M3_A layer

OP-15H18

OP-08H18

0

150

300

OP-15H18

OP-08H18

0

150

300

72

4.8 Forecast Results of EnCana’s Simulation Model

The CO2 injection process running October 2000 through October 2002 was

ulated using EnCana’s history matched model. The simulation results of horizontal

producers are presented here for each pattern separately. The West and North patterns

are not presented here since there was no production response observed in the field.

sim


Figure 4.32 and Figure 4.33 show the results of the production forecast of the well

OP-01H13 and OP-09HB12. The timing of the calculated oil production increase in both

wells were slightly late than the actual, and the calculated oil production were lower than

the history. The most noticeable discrepancy was the gas production. The significant

increase in gas production indicates the CO2 breakthrough.

4.8.1.1 Placement of CO2 in the South Pattern

Figure 4.34 shows the CO2 mole fraction in the liquid phase in one of the main

Marly layers and the Vuggy layers after one year of the gas injection. These pictures

indicate that the CO2 front in the Vuggy is farther ahead of the front in the Marly

formation. This observation contradicts what the P-impedance picture presented in the

previous chapter. Furthermore, when the cross-sections of the South patterns (Figure

4.35) was examined, the picture revealed that the injected CO2 at CD-10H12 reaches both

producers (OP-01H13 and OP-09HB12) through the Vuggy formation, bypassing the

targeted oil in the Marly formation. Even though the CO2 was injected into the Marly

formation, it migrated down to the Vuggy formation, remained in the Vuggy, and reached

horizontal producers causing the CO breakthrough. 2

73

O c t. 2 0 0 0 O c t. 2 0 0 1 O c t. 2 0 0 2O c t. 2 0 0 0 O c t. 2 0 0 1 O c t. 2 0 0 2

Figure 4.32: Production match of well OP-01H13


Figure 4.33: Production match of well OP-09HB12

74

Figure 4.34: The South pattern, liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right)

Figure 4.35: Cross section of the South pattern showing CO2 mole fraction in liquid phase. Notice that all horizontal wells are positioned in the Marly zone

Marly

Vuggy

OP-01H13 OP-09HB12CD-10H12

Marly

Vuggy

OP-01H13 OP-09HB12CD-10H12

0

1Marly 3A Vuggy 2A

0

1Marly 3A Vuggy 2A

75

4.8.2 The East Pattern

Figure 4.36 and Figure 4.37 are the results of the production forecast for wells

OP-08H18 and OP-15H18. Recall that the production matches of these wells before

CO2 injection was reasonably close (Figure 4.29 and Figure 4.28). Both wells show oil

production increase due to CO2 injection; however, the production rates were lowe

the actual throughout the CO2 injection period, especially well OP-15H18. The gas

production rates were also much lower than the history.

Figure 4.31 showed abnormally low pressure at these wells, and it was suspected

due to low vertical permeability between Marly and Vuggy. The production mism

during the CO2 injection period seems to be caused by the same modification around

these wells.

the

r than

atch

4.8.2.1

Placement of CO2 in the East Pattern

in

th

Figure 4.38 shows the CO2 mole fraction in the liquid phase in one of the ma

Marly layers and the Vuggy layers after one year of CO2 injection. These pictures

indicate that the CO2 front in the South pattern Vuggy formation was ahead of the front in

the Marly formation. The CO2 had reached adjacent horizontal producers in the Sou

pattern, however, the CO2 did not reach the horizontal producers in the East pattern,

which can be confirmed by the cross sectional picture of the pattern (Figure 4.39).

76





77

Figure 4.38: The East pattern, liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right)

Figure 4.39: Cross section of the East pattern showing CO2 mole fraction in liquid phase. Notice that all horizontal wells are positioned in the Marly zone

Marly

Vuggy

OP-15H18 OP-08H18CD-10H18

Marly

Vuggy

OP-15H18 OP-08H18CD-10H18

0

1Marly 3A Vuggy 2A

0

1Marly 3A Vuggy 2A

78

4.9 Cumulative Production

The cumulative production volume of each phase in the South pattern is shown in

Figure 4.40. Notice that there is a mismatch of oil and water production volumes,

starting in day 6,000. This is due to the production rate mismatch at corner wells in the

pattern. The discrepancy in the cumulative gas volume is more pronounced than the

discrepancy in the cumulative oil volume. However, the difference is almost constant

once it was established. This is probably because produced gas was not measured

ctly early in the life of the field. The cumulative gas volume also shows the early

breakthrough of CO2 from the horizontal producers near the end of the curve.

As for the cumulative production volume for the East pattern (Figure 4.41), the

tches of oil and water production are excellent, except for the difference in water

corre

ma

erence is due to the water production

ismatch of the horizontal wells, OP-15H18 and OP-04H18, as shown in Figure 4.29 and

igure 4.30. Calculated water production at well OP-04H18 was much lower than

production beginning around day 14,000. The diff

m

F

observed production.

79

E a r ly b re a k th r o u g h

D u e to m is m a tc h a t c o rn e r w e lls

E a r ly b re a k th r o u g h

D u e to m is m a tc h a t c o rn e r w e lls

Figure 4.40: Cumulative production volume of the South pattern.

W a te r p ro d u c t io n ra te m is m a tc h o f H Z w e llsW a te r p ro d u c t io n ra te m is m a tc h o f H Z w e lls

Figure 4.41: Cumulative production volume of East pattern

80

81

Chapter 5

FORWARD MODELING AND P-IMPEDANCE

DATA

5.1 Introduction

One of the goals of this work was to integrate static and dynamic data from

multiple disciplines. This means that results from the flow simulation need to be

pared to the actual P-impedance data. Direct comparison of flow simulation resu

with P-impedance data requires using rock physics modeling. With the flow modeling,

pressure and saturation changes can be related to seismic responses. The idea is to obtain

com lts

two different seismic

urveys, then to calculate corresponding seismic attributes based on the pressure and

saturation distributions. The difference in the seismic attributes can be compared to

5.2

pressure and saturation changes from the flow simulation between

s

actual seismic attributes to evaluate how realistic the flow simulation model is.

In this chapter, the rock physics modeling for Weyburn Field is presented in

Section 5.3. Then, Section 5.6 discusses the P-impedance change due to CO2 injection.

Section 5.4 presents a method to optimize the simulation model using the P-impedance

data by means of the objective function.

Summary

In order to effectively utilize the P-impedance data calculated by Herawati,

Gassmann’s theory was used to calculate the P-impedance values based on flow mode

results. The equations in the theory, KDRY and µDRY, were corrected by Brown for the

l

application in Weyburn Field.

82

The actual time-lapse P-impedance data show that apparent anomalies, the P-

impedance change, are present in the Marly formation in the South and East patterns.

The anomalies in the East and North patterns are almost negligible in the Marly

formation. The anomalies in the Vuggy formation are also evident in the South and East

patterns; however, the areal extent of the anomalies is less than in the Marly formation.

The West pattern shows an anomaly in the Vuggy formation. It is limited to the area

around the vertical injector, which is located between the branches of the CO2 injector.

This suggests that the injected gas migrated from Marly down to Vuggy, and possibly to

Frobisher through the water injection well. A study done by Galikeev has suggested gas

migration into Frobisher.

Once the P-impedance values are calculated using Gassmann’s theory, they need

to be compared to actual values. The degree of similarity between calculated and actual

P-impedance data is calculated using an objective function. The function includes the

similarity in the time-lapse P-impedance as well as the matches in the production rates.

The pictures of the calculated time-lapse P-impedance values show different

results than those provided by Herawati (Figure 5.7 and Figure 5.8). The change of the

P-impedance caused by the CO2 breakthrough is obvious at the horizontal producers.

The pictures of the calculated P-impedance shows the CO2 front within the reservoir.

The front is farther ahead in the Vuggy than in the Marly (Figure 5.9).

5.3 Rock Physics Modeling for Weyburn Field

Fluids in the rock change the P-wave velocity of the rock-fluid system by

influencing the density and the bulk modulus as in the following equation:

83

ρ3 µ4

+=

SAT

P

KV Equation 5.1

where Vp is the P-wave velocity, KSAT is the saturated rock bulk modulus, µ is the shear

modulus, and ρ is the bulk density (Schon 1996). The fluid has no effect on the shear

minor influence on shear-wave velocity, VS, as indicated in the

followi

modulus and has a

ng equation (McQuillin, Bacon et al. 1984).

ρµ

=SV Equation 5.2

Gassmann (1951) developed an expression for the bulk modulus from the theory

of elasticity of porous media.

21

M

DRY

MFL

MDRYSAT

KK

KK

KKK

−−

+

⎟⎠

⎜⎝+=

φφ Equatio

In the equation above, K

2

DRYK ⎞⎛1 ⎟⎜ −

n 5.3

k bulk modulus, KM is the mineral modulus, φ is

porosity, and KFL is the fluid bulk modulus. Leo Brown (2002) has performed the

iment using the cores from Weyburn Field to develop the petrophysical

model that is suitable for W

DRY is the dry roc

laboratory exper

eyburn. He found that pressure and porosity corrections are

needed for the dry rock bulk modulus and the shear modulus.

84

The equations for the pressure correction for Marly are:

11.133542.010325.110731.1 2234 ++×−×= −− PPPKDRY Equ

78.82989.010828.910157.1 2234 ++×−×= −− PPPDRYµ Equation 5.5

where the units of K

ation 5.4

Equation 5.6

core th e

on:

DRY and µDRY are GPa and the unit of pressure, P, is MPa. The

pressure-dependent moduli equations for the total Vuggy zone are:

23.322616.010560.2 23 ++−= − PPK xDRY

05.1910777.610437.8 224 ++−= −− PP xxDRYµ Equation 5.7

These equations were obtained from the measurement of ultrasonic velocities using a

at was taken outside of the RCP survey area. Brown suggested that when thes

equations are used in another area with different porosity, the calculated values must be

adjusted for porosity differences using the following equations. For the Marly formati

( )

( ) 015.050.31

=29.0 −= φφ

φ

DRYK5.8 DRYK Equation

( )

( ) 0807.017.329.0 +=

= φφµ1φµ

DRY

Equa

DRY tion 5.9

85

For the Vuggy formation:

( )

( ) 44.060.51

1.0 −=

= φφφ

DRY

DRY

KK Equation 5.10

( )

( ) 494.006.51

1.0 +=

= φφµφµ

DRY

DRY Equatio

n 5.11

The mineral modulus KM was determined previously by Brown. He extrapolated

dry rock moduli versus porosity relationships to zero porosity. For the Vuggy zone, this

yields KM of 72 GPa and M M M

conclusive (Reasnor 2001). Thus, µM was estimated to be 48 GPa, based on a range of

values

3) was estimated from the following equations: for

e Marly zone,

µ of 33.5 GPa. As for the Marly, K is 83GPa, but µ was

in

for dolomite provided in Mavko et al. (1998).

The Bulk density of rock (kg/m

th

29221890 +⋅−= φρDRY Equation

For the Vuggy zone,

5.12

27091650 +⋅−= φρDRY Equatio

Gassmann’s equation provides a simple model for determining the bulk modulus

of a rock with different fluids, a method known as “fluid subst

n 5.13

itution”. The theory is

based on isostress conditions for an isotropic, homogeneous, monominerallic rock at the

low frequency limit. The equation may not be appropriate to seismic modeling of

86

Weybu nisotropic. However,

rown concluded

Gassmann’s equation does not accurately reproduce the seismicmeasured on core velocities, perhaps due to frequency effects. However, it does reproduce the differences in seismic velocities due to fluid and pressure changes, so it is acceptable for fluid substitution on Weyburn reservoir romonitoring purposes.

rn Field since the reservoir is known to be fractured and a

B

velocities

ck for time-lapse

5.4 Computer Program to Calculate P-Impedance from Simulation Results

VISUAL BASIC with Microsoft EXCEL was used to calculate the P-impedance

values from the simulation results. The outputs of the s

saturations and densities of fluids, and total fluid compressibility.

