Analysis of Typical Data on Faults and Fractures and Its Application to the Assessment of Potential Migration of Injected CO2 in the Deep Subsurface,

Including Leakage through the Primary Seal(s)

Develop geologically representative DFNs and carry them into flow simulation for iterative history matching

WVUTom WilsonDeng Gao

NETLMark McKoyDuane Smith

Long Term Objective

Develop software and techniques for analyzing borehole logs and seismic data:

for faults and fracture networks in reservoir rock and overlying strata, with emphasis on assessing potential leakage routes through

seals.

Establish procedures to produce DFNs for flow simulation.

Support risk assessment efforts:Migration within reservoirleakage through primary seals.

Provide one or more useful examples that the CO2sequestration industry could follow.

Technical ApproachDevelopment of data processing software and techniques to define field scale DFNs:

1) static-phase waveform (texture) model regression &,2) local Radon (or τ-p) transform for directional analysis of seismic attributes.

n

jyixf

yxfyxr i j∑∑ ++

−=

),(

),(),(

[ ] [ ]( , ) ( , ) ( )pR r x y r x y y px dxdyτ δ τ∞ ∞

−∞ −∞= − +∫ ∫

Technical Approach

For 1 or more selected sites: Use of selected seismic attributes for identification & mapping of faults, fracture zones and general fracture network characteristics in the reservoir, primary seal and overlying strata.

Use of borehole logs for interpretation & assessment of fracture/fault networks in the reservoir and sealing strata.

Use of field observations and aerial imagery to supplement the interpretation & assessment of fracture/fault networks in the deep subsurface.

For 1 or more selected sites: Generate representative DFNs for reservoir and up through

the primary seal.

Use DFNs for flow simulations within reservoir and up through the primary seal.

Assess CO2 plume spread within reservoir plus leakage ratesthrough primary seal.

Technical Approach

Seismic from San Juan Basin CO2 Pilot

Fault and Fracture Zone Interpretations are Difficult in Conventional Amplitude Displays

Defining the reservoir scale fracture systems

1626:Naci

1989:Ojo2018:C12056:Kirt

2690:C2

2826:Fr

2950:UFZ-T2987:UFC-B3056:MFC-T3072:MFC-B3111:LFC-T

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925.0580.0

925.0600.0

925.0620.0

925.0640.0

925.0660.0

925.0680.0

925.0700.0

925.0720.0

925.0740.0

925.0760.0

Line:Trace:

EPNG COM A EC A 300 COM A 300EPNG COM A ING 1 COM A ING1SP-A SP ASP-B SPB SP-C SPC

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4.1523.9033.6543.4053.1552.9062.6572.4082.1591.9101.6611.4121.1630.9130.6640.4150.166-0.083-0.332-0.581-0.830-1.080-1.329-1.578-1.827-2.076-2.325-2.574-2.823-3.072-3.322-3.571-3.820-4.152

The Kirtland Shale primary seal (caprock)

Fruitland Formation reservoir zone

Seismic Attribute: Absolute value of finite differencePost-stack processing helps enhance seismic discontinuities

The Kirtland Shale primary seal (caprock)

Fruitland Formation reservoir zone

Structure-Oriented Attribute Analysis

1. Structure-oriented seismic attribute analysis: a) characterization of fluid migration pathway, b) caprock sealing capacity.

2. Results promote: a) optimally placing injection and monitor wells,b) using seismic constraints for DFN modeling and flow simulation.

Structure-oriented attribute analysisConstruction of texture model

Mi (i = 1…n)

Retrieval of dataDi (x,y,z) (i = 1…n)

Linear least-squares regressionMi ~ Di (x,y,z)

Output the value of ABSOLUTE gradient g (x,y,z)

Next location (x,y,z)

Mi

Di

∑

∑

=

=

−

−−= n

ii

n

iii

MM

DDMMg

1

2

1

)(

))((

Original Model regression Phase

Reservoir rock with high porosity

Primary caprock with low fracture intensity

Original Structure attribute Phase

Primary caprock with low fracture intensity

Reservoir rock with high porosity

0.5 km0.0 1.0

A

B

Original amplitude

Structure attribute

0.5 km0.0 1.0

A

B

Original

Structure attribute

0.5 km0.0 1.0

A

B

Original

Structure attribute

1 mile

Original

Structure attribute

????

Formation with highstorage capacity

Caprock with potential leaky fractures

Derived from amplitude Derived from structure attribute

N N

1 mile

Improvement in Edge Enhancement

CO2 injection well

Tracer test

????

