SPE-AAPG ATW on Naturally Fractured Reservoirs, October 2010 … · 2013-02-28 · Background SPE-AAPG ATW on Naturally Fractured Reservoirs MURPHY CREEK 33025009160100 LARSEN 13-1H

Integration of Microseismic, Production Data and Numerical Simulation to Evaluate Uncertainties in

Unconventional Reservoirs.What is the Impact on Estimated Ultimate Recovery?

Randy Billingsley, Tracker Resources Development LLCSherilyn Williams-Stroud, MicroSeismic Inc

Chet Ozgen, Nitec LLC

SPE-AAPG ATW on Naturally Fractured Reservoirs, October 2010

OutlineBackgroundObjectivesAvailable DataInterpretations & AssumptionsUncertain Parameters of the AnalysisDynamic Calibration Process and ResultsPredictions and Sensitivity Analyses

SPE-AAPG ATW on Naturally Fractured Reservoirs

Background


Background


MT

WYSD

ND

MBSKAB

Project Area

Williston BasinWilliston Basin

Background


DunnDunn

- 8750

- 8500

8250

-825

0

- 8000

- 800

0

- 775

0

- 7500

2

3 30

4

2

4

2

3

0

3

0

0

1

0

2

2

5

64

6

5

7

4

8

6

4

5

4 4

5

4

12

4

16

16

1819

17

11

12

12

12

11

10

7

18

5

5

4

16

1515

15

16

16

16

4

55

67

785

12

11

14

15

16

13

13

16

1614

5

19

14

16

11

0

6

11

8

6

15

10

6

19

13

9

17

3

7

0

21

20

8

16

9

9

5

14

7

14

6

14

14

5

17

12

4

17

12 14

9

13

13

5

21

13

17

10

0

6

8

12

22

16

14

14

12

5

9

12

14

14

6

13

12

14

15

14

1315

16

15

22

12

12

10

9

6

107

8

157

6

13

12

13

11

13

1213

11

7

59

3

18

18

20

16

22

16

17

18

19

17

18

18

18

18

18

1818

4

19 1816

15

25

5

6

4

6

7

10

69

31

2322

11

10

6

6

7

56

6

4

6

3

11

4

10

3

10 17

10

5

13

2

6

18

17

14

10

FEET

0 25,285

PETRA 9/14/2010 7:58:24 AM

Project WellProject Well

Little Knife Anticline

Background


MURPHY CREEK

33025009160100LARSEN

13-1HT144N R95W S13

WILDCAT

33025007150001FRITZ30-1H

T144N R94E S30

0 200GR [GAPI]

6 20HCAL [IN]

0.2 2000AT90 [OHMM]

0 20PEFZ [B/E]

0.3 -0.1DPHI_DOL_TF_278

0.3 -0.1DPHI_DOL

0.3 -0.1DPHZ [CFCF]

1 0SW_TFX

1 0SW [PERCENT]

0 200GR [GAPI]

6 20HCAL [IN]

0 150GAMMA_CURVE [API]

0.2 2000AHT90 [OHMM]

0.2 2000AHT90_1 [OHMM]

0.2 2000AHT90 [OHMM]

MD-B [NDOG]

MID_BAKKEN [RLB]

LOWER_BAKKEN_SHALE [RLB]

D-TF [NDOG]THREE_FORKS [AJF]

10,6

0 0

U Bakken Shale

M Bakken Dolomites

L Bakken Shale

Background


FMI Rose from TRD Thomas 4-1H (~15 mi NW)

High Angle Type I Regional Extension Fractures (small aperture)

Lower Angle Shear Fractures related to Basement Faulting

2 Directions of Surface Lineaments inferred to be related to Basement

Faulting

DEM of Area

Surface and Subsurface Data Suggests a Diverse Natural Fracture Population Across

the Location.

Background


Gas shows are inferred to be related to natural fracture swarms

Background


Sliding sleeves colored by stage

Swell Packers isolate treatment

intervals

Frac treatment: 6/4/2008Early multistage,

Generation II, completion

Eight Ball/Sleeve Stages:Job Type Slickwater

BORAjel-5Sliding Sleeves: 11,400’ – 19,861’Max Slurry Rate: 56.1 bpmAvg. Slurry Rate: 37.9 bpmMax Pressure: 6,382 psiAvg. Pressure: 5,919 psi20/40 Ottawa: 351,000 lbs.20/40 Super L/C: 94,800 lbsFluid: 17,688 bbls.

Background


Stage 2

Stage 6Stage 5Stage 4Stage 3

Stage 7Stage 8

Stage 1

Objectives


ObjectivesTo understand the impact of “seismic event

window” on dynamic calibration and EUR predictions

To understand the impact of “assumptions in DFN generation” on dynamic calibration and EUR predictions

To understand the impact of additional wells on NPV and EUR


ObjectivesTo understand the impact of “seismic event

window” on dynamic calibration and EUR predictions

To understand the impact of “assumptions in DFN generation” on dynamic calibration and EUR predictions

To understand impact of additional wells on NPV and EUR


This presentation focuses on the second objective

Available Data


Available DataDrilling - vertical and horizontal wells

Mud log, gas chromatographyCores from nearby wells

Porosity, permeability, capillary pressureElectric logs from the vertical well

Stratigraphy, NTG, porosity, ~water saturationHydraulic fracturing operation

Injection pressure, injection volume, microseismicProduction operation

Oil, gas and water volumes, flowing THP


Interpretations and Assumptions




Microseismic Events Monitored during the Completion are used

as seed loci for Stochastic DFN

Generation

Aperture and Connectivity are linked to Event Amplitude and

Distribution



Wellbore Pseudo Fractures –White

FMI/Lineament Fractures –Purple/Blue

Hydraulic Fracture Network -Green



Only simulated fractures actually

coincident with the wellbore or

connected to the wellbore through adjacent fractures

are shown.



