Research advisor: Dr. Thomas W. Engler

Committee members: Drs. Mike Kelly and Reid Grigg

Presented by

Akapak “Nick” Srichumsin

Graduate Student

New Mexico Tech

1

2

Introduction

Reservoir characterization

Model construction

History matching

Prediction

Conclusions

2

3 3

4

This research is one part of the project entitled “Mini-Waterflood: A New Cost

Effective Approach to Extend the Economic Life of Small, Mature Oil

Reservoirs”.

The project focuses on assisting small producers with technical knowledge to

enhance oil recovery for a mature oil field.

4

Reservoir

Characterization

Reservoir Simulation Core Analysis

Evaluation of

Mini-Waterflood

Potential

5

The targeted reservoirs are small, mature, shallow, low pressure, low

temperature, and has unfavorable mobility.

Typically ignored, this type of reservoir generally still contains significant

amount of oil-in-place.

5

Round Tank

Fields with high oil production have experienced waterflood.

6

The main objective of this thesis is to evaluate the waterflood potential of the

Round Tank (Queen) reservoir and determine the best strategy for the field by

using reservoir simulation.

6

7 7

New Mexico

Texas

Miles

0 100

Carlsbad

Hobbs

Roswell

Lea

County

Eddy

County

Chaves County

Goat Seep reef

Caprock

Queen

Double L

Vest Ranch

S Lucky Lake

Sulimar

Round Tank

High Lonesome

miles

0 12

Delaware Basin

New Mexico

Texas

Miles

0 100

Carlsbad

Hobbs

Roswell

Lea

County

Eddy

County

Chaves County

Goat Seep reef

Caprock

Queen

Double L

Vest Ranch

S Lucky Lake

Sulimar

Round Tank

High Lonesome

miles

0 12

Delaware Basin

Thin reservoir (~16’ thick).

Stratigraphic trap

~1,500’ from the surface

The Round Tank Queen sand

8 8

Gp = 4.2 Bscf

Pi = 600psi

P ~ 50psi

RF ~ 92%

Np = 26 MBO

OOIP = 2.85 MMBO

RF ~ 1%

9 9

Gas properties

Dry gas w/ high N2

(61% N2 and 28% CH4)

Oil properties

Dead oil (very low GOR)

35°API w/ 13.67cp

10 10

To locate injectors along the downdip edge of the oil column in the water leg,

and producers along the updip edge of the oil column.

11 11

Data Acquisition

Data Interpretation

Model Construction

Model Validation

Prediction

Reservoir Characterization

Reservoir Simulation

12 12

13

A common problem in small, mature fields is the limited and poor quality data,

typically consisting of only old logs and production history.

Evaluation of the field relies on existing data or data which are easy to acquire.

Old logs (circa 1960s), 14 modern logs and one-core are the main sources for

this reservoir study.

13

14

Available wireline logs for acquiring porosity

Modern logs (late 2000s) – a combination of density and neutron logs.

Old logs (1960s to 1970s)

• Neutron

• Sonic

• Density

The main problems applying old logs are (1) the poor quality and reliability and

(2) the required conversion.

14

In general, only one type is available at each well location.

15 15

Density/neutron crossplot

Anhydrite layer

Anhydrite layer

Maximum porosity interval

16

A common problem for the old neutron log is the units; generally, CPS or API

unit was used.

Typically, these units can be converted to porosity unit (either % or fraction) with

the use of calibration chart provided by a logging company.

16

Calibration chart (courtesy Schlumberger)

If the proper calibration chart is not accessible, a linear relationship of tool

response and porosity can be created from two known, porosity control points.

Different in

operating companies,

scale ranges,

borehole conditions,

and calibration

17

All the neutron logs with various scale-ranges were normalized into 0-1 scale-

range with a linear relationship.