Migration pathway

Sealingfaults

1.0 km

Complex fracture patterns will cause complex flow and irregular plume geometry of injected CO2

Attribute analysis enhances our ability to detect fracture systems in caprock and reservoir intervals

Interpretation Based on Structure Attribute

Attributes provide plan-view input to DFNs

San Juan Basin Pilot

Attribute Analysis Used to Identify Vertical Continuity in Potential Flow Paths

Kirtland Shale Caprock

Fruitland Coals

480 ms 430 ms 400 ms

NacimientoUpper KirtlandMiddle KirtlandA) B) C)

Orientations of possible fracture systems in the caprock

Use of fracture detection logsN23E σH

Entire Borehole Upper Fruitland Reservoir Zone

Identify drilling induced breakouts and define

present day in-situ stress

Kirtland Shale –Primary Seal

Identify natural fractures in-situ

Note consistency with dominant attribute mapped trend

Use of “sonic scanner” logs & regional/local stress data

Entire Borehole Fruitland Coal Section

Measurements obtained using Schlumberger’s Sonic Scanner

1 23

45

6

7

8 YX

Field-mapped fracturesImage-mapped fractures:

site 1Image-mapped fractures:

site 2

Use surface fracture system information to fill gaps in input data for DFNs

Use of data from ground surface (field observations and areal images (scanner images, aerial photos, fracture maps)

INPUTS: Well logs, outcrop data and seismography determine fracture network statistics.

Conceptual model fills the blanks!

OUTPUTS: Fracture Sets characterized by averages and variances in length, orientations, effective apertures, and locations

Fracture Detection Log

Fracture/Fault Data FRACGEN

2. Axis of Horst1. Seismically Resolved Fold Axes 3. Seismically Resolved Faults

Seismically-resolved features may be input directly into a DFN. Statistical parameters are input for features not directly observed.

Faults & Fractures Zones Define Major Structural Components of Reservoir

Identify fracture sets and their statistical parameters

• FILE IDENTIFICATION (<= 80 CHARACTERS) FRACGEN 6th EDITION• Conceptual Model of Major Flow Paths in Southern Half of Storage Field• X & Y DIMENSIONS OF FLOW REGION• 32000.0 52000.0• EFFECTIVE DEPTH OF MID-LAYER; EFFECTIVE THICKNESS OF FRACTURED LAYER• 6139.0 170.0• NUMBER OF SETS (including MODEL 0 sample trace set)• 8• MODEL -------------------------------------------------------------- SET 1• 1• SET IDENTIFICATION (<= 80 CHARACTERS)• Seismically-Resolved Faults• MEAN AND SDEV OF FRACTURE ORIENTATION (360.0=UNI)• 0.0 0.0• MIN/MEAN AND MAX/DEV FRACTURE LENGTH, DIST. (0=UNI,1=EXP,2=LOG,3=INT)• 0.0 0.0 0• MEAN AND SDEV OF FRACTURE APERTURE• 0.0 0.0• DENSITY OF FRACTURE CENTER POINTS• 0.0• CORRELATIONS (len=F(order), ori=F(len), wid=F(len))• 0.0 0.0 0.0• MAXIMUM PERCENT FRACTURE SHIFT: MODE I, II, III• 0.0 0.0 0.0• SYNTHETIC ANNEALING CONTROLS (pstart,nswaps,swapl,ifreq)• 100.0 0 0 0• RELATIVE FREQUENCIES OF T-TERMINATIONS (T2,T1)• 0.0 0.0• FRACTURE INTERSECTION FREQUENCIES (%): ZERO TO 10+ INTERSECTIONS• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0• PERCENT FRACS PENETRATING OVERLYING LAYER; CORRELATION TO FRAC LENGTH• 0.0 0.0• NUMBER OF USER-SUPPLIED FRACTURES• 97• FRACTURES: X-LEFT, Y-LEFT, X-RIGHT, Y-RIGHT, WIDTH, SHIFT(%), PERCENT• 2440.00 5200.00 4520.00 9000.00 .350E-02 0.0 0.0• 4520.00 9000.00 6800.00 13800.00 .350E-02 0.0 0.0• 6800.00 13800.00 8960.00 20840.00 .350E-02 0.0 0.0• 8960.00 20840.00 11000.00 27480.00 .350E-02 0.0 0.0• 11000.00 27480.00 11480.00 35280.00 .350E-02 0.0 0.0• 11480.00 35280.00 13560.00 41680.00 .350E-02 0.0 0.0