Discrete Fracture Network is upscaled to

delineate the Stimulated Rock Volume (SRV)

distribution, connectivity and

associated permeability.

Interpretations and AssumptionsIn this presentation we compare 2 DFN Models

Model #1 has one fracture set, with strike parallel to the main axis and limited scatter in the strike orientation.

Model #2 has two intersecting fracture sets with one parallel to the main axis and other having strike of 80 degrees with significant amount of scatter.

Both models were upscaled for porosity, permeability and sigma array associated with the hydraulic fracture




Larger Connected SRV estimated for Model #2

Interpretations and AssumptionsEffective porosity of bounding shales = 1%Dolomite matrix porosity = 6.5%Dolomite matrix permeability = 0.010 mD

Single water-oil matrix drainage capillary pressure curve that corresponds to 6.5% porosity

Zero capillary pressure in the fracturesStraight line water-oil matrix/fracture relative

permeability curves




Pc Drainage (oil-water)

0

100

200

300

400

500

600

0 0.2 0.4 0.6 0.8 1

Sw (fraction)

Pc

(psi

)

Uncertain Parameters of the Analysis


Uncertain Parameters of the Analysis– Initial reservoir pressure

• 72-hour buildup shows minimum of 5200 psia– Initial matrix water saturation

• set through depth of pseudo WOC– Water-oil relative permeability scaling

• Krw left constant and Kro is scaled


Uncertain Parameters of the Analysis– Vertical communication among the layers

• Intercalated shale streaks– Permeability of the natural fractures

• Assume uniform value– Porosity of the natural fractures

• Assume uniform value– Sigma for the natural fractures/matrix

• Assume uniform value


Uncertain Parameters of the Analysis– Amplitude of HF permeability distribution

• Use multiplier to upscaled DFN values– Amplitude of HF porosity distribution

• Use multiplier to upscaled DFN values– Amplitude of HF based sigma distribution

• Use multiplier to upscaled DFN values– Connection % of HF to the wellbore

• Use well PI (or WI) multiplier


Dynamic Calibration Process and Results



Unstable early THP data

Installation of artificial lift

Reliable THP


Flow back of HF fluids

Reliable water production

Dynamic Calibration Process and ResultsDFN Model #1

In-house Assisted History Matching Software11 history matching parametersExperimental design for coverage of rangeANN and Genetic Algorithm for global searchResponse Surface and GA for optimizationRuns ~15 minutes - maximum 5-day time stepsApproximately 170 simulation runs



Excellent match of THP data

Excellent match of water data


The difference in water production is 8000 barrels.

This indicates that 44% of the fracturing fluid was recovered



Dynamic Calibration Process and ResultsDFN Model #2

In-house Assisted History Matching Software11 history matching parametersExperimental design for coverage of rangeANN and Genetic Algorithm for global searchResponse Surface and GA for optimizationRuns ~15 minutes - maximum 5-day time stepsApproximately 240 simulation runs



Average match of THP data

Excellent match of water data

Dynamic Calibration Process and ResultsPinit WOCKrocw KzfMultWPImult

NFKadd HFKmultNFPadd HFPmultNFSadd HFSmult


SPE-AAPG ATW on Naturally Fractured ReservoirsTop 20 solutions for DFN Model #1

SPE-AAPG ATW on Naturally Fractured ReservoirsTop 20 solutions for DFN Model #2


Dynamic Calibration Process and ResultsUncertain parameters for best solutions

Best solutions are especially different in NF Permeability values


Dynamic Calibration Process and ResultsFracture delta P at 6/2010 for both DFN Models

Filtered at minimum fracture delta P of -500 psi


Dynamic Calibration Process and ResultsMatrix delta P at 6/2010 for both DFN Models

Filtered at minimum fracture delta P of -500 psi


Dynamic Calibration Process and ResultsMatrix delta P at 6/2010 for both DFN Models

Filtered at minimum matrix delta P of -500 psi

Predictions and Sensitivity Analyses


Predictions and Sensitivity AnalysesResponse surface + Monte Carlo: 100 solutionsClassified 100 solutions into 5 clustersFor each DFN model:

Repeated five history match runsPerformed five predictions into the futureEach prediction has different probability

Kept the flowing BHP at 6/2010 values


SPE-AAPG ATW on Naturally Fractured Reservoirs5 clustered solutions for DFN Model #2


For DFN Model #1oil recovery range

at 50 years is340 to 360 MSTB

Predictions and Sensitivity AnalysesPerformance of DFN Models #1 and #2


16% Difference in 50-year Oil Recovery Estimates


Significant Difference in Predicted Water Cut Profile

Predictions and Sensitivity AnalysesImportance of measuring water production

The End


Integration of Microseismic, Production Data and Numerical Simulation to Evaluate Uncertainties in

Unconventional Reservoirs.What is the Impact on Estimated Ultimate Recovery?

Randy Billingsley, Tracker Resources Development LLCSherilyn Williams-Stroud, MicroSeismic Inc

Chet Ozgen, Nitec LLC

Documents

SPE-AAPG ATW on Naturally Fractured Reservoirs, October 2010 … · 2013-02-28 · Background SPE-AAPG ATW on Naturally Fractured Reservoirs MURPHY CREEK 33025009160100 LARSEN 13-1H