The bulk density ρB is calculated from the following

imulation runs are pressure,

equation:

( )wwggooDRYB SSS ρρρφρρ ++⋅+= Equation 5.14

where So, Sg, and Sw are oil, gas , and water saturations, respectively. Similarly, ρo, ρg,

and ρw are oil, gas, and water densities.

The fluid modulus KFL is the inverse of total fluid compressibility, which is one of

the simulation outputs.

P-impedance Z is expressed by the following equation:

PB VZ ⋅= ρ Equation

here ρB is the bulk density, and VP is the P-wave velocity (m/s). The P-impedance

the surveys represent the seismic response from the entire Marly and Vuggy

formations. The flow model, however, has five layers in the Marly and eight layers in the

5.15

w

values from

87

Vuggy. The P-impedance can be calculated for each cell in each layer. In order to

ompare the calculated P-impedance with the survey P-impedance, upscaling of the

calculated P-impedance is required. The fi

thickness-weighted average as shown in the equation below:

c

rst upscaling procedure considered was the

∑∑ ⋅

=hZh

Z Equation

where

5.16

h is the thickness of each layer and Z is the seismic attribute.

The second upscaling procedure considered was the pore volume-weighted

average shown in the equation below:

∑∑

PVEquation 5.17

ore volume of each cell.

Equation 5.17 was used in this work. Ca

were made using both upscaling procedures. The differences in the values of the

discussed below using each of these upscaling procedures were

negligible.

There are other upscaling pro

accuracy and resolution of the seismic data in the vertical direction, it was assumed that

he abo

⋅=

ZPVZ

where PV is the p

lculations of upscaled P-impedance data

objective function OF

cedures available. However, considering the

t ve procedure would be sufficient to obtain appropriate results.

5.5 P-Impedance Value within Simulation Grid Block

Figure 5.1shows the location of actual P-impedance values calculated by

Herawati (2002) placed over the simulation grid. Since the seismic acquisition was done

88

with a bin size of 20-meter by 20-meter and the simulation grid cell size is larger, there

are as many as nine different data points within one grid cell (Figure 5.2). Therefore, the

actual P e

P-impe

results.

es were picked from a set of bin cells and the arithmetic

average of those points was used in the comparison. When the points were located near

r in the

averagi

of the P-impedance

data di that the P-

pedance change alongside the CO2 injectors can be seen.

-impedance needed to be averaged over several bin cells so that a representativ

dance value could be compared to the P-impedance calculated from simulation

he P-impedance valuT

the grid lines or on the lines of the seismic bin, those points were not accounted fo

ng. This process was performed for each grid cell within the red square indicated

on Figure 5.1.

Figure 5.3and Figure 5.4 shows the results of the averaging

scussed previously. The well location map was superimposed so

im

Figure 5.1: Location of P-impedance values and the simulation grids. The red rectangle is the area for comparison.

89

Figure 5.2 Close up view of the location of P-impedance values and the simulation grids

Figure 5.3: Averaged P-im

W N

S E

W N

S E

pedance data in Marly

90

F

W N

S E

W N

S E

igure 5.4: Averaged P-impedance data in Vuggy

5.6 P-Impedance Change due to CO2 Injection

tion of the P-impedance, the bulk density includes

rock and fluid inside of the rock. Therefore, if fluid substitution occurs during the

there is a change in the sa

by a lighter fluid, such as CO2

evident.

Brown (2002) analyzed the fluid and core from

changes in the fluid density and the elastic moduli as a function of pressure. He studied

In the equa the density of the

injection and production process, turation of fluids within the

rock. If the fluids are replaced , the change of the bulk

density will become

Weyburn Field and studied the

anges in the fluid composition have a larger effect on the P-

impedance than the changes in pressure (Figure 5.5and Figure 5.6). The calculation of

the variation of the P-wave velocity with pore pressure for different fluid compositions.

The results show that the ch

91

the P-im

and CO2. The bulk m il, because of the

high comp 2 is less

than that for the other fluids.

Figure 5.5 Variation of Marly P-wave impedance with fluid saturation and pressure at constant crack density (Brown 2002).

pedance changes for Weyburn Field includes three different fluids: oil, water,

odulus for CO2 is much less than that of water or o

ressibility of the gas. Therefore, the calculated P-wave velocity for CO

92

Figure 5.6 Variation of Vuggy P-wave impedance with fluid saturation and pressure at onstant crack density (Brown 2002).

5.7

c

P-Impedance Data

of being able to differentiate the

seismic

d,

mpedance data can be used to see the changes in reservoir

conditi re

Herawati (2002) investigated the possibility

data between the Marly and Vuggy formations. Her analysis shows that the

seismic velocity and porosity data can be used to differentiate these formations.

However, since Weyburn Field is a relatively thin reservoir, the differentiation was

limited to the Marly and Vuggy formations only. Because the data can be differentiate

according to Herawati, the P-i

ons in the Marly and Vuggy formations separately. The P-impedance changes a

used here to provide lateral information within the survey area.

The fluid substitution experiments conducted by Brown show that the P-

impedance changes can occur both in the Marly and in Vuggy, as discussed in the

93

previous section. The changes due to CO2 injection are expected to be larger in the Mar

than in the Vuggy due to the higher porosity of the Marly. The expected changes for th

Marly and the Vuggy are -8% to -12% and -1 to -5%, respectively. The pressure changes

before and after the CO

ly

e

ore, the pressure effect on the P-impedance changes is

expected to be much less than that of fluid composition changes.

5.7.1

2 injections are not large since the field has been waterflooded

prior to CO2 injection. Theref

P-Impedance Change in Marly

im

reasonable to say that the anomaly is least in the North pattern due to its low cumulative

volume of injected gas. However, there is no significant P-impedance change in Marly in

the West pattern despite the fact that the pattern has received the second highest volume

of CO2.

Figure 5.7 shows the P-impedance change map for the Marly. The large

pedance changes of -6 to -10% in Marly are observed along the injection well in the

South pattern. The pattern shows large P-impedance changes that are analogous to the

highest injection volume of CO2. The spread of the P-impedance change is not uniform

alongside those injection legs. The picture indicates that highly communicative zones

associated with CO2 fingering may be present between the injector and the producer

located north of the injector.

The East pattern also shows a similar anomaly, but the area is not as extensive as

in the South. The P-impedance change ranges from -6 to -8%. The spread is also not

uniform in this pattern, which indicates there may be a high permeability zone caused by

fractures or local heterogeneity. The anomaly is apparent in only two-thirds of the

injection branches. This implies that most injected CO2 was taken by the first two-thirds

of the injection branches.

The anomalies in the West and North patterns are almost negligible. It is

94

Figure 5.7: P-impedance differences map using the sparse-spike inversion for the Marly formation (Herawati 2002).

5.7.2 P-Impedance Change in Vuggy

Figure 5.8 is the P-impedance change in the Vuggy formation. In the South

pattern

arly

, there is a change, but the area is not as extensive as in the Marly formation.

Also, the degree of the change is smaller than in the Marly.

In the East pattern, the shape of the change is roughly the same both in the M

and Vuggy formations, except there seems to be a communicating zone between the

injector and the producer in the northeast causing the fingering.

95

Figure 5.8: P-impedance differences map using the sparse-spike inversion for the Vuggy formation (Herawati 2002).

There is an observed P-impedance change in the West pattern which is not

observed in Marly. The change is concentrated at the water injection well. The

communication between the CO and water injectors was expected since they are near

one another. Thus, once the comm2

unication was established, the CO2 was most likely

cross-f

ev studied the frequency decomposition of the P-

wave, a ely

lowing from the perforations in the Marly zone to the Vuggy perforations within

the water injector, or possibly, behind the casing.

The West pattern has received the second most CO2 volume. The South and the

East, the first and third in injection volume, showed extensive P-impedance changes near

the CO2 injectors. However, the area of the P-impedance change in the West is much

smaller than in the other two. Galike

nd extended the study horizon to Frobisher. He found that there is a relativ

large anomaly in the formation near the water injector. The water injector is completed

in Marly and Vuggy only; however, the well was originally drilled down to Frobisher.

96

The general hypothesis is that there is communication behind the casing due to a

deteriorated casing that is

5.8

more than fifty years old.

Objective Function

Once the P-impedance is calculated, the values need to be compared to th

observed values. The degree of proximity between the calculated and the observed

values can be quantified by the objective function (OF) expressed in the following

( )

e

equation:

∑ −= 2ObservedCalculatedOF Equation 5.18

At each grid cell for Marly and Vuggy, the square root of the difference is

, and then those values are added to obtain the OF. A low value of OF implies

the observed and calculated P-impedance values are comparable.

owever, if the production data do not match, the flow model

is useless. Thus, another OF needs to be introduced to account for the production match.

ucing the weighting factors that assess the OF

of the P

calculated

The OF of the P-impedance data could be minimized if we did not worry about

matching production data. H

The total OF can be determined by introd

-impedance and the production match.

oductionimpedancePTOTAL OFwOFwOF Pr21 += − Equation 5.19

w1 is one,

then the OF is honoring the P-impedance only. The production data used in the above

equation are the oil and water production rates and the gas-oil ratio (GOR).

In the equation above, w1 and w2 are weighting factors that must be in the range

between zero and one, and the sum of these values must be one. Thus, when

97

When the total OF was calculated, the difference in the magnitude between the

pedance and production data was evident. Since the OF values of P-

pedance and production data are entered into the total OF, the contribution of

ters with large magnitudes will dominate the overall OF unless the param

the objection function are normalized. To resolve this matter, a new OF shown below

OF of the P-im

im

parame eters in

was considered.

∑ ⎟⎠⎞

⎜⎝⎛ −

=2

ObservedObservedCalculatedOF

After the calculation of OF using the equation above, another problem

Equation 5.20

was

ro, the OF terms using the difference between calculated

and observed values is significantly higher than terms using high production rates. In the

produc

should

observed using low production rate data. When the observed production rate is low,

especially as it approaches ze

tion data, the influence of low or negligible production rates have a

disproportionate influence on Equation 5.20, and suggests that a new OF equation

be defined.

The following equation defines the OF that was used in the comparison of P-

impedance and production data in this study:

∑ ⎟⎟⎠

⎞⎜⎜⎝

⎛ −=

2

observed

ObservedCalculatedOFσ

Equation 5.21

where σ is the standard deviation. Equation 5.21 was used by Arenas, et al. (Arenas,

Krujijsdijk et al. 2001). The standard deviation σ is used as the normalization factor.

98

The difference in the magnitude of two different data types was still appar

Thus, instead of calculating the absolute total OF, a r

ent.

elative objective function, ROF, was

calculated using EnCana’s results as a base case. The following equation shows the

relative objective function (ROF) used in the analysis.

( )

( )( )

( )∑∑ +=BASEreservior

reservior

BASEseismic

seismic

OFOF

OFOF

ROF Equation

It i

5.22

s possible to compare every single P-impedance data point and calculate the

F from it. However, the accuracy of time-lapse seismic data is limited. Thus, a cut-off

value was introduced into the OF calculation so th

difference that were less than the cut-off value were ignored. Minimum cut-off values of

%, 2% to the

ory. However, using

the higher cut-off values would honor only high percent changes in the P-impedance

values, and m

O

at values of P-impedance percent

1 , and 4% were used in the calculation. Lower cut-off values impose a limit

data accuracy. Higher cut-off values limit the number of data points included in the OF

calculation, which reduces the OF values and smoothes the OF hist

ay not accurately represent the proximity of the observed and calculated P-

impedance data.

5.9 P-Impedance calculation

As described in the previous section, the P-impedance was calculated based on

Gassmann’s theory. Figure 5.9is a picture of the cal

nCana’s history matched model. The picture on the left is the P-impedance change in

the Ma

culated time-lapse P-impedance of

E

rly. It shows an apparent P-impedance change only along the branches of CO2

injectors. In the South and East patterns, the P-impedance change is also obvious at

adjacent horizontal producers where CO2 breakthrough has been discussed in previous

sections.

99

The picture on the right of Figure 5.9 is the P-impedance change in the Vuggy

formation. The change is not as large in Vuggy as in the Marly area where the legs o

CO

f

terns.

tures are different from the actual P-impedance maps shown in Figure

.7 and Figure 5.8. The range of the calculated P-impedance change is smaller than the

range of the observed P-impedance change. The objective is to adjust the flow m

that the calculated P-impedance values are closer to the actual values.

