Shale Gas Development: Integrated Approach

1. Shale Gas Development:Integrated Approach Hemant Kumar Dixit Mumbai, India 18 January-2013

2. 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 Completion Drilling Installations

3. Motivation of Unconventional Resources • 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 Source: Halliburton 2011-03

4. Challenges in Shale Explortaion A mixture of water, sand and chemical agents is injected at high pressure in the well 0 ft • The challenge: prediction and control of fracturing Sand keeps fissures open Fissure 2,000 ft Natural gas flows from fissures into well Mixture of water, sand and chemical agents • What seismic brings: • Seismic Reservoir Characterization • Stress & Fracture modeling • Real-time Microseismic 4,000 ft 6,000 ft Well Fissures 8