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Shale Gas Development:Integrated Approach

Hemant Kumar DixitMumbai, India18 January-2013

Introduction

Motivation: Use seismic data to improve economics in resource shale plays

– Higher margins with less drilling and perforations/fracturing stages– Minimize environmental impact

Challenges: – Sweetspot identification – Optimize well location– Optimize completions

Drilling Completion

Installations

Motivation of Unconventional Resources

Source: Halliburton 2011-03

23% US gas production is from unconventional reservoirs (2010) Coal stores 6-7 times more gas than conventional reservoirs 4 trillion bbl of oil in Canada oil sands and Venezuela heavy oil Environment – proppant, water, noise, contamination

Based on graphic by Al Granberg

Fissures

The shale is fractured by the pressure induced

in the well10,000 ft

2,000 ft

8,000 ft

4,000 ft

6,000 ft

0 ft

Fissure

Sand keeps fissures open

Mixture of water, sand and chemical

agents

Well

Natural gas flows from fissures into

well

A mixture of water, sand and chemical agents is injected at high pressure in

the well

The challenge: prediction and control of fracturing

What seismic brings: Seismic Reservoir Characterization Stress & Fracture modeling Real-time Microseismic

Challenges in Shale Explortaion

CGGV North American Experience

2007 - 2011

5 Projects726 sq km

Marcellus

2008 - 20116 Projects

1405 sq km

Montney

2009 – 2 projects

178 Sq km+ 2D

Regional

Utica

2009 - 20112 Projects

5607 sq km

Haynesville

2010 - 2011

13 Projects6920 sq

km

Woodford

2009 - 2011

8 Projects1155 sq

km

Horn River

2010 - 1 Project

340 sq km

Eagle Ford

2009 - 3 Projects457 sq km

Bakken

2006 - 20083 Projects

+440 sq km

Picenace / Uinta

2007 – 8 Projects

+500 sq km

Barnett

More than 40 projects and 18,000 km2

CGGV in Shale Resource Exploration

Integrated solutions for Unconventional Resources Full suite of tools and technologies From prediction to monitoring Calibration & correlation with well data

Data acquisition Processing & Imaging

Fracture / stress characterization & rock properties

Sweet spot prediction with well-calibrated

attributes

Microseismic fracture

monitoring

Feasibility study & survey design

Calibration with well data – correlation with production data

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Generating Geomechanical Properties and Sweet Spot Identification for optimum driling

Tri-Parish Line Case Study

Shale Plays: Questions?

Shale TypeDuctile or Britle

Gas ContentTOC, Bulk Volume of Gas

FractureFracture Type, Direction and Length

Validation

Shale Plays: Seismic Driven Answers?

Shale Gas

Randomly oriented fractures

Bulk Volume Gas

Closure Pressure

Young’s Modulus

Poisson’s Ratio

17

Reservoir Quality

Brittleness

Stress

Shale Plays: Seismic Workflow

Haynesville Shale: Bulk Volume Gas

Bulk Volume Gas = Total Porosity x (1–Water Saturation)

Stress Analysis Workflow

Seismic AzAVO Terms E – Young’ s Modulus n – Poisson’s Ratio ZN – Normal Compliance

Hooke’s Law / Linear Slip Theory

h H

H

h

V

V

Patent Pending

Differential Horizontal Stress Ratio (DHSR)

If sHmax ≈ shmin (DHSR ≈ 0) Tensile cracks any direction

|| rock weakness Fracture network

If sHmax >> shmin (DHSR > 3-5%)

Fractures || sHmax

Shear Fractures Tensile Fractures

Connect to existing fracture network for production sHmax

sHmax

Pressure

shmin = Closure Stress

shmin

Patent Pending

H - h

HDHSR

Cross-plot DHSR vs. Young’s Modulus

Static Young’s Modulus

Aligned Fractures will form (YELLOW)Fracture Swarms will occur (GREEN)

Ductile (RED)

Diff

eren

tial H

oriz

onta

l Str

ess

Rat

ioDuctile Brittle

DHSR platelets overlaying Young’s Modulus

Plate orientation: direction of maximum horizontal stressMap colour: derived Young’s modulus

DHSR

BRITTLE

H - h

H

Volumetric Interpretation

16

Aligned Fractures (YELLOW)Fracture Swarms (GREEN)

Ductile (RED)

Probable Zones of Better Hydraulic Fractures

Static Young’s ModulusDiffe

rent

ial H

orizo

ntal

Stre

ss R

atio

H-h

H

Percentage of Hydraulic Fractures HighProbability: Zones of better hydraulic fractures (random pattern)

Low

H

h

H- h

H

Bottom of HVL

Multi-Attribute Analysis

High

Low

Highlighting Potential Good Production Areas

Validation: Analysis of orientation of H

Triaxial Measurements and Orientation H from

oriented core samples from different depths in the

Haynesville Shale

Orientation H across the Haynesville Shale derived

from seismic

EASTWEST

The direction of maximum horizontal stress predicted from

the seismic observations matched the corresponding

core stress measurements to within 5%.

compared with

-25o

Conclusions

Fully Integrated workflow for shale plays – acquisition to interpretation

Flexible multi-attribute solution correlating seismic observations to production figures, using Geomechanical rock properties Stress – HTI

Applications for: Sweet spot identification Well location optimization Completions optimization

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Conclusions

Environment Water access Proppant access Leakage prevention

Financial Well costs reduced Well performance enhanced Return On Investment

SEISMIC can help!

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22

Thank You

Reference:

Gray et. al.Estimation of Stress and Geomechanical Properties using 3D Seismic Data, First Break, Volume 30,March 2012

Differential Horizontal Stress Ratio (DHSR)

If sHmax ≈ shmin (DHSR ≈ 0)

Tensile cracks any direction || rock weakness Fracture network

If sHmax >> shmin (DHSR > 3-5%) Fractures || sHmax

Shear Fractures Tensile Fractures

Connect to existing fracture network for production

sHmax

shmin

sHmax

Pressure

shmin = Closure Stress

H - h

H

E: Young’s Modulus

DH

SR

E E

DHSR and Young’s Modulus Crossplot