2 injectors are, but the spread of the CO2 can be seen in the South and East pat

The change was expected to be larger in the Marly since the formation has higher

porosity.

These pic

5

odel so

-7% 4%

W N W NMarly Vuggy

S E S E

-7% 4%

W N W NW NMarly Vuggy

S E S ES E

Figure 5.9: Calculated time-lapse P-impedance of EnCana’s history matched model.

100

101

6.1

Chapter 6

MECHANISMS AFFECTING THE MOVEMENT OF

CO2 IN RESERVOIRS

Introduction

Time-lapse seismic surveys provide dynamic data that can help improve the

characterization of reservoirs in flow models. The superior areal resolution that time-

lapse seismic data provides can be used to complement and supplement the data that is

ordinarily used in a history matching study. This approach should reduce interwell

reality.

injec

form

discusses the questions that arose from the results of the simulation of the flow barrier.

uncertainties and help the modeler develop a flow model that more accurately represents

As presented in the previous chapter, EnCana’s flow model did not match the

production rates that were observed during CO2 injection. A large volume of CO2 is

present in the Vuggy formation and not in the Marly formation. This causes the CO2

breakthrough observed in Vuggy wells. The calculated time-lapse P-impedance data

showed that the seismic anomaly observed in the Marly formation was not extending

toward the horizontal producers as it should, but was limited to the cells where horizontal

tors are completed.

This chapter presents an early attempt to keep the injected CO2 in the Marly

ation and the discovery of CO2 movement within the layered reservoir. Section 6.2

presents the introduction of a flow barrier based on flow unit analysis. Section 6.3

102

6.2 Summary

Observed time-lapse P-impedance data showed a larger change in the Marly

formation than in the Vuggy. EnCana’s flow model showed that CO2 broke through at

the producers through Vuggy formation completions, but the P-impedance distribution

calculated from flow model results was quite different. The first attempt to history match

observed P-impedance results was to maintain CO2 in the Marly formation by introducing

a flow barrier. The introduction of the flow barrier seemed to be a reasonable approach

based on flow unit analysis. However, the results were completely unacceptable. Three

questions emerged from the behavior of EnCana’s flow model with the hypothesized

flow barrier. These questions were answered by developing conceptual models of the

layered formations: (1) The CO2 at reservoir conditions is buoyant in the reservoir, (2)

the CO2 tends to migrate down to the layer with high permeability and remain there, and

(3) the CO2 can migrate up into the upper formation if there is high vertical permeability.

This conceptual model study showed that the high vertical permeability associated with

existing vertical fractures plays a significant role in the CO2 injection process.

6.3 Simulation of Flow Barrier Based on Flow Unit Analysis

We pointed out in the previous chapter that EnCana’s model showed that CO2

was migrating down into the Vuggy formation, which contradicts what the observed P-

impedance results indicated. Thus, the first effort of the history matching process was to

learn what mechanisms were needed to keep CO2 in the Marly formation.

David Pantoja performed a flow unit study of the Weyburn Field based on

available porosity and permeability measurements from cores. The flow unit study is the

study of geologic characteristics that relate fluid flow. Figure 6.1 and Figure 6.2 show

the flow units obtained from an analysis of the vertical well in the South pattern.

103

Cumulative kh, or cumulative f , was plotted against cumulative φh,

or cumulative s eological sub

formation based on the analyst’s in slope of the cumulative kh

versus cumulative φh plot. The different flow units are identified by observing the

change in the degree of the slope of the plotted data. A nearly horizontal slope within

ow. A vertical or nearly vertical slope

indicates that the flow capacity is low, which suggest it forms a flow barrier. From these

figures ns at

r.

d

elp

Figure 6.1: Flow unit study of Well OP-02-13 (Pantoja 2000)

low capacity

torage capacity. The horizontal lines label the top of each g

interpretation of changes

one flow unit indicates high capacity of fluid fl

, we can see a low flow capacity zone between the Marly and Vuggy formatio

the top of the Vuggy formation. Flow unit plots for other wells showed the same barrie

This analysis was used to justify the introduction of a flow barrier between the Marly an

Vuggy formations in EnCana’s model. It was thought that this flow barrier would h

keep CO2 in the Marly formation.

104 104

n th

low model run was

restarted from the beginning of CO

icantly lower

than the actual production in al

(Figure 6.8).

Figure 6.2: Flow unit study of Well OP 04-18 (Pantoja 2000)

I e flow model, the vertical transmissibility between layers 7 and 8 was

multiplied by 0.001 in order to simulate the barrier, and then the f

2 injection.

The results are shown in Figure 6.3 through Figure 6.7. Notice that the

production matches of oil and water became worse than the previous case (Section 4.8.1

and Section 4.8.2). Particularly, the calculated water production was signif

l wells shown here. Regarding the gas breakthrough that

was discussed in previous sections, it was not seen in the flow model run with the flow

barrier; instead, there was an increase in gas production in early time due to hydrocarbon

gas coming out of solution because the pressure dropped below the bubble point pressure

105

Injected CO2 was expected to stay only in the Marly zone once the flow barrier

was introduced. The cross-sectional view of the CO2 mole fraction in the liquid phase in

the South pattern (Figure 6.9) shows that the CO2 stayed in the Marly zone after one year

of injection, however, the lateral extension of the injected flood zone is rather narrow

does not match frontal advance based on P-impedance data.

Figure 6.10 is the cross sectional view of the CO

and

e CO2 was injected into the Marly from well CD-

10H18, but as shown in the South pattern, the lateral extent of the displacing flood zone

the CO2

injec

This im

2 mole fraction in the liquid

phase in the East pattern. Notice that there is CO2 in the Vuggy zone and a small amount

of CO2 in the Marly zone as well. The CO2 in the Vuggy came from well 101/10-18-006-

13 (WG-10.18), which is a WAG well that is completed both in the Marly and Vuggy

zones. Even though the vertical transmissibility between the Marly and Vuggy was

reduced, the completion of WG-10-18 allows CO2 to be injected into the Vuggy and

showed up in the cross-section. Th

is very narrow. The adjacent producers are not getting adequate support from

tor.

Introducing the barrier resulted in significant mismatches of production history.

plies that the communication between Marly and Vuggy plays a role in the

injection and production process in Weyburn Field.

106

Figure 6.3: Production match of well OP-01H13 with flow barrier

duction match of well OP-09HB12 with flow barrier Figure 6.4: Pro

107



108


0

300

150

0

300

150

Figure 6.8: Pressure (barsa) at the end of history match in M3_A layer with flow barrier. Notice that the pressure at horizontal producers are low.

109

action in liquid phase.

Figure 6.10: Cross section of mole fraction in liquid phase.

Marly

Vuggy

OP-01H13 OP-09HB12CD-10H12

Marly

Vuggy

OP-01H13 OP-09HB12CD-10H12

Figure 6.9: Cross section of the South pattern showing CO2 mole fr

Marly

Vuggy

OP-15H18 OP-08H18CD-10H18

Marly

Vuggy

OP-15H18 OP-08H18CD-10H18

the East pattern showing CO2CO2 in the Vuggy is from WG-10-18.

110

6.4 Understanding CO2 Movement in the Reservoir

The results of EnCana’s history match did not predict the appropriate CO2

distribution in the Marly and Vuggy formations as the observed P-impedance data had

indicated. Even though CO2 was injected into the Marly formation, the fluid was

migrating down to the more permeable Vuggy formation. This result raised some

questions regarding CO2 movement within the reservoir. To examine such behavior of

CO2, a conceptual model with dimensions of 9 by 1 by 9 was created using the same

compositional PVT data set as the ECLIPSE 300 simulation model. . The reservoir

pressure calculated by the model is greater than MMP in the simulation runs.

6.4.1 Is CO2 heavier than oil at reservoir conditions?

EnCana’s flow m

Does this cause CO

answered by sim

that CO2

6.4.2

Some questions that emerged from the observation of CO2 movement in

odel were: Is CO2 heavier (more dense) than oil at reservoir conditions?

2 to migrate down to the Vuggy formation? These questions were

ulating an isotropic model with permeabilities of 100 md in all

directions. Figure 6.11 shows that CO2 is overriding the oil phase, which demonstrates

is lighter (less dense) than oil at reservoir conditions.

Why would CO2 migrate down into the Vuggy?

In Section 6.4.1 we verified that CO2 is lighter (less dense) than the oil phase at

reservoir conditions. The next question to consider was: Why does CO2 migrate down to

ation, even though the CO2 injection point is located above the Vuggy

ation in the Marly formation and CO2 is lighter than oil? The conceptual flow model

the Vuggy form

form

rmation. It is also thinner than

was modified to simulate a simple Weyburn case by introducing permeability contrast.

The Marly formation is less permeable than the Vuggy fo

111

the Vuggy formation. Therefore, the top three layers of the model represent the Marly

formation with the horizontal permeability set equal to 50 md. The bottom six layers

represent the Vuggy formation with the permeability set equal to 100 md. The vertical

permeability was set to one-tenth of the horizontal permeability in both the Marly and

Vuggy formations. The porosities of Marly and Vuggy are set to 25% and 15%,

respectively.

The simulation proved that even though the injection point is in the Marly

formation and the injected fluid is lighter than oil, it is possible for CO2 to migrate down

to the Vuggy formation where the permeability is higher (Figure 6.12). Injected CO2 is

able to advance faster, and therefore farther, from the injector through the higher

permeability Vuggy than the injected gas would have advanced if it had stayed in the

Marly formation. The pictures of the P-impedance (Figure 5.7 and Figure 5.6) show that

uggy formation in the South pattern, and the P-impedance change was almost the same

ormations for the East pattern. However, the full-field flow model results

indicate otherwise.

6.4.3

the areal extent of the P-impedance change was greater in the Marly formation than in the

V

in both f

Why would CO2 stay in the Vuggy zone?

Results of the conceptual model study described in Section 6.4.2 raised the

following question: Since CO2 is less dense than oil, can CO2 migrate back up to the

Marly zone if there is enough vertical permeability to allow upward CO2 migration to

occur? A further survey of the technical literature yielded several papers that described

studies of the gravity segregation of CO2 in Weyburn Field. Srivastava (2000)

commented that the “Marly-Vuggy arrangement of the reservoir offers potential to utilize

ng (2002) concluded that it is possible to take

gravity segregation effects to enhance oil recovery.” Likewise, the core flood

experiments that were conducted by Do

112

advantage of the gravity segregation in the CO2 flood due to the unique geologic setting

in the W

o

hat the

in

Figure

eyburn Field.

Therefore, the third conceptual model was to increase the vertical permeability t

200 md throughout the model to simulate gravity segregation. Figure 6.13 shows t

CO2 front in the Vuggy zone does not advance as far as the previous case described

Section 6.4.2. In addition, more CO2 appears in the Marly formation.

0 1CO mole fraction20 1CO mole fraction2

6.11: CO2 mole fraction in liquid phase, isotropic model

113

Figure 6.12: CO2 mole fraction in liquid phase, simple Weyburn case with low vertical permeability

Figure 6.13: CO2 mole fraction in liquid phase, simple Weyburn case with highpermeability

vertical

0 1CO2 mole fraction

Marly

Vuggy


Marly

Vuggy

Marly


Vuggy


Marly

Vuggy

114

6.5 Vertical Displacement Efficiency

The recognition that gravity segregation is important in the previous section led to

the calc

en

y by conducting

scaled experiments using sandstones. The results of linear displacement experiments

yielded a dimensionless group called viscous/gravity ratio, Rv/g, which is shown in the

following equation.

ulation of the vertical displacement efficiency in Weyburn Field. The vertical

displacement efficiency is influenced by gravity segregation caused by density

differences, mobility ratio, vertical to horizontal permeability, and capillary forces (Gre

and Willhite 1998). Craig et al. (1957) studied vertical sweep efficienc

⎟⎠⎞

⎜⎝⎛⎟⎟⎠

⎞⎜⎜⎝

⎛∆⋅⋅⋅

=hL

ku

R dgv ρ

µ2050/

is darcy velocity (bbls/day-ft2), µd is displaced phase viscosity (cp),

(md), ∆ρ is density difference between displacing and displaced fluids

the length of the linear system (ft), and h is the height of the system

Since the vertical permeability is different from horizontal perm

ated by the following equation as suggested by Stalkup (1983).

