IMPROVED RESERVOIR ACCESS THROUGH REFRACTURE

TREATMENTS IN TIGHT GAS SANDS AND GAS SHALES

Mukul M. Sharma

The University of Texas at AustinPetroleum and Geosystems

Engineering

April 15, 2009

OutlineProject Objective and GoalsTiming, Project Participants, Major MilestonesValue of the Research – Project ImpactTechnical Overview – Status of Current Technology Project DeliverablesProgress to DateTechnical Issues/Problems EncounteredSummarize

Project Objectives and GoalsUse stress reorientation models to quantify the role played by stress reorientation on refrac productivity improvement.Calibrate the findings with analysis of extensive field dataImprove our ability to predict refracproduction enhancement

Candidate well selectionTiming of refracs

Improve refrac design based on findings.

Project ParticipantsUniversity of Texas at Austin

ContactMukul M. Sharma

Professor of Petroleum & Geosystems Engineering

Noble EnergyContact

Michael ZollCompletions Manager

Denver, CO

BJ ServicesContact

Satya GuptaSenior Research Leader

Tomball Technology Center

Pinnacle TechnologiesContact

Steve WolhartRegion Manager

Anadarko Petroleum Corp.Contact

Jon David CaronProject Engineering Advisor

1 Research Management Plan2 Technology Status Assessment3 Data compilation for the Codell formation 4 Data compilation for the Barnett shale5 Stress reorientation model implementation and runs for Codell re-fracs6 Stress reorientation model implementation and runs for Barnett shale re-fracs7 Evaluation of fractured well performance in the Codell, Barnett and horizontal

wells8 Candidate well selection based on poro-elastic model and field data analysis9 Design of re-frac treatments in the Codell, and Barnett based on simulations, new

fluids and proppants10 Design of re-frac treatments in horizontal wells based on simulations, new fluids

and proppants11 Implementation of re-frac treatments in the Codell, and Barnett (new designs).12 Post frac evaluation of re-frac treatments in the Codell, Barnett and horizontal

wells13 Workshop in Houston to discuss results 14 Final report with all the findings from the study

Milestones

Project Timing1 3

Task Year 2 Year 3

4

5

6

7

8

9, 10

Value of the Research –Project Impact

Beating the decline curve in unconventional gas reservoirs requires continuous drilling and fracturingIn a low gas price environment re-fractreatments offer a low cost alternative to drilling new wells.Performance of re-fracs is highly variable and must be made more reliable and predictable.This project aims to help accomplish that.

Status of Current Technology

Refrac candidate well selection is based on:Statistical databases

Heuristic rules of thumbNeural networks

No systematic way of deciding on the timing of the refracsCurrent refrac treatment designs are done very much like the original fracs.Typically, no account is taken of stress reorientation or previously placed proppant.

Project DeliverablesMonthly status reports. A final report on the results of the Defined Effort. Guidelines for selecting candidate wells for refracturing.Guidelines for selecting the appropriate timing of refracturing given a set of reservoir properties.New designs for better placement of proppants during refracturing operations.Guidelines for fracture placement and spacing in horizontal wells.Guidelines for avoiding fracture interference in wells with multiple fractures.New proppant placement strategies for horizontal well fractures.Detailed analysis and results for at least four refracture treatments in tight gas and gas shale wells.

Project DeliverablesA report on statistical analysis of the refracture database in the Codell formation (2500 refracture treatments).Quantitative guidelines for when to use energized fluids when refracing depleted formations.Guidelines for when to use light weight proppants in refracture treatments.A web site with information about the project and updates as appropriate.A minimum of two presentations in local professional organization meetings; one each in Permian and San Juan Basin areas.At least one presentation at a RPSEA-directed event.An article discussing this project to at least one producer-oriented trade journal.UT will provide technical results containing details and data to be utilized for determination of program impact as requested by RPSEA.

Proposed TasksTask 4. Stress Reorientation around Fractured Wells: Implications for Re-fracturing

Subtask 4.1 Data compilation in the Codell formation and the Barnett shaleSubtask 4.2 Stress re-orientation around fractured wells in shales and tight gas sandsSubtask 4.3 Models for stress reorientation in naturally fractured formations

Task 5. Selecting Timing and Candidate Wells for Re-fracturingTask 6. Re-fracture Designs for Deviated and Horizontal WellsTask 7. Proppant Placement in Re-fracturing Treatments (Vertical and Horizontal Wells)Task 8. Use of Novel Proppant Placement Strategies in Re-fracturing Operations Task 9. Field Design of Re-Fracture Treatments in the Wattenberg FieldTask 10: Design, Implementation and Evaluation of Field FractureDesigns

Task 4: Stress Reorientation

Elastic, homogeneous and isotropic reservoirBiot’s poroelasticity theoryConstant pressure in vertical well and initial fracturePresence of bounding layers with different mechanical properties