17

(from Modern logs)

Min. Ф interval

Max. Ф interval

Control point 2

Ф = 23.4%

Control point 1

Ф = 1%

18

Two linear relationships were made:

(1) Linear porosity vs. linear tool response

(2) Log porosity vs. linear tool response

18

(1)

(2)

Adjacent

wells

19

Advantages

The normalizing process helps to mitigate the effects of the different conditions

among wells such as hole size, mud type, and logging company.

The proposed application, therefore, improves unreliable and poor quality data

to useful and reliable data.

19

20

Wyllie’s and Raymer-Hunt transforms

(courtesy Schlumberger)

ФHi t & Mod t > 29%

Porosity-transform correlations

Wyllie’s transform

- Clean and consolidated formation

Raymer-Hunt transform

- Unconsolidated/friable formations

21 21

Adjacent well

Adjacent wells

Raymer-Hunt

Raymer-Hunt

Raymer-Hunt transform is not applicable within the Round Tank Queen formation.

22 22

Comparison between Raymer-Hunt transform with Gulf of Mexico data obtained from moderately consolidated to unconsolidated sands (Bassiouni 1994)

Unconsolidated sands from Gulf of Mexico do not comply with the Raymer-Hunt

transform; the actual porosities from core experiment tend to be lower than

calculated.

23

In general, abnormally high interval transit time is due to the effect of reservoir

gas and uncompacted formation.

Core samples collected from Round Tank Queen Unit No.6-Y indicate friable

characteristic of the formation.

23

Main factor causing abnormally high t

24

(max)

(max)

known

R

cU

Overestimated porosities due to the effect of friable sand need to be corrected.

The work was done by modifying Raymer-Hunt transform with the correction

factor, an Uncompaction Correction (Uc).

Uc is the ratio of apparent sonic porosity to known porosity.

24

log

log

t

ttC

ma

R

c

RR

U

'

C = 0.6 for gas zone,

C = 0.67 for oil and water zones

tma = 56 μsec/ft for sandstone formation

Raymer-Hunt transform

Modified Raymer-Hunt transform

Adjacent new wells

Raymer-Hunt Trans.

25 25

Comparison between modified Raymer-Hunt

transforms with Gulf of Mexico data obtained from

moderately consolidated to unconsolidated sands

The proposed procedure gives

satisfactory results in both value

and curve trend.

26

Water saturation of the field was observed through well logs with the use of

Archie’s equation.

Where a = tortuosity factor

m = cementation exponent

n = saturation exponent

26

n

T

w

wR

FRS

/1

m

aF

27

Resistivity/porosity crossplot or Pickett plot is applied for this study to examine m

and n exponents.

27

28 28

c OWC (~2210’)

Transition zone

FWL (???)

Hydrocarbon zone w/ Siw =41.7% (from core Siw =43%)

29

Capillary pressure curve was

constructed based on published

correlation and log-derived water

saturation.

The power function proposed by

Brooks and Corey (1964) is

applied to create Pc curve.

29

/1'

w

dc

S

pp

iworw

iwww

SS

SSS

1

'

ow

cpheight

433.0

where λ = pore-size distribution index. Pd = entry pressure

S’w = normalized water saturation

Pc curve can be converted to

height curve by

30

Layers of the Round Tank Queen Sand need to be identified to acquire accurate

definition of the geologic flow units within the sand.

A stratigraphic layering approach was chosen to identify the number of layers and

layer thicknesses.

30

31

Evidence of abnormally high responses from sonic logs indicates that a friable zone exists with the Queen sand.

The observation of friable zone was made by focusing on two dimensions – areal and vertical.

Areal Vertical

Highest

over-response

32

A core sample from Round Tank Queen Unit No.6-Y also supports that Layer3

is the most friable interval.

32

33

Mineralogy of the Round Tank Queen sand has been studied through

examination of core samples and interpretation of wireline logs.

33

Thin section study from core samples (Wilson 2010)

The main mineral is quartz, mixed with potassium feldspar, anhydrite, micas,

and illite.