Equation 6.1

where u k is

permeability

(g/cm3), L is (ft).

eability, k is

estim

hv kkk ⋅= Equation 6.2

where kv is vertical permeability and kh is horizontal permeability.

Using the appropriate values for each variable in the equations for Weyburn as

listed in Table 6.1, the resulting values of Rv/g ranges from 20 to 1,800.

115

Figure 6.14 shows the vertical displacement efficiency as a function of th

ravity ratio. The figure also shows that the efficiency is also a function of

mobility ratio, M. For the Weyburn fluids, using the viscosity of CO2 as 0.

t reservoir condition, the calculated mobility ratio for the CO2 injec

process is about 40, which is not a favorable value. Using this value, the displa

practically not affected by the viscous/gravity ratio, according to Figure

6.14. The displacement efficiency is limited to 20% at maximum.

Figure 6.15 shows the volumetric sweep efficiency as a function of the

ravity ratio and the mobility ratio. Using the calculated values for We

efficiency is approximately 20 % at maximum. Figure 6.16 shows the pictures of flow

s categorized by region in Figure 6.15. For the Weyburn fluids, it falls in Region

e

viscous/g

046 cp and 2

cp for oil a tion

cement

efficiency is

viscous/g yburn, the

regime

isplacement and volumetric efficiencies.

Table 6.1: V

III, which shows the CO2 overriding the oil with some fingering of CO2, which leads to

poor vertical d

alues used to calculate viscous/gravity ratio for Weyburn

Variables Values, Value Range u (bbls/day-ft2) 0.1 ~ 1.0

µd (cp) 0.046 kh (md) 100 kv (md) 10 ~ 300

ρ of oil (g/cm3) 0.85 ρ of CO2 (g/cm3) 0.65

L (ft) 500 h (ft) 200

116

Figure 6.14: Plot of vertical displacemenratio(Craig 1957)

Figure 6.15: Plot of voluratio

t efficiency as a function of viscous/gravity

metric displacement efficiency as a function of viscous/gravity

117

Figure 6.16: Flow regimes in miscible displacement of unfavorable mobility ratio (Stalkup 1983)

118

The calcu

experiments tic if the

ain layers

with distinctively d 2 would

override

y without high vertical

permeability

vertical disp

To quantif roduction

e cumulative oil

hows improved vertical displacement efficiency due to high vertical

ermeability in the layered reservoir

Table 6.2: C

lation and classification presented above is based on laboratory

with a linear system. Therefore, these findings would be realis

reservoir is a single layer. However, the Weyburn is a reservoir that has two m

ifferent characteristics. Figure 6.11 showed that the CO

the oil in the uniform permeability reservoir.

Figure 6.12 showed the CO2 would bypass the oil in Marl

. Figure 6.13showed the CO2 would migrate up into Marly due to gravity

segregation. This unique configuration of two different layered reservoirs is enhancing

lacement efficiency.

y the vertical displacement efficiency, the cumulative oil p

was obtained for the two different scenarios presented in Section 6.4. Th

production at the time of CO2 breakthrough is shown in Table 6.2. The cumulative

production clearly s

p

umulative oil production at the time of breakthrough

Scenarios Cumulative oil production at the time of CO2 breakthrough

Weyburn case with low vertical permeability 1,600 sm3

Weyburn case with high vertical permeability 2,000 sm3

ervoir.

n view of the reservoir showing the CO2 in liquid phase (Figure 4.35 and Figure

4.39) revealed that the CO2 or oil/CO2 mixture cannot reach the lower part of Vuggy

Figure 3.4 depicted the expected advance of oil, CO2, and water in the res

However, the picture is different when gravity segregation is considered. Also, the cross-

sectio

119

formation due to the

(Figure 6.17) was created to il xture based on

the observations.

2 injection process.

ir low densities compared to oil or water. Thus, a new picture

lustrate the movement of CO2 or oil/CO2 mi

Figure 6.17: Side view of the reservoir showing movement of fluids during CO

Oil bank

Marly

Vuggy

2CO

WaterInjector

VeProdu

rticalcer

HorizontalProducer

CO2 Injector

Oil bank

Marly

Vuggy

2CO

WaterInjector

VeProdu

rticalcer

HorizontalProducer

CO2 Injector

120

121

Chapter 7

EFFECTS OF NATURAL FRACTURES IN FLUID

FLOW

7.1 Introduction

There is much evidence that the formations in Weyburn Field are naturally

fractured. Previous studies of natural fractures in Weyburn discovered the major fracture

set oriented N45˚E. However, there were some disagreements when it came to other

fracture sets. Bunge (2000) saw two other fracture sets that were open to flow. Beliveau

(1991) also saw other fracture sets that could influence fluid flow. However, Eddy

(1998) mentioned that Edmonds saw other fracture sets but concluded that those sets

were closed fractures that could not be a factor in influencing fluid flow.

Two different conceptual models were built in the E300 reservoir simulator to

help us understand fluid flow in natural fractures. The first model was a dual-continuum

model (Section 7.2), which simulated fractures as very thin grid cells surrounded by

normal size grids. The second model was a dual porosity model (Section 7.3) that

includes the effect of natural fractures in the computation.

7.2 Summary

The results of the dual continuum model revealed that fractures that were not

connected to each other did not affect fluid flow in the reservoir. The fractures need to be

connected to create a fracture network in order to enhance fluid flow.

The dual porosity model with three different cases showed the same results as the

first conceptual model presented in the previous chapter. Even though the matrix

122

permeability was low, the fracture allowed CO2 to migrate upward to contact targeted oil

in the Marly formation. It also showed that the recovery of oil in the Vuggy formation

via waterflood was almost identical whether there was vertical communication, either

large or small. However, the degree of vertical communication makes a substantial

impact on flow performance during CO2 injection.

7.3 Dual Continuum Model

In the dual continuum model, fractures were simulated by very thin grid cells.

The initial attempt to set the fracture width to 0.001 ft failed due to a throughput

limitation. Thus, the width was set to 0.1ft for the simulation runs to proceed. The

fracture permeability was set to 10 darcy (10,000 md) and the matrix permeability was

set to 25 md. Three possible cases were run to investigate the role of fractures. The first

case was the non-connected fracture set simulating only the major fracture set in

Weyburn. Figure 7.1 is the dual continuum model with a non-connected fracture set.

The solid black lines indicate the thin grid cells with high permeability, which simulate

fractures. The simulated fractures exist only in one direction and they are not connected

to each other. The second case was the connected fracture set creating a fracture network

in the reservoir. In Figure 7.2, the simulated fractures are all connected to simulate a

fracture network. The third case was the non-fractured model where the thin grid cells

have the same permeability and porosity as the matrix. The non-fractured model is not

shown here.

123

Figure 7.1: Dual continuum model with non-connected fracture set (top view). Solid black lines indicate fractures.

Figure 7.2: Dual continuum model with connected fracture set (top view). Solid black lines indicate fractures.

124

A CO2 injector was placed in the upper left hand corner and a producer was

placed diagonally from the injector. The simulation of CO2 injection was run in all thre

models and CO

e

e

s simulation runs were above MMP.

he CO2 front in the non-fractured model (Figure 7.3) is spread uniformly around

ected fracture model shows practically the same result

(Figure 7.4) despite the existence of the fractures. However, once the fractures are

connected, the CO

Figure 7.3: CO2 mole fraction in the non-fractured model

2 mole fractions in these models are compared in Figure 7.3 through

Figure 7.5. These pictures show the CO2 mole fraction in the liquid phase at the sam

time step. The calculated reservoir pressure in these

T

the producer, and the non-conn

2 can reach the producer through the conduit between the injector and

producer created by the fracture network (Figure 7.5).

125

Figure 7.4: CO2 mole fraction in the non-connected fracture model

Figure 7.5: CO2 mole fraction in the connected fracture model

126

In reality, the CO2 breakthrough as shown in Figure 7.5 is not a desirable eve

The purpose of this simulation analysis is to understand the role of fractures, and it has

nothing to do with the actual CO

nt.

ey 2 injection program. The important thing from this

analysis is that one can conclude that if the fractures are not connected to each other, th

have a negligible effect on fluid flow in this pattern.

7.4 Dual Porosity Model

In addition to the dual continuum model presented in the previous section, a dual

porosity model was also created to understand the effect of natural fractures in Weyburn

Field. The dual porosity model is a model that handles matrix and natural fractures

separately; each has its own porosity and permeability. Due to the handling of matrix and

fractures, the am the matrix has

much higher porosity tha permeability

than the matrix.

Unlike in th

created for the analys atrix and the

fractures were handled separately ovement in the cross-

sectional view. In the an lated. All three

models have the sam ing a permeability

of 1 md ermeability was

varied in the three m ) no vertical

fracture permeability, a

njected into the Vuggy

ormation in all three models so that the oil saturation in the Vuggy formation became as

low as in the actual field case. After water injection was stopped, CO2 injection was

started. There are two wells in the models; one is an injector and one is a producer.

ount of data for each grid is doubled. Characteristically,

n fractures while the fractures have much higher

e conceptual model in Section 6.4, a model with a 9 x 1 x 9 grid was

is (in the simulation, it is 18 x 1 x 18 since the m

). This was done to see the CO2 m

alysis, three different scenarios were simu

e matrix permeability, with a simulated barrier hav

between the Marly and Vuggy formations. Then, the fracture p

odels as (1) low vertical fracture permeability, (2

nd (3) high vertical fracture permeability.

To simulate the Weyburn case closely, water was i

f

127

During water injection, the com

formation, a ation for CO2 injection.

In the producer side

The calcu ved to be greater than the MMP of the

Weyburn fluid system

7.4.1

pletion interval of the injector was in the Vuggy

nd then the interval was moved up in the Marly form

, the same change was made for the CO2 injection.

lated reservoir pressure was obser

.

Dual Porosity Mode bilityl with Low Vertical Fracture Permea

The first cas se. The fifth

layer from e matrix flow barrier.

It has the horizontal and vert d, respectively.

le 7.1.

Table 7.1: Dual porosity model parameters

Vuggy

e to be simulated was the low vertical permeability ca

the top (V1 in Table 4.1) is a thin layer that represents th

ical matrix permeability of 1 md and 0.001 m

The permeability and porosity of other layers are summarized in Tab

Marly

Matrix Porosity 0.25 0.15 Fracture Porosity 0.015 0.015

Matr 50 md 50 md

ix Permeability X Z

20 md 20 md

Fractur 3000 md

1 md

e Permeability X Z

1000 md

1 md

ation. The oil saturation in

the ma

in the Vuggy was displa

Water was injected for 300 days into the Vuggy form

trix and fracture at 300 days is shown in Figure 7.6 and Figure 7.7. Most of the oil

ced by the water, leaving the oil in the Marly.

128

With the low vertical fracture permeability, the injected CO2 at the Marly

migrated down into the Vuggy formation in both matrix and fracture (Figure 7.8 and

Figure 7.9) as seen in the previous simulation results (see Section 6.4). The CO2 seem

to migrate up into the Marly in the fracture system, but it is not a significant amount.

Moreover, the front of the CO

ed

went much farther than the CO2 in

the matrix system. Injected gas movement through the fracture system was the source of

breakthrough gas.

2 in the fracture system

Figure 7.6: Oil saturation of matrix after 300 days of water injection into Vuggy. Black dots represent completed formation.

Water Injector Producer

0.2

0.7


0.2

0.7

0.2

0.7

129

Figure 7.7: Oil saturation of fracture after 300 days of water injection into Vdots represent completed formation.

uggy. Black

Figure 7.8: CO2 mole fraction in liquid phase in matrix after 30 days of injection into Marly. Black dots represent completed formation.

Producer

1


00

1

0

1

Water Injector

CO2 Injector Producer

0

1


0

1

0

1

130

Figure 7.9: CO2 mole fraction in liquid phase in fracture after 30 days of injection into Marly. Black dots represent completed formation.