Pay Zone

Bounding Layer

Initial Fracture

Task 4: Stress Reorientation around a producing well

Analytical solution compares well with numerical solution

Ref: Zhai, Sharma, 2004

Stress Reorientation Around Producers and InjectorsProducer Injector

Stress Reversal occurs

No Stress Reversal

Direction of Maximum Stress

Angle of Stress Reorientation

Stress Reversal Region

Producer

Isotropic point

Fracture half-length

Direction of Maximum Stress

Angle of Stress Reorientation

Stress reversal region impacts directionof refracture measured in the field

Dimensionless Parameters (Berchenko et al., 1997; Siebrits et al., 1998; Rousell and Sharma, 2009)

Dimensionless Time

Dimensionless Stress Deviator

Dimensionless Fracture Height RatioDimensionless Shear Modulus Ratio

( )( )( )

2 22

4 441 1 21

1xf xf

xf

ct t ktL S L

LM E

κτα ν ν

μν

= = =⎛ ⎞+ −

+⎜ ⎟−⎝ ⎠

Π=S0

σ*

=S0

ηp*

=σhmax−σhmin

α 1−2ν( )1−ν

pRi−pwf

γ =HLxf

β =Gb

Gr

January 20, 2009 DOE Project Kick-off Meeting 18

Parameters Affecting the Stress Reversal Region

The areal extent and timing of the stress reversal depend on:

Fluid propertiesReservoir characteristicsStress contrastDrawdownThickness of the reservoirMechanical properties of the bounding layers

Task 5. Selecting Timing and Candidate Wells for Re-fracturing

The main results were recently published. “Quantifying Transient Effects in Altered-Stress Refracturing of Vertical Wells”, SPE 119522, Presented at the SPE Hydraulic Fracturing Meeting, Woodlands, 2009, Nicolas P. Roussel, Mukul M. Sharma.Work continues to include the effects of stresses induced by fracture creationComparison with field data.

Task 5. Selecting Timing and Candidate Wells for Re-fracturing

0

0.05

0.1

0.15

0.2

0.25

0.001 0.01 0.1 1 10 100 1000

Time (months)

L xf'

/ Lxf

ShaleTight GasSandstone

τmax = 1.3 days

λmax

Optimum time for refracturing

Maximum areal extent of stress

reversal

τmax = 4.13 years

τmax = 1.15 months

Main FindingsAn approaching fracture will go:

Away from a production wellToward an injection well

Stress reorientation depends on:DrawdownStress anisotropyModuli

Stress reversal does occur in fractured producers. We can now compute its,

Spatial extentTiming

January 20, 2009 DOE Project Kick-off Meeting 22

Field Data for Validation

3 wells where refracs worked and 3 wells where refracs did not workA complete dataset would include:

Wellbore schematicBase map showing location of wellsDetails of frac and refrac jobsLogs (dipole sonic)MicroseismicGas flow rate before / after refrac

t = 0

Task 6. Re-fracture Designs for Deviated and Horizontal Wells

t = 0

Stress Reorientation for a Production, Injection Well Pair

t = 0

Stress Reorientation for 1 Production, 2 Injection Wells

t = 0

Stress Reorientation for 2 Production, 1 Injection Well

Task 7, 8. Use of Novel Proppant Placement Strategies in Re-fracturing Operations

Status: Work is underway and we have some initial results.

Wattenberg field, D-J basinCodell formation

Thin sandstone layerLow permeability, requires stimulation

Refractured since 1998Observations indicate that refracture performance is dictated by fracture-fluid viscosity profile (Ref: Miller, J. et al., 2004, SPE 90194)

Fracture reorientation has been reported (Ref: Wolhart, S. et al., 2007, SPE 110034)

Task 9, 10. Design of Re-Fracture Treatments in the Wattenberg Field

Source: USGS

ObjectivesUse principal component analysis to determine the increase in production rate after a refracture treatment.Use stress reorientation models to study the role played by stress reorientation vs other factors such as GOR and depletion.Use these findings to recommend timing for refracsCreate a statistical, predictive model for

Production enhancement Candidate well selection

Groups DescriptionWell information Year

Orig. frac treatment Volume of gel and proppant during the first fracture

Pre-refrac data Production information and number of perforations

Refrac design Gel loading, pad size, surfactant, etc

Refrac treatment Fluid injection, perforations

Rheology Viscosity measurements, gel usage

Water quality Water source, compositionJob comments Problems during the job

Refrac data Production increment

Data SetRefracture well data, approx. 4000 wells Anadarko, Noble Energy (1999 - 2008)

Issues with Data Analysis

Too many parameters (58)Incomplete data setsWide range of refrac production increment

-19.6 ~ 4756 BOE/moNon-numeric data

Data Set ReductionElimination

Elimination criteria

# missing entry > 500

Wells with any missing parameter values

Reduced dataset

Parameters: 58 43

Entries: 2154 1279

Refrac Treatment

Param MGAL

AVG. RATE

New PERF

Total PERF

Leakoff Coef.