• MODEL -------------------------------------------------------------- SET 2• 2• SET IDENTIFICATION (<= 80 CHARACTERS)• Sub-Seismic Faults Associated w/ Horst• MEAN AND SDEV OF FRACTURE ORIENTATION• 360.0 6.0• MEAN AND SDEV OF CLUSTER ORIENTATION• 0.0 0.0• MIN/MEAN AND MAX/DEV FRACTURE LENGTH, DIST. (0=UNI,1=EXP,2=LOG,3=INT)• 4000.0 10000.0 0• MIN/MEAN AND MAX/DEV CLUSTER LENGTH, DIST. (0=UNI,1=EXP,2=LOG)• 10000.0 22000.0 0• MEAN AND SDEV OF FRACTURE APERTURE• 0.001390 0.0• MEAN INTRA-CLUSTER FRACTURE SPACING• 2400.0• MEAN AND SDEV OF INTRA-CLUSTER FRACTURE DENSITY• 0.00000010 0.0• DENSITY OF CLUSTER CENTER POINTS• 0.0000000020• .• .• .• RELATIVE FREQUENCIES OF T-TERMINATIONS (T2,T1)• 40.0 40.0• FRACTURE INTERSECTION FREQUENCIES (%): ZERO TO 10+ INTERSECTIONS• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0• PERCENT FRACS PENETRATING OVERLYING LAYER; CORRELATION TO FRAC LENGTH• 0.0 0.0• NUMBER OF USER-SUPPLIED CLUSTERS• 4• CLUSTERS: X-LEFT, Y-LEFT, X-RIGHT, Y-RIGHT, WIDTH, SHIFT(%), PERCENT• 9360.00 -4600.00 9800.00 11680.00 2400.00 0.0 0.0• 8800.00 7760.00 16960.00 24320.00 2400.00 0.0 0.0• 14600.00 17080.00 19160.00 46440.00 2400.00 0.0 0.0• 16800.00 40480.00 27000.00 56520.00 2400.00 0.0 0.0

• MODEL -------------------------------------------------------------- SET 3• 1• SET IDENTIFICATION (<= 80 CHARACTERS)• Small Sub-Seismic Faults• MEAN AND SDEV OF FRACTURE ORIENTATION (360.0=UNI)• 20.0 8.0• MIN/MEAN AND MAX/DEV FRACTURE LENGTH, DIST. (0=UNI,1=EXP,2=LOG,3=INT)• 2000.0 4000.0 0• MEAN AND SDEV OF FRACTURE APERTURE• 0.000800 0.0• DENSITY OF FRACTURE CENTER POINTS• 0.00000020• CORRELATIONS (len=F(order), ori=F(len), wid=F(len))• 1.0 0.6 0.0• MAXIMUM PERCENT FRACTURE SHIFT: MODE I, II, III• 49.0 40.0 0.0• SYNTHETIC ANNEALING CONTROLS (pstart,nswaps,swapl,ifreq)• 5.0 10 15 2• RELATIVE FREQUENCIES OF T-TERMINATIONS (T2,T1)• 65.0 30.0• FRACTURE INTERSECTION FREQUENCIES (%): ZERO TO 10+ INTERSECTIONS• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0• PERCENT FRACS PENETRATING OVERLYING LAYER; CORRELATION TO FRAC LENGTH• 0.0 0.0• NUMBER OF USER-SUPPLIED FRACTURES• 0• FRACTURES: X-LEFT, Y-LEFT, X-RIGHT, Y-RIGHT, WIDTH, SHIFT(%), PERCENT•

• MODEL -------------------------------------------------------------- SET 4• 2• SET IDENTIFICATION (<= 80 CHARACTERS)• Right-Lateral Sub-Seismic Oblique-Slip Tear Faults• MEAN AND SDEV OF FRACTURE ORIENTATION• 83.0 6.0• MEAN AND SDEV OF CLUSTER ORIENTATION• 0.0 0.0• MIN/MEAN AND MAX/DEV FRACTURE LENGTH, DIST.