7.4.2 Dual Porosity Model with Flow Barrier between Marly and Vuggy

The second scenario was to simulate the flow barrier with no vertical fracture

communication between Marly and Vuggy formations. Table 7.2 summarizes the

eters used in the model. param

Marly Vuggy


Matrix Porosity 0.25 0.15 Fracture Porosity 0.015 0.015

Matrix Permeability X Z

20 md 20 md

50 md 50 md

Fracture Permeability X Z

1000 md

0 md

3000 md

0 md


0

1


0

1

0

1

131

As in the previous case, water was injected for 300 days into the Vuggy

ation. Oil saturation distributions in the matrix and fracture at 300 days are shown in

Figure 7.10 and Figure 7.11. Most of the oil in the Vuggy was displaced by the water,

and the oil in the Marly remained untouched by the water due to the barrier.

In this model, since there was no communication between Marly and Vuggy, all

ted CO2 stayed in the Marly in both the matrix and fracture system (Figure

7.12and Figure 7.13). One could reason that this is what is taking place at Weyburn.

However, when the oil and water production rates were studied, the water cut was

lly zero since injected water was retained in the layers below the flow barrier

the production data plots shown in the previous chapters, the water production rates were

form

of the injec

virtua . In all

higher than the oil production rates. It can be concluded that the injected water in the

though there is a tight formation between Marly and Vuggy formations, there appears to

communication between these formations through vertical fractures.

ck

Vuggy affected pressure and production of the wells completed in the Marly zone. Even

Producer

0.2

70.


0.2

70.

0.2

70.

Water Injector

Figure 7.10: Oil saturation of matrix after 300 days of water injection into Vuggy. Bladots represent completed formation.

132

Figure 7.11: Oil saturation of fracture after 300 days of water injection into Vuggy. Black dots represent completed formation.

Figure 7 ion in liquid phase in matrix after 30 days of injection into Marly. Black dots represent completed formation.

Producer

0

1


0

1

0

1

Water Injector


0

1


0

1

0

1

.12: CO2 mole fract

133

CO In tor2 jec Producer

Figure 7.13: CO2 mole fraction in liquid phase in fracture after 30 days of injectionMarly. Black dots represent completed formation.

7.4.3

into

Dual Porosity Model with High Vertical Fracture Permeability

The third scenario was to simulate the communication between Marly and Vuggy

through vertical fractures. The model parameters are the same as in the low vertical

fracture permeability case, except for the change in the vertical fracture permeability.

he vertical fracture permeability is the same as the horizontal fracture permeability.

Table 7.3 summarizes the parameters used in the model.

Water was injected for 300 days into the Vuggy formation as in the two previous

cases. The oil saturation in the matrix and fracture at 300 days is shown in Figure 7.14

and Figure 7.15. The oil saturations are similar to the ones in the low vertical fracture

permeability case, which suggests that the vertical permeability is not critical during the

recovery via the waterflood as long as there is sufficient communication between Marly

and Vuggy.

T

0

1

CO In tor2 jec Producer

0

1

0

1

134


Marly Vuggy Matrix Porosity 0.25 0.15

Fracture Porosity 0.015 0.015 Matrix Permeability

X Z

20 md 20 md

50 md 50 md

Fracture Permeability X Z

1000 md 1000 md

3000 md 3000 md

2 advance through both the matrix and fractures

depended on owed

down into th

segregation.

Once CO2 injection was started, the difference in cases with high and low vertical

permeability was apparent. The CO

vertical permeability. In this high vertical permeability case, CO2 fl

e Vuggy and then flowed upward into the Marly because of gravity

135

Producer

0.

0.

2

7


0.

0.

Water Injector

2

7

0.

0.

2

7

Figure 7.14: Oil saturation of matrix after 300 days of water injection into Vuggy. Black resent completed formation.

dots rep

Figure 7.15: Oil saturation of fracture after 300 days of water injection into Vuggy. Black dots represent completed formation.

Producer

0

1


0

11

Water Injector

0

136

CO Injector Producer

Figure 7.16: CO2 mole fraction in liquid phase in matrix after 30 days of injection into Marly. Black dots represent completed formation.

Figure 7.17: CO mole fraction in liquid phase in fracture after 30 days of injection into Marly.

2 Black dots represent completed formation.

2CO Injector Producer2

0

1

0

1

0

1


0

1


0

1

0

1

137

Chapter 8

HISTORY MATCHING USING TIME-LAPSE

8.1

SEISMIC DATA

Introduction

Once a flow simulation model is created, geostatistically or deterministica

model needs to match the production history so that the model can be used to forecast the

future performance of the field. The typical history matching process modifies

eability and porosity globally and locally in order to achieve an acceptable matc

atching is a time-consuming process that does not produce a unique solution.

EnCana’s model matched field performance data from the beginning of

lly, the

perm h.

History m

sity, both globally and locally. Even though the

match was achieved, the forecast of the production during the CO2 injection process, as

resented previously, did not match observed production history. This demonstrates the

limited validity of the EnCana model. The EnCana model provided an acceptable history

match that did not accurately predict the performance of the CO2 injection process.

In this chapter, a new waterflood history match is presented. It is followed by the

history match using the 4-D seismic data (P-impedance). Then, the results of the

calculation of the objective functions are presented.

8.2

production up to the injection of CO2. The history match was achieved by the

modification of permeability and poro

p

Summary

A new waterflood history match was built by matching the timing of water

breakthrough in the on-trend and off-trend wells in the South and East patterns. Then,

138

the sim pedance

pedance

im

de the

tive

form

case. The OF for the production history

hows the overall improvement of the flow simulation model. The use of time-lapse P-

im

8.3

ulation run was extended to include the CO2 injection period. The P-im

was calculated based on the simulation results and compared to observed P-im

changes which clearly showed the movement of injected CO2. Calculated values of P-

pedance changes were lower than the observed values. Time-lapse P-impedance data

helped identify details of fluid movement, such as possible injection intervals besi

branches of horizontal wells.

An objective function was calculated to measure the proximity of the observed

and calculated P-impedance values. The OF in the Marly formation was reduced rela

to the EnCana model performance in both the South and East patterns. For the Vuggy

ation, the OF increased slightly.

The relative OF that includes both the P-impedance and production data was

calculated by using EnCana’s case as a base

s

pedance data to improve the existing flow model proved that this data provides

valuable information that other data does not.

Waterflood History Matching

As mentioned previously, EnCana and others found that the major fracture trend

e reservoir was oriented N45˚E. Due to the trend, the producers that are located

along the “on-trend” direction responded more quickly to fluid injection than the

producers located “off-trend”. In order to match the different response times,

eability in the NE-SW direction, which corresponds to the permeability in th

within th

perm e X-

direction in the flow model, was increased more than the permeability in the Y-direction.

roduction history to calibrate the timing of water breakthrough at each well.

After each modification, the calculated production data were compared to the actual

p

139

2

re

ma ry

match m tch was

started.

8.3.1

The modifications to EnCana’s history match were performed globally as well as

locally. In the matched model, the local modifications were noticeable throughout the

model. The modifications resulted in a reasonable history match up to the onset of CO

injection in most of the producers; however, it also caused problems in the pressu

tch during the waterflood and CO2 injection periods. In this research, the histo

odifications introduced by EnCana were removed, and a new history ma

On-Trend and Off-Trend Wells

The history match of the waterflood period was performed by observing the

f

a water injector in each pattern. By multiplying the PERMX (permeability in x-direction)

and PERMY (permeability in y-direction) by different values, permeability anisotropy

was introduced into the flow model. PERMX was the same direction as the on-trend

fracture direction. Thus, by setting a larger multiplier for PERMX than for PERMY, the

anisotropy created by the major fracture set was simulated. Table 8.1 shows the

multipliers used for the history match in order to match the waterflood period. Notice

that the multiplier for Marly is larger than for Vuggy. The original permeability values of

Marly are much lower than of Vuggy. Even if the multiplier for Marly is larger than for

Vuggy, the permeability of Vuggy is still larger than of Marly. Table 8.2 also shows the

permeability multipliers for global vertical permeability modifications.

In the South pattern, OP-04-18 and OP-10-12 are the on-trend wells, and OP-02-

13 and OP-12-07 are the off-trend wells. The production history matches of these wells

up to one year of CO2 injection are shown in Figure 8.1 through Figure 8.4. The matches

are reasonable for these wells. There was a noticeable mismatch at the timing of water

timing of the water breakthrough at on-trend and off-trend wells relative to the location o

140

breakthrough of OP-02-13. It is slight e simulation; however, the overall

match is reasonable

In the East pattern, OP-10-1 ducer, and OP-12-18 and OP-02-

18 are the off-trend producers. OP-02-18 is located on the edge of the simulation model.

The results are shown in Figure 8.5 through Figure 8.7. The production rates and the

akthrough are reasonably matched.

ly early in th

throughout the history.

8 is the on-trend pro

timing of water bre

Table 8.1: Permeability multiplier for global horizontal permeability modification

Marly Vuggy

PERMX 35 20

PERMY 20 10

Table 8.2: Permeability multiplier for global vertical permeability modification

Layer Multiplier 2 40 3 60

4 - 6 40 7 100 8 40 9 5

10 - 14 20

141

Figure 8.1: Production match of on-trend well OP-04-18 (South pattern)

Figure 8.2: Production match of on-trend well OP-10-12 (South pattern)

142

Figure 8.3: Production match of off-trend well OP-12-07 (South pattern)


143

Figure 8.5: Production match of off-trend well OP-02-18 (East pattern)


144


8.3.2 Corner Wells

In EnCana’s history match, the modifications of permeability and porosity were

applied to attempt to match production from wells in the corners of the well patterns.

Despite those modifications, production from corner wells was not matched as well as

on-trend and off-trend wells. The new history match of these wells also faced the sam

iculty: water production in the flow model was significantly less than actual

production. This observation indicates that injected water was not reaching corner wells

in the flow model. The EnCana history match attempted to increase the permeability

both X and Y directions so that injected water could reach the corner wells quickly

enough to match observed water production times; however, the permeability changes

caused early water breakthrough in both on-trend and off-trend wells.

e

diff

in

Since the corner wells are located diagonally from the injection wells in the X-Y

tion was due to coordinate system used for the grid, it was possible that low water produc

145

the longer path that water has to take from the injection wells in this finite-difference

ulation model. The default option of the simulation is the five-point calculation

e that does not account for transmissibilities between a center-cell and cells located

in diagonal directions. Therefore, the nine-point calculation scheme option was activated

in E300 to address this problem. However, the results indicated that the nine-point

calculation scheme produced a negligible water production increase. Figure 8.8 depicts

these finite difference stencils.

sim

schem

8.3.3

Figure 8.8: Five-point and Nine-point finite difference stencils

Relative Permeability Curve for Water

The next attempt to match water breakthrough times was to increase the relative

eability of water (krw) so that the water phase becomes more mobile relative to

other phases. During the waterflood period, water was mainly injected into the Vuggy

mation where it is much more permeable than the Marly formation. Therefore, the

krw in Vuggy was increased to match the production of the corner wells. The original

perm

for

value of krw at the residual oil saturation in the Vuggy formation was 0.2, and the plot of

t value was the relative permeability curve is a straight line (Figure 4.3). The endpoin

2 4

5

3

1

4 6

8

5

2

7

1

9

3

2 4

5

3

1

4 6

8

5

2

7

1

9

3

146

increased from 0.2, and the final value that matched the water production of corner wells

was 1.0. The boost of the water relative permeability curve achieved a better match, but

it was further improved by reducing the oil relative permeability curve of the Vuggy

rmation. Figure 8.9 and Figure 8.10 show the relative permeability plots of the Ma

and Vuggy formations. The increase of krw improved the history match of the corner

wells without porosity or permeability modification around those wells. Figure 8.11 and

Figure 8.12 show the results of the history match before and after the relative

eability curve modification.

fo rly

perm

Figure 8.9: Relative permeability of Marly

147

Figure 8.10: Relative permeability of Vuggy

ity

ating

ow model,

howeve

The relative permeability of water was increased by a factor of 2.0 as a sensitiv

case. This increase in water relative permeability resulted in a better production match

during the waterflood in Weyburn. A study conducted by Lantz (1970) showed that

relative permeability greater than one could be achieved as a means of approxim

miscible flood behavior in a reservoir simulator. The maximum value of the relative

permeability depended on the viscosity ratio of non-wetting and wetting phases. Values

of relative permeability greater than one were not used in the Weyburn model. This

preserved the original physical meaning of water relative permeability used in the flow

model. Future work might consider renormalizing permeability in the fl

r, this is considered a secondary issue when compared with the recommendation

148

made below that the single porosity flow model should be replaced with a dual porosit

flow model.