34 34

Mineralogy analysis through wireline logs

Density/neutron crossplot Lithodensity MID plot

1510

1515

1520

1525

1530

1535

1540

1545

1550

1555

00.10.20.3

True Porosity, frac.

Dep

th, f

t

The Queen

Interval

Example from Eskimo State No.2

Mineralogy analysis was made by using density/neutron crossplot and lithodensity

MID plot.

35 35

Mineral identification chart (courtesy Schlumberger)

The result supports the core analysis about clay types.

Thorium/potassium ratios (Th/K) are quite consistent among layers (~1.7 Th/K).

36 36

Because the formation is characterized into 2 zones, friable and consolidated,

two porosity/permeability correlations are applied.

Round Tank Queen core experiment (taken from samples located in the friable zone)

Adjacent field core experiment

(the Sulimar Queen and South Lucky Lake fields)

37 37

38 38

To achieve the main objective of the study, the following approaches are

selected for constructing the simulation model:

Actual, full-field model with three-dimension aspect.

Isotropic permeability with a single porosity system.

Black-oil fluid description (Eclipse E100 is used for the study).

Fully-implicit equation solver.

39

No sensitivity analysis of gridblock number has been made on this study.

A rule of thumb mentioned in Ertekin (2001) is applied;

3 - 5 gridblocks between production wells.

39

The shortest distance

between wells (L)

L

Gridblock size (WxL) = L/5 x L/5

40

To accurately construct the model, coverage of friable zone need to be considered.

40

Areal Vertical

Porosity map of Layer3 before corrections of friable effect

Friable Consolidated

Friable

Consolidated

Friable Consolidated

41 41

3D-Blackoil

simulation model

Geologic

Description

- Structure

- Porosity

- Permeability

Fluid PVT

Properties

- Dead oil

- Dry gas

- Water

Petrophysics

- Pc curve

- Kr curves

42 42

10% Porosity cut-off for reservoir boundary

43 43

44

Reservoir pressure, well production and bottomhole flowing pressure are the

three parameters for history matching.

Assumption: All the wells, especially oil wells, were operated with low bottom

hole pressure.

Production rates were used in the model to constrain operating conditions when

running the simulation.

44

Model Validation

Well production

Reservoir pressure

Bottomhole flowing pressure

45

The decline curve analysis from Fetkovich (1996) type curve indicates that

most gas wells had produced with constantly low bottom hole pressure.

45

Mehurin#3, b=0.5

JW-State#2, b=0.5

46 46

Before history matching

After history matching (manual history-matching approach was applied)

JW-State#2

JW-State#2

47 47

48 48

60% Reduction

60% Reduction

75% Reduction

The large reduction indicates that permeability in the Round Tank Queen field is

significantly lower than the other Queen sands.

30% increased for kro

49 49

50 50

The proposed flooding pattern is to locate injectors along the downdip edge of the

oil column in the water leg, and producers along the updip edge of the oil column.

The pattern design, well locations and spacing, strongly depends on the existing

new wells in the field to reduce the cost of infill drilling.

The pattern consists of 6 producers and 6 injectors.

51 51

The prediction was performed by running the simulation for 20 years.

Injection and production rates were controlled by bottomhole flowing pressures.

All production wells produce with the minimum bottomhole flowing pressure.

The maximum bottomhole pressure for injection wells is limited at fracture

pressure.

~3.5 BWPD/well

~1.33 BOPD/well

- Prediction results -

Field injection and production rates

Injection rate

Production rate

The prediction results show extremely poor water injection and oil production.

52 52

The observation of oil saturation and

reservoir pressure through time

indicates the poor waterflooding

performance - slow flood front

movement and unable to fill-up

reservoir pressure.

53 53

Reservoir properties and water

injection rates of the Round Tank

Queen field were compared with

the successful waterflooding field,

the Sulimar Queen.

Water injection rates were

calculated from radial-flow,

steady-state equation with

various differential pressures

(dP).