(0=UNI,1=EXP,2=LOG,3=INT)• 8000.0 19000.0 0• MIN/MEAN AND MAX/DEV CLUSTER LENGTH, DIST. (0=UNI,1=EXP,2=LOG)• 11000.0 26000.0 0• MEAN AND SDEV OF FRACTURE APERTURE• 0.000600 0.0• MEAN INTRA-CLUSTER FRACTURE SPACING• 1000.0• MEAN AND SDEV OF INTRA-CLUSTER FRACTURE DENSITY• 0.00000012 0.0• DENSITY OF CLUSTER CENTER POINTS• 0.0000000010• .• .• .• RELATIVE FREQUENCIES OF T-TERMINATIONS (T2,T1)• 20.0 70.0• FRACTURE INTERSECTION FREQUENCIES (%): ZERO TO 10+ INTERSECTIONS• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0• PERCENT FRACS PENETRATING OVERLYING LAYER; CORRELATION TO FRAC

LENGTH• 0.0 0.0• NUMBER OF USER-SUPPLIED CLUSTERS• 4• CLUSTERS: X-LEFT, Y-LEFT, X-RIGHT, Y-RIGHT, WIDTH, SHIFT(%), PERCENT• 14360.00 -4600.00 14800.00 11680.00 1000.00 0.0 0.0• 13800.00 7760.00 21960.00 24320.00 1000.00 0.0 0.0• 19600.00 17080.00 24160.00 46440.00 1000.00 0.0 0.0• 21800.00 40480.00 32000.00 56520.00 1000.00 0.0 0.0

• .• .• .• MODEL -------------------------------------------------------------- SET 7• 1• SET IDENTIFICATION (<= 80 CHARACTERS)• Regional Extension (Master) Fractures• MEAN AND SDEV OF FRACTURE ORIENTATION (360.0=UNI)• 83.0 8.4• MIN/MEAN AND MAX/DEV FRACTURE LENGTH, DIST. (0=UNI,1=EXP,2=LOG,3=INT)• 4881.6 2140.2 2• MEAN AND SDEV OF FRACTURE APERTURE• 0.000190 0.0• DENSITY OF FRACTURE CENTER POINTS• 0.000000663• CORRELATIONS (len=F(order), ori=F(len), wid=F(len))• 1.0 0.8 0.0• MAXIMUM PERCENT FRACTURE SHIFT: MODE I, II, III• 49.0 40.0 0.0• SYNTHETIC ANNEALING CONTROLS (pstart,nswaps,swapl,ifreq)• 100.0 10 15 2• RELATIVE FREQUENCIES OF T-TERMINATIONS (T2,T1) 20.0 55.0• 50.0 40.0• FRACTURE INTERSECTION FREQUENCIES (%): ZERO TO 10+ INTERSECTIONS• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0• PERCENT FRACS PENETRATING OVERLYING LAYER; CORRELATION TO FRAC

LENGTH• 0.0 0.0• NUMBER OF USER-SUPPLIED FRACTURES• 0• FRACTURES: X-LEFT, Y-LEFT, X-RIGHT, Y-RIGHT, WIDTH, SHIFT(%), PERCENT•

Multilayer DFNs developed in FRACGEN go directly into NFFLOW for flow simulation and iterative history

matching efforts

Oriskany Well Site

4 layers

1,700 ft x 1,500 ft x 200 ft

10,873 fractures

Time Frame and Costs

Year 1: Initial software development and testing; log, field and image-based fracture analysis (site dependant); preliminary DFN for leakage risk assessment

Year 2: Complete software development; complete 3D seismic analysis; refine/complete model DFN; begin iterative flow simulation efforts through primary seal and reservoir intervals

Depending on project opportunities > refine and continue DFN/flow simulation process.

Annual budgets: $100K -$140K costs will be

site/application dependant

In Summary …

• develop and test of new seismic processing algorithms to support development of realistic caprock and reservoir DFNs.

• produce discrete fracture networks to simulate flow through caprock and reservoir intervals

• work with NETL modelers to evaluate possible leakage risk & reservoir behaviors through

flow simulation <> iterative DFN adjustments

Open Fractures observed in the

wellboreSurface fractures

Shear wave anisotropy

1626:Naci

1989:Ojo2018:C12056:Kirt

2690:C2

2826:Fr

2950:UFZ-T2987:UFC-B3056:MFC-T3072:MFC-B3111:LFC-T

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925.0680.0

925.0700.0

925.0720.0

925.0740.0

925.0760.0

Line:Trace:

EPNG COM A EC A 300 COM A 300EPNG COM A ING 1 COM A ING1SP-A SP ASP-B SPB SP-C SPC

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Questions?