The Midale formation is a highly fractured formation whose flow is dominated by

fractures. Thus, such a high krw value is believed to be required in this single porosity

model. Moreover, the relative permeability curves were generated in laboratory

experiments and the curves represents matrix relative permeability, not fracture relative

permeability. Aguilera (1980) s

y

tated, “The best set of relative permeability curves for a

fractured reservoir is probably the one determined from actual performance”. Weyburn

is a cas ormance.

water

eability led to

form eability

through the horizontal wells.

The history match results for other corner wells are shown in Figure 8.13 through

ermeability, the

match of the water rate of OP-14-07 (Figure 8.14) was only marginally improved by

ssible reason for the mismatch of the

rate is d

t

e where relative permeability needed to be determined based on well perf

The increase of water relative permeability also affected horizontal well

producers. The increase of water relative permeability improved the match of

production, but did not yield an exact match of the oil production rate. The water

production match was improved because the change in water relative perm

a reduction in oil production from the Marly formation and allowed water in the Vuggy

ation to reach the corner wells. Before the modification of the relative perm

curves, the injected water tended to rise to the Marly from the Vuggy and was produced

Figure 8.16. Despite the modification of the water relative p

matching the timing of water breakthrough. A po

ue to the location of the well at the boundary of the flow model. It is possible

that production from the well is supplemented by fluids from other wells that were no

included in the flow model.

149

0 16200 0 162000

Time (days)

140

70

Rat

e (s

m3 /d

ay)

Before After

0 16200 0 162000

Time (days)

140

70

Rat

e (s

m3 /d

ay)

Before After

Figure 8.11: Production plots of OP-08-13 (South pattern). Notice better water atch at water breakthrough. production m

Figure 8.12: Production plots of OP-14-12 (South pattern). Notice better water

0 16200 0 162000

100

50

Time (days)

Rat

e (s

m3 /d

ay)

Before After

0 16200 0 162000

100

50

Time (days)

Rat

e (s

m3 /d

ay)

Before After

production match at water breakthrough.

150


Figure 8.14: Production match of corner well OP-14-07 (South pattern)

151

Figure 8.15: Production match of corner well OP-14-18 (East pattern)

Figure 8.16: Production match of corner well OP-08-18 (East pattern)

152

8.3.4 Horizontal Wells

There was a difficulty matching the initial production of the horizontal wells.

When these wells were drilled in the 1990s, the oil production started high in all

horizontal producers, and then the rate declined to stabilized rates before the hor

wells responded to CO2 injection. EnCana’s model has matched initial oil production

from wells OP-15H18 and OP-08H18, which are in the East pattern. However, the

vertical flow barrier introduced between the Marly and Vuggy formations in the EnCana

model caused abnormally low pressure in the region. The modification of the relative

permeability curves, discussed in the previous section, slightly improved the initia

production rates; although the calculated rates were still lower than actual rates (F

8.17).

izontal

l

igure

rts of the

injected fluid. This provides an explanation for

e high initial production rate followed by a decline in rate. This could also explain why

ulate

odel

When a well is drilled into a formation, the new wellbore may expose pa

reservoir that have not been swept by any

th

the high initial production rates were hard to match since the flow model cannot sim

the unswept reservoir or matrix with the current grid size and the single porosity m

scheme.

Figure 8.18 is the production match for well OP-04H18. Figure 4.30 showed the

significant mismatch of water in this well due to low vertical permeability. Once the

vertical permeability was increased, the water production increased without affecting oil

production. The production matches of other horizontal wells with the production

response to the CO2 injection are shown later in this chapter.

153

16200 0 16200

Time (days)

Before After

00

200

50

Rat

e (s

m3 /d

ay)

16200 0 16200

Time (days)

Before After

00

200

50

Rat

e (s

m3 /d

ay)

Figure 8.17: Production plots of OP-09HB12. Notice improved oil production rate after the modification of water relative permeability curve.

Figure 8.18: Production match of corner well OP-04H18

154

8.3.5 Reservoir Pressure

Reservoir pressure data was measured by EnCana throughout the history of the

field, but the measurements were not extensive. The reservoir pressure in the flow mo

was compared to the available observed pressure data. The comparison revealed that

lated reservoir pressures at different well locations were generally higher than

observed pressures. This was true with both EnCana’s history match and the new

history-matched model.

In order to reduce reservoir pressure in the flow model, the injection rates at wate

tors were reduced from actual values to lower rates to simulate the loss of injected

water into the Frobisher formation. Historically, water injectors were drilled through the

Midale formation and down into the Frobisher formation. Then, the wells were plugged

del

calcu

r

injec

ack. According to a geologic study of Weyburn (Churcher and Edmonds 1994), the

n interaction

etween Vuggy and Frobisher. Moreover, a weak aquifer was simulated using a Carter-

racy analytic aquifer model in EnCana’s model, which also implies communication

between Vuggy and Frobisher. This issue was discussed with Ryan Adair, an EnCana

reservoir engineer. He agreed that there was a loss of injected fluid into Frobisher in the

simulation area. These factors justified the reduction of injection rates in order to lower

the pressure. As a result, a reasonable match was achieved (Figure 8.19).

8.4

b

original oil-water contact was found in the Frobisher, which suggests a

b

T

Waterflood History Matching to CO2 flood History Matching

The new history match of the waterflood process was relatively simple to achieve

once the shape of relative permeability curves was determined to be a key factor. Then,

based on the waterflood history match, the simulation was extended to the CO2 flood by

restarting the simulation run at the end of waterflood simulation. After a reasonable

match was obtained for the CO2 injection period, the flow model input data set was reset

155

to the beginning of field history to rerun the complete field history. Then, another history

match process was started based on the previous run to further modify the simulation

model. Figure 8.20 shows the iterative history match work flow.

Vertical permeability was increased based on the observations presented and

discussed in previous chapters. Each simulation run took a longer time to run than earlier

runs with lower vertical permeability because the increase in vertical permeability led to

increased throughput. The thickness of some layers in the model was very small, which

caused throughput to exceed a preset limit through those thin layers. When the limit was

exceeded, the time step size needed to be reduced, which resulted in long simulation run

times.

Figure 8.19: Measured and calculated pressure

0

50

100

150

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Pres

sure

(BA

RSA

)

250250

Measured CalculatedMeasured CalculatedMeasured Calculated

0

50

100

150

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Pres

sure

(BA

RSA

)

156

Figure

Waterflood CO2 flood

On-trend, off-trend, corner wells response• Waterflood history match

Horizontal producer’s response

• CO2 flood history match

1958 2000 2001

RESTART from the start of CO2 injection

Run both water and CO2 floods to verify

8.20: History match flow

8.5 History Matching using 4-D seismic Data

The production history match during the CO flood was performed in the So

and East patterns, mainly to match production response to CO2 uth

2 injection. Wells OP-

09HB12 and OP-01H13 in the South pattern and OP-15H18 and OP-08H18 in the East

producers during the CO2

jection period were reasonably close once the waterflood was considered acceptable.

have shown the most significant responses to CO2 injection, thus these wells were studied

closely in the matching process. The matches of other

in

157


d on

ma

perm

oduction data was to modify

e Marly and Vuggy formations. Since the

relative permeability curves were derived from core data, the appropriate modification

was thought to be applicable as it was ar

ate.

EnCana tried to run an injection profile log on injection well CD-10H12 using a

coiled-tub

The pictures of the P-impedance data (Figure 5.7 and Figure 5.8) showed a

significant anomaly in vicinity of well OP-09HB12. Correspondingly, the production

increase of the well when it responded to CO2 injection was much greater and sooner

than the oil production increase observed in well OP-01H13. Many simulation runs were

executed in an attempt to match the oil production increase of these wells. The

production response of well OP-01H13 was matched when a suspected high permeability

zone or channel was simulated. The possibility of a high permeability zone was base

observed P-impedance data (Figure 8.21). However, a difficulty was encountered in

tching the production increase of well OP-09HB12.

In order to match the production from well OP-09HB12, abnormally high

eabilities in the Y direction, up to 1 darcy, were tried in the simulation, but this

approach was unsuccessful. The next attempt to match pr

the oil relative permeability curves in th

gued in Section 8.3.3. The oil relative

permeability in Marly was increased so that the oil becomes more mobile throughout the

saturation range. This modification slightly improved the initial production rate of the

horizontal wells; however, the production response of well OP-09HB12 was still delayed

by at least five to six months, and the oil rate increase was lower than the observed r

ing unit. They encountered technical difficulties and decided to halt the

logging operation before the tool was able to get into either leg. Since these legs of the

injection well were completed open-hole, it is impossible to know where CO2 was

injected into the reservoir. Moreover, it is not even possible to quantify how much of the

injected fluid was allocated into each leg of the well without the injection profile log.

158

A closer look at the time-lapse P-impedance picture pointed out that the spread of

the anomaly was approximately an equal distance on the NW and SE sides of the

southern leg of the well. In the right picture of Figure 8.21, the north leg was removed

that the symmetry of the anomaly around the southern leg of the well can be easily

observed. Based on this observation, all of the completions in the northern leg were shut

in the flow model except for grid cells that intersect with the channels disc

so

ussed

previously (Figure 8.23). This completion change accelerated the response of well OP-

09HB12. In addition, this change did not affect the response of well OP-01H13.

There is an extension anomaly toward well OP-10H12 from the tip of the

injection we

the

ice that CO2 contacted

just the upper portion of the Vuggy.

nce, including P-impedance changes caused by CO2 injection.

ll. Injected CO2 appears to proceed toward the horizontal producer, which

has shown a production response in the second year of the gas injection project. Figure

8.22 also indicates the advance of the CO2 front toward the producer in the Vuggy.

Figure 8.24shows the CO2 mole fraction in the liquid phase. Due to the high

vertical permeability and introduction of high permeability channels, more of the injected

gas appears to be in the Marly than the Vuggy. The cross-section (Figure 8.25) shows

distribution of the injected fluid and more CO2 in the Vuggy. Not

Calculated time-lapse P-impedance changes ranged from -7% to 1%, which is

much narrower than the actual range from -10% and +10%. As mentioned previously,

Gassmann’s equation was used in the calculation of P-impedance, and it is suggested by

Brown that the equation is adequate for fluid substitution in Weyburn reservoir rock for

time-lapse seismic monitoring purposes. Figure 8.26 shows the calculated time-lapse P-

impeda

159

Figure 8.21: Marly P-impedance change of the South pattern indicating the channels and the equal spread of the anomaly from the southern leg

OP-01H13

OP-09HB12

channels

OP-10H12

CD-10H12OP-01H13

OP-09HB12

channels

OP-10H12

CD-10H12

Figure 8.22: Vuggy P-impedance changes in the South pattern.

OP-01H13

OP-09HB12

CD-10H12

OP-10H12

OP-01H13

OP-09HB12

CD-10H12

OP-10H12

160

Figure 8.23: Completion changes in injection well CD-10H12

Figure and

0

1

0

1

8.24: The South pattern liquid phase CO2 mole fraction in layer M3_A (left)V2_A (right)

161

Figure 8.25: Cross section of the South pattern showing CO2 mole fraction in liquid phase.