PerfFriction

Avg.PSI

131.10 13.60 19 28 0.0010 54 6550

131.21 13.50 30 43 0.0021 100 4400

132.59 13.90 0 60 0.0027 12 5300

132.00 13.00 28 34 270 4900

131.88 14.00 30 50 0.0013 0 7600

131.45 14.50 26 33 0.0013 40 4600

130.76 12.80 18 33 0.0013 210 6100

135.00 14.00 37 0.0013 10 4850

Value

Missing

Entries

127.39 13.00 40 49 0.0013 667 6750

55 58 108 206 1560 1548 62

Missing Values

-2000 0 2000 4000 6000 80000

100

200

300

400

500

600

700

800

Production Increment (BOE/mo)

Freq

uenc

y

Mean : 1282.6Median : 1152.3

Std: 814.7

Mean : 1302.9Median : 1161

Std: 754.5

Data SetReduction

-1000 0 1000 2000 3000 4000 50000

50

100

150

200

250

300

350

400

Production Increment (BOE/mo)Fr

eque

ncy

Data Set ReductionChange of Statistical Properties

0 1 2 3 4-1000

0

1000

2000

3000

4000

5000

Codell Phi*H

Pro

duct

ion

Incr

emen

t (B

OE

/mo)

0 0.2 0.4 0.6 0.8 1-1000

0

1000

2000

3000

4000

5000

Pre-Refrac Cum Rec. Factor

Pro

duct

ion

Incr

emen

t (B

OE

/mo)

Corr. value : 0.21Corr. value: 0.25

Statistical AnalysisCorrelation (2)

Observe the correlations between production increment and parameters

Statistical AnalysisCorrelation (1)

0 1 2 3 40

0.2

0.4

0.6

0.8

1

Codell Phi*H

Pre

-Ref

rac

Cum

Rec

. Fac

tor

0 50 100 150 2000

100

200

300

400

500

600

700

Calcium ppm

Tota

l Har

dnes

s pp

m

Corr value : 0.98Corr. value : 0.13

Observe correlations between parameters

Statistical AnalysisLinear Regression

R2 = 0.47Median error = 42.5%Mean error = 95.9%Less number of dimensions can help improve regression 0 500 1000 1500 2000 2500 3000 3500 4000

0

500

1000

1500

2000

2500

3000

3500

4000

Actual production increment

Pre

dict

ed p

rodu

ctio

n in

crem

ent

goodbad

Parameter ReductionCorrelation among parameters suggest a presence of highly correlated parametersEliminate highly correlated parameters: 43 25

Water quality (11)

Total hardness

Pre-refrac (4)

Pre-refrac Cum Rec. Factor

Orig. Fractreatment (5)

•Orig. Vol (MGAL)•Orig. Zone

• More entries recovered: 1279 1316

Statistical AnalysisLinear Regression w/ Reduced Parameters

R2 = 0.31Median error = 42.1%Mean error = 100.9%Requires a more sophisticated method for better fits

0 500 1000 1500 2000 2500 3000 3500 40000

500

1000

1500

2000

2500

3000

3500

4000

Actual production increment

Pre

dict

ed p

rodu

ctio

n in

crem

ent

goodbad

Statistical AnalysisPrinciple Component Analysis

Original dataset [m x n] mapped into new orthogonal vectorsVariance of dataset can be captured with less dimensionsReduction of dimensions provides a better regression

Choose eigenvectors [n x k]

Covariance matrix [n x n]

Eigenvectors [n x n]

Dataset transformation [m x k]

Future Work

Fill-in missing data instead of row elimination to increase the number of wells in data set.Work with Noble Energy on adding additional data (e.g. regional stress data)Data mining techniques

K-means clusteringNeural nets

Technical Issues/Problems Encountered

Minor issues with getting contract in place.Data access issues have been resolved.

Summary of Progress to Date

Stress reorientation due to poroelastic effects has been calculated for vertical, fractured and horizontal wells.Key parameters and conditions that control this stress reorientation have been identified.The optimum timing of refrac treatments has been computed for the first time. A data set of refrac treatments from the Wattenburg field has been reviewed and is being analyzed for statistical trends.Review of refrac treatment designs in progress.

Thank youQuestions?

I would like to Acknowledge:

RPSEA for their support.

Our partner companies (Anadarko, BJ Services, Noble Energy, Pinnacle) for collaboration and access to data.

Members of the Fracturing and Sand Control JIP at the University of Texas at Austin (Anadarko, BJ Services, BP, ConocoPhillips, Halliburton, Schlumberger, Shell, Total) for providing the cost sharing for this project.