SrrB

PPhkkq

weww

Rwfrw

w

)/ln(

)(00708.0

Many factors contribute to the low injection rate of the Round Tank Queen field

such as low permeability, low krw and low differential pressure.

54 54

Indication of the poor transmissibility of the formation.

~3.5 BWPD/well

~1.33 BOPD/well

- Prediction results -

Field injection and production rates

Injection rate

Production rate

55 55

Low production and injection rates would also be influenced by high oil viscosity.

56 56

An influence of the depleted reservoir pressure to waterflooding performance was

also investigated.

The observation of pressure fill-up trend was made by running the simulation

without opening any producers.

Shut-in all producers

Small pressure increase in oil and water zones; approximately 150 psi of pressure

is increased for 20 years of water injection.

57 57

The investigation was further made by multiplying permeability of the model with a

factor of 10 and reduce μo to 7 cp to reduce the effect of poor transmissibility.

10xPermeability and 7 cp oil viscosity

Even at higher injection rate and

better formation transmissibility,

pressure fill-up is still unfavorable.

Significant amount of oil moves up

into the gas cap due to water

displacement.

The proposed flooding pattern

seems not to be effective.

Water inj.

Oil prod. Water prod.

58 58

59

Successful characterization of the Round Tank Queen reservoir with limited and

poor quality data was made with the assistance of modern logs and core

analysis.

Normalization of old neutron logs and calibration of old sonic logs were two

techniques applied to acquire valuable information.

The study of mineralogy indicates that quartz is the main mineral of the

formation with other minor minerals present a combination of potassium

feldspar, anhydrite, micas and illite.

A newly discovered friable sand bed was identified and has implications on

reservoir performance.

The results from history matching show satisfactory outcomes; a minor

adjustment was made for the porosity distribution, and reservoir boundary was

identified.

59

60

The large permeability reduction from history matching indicates that

permeability of the Round Tank Queen formation is significantly lower than the

other Queen sands.

The prediction results of the proposed flooding pattern show poor performance:

low oil production and water injection rates, slow flood front movement and

unable to fill-up reservoir pressure.

Many factors contribute to the poor performance including low permeability,

high oil viscosity, depleted gas-cap and low differential pressure between

bottomhole and reservoir.

60

61 61

Research Partnership to Secure Energy for America (RPSEA)

Dr. Thomas W. Engler

Drs. Mike Kelly and Reid Grigg

Drs. Her-Yuan Chen and Robert E. Bretz

Armstrong Energy and Bruce Stubbs

Garrett A. Wilson, Albert Ofori, and Oluwafemi Oduye

Karen M. Balch

62 62

Q&A

63 63

Backup

64 64

Round Tank

Queen

Sulimar

Queen

krw' 0.06 0.3

uw 1.56 1.64

kro' 0.39 0.55

uo 13.67 7.6

M' 1.35 2.53

wkro

okrwM

'

''

65

Model discretization is the process of dividing space and time of the simulation

model into discrete segments.

Space discretization gives information about grid-number needed for horizontal

and vertical directions whereas time discretization provides the timesteps used

in the model.

65

66

Space Discretization

Vertical discretization (layering)

As stated previously, the Round Tank Queen sand can be divided into three

layers based on gamma ray logs.

66

Time Discretization (Timesteps)

Timesteps are placed on any major well history occurred such as 1st production,

shut-in, and workover.

Timesteps from all the wells are placed on yearly intervals, and all the wells share

the same timestep (Jan 1 of every year) for simulator computation.

67

No sensitivity analysis of gridblock number has been made on this study.

A rule of thumb mentioned in Ertekin (2001) is applied;

For primary recovery, 3 - 5 gridblocks between production wells.

For waterflooding recovery, 5 - 10 gridblocks between adjacent wells.

67

The shortest distance

between wells (L)

L

Gridblock size (WxL) = L/5 x L/5

> 10 Gridblocks