Figure 8.26: The image of the calculated P-impedance

W N

S E

W N

S E

-7% 4%

Marly VuggyW N

S E

W NW N

S ES E

W N

S E

W NW N

S ES E

-7% 4%

Marly Vuggy

Marly

Vuggy

OP-01H13 CD-10H12 OP-09HB12

Marly

Vuggy

Marly

Vuggy

OP-01H13 CD-10H12 OP-09HB12

162

8.5.1.1 Production Match Results

The P-impedance data used for the history match was from 2000 to 2001.

flow model was modified based on the P-impedance data and the production data. Since

the production history for 2002 was available, the simulation run was extended to

The

Octobe

lso,

the pro

r well OP-09HB12. The timing of the production

increas f

s

ch lower than

the corresponding rate in EnCana’s model.

Figure 8.28 shows the production m

towards well OP-01H13 were sim ward the well

from the injector. The ma tch for well

OP-09HB12. There is a slight delay in

production response could be m

However, increasing channel permeability caused a high gas rate during the second year

along with reduced oil rate. Therefore, channel permeability was reduced so that the

r 2002, which covers a total of two years of CO2 injection.

Simulation of the CO2 injection period with EnCana’s model resulted in a good

match of oil production, but did not match gas breakthrough because the EnCana model

had relatively low vertical permeability, which keeps CO2 in the Vuggy formation. A

duction of oil during the second year of injection was not matched.

As presented in previous chapters, vertical permeability was increased in the new

history matched model so that gravity segregation could occur. Gravity segregation helps

prevent early CO2 breakthrough as a result of flow through the Vuggy formation. Figure

8.27 is the production match results fo

e was about one month late despite the modification of the completion interval o

the CO2 injector mentioned in the previous section. An increase in permeability toward

well OP-09HB12 was included in the simulation model in an attempt to match the oil

production increase. However, further improvement in the match was limited until CO2

breakthrough was achieved. The match improved as the run progressed into the second

year of injection. Also, the gas production rate in the new model was mu

atch results for well OP-01H13. The channels

ulated by increasing the permeability to

tch of initial production is much better than the ma

the production response. The timing of the

atched by increasing the permeability in the channels.

163

calculated gas rate was lowered. This change still resulted in a high gas rate during the

for

Figure 8.27: Production match of OP-09HB12

second year, but the oil rate was not reduced by breakthrough of injected gas.

Figure 8.29 and Figure 8.30 show the area of local permeability modification.

The modification was to simulate the channels and to increase permeability in the Marly

mation.

Oct. 2000 Oct. 2001 Oct. 2002Oct. 2000 Oct. 2001 Oct. 2002

164

Figure 8.28: Production m

igure 8.29: The location of local permeability modification in Marly. The shaded area is odification.

atch of OP-01H13

O c t. 20 0 0 O c t. 2 0 0 1 O c t. 20 0 2O c t. 20 0 0 O c t. 2 0 0 1 O c t. 20 0 2O c t. 20 0 0O c t. 20 0 0 O c t. 2 0 0 1O c t. 2 0 0 1 O c t. 20 0 2O c t. 20 0 2

S ES E

Fthe area of the m

165

S ES E

Figure 8.30: The location of local permeability modification in Vuggy. The shaded area is the area of the modification.

8.5.1.2 Objective Function

the accu

s the OF history

P-im

points to ber

ined the

same

pedance match was improved in Marly compared to EnCana’s, but not

in Vuggy. The OF for both Marly and Vuggy did not decline significantly after the

ertical permeability was increased. As for the objective function for the production data

r the one-year period of CO2 injection (Figure 8.32), the OF for oil production and

Objective functions were calculated as discussed previously in order to quantify

racy of model calculated P-impedance and production matches. The trial #1 on

each OF plot represents the results of EnCana’s model. Figure 8.31 show

for the P-impedance match in Marly and Vuggy in the South pattern using a 2% cut-off in

pedance change. The OF was also calculated using a 4% cut-off value. The OF

value with a 4% cut-off was reduced to a lower cut-off to allow more data

included in the calculation. However, the basic trend of the OF history rema

and there was less fluctuation in the plot. The 2% cut-off value was used to honor

more data points in the OF function calculation and is presented here.

The P-im

v

fo

166

GOR showe

same.

performa

the timing

CO2

d improvement, but the OF for water production remained practically

unchanged. The same plot was created using 1% cut-off and the trend was essentially the

Figure 8.32 is the objective function history for matching horizontal well

nce in the South pattern. The EnCana model performed best (had the lowest

OF) for the one-year CO2 injection period since it achieved a better match of

and production rates of the oil production response in both wells OP-01H13 and OP-

09HB12. On the other hand, EnCana’s model had the poorest match of GOR because

breakthrough was not matched as well as the new model (Figure 8.33).

Figure 8.31: Objective function history of the P-impedance in the South pattern

167

Figure 8.32: Objective function history of the production in the South pattern

Figure 8.33: Objective function history of the production (oil and water rates) of only horizontal wells in the South pattern

168

Figure 8.34: Objective function history of the production (GOR) of only horizontal wells

The OF for the production presented earlier was for a one-year period following

CO2 injection. The simulation was run for two years into the injection; thus, the OF for

production for the two-year period following CO2 injection was also calculated. Figure

8.35 is the OF for the two-year production period in the South Pattern. As in the one-

year OF, the value decreased in all three variables. Recall that the lowest OF for

horizontal wells in the South pattern for the one-year production period was for EnCana’s

model because it had a better match of breakthrough timing and production rates.

However, when the period of interest was extended to two years, the OF value in the new

model was lower than the corresponding OF for the EnCana model since the production

match for the two-year period in the new model was more accurate (Figure 8.36).

in the South and East patterns

169

Figure 8.35: Objective function history of the 2-year production in the South pattern

Figure 8.36: Objective function history of the 2-year production of horizontal well only in

the South pattern

170

8.5.1.3 Cumulative Production of the South Pattern

m

gas increase was improved.

Figure

Figure 8.37 shows cumulative production from the South pattern. Notice that the

calculated total oil production is greater than observed total oil production due to the

ismatch of the production rates at corner wells, especially well OP-14-07 (Figure 8.14).

The increased oil production occurred because production rates were constrained by

liquid rate, which replaced missing water with oil when water was not available in the

model for production from corner wells. Recall that the increase in cumulative gas

production from EnCana’s model was early due to CO2 breakthrough (Figure 4.40).

Since the early breakthrough was resolved in the new model, the timing of the calculated

8.37: Cumulative production of South pattern

D u e t o m is m a tc h a t c o r n e r w e l ls D u e t o m is m a tc h a t c o r n e r w e l ls

171

8.5.2 East Pattern

Figure 8.38 shows P-impedance change in the East pattern. The area of the

change is not as big as in the South pattern, and the spread from injection legs seems

uniform sistent

.

hese

channels. Production matches for the horizontal producers in this pattern were not as

difficult to achieve as they were for producers in the South pattern.

In the new flow model, well WG-10-18 is a WAG well located just NE of well

rmation(s)

show so 2 to other

reservo

patte

perm rth.

ore CO2

ntrated

near th n completion intervals of well CD-10H18.

, except there is almost no change along one-third of each leg. This is con

in both Marly and Vuggy. The injection profile log has not been obtained for this well

Thus, the last one-third of the injection legs was shut in the flow model so that CO2 is

injected into the first two-thirds of the legs near the wellhead.

There are anomalies that may be indicating channels toward both wells OP-

08H18 and OP-15H18. Permeability was modified accordingly to simulate t

CD-10H18. The CO2 injected into well WG-10-18 appeared in the flow model, but not

in observed P-impedance data. Unless all of the injected CO2 was lost to fo

other than Marly or Vuggy, the observed time-lapse P-impedance differences should

me change. Since none of the available evidence shows the loss of CO

irs, no modification at well WG-10-18 was applied.

Figure 8.40 shows the CO2 mole fraction in the liquid phase. As seen in the South

rn, the areal coverage of injected gas occurs in Marly due to high vertical

eability. The figure also shows the CO2 injected into well WG-10-18 in the no

The cross section (Figure 8.41) shows the areal coverage of injected gas with m

in Vuggy than Marly.

Figure 8.26 is the calculated time-lapse P-impedance, which shows the P-

impedance change caused by CO2 injection. The change of P-impedance is conce

e ope

172

No injection?

Channel

OP-15H18

CD-04H18

OP-08H18

Marly Vuggy

WG-10-18No injection?

Channel

OP-15H18

CD-04H18

OP-08H18

Marly Vuggy

WG-10-18

Figure 8.38: Vuggy P-impedance change indicating no injection sections of the horizontal ward horizontal producers.

igure 8.39: Completion change of CD-10H18

legs and possible channels to

F

173

Figure 8.41: Cross section of the East pattern showing CO2 mole fraction in liquid phase.

0

1

Figure 8.40: The East pattern liquid phase CO2 mole fraction in layer M3_A (left) and V2_A (right)

0

1

0

1

Marly

Vuggy

OP-15H18 CD-10H18 OP-08HB18

Marly

Vuggy

OP-15H18 CD-10H18 OP-08HB18

174

8.5.2.1 Production Match Results

Figure 8.42 is the production match for well OP-08H18. The initial p

tched, and the possible reason was discussed in previous sections. As for the

production response to injection, the well showed a gradual increase in oil production,

unlike the two horizontal wells in the South pattern. The plot shows the increase in

calculated oil production occurred later than the observed increase in oil production, even

odel included a high permeability channel that extended fro

ll to the production well. The permeability of Marly was incr

, but it required the value in the range of one darcy, whic

0 meter by 60 meter cell containing tight formation and natural fractures.

roduction

was not ma

though the flow m m the

injection we eased to match

the response h is not a realistic

value for a 6

ll

ulation results were considered acceptable.

There was a difficulty in matching the production history for well OP-15H18,

especially the gas rate. Similar to well OP-08H18, the timing of the oil production

increase was or toward well

OP-15H18 was sim ted gas

production rem injected at well

Attemp tch of overall

Therefore, the permeability was reduced to lower, more reasonable values. The overa

sim

off. A postulated high permeability channel from the inject

ulated by increasing the permeability in the direction. Calcula

ained high relative to observed gas production. The CO2

WG-10-18 also reached the producer and made the gas production problem worse.

ts to refine the history match at this well were suspended, and the ma

oil production rate with lower gas rate was accepted as the best match that could be

achieved using the single porosity model adopted here.

175

Figure 8.42: Production match of OP-08H18

Figure 8.43: Production match of OP-15H18

Oct. 2000 Oct. 2001 Oct. 2002Oct. 2000Oct. 2000 Oct. 2001Oct. 2001 Oct. 2002Oct. 2002

Oct. 2000 Oct. 2001 Oct. 2002Oct. 2000Oct. 2000 Oct. 2001Oct. 2001 Oct. 2002Oct. 2002

176

8.5.2.2 Objective Function

8.44.

e

ed

match

orizontal wells only.

In spite r

8.5.2.3

The objective function history of the P-impedance match is shown in Figure

The results are similar to the South patterns: improvement for Marly and slight increas

for Vuggy. The OF was most sensitive to an increase in vertical permeability. There is a

slight improvement after the completion interval change at well CD-10H18. As shown in

Figure 8.26, the P-impedance change in Marly was concentrated where the well

completions were open.

The OF for the production match during the first year of CO2 injection show

that all variable changes lead to improvements in the OF as the number of history

trials increased (Figure 8.45). The most significant improvement occurred with GOR.

Figure 8.46 is the OF history for the oil and water production from h

of the difficulty of matching production, the OF was reduced. The plot of OF fo

the GOR also showed improvement (Figure 8.34). The OF’s for both the complete East

pattern and the case with horizontal wells only decreased during the two-year injection

period (Figure 8.47 and Figure 8.48).

Cumulative Production

.49. The

om horizontal wells resulted in a calculated oil production rate

that was lower than the observed rate starting around day 14,000. A correspondingly high

water p a’s

e now considered unreasonable.

The cumulative production plot for the East pattern is shown in Figure 8

discrepancy between observed and calculated oil production that was noted in the match

of the South pattern was not as big in the East pattern. The inability to match observed

high initial production fr

roduction rate was calculated during the same period. Nonetheless, EnCan

cumulative production rate was much better than this plot (Figure 4.41), but the improved

EnCana match was associated with modifications that ar

177

Figure 8.44: Objective function history of the P-impedance in the South pattern (2% cut-

off)

Figure 8.45: Objective function history of the production in the East pattern

178

Figure 8.46: Objective function history of the production (oil and water rates) of only horizontal wells in the East pattern

Figure 8.47: Objective function history of the 2-year production in the East pattern

179

Figure 8.48: Objective function history of the 2-year production of horizontal wells onlyin the East pattern

Figure 8.49: Cumulative production of East pattern

180

8.5.3 Total Objective Function and Relative Objective Function

In order to measure the correctness of the simulation model, the overall OF for the

lete production history (from 1956 to 2002) was calculated. Figure 8.50 and Figure

8.51 are the OF for the overall production from the South and East patterns, respectively.

Both show a decrease in OF values.

The OF of the pressure match is also shown in Figure 8.52. The reduction in

ciated with the loss of injected water into the Frobisher form

lated by reducing the injection efficiency of vertical water injectors in the m

Subsequently, the relative OF was calculated by combining both OF for both P-

pedance and production as discussed in Section 5.8. Using EnCana’s model as the

e relative OF was calculated at each trial. There are a total of five variab

comp

pressure asso ation was

simu odel.

im

base case, th les

and GOR. Therefore, the

elative OF included ten variables for the two patterns. Since EnCana’s model was

lated OF

represents E

permeability

pressure ma tch of South

e decline as the

history ma istory

match m

in each pattern: P-impedance in Marly and Vuggy, oil, water,

r

defined as the base case, EnCana’s model is assigned the value of ten. The calcu

values were divided by the EnCana’s model value. Figure 8.53 is the plot of the relative

overall objective function without OF of the pressure match. The initial value of ten

nCana’s model. The OF value continued to decline as the vertical

and local modifications were added to the simulation model.

Figure 8.54 is the plot of relative overall objective function with OF of the

tch. The initial value became twelve since OF of pressure ma

and East patterns were added to the previous plot. The plot also shows th

tch modifications were applied to the model. This indicated that the h

odifications helped improve flow model results.

181

Figure 8.50: Objective function history of overall production in the South pattern

Figure 8.51: Objective function history of overall production in the East pattern

182

Figure 8.52: Objective function of pressure match

Figure 8.53: Relative objective function without OF of pressure

183

tion with OF of pressure Figure 8.54: Relative objective func

184

185

Chapter 9

CONCLUSIONS AND RECOMMENDATIONS

9.1 Introduction

This research successfully demonstrated that time-lapse P-impedance data used in

conjunction with production data improved an existing reservoir flow model. This is the

first study to use time-lapse seismic data to constrain a flow simulation model of CO2

injection into a layered, waterflooded reservoir. The time-lapse data provided interwell

information that was helpful in modifying the flow model and improving reservoir

characterization. In addition, this study examined several important factors discussed

below.

9.1.1 Time-Lapse P-Impedance Data

In this study, the time-lapse P-impedance data provided valuable interwell

information that assisted the history matching process. Without the data, the flow model

would be les

factor, vertical permeability, the controlled fluid movement in this layered reservoir.

s accurate in forecasting future production and the movement of fluids

within the reservoir. For example, the large P-impedance change in the Marly formation

helped us understand CO2 movement in the reservoir, and helped us identify the key

The P-impedance data showed a possible high permeability zone in the “off-

trend” direction that was not detected with other approaches. One benefit of time-lapse

P-impedance data is that it provides an image of pressure and saturation changes in the

reservoir. Another benefit in this case was the usefulness of P-impedance data for

indicating the effectiveness of injection along the length of legs in multilateral, horizontal

186

wells. The recognition of high permeability zones and injection profiles significantly

helped in improving the flow model.

The procedure for integrating time-lapse seismic surveys presented here can be

extended to other areas of Weyburn Field and to analogous fields. The seismi

shot by RCP were high-resolution multi-component surveys that are mo

conventional surveys. Future time-lapse survey(s) should be conducted to m

nce control of the injected gas in the reservoir. The acquired data should be

odel so that the future injection and production perform

c surveys

re expensive than

onitor the

conforma

integrated into a flow m ance can

be forecast.

9.1.2 Forward Modeling and Optimization

Gassmann’s theory was used for this study. It is appropriate to use for s

changes in P-impedance data. The magnitude of the calculated P-impedance

tudying

changes

was less than the observed changes. The observed P-impedance changes clearly showed

where t sults.

odel in other areas of Weyburn

Field to predict the response of seismic surveys to reservoir conditions that arise under

different operating scenarios. This enables geophysicists to optimize the timing and

he overall objective functions (OF) for the Marly and Vuggy in both South and

ast patterns were improved by increasing the vertical permeability. However, the OF

or P-impedance in the Vuggy could not be reduced. Although the improvement of the P-

impedance match for the Vuggy was unsuccessful, the OF for production was

he CO2 was injected and could be compared with calculated P-impedance re

The forward modeling process provided useful information for interpreting fluid

movement once appropriate modifications were made for the Weyburn Field. This

forward model can be used in conjunction with the flow m

frequency of the seismic surveys in the future.

T

E

f

187

successfully nt of the flow

model.

9.1.3

reduced. The relative OF also signifies the overall improveme

Natural Fracture Characterization and Simulation Model

Natural fracture characterization has been studied extensively by many

researchers. This information needs to be built into the flow model to direc

fluid flow in a fracture network. Since the time-lapse P-impedance data showed possible

eability zones, the data can also be incorporated into a new flow m

llected with the P-wave data could also provide valuable inform

tly represent

high perm odel. The

shear wave data co ation

these data should im

core and log

appears to b ased by

relativel ated flow in

form ultiplier is

probably best

to m t for

horizon al producers drilled into the Marly formation.

Through this research, limitations of the single porosity assumption were

encountered during the history matching process. Permeability was multiplied by a

relatively large number to match the waterflood and CO2 flood responses. Also, the

to characterize the fracture network of the reservoir (Terrell 2004). The inclusion of

prove the flow model, especially during the CO2 injection period.

EnCana’s model is a single porosity model that was developed from

data. This does not directly account for the effect of fluid flow in natural fractures. That

e the reason why the permeabilities in the model needed to be incre

y large values in some instances: the permeability changes approxim

natural fractures. Since the Vuggy formation is much more fractured than the Marly

ation, the single porosity model may be adequate if a high permeability m

applied to account for high permeability flow in fractures. However, it is

odel the less fractured Marly formation with the dual porosity model to accoun

flow in fractures as well as the interaction between the fractures and the matrix.

Conceptual model work suggests that the single porosity model assumption was the

reason we encountered considerable difficulty matching the production response of

t

188

relative p

modification inal

relative p lude the

es if the naturally

fractured res

odel that

incorporates

comp rns, such as

ual

9.1.4

ermeability curves were modified significantly. We believe that such

s were necessary to approximate flow in natural fractures. The orig

ermeability curves were measured with core data, which does not inc

effect of fractures. It is difficult to calibrate relative permeability curv

ervoir is modeled within the context of a single porosity flow model.

Therefore, it is recommended that future studies employ a dual-porosity flow m

fracture studies.

The dual-porosity model would take more simulation time due to its greater

lexity. Thus, a flow model that covers a small number of injection patte

the RCP survey area model, would be ideal for evaluating the relative merits of the d

porosity calculation scheme with the single porosity model.

Horizontal CO2 Injectors

ertical

ells

and drain mu

re expensive to

drill than ve

multila

field. The form

Since the ho ractice in

a “hard rock trol

sections. Furthermore, the injection wells with two legs make the problem more difficult.

The horizontal wells used in the study have many advantages relative to v

wells. In general, horizontal wells have higher productivity/injectivity than vertical w

ch larger areas. Horizontal producers can reduce water coning effects when

operated at appropriate rates. On the other hand, horizontal wells are mo

rtical wells.

As for horizontal wells in Weyburn Field, horizontal producers were selected to

help recover bypassed oil from the tight Marly formation. However, the choice of

teral, horizontal wells as CO2 injectors did not seem to be the best choice for this

ations in the Weyburn Field are heterogeneous and naturally fractured.

rizontal injectors were completed open-hole, a normal completion p

” formation, the placement of injected gas is practically impossible to con

without special tools such as liners with external casing packers to block out certain

189

Actual gas injection into the legs of one multilateral well may have been

disproportionately excessive in one leg relative to the other leg based on calculated

completion flow capacities. . If low injectivity was an issue and horizontal wells were

necessary, the well should have been drilled with just one leg, or if possible, several

horizontal wells with short legs, or vertical injection wells.

The problem with the current horizontal completion is the lack of fracture

characterization. If fracture information is available, the horizontal wells can be placed

in the right spot and arrangement so that we can take advantage of the fracture system in

order to optimize oil recovery and CO2 utilization.

Once wells are utilized as injectors, it is imperative to know the placement of the

injected fluid. It is cheap and easy to run the injection profile logs on vertical wells, but

not so for horizontal wells because the tool needs to be conveyed with tubing or a coiled-

tuning unit. A well with two legs requires more tools, such as a directional tool, which

increases the cost of the job and makes the job intricate. EnCana has tried to run the

injection profile logs in horizontal CO2 injectors, but failed to do so successfully. The

lack of availability of injection profile logs made the history match process difficult; the

change in completed sections of the horizontal well where CO2 was injected made a

significant difference in production response at adjacent horizontal producers. The time-

lapse P-impedance data provided information about where CO2 was injected along the

length of each horizontal injector leg. That information lead to the hypothesis that the

allocation of injected gas along the length of a horizontal well leg may be problematic

and should be investigated further. If this problem is valid, the use of horizontal injection

wells needs to be re-evaluated. In this case, the operator should consider replacing

horizontal wells with several vertical injectors or horizontal wells with short legs for

better control and monitoring of injected fluid. Also, instead of injecting CO2 into the

Marly formation, the gas may be injected into the Vuggy formation to take advantage of

gravity segregation so that some oil left in the Vuggy formation can also be recovered. In

190

this case, a WAG injection scheme should be considered to delay CO2 breakthrough

within the Vuggy f

ormation.

191

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196

197

APPENDIX

60 1 60 8 15 /

0 1 60 2 2 /

--------------------------

A-1 ECLIPSE data file

-- ******************* PERM Modification ******************** -- -- GLOBAL CHANGE----------------------------- MULTIPLY -- Marly PERMX 35.0 1 60 1 60 2 6 / PERMY 20.0 1 60 1 60 2 6 / -- Vuggy PERMX 20.0 1 60 1 60 8 15 / PERMY 10.0 1/ ADD PERMY 220.0 1 60 47 55 2 2 / PERMY 220.0 1 60 47 55 4 4 / / -- Increase PERMZ MULTIPLY PERMZ 40 1 6PERMZ 60 1 60 1 60 3 3 / PERMZ 40 1 60 1 60 4 4 / PERMZ 40 1 60 1 60 5 5 /

60 1 60 6 6 / PERMZ 40 1 PERMZ 100 1 60 1 60 7 7 / PERMZ 40 1 60 1 60 8 8 / PERMZ 5 1 60 1 60 9 9 /

60 1 60 10 14 / PERMZ 20 1 / -- LOCAL CHANGE --- -- Reduce PERMY NEAR WI-06-13 MULTIPLY PERMY 0.01 8 14 30 35 9 14 / /

198

-- SOUTH PATTERN *******************************

12 45 56 2 14 / 13 45 56 2 14 /

area toward OP-09HB12

2 14 /

MULTIPLY -- Marly channel toward OP-01H13 PERMY 1.3 12PERMY 1.3 13PERMY 1.5 14 14 45 56 2 14 / PERMY 1.5 7 7 45 60 2 14 / PERMZ 1.5 12 14 45 50 2 14 / PERMZ 1.5 7 7 45 50 2 14 / -- Marly high permPERMY 1.5 4 6 51 52 2 14 / PERMY 1.5 3 6 53 53 2 14 / PERMY 1.5 2 5 54 54 2 14 /

4 55 55 PERMY 1.5 1 -- EAST PATTERN ********************************** -- Channel toward OP-08H18 PERMY 1.5 31 33 52 56 2 14 / -- Channel toward OP-15H18 VUGGY ONLY PERMY 1.0 33 34 47 49 8 14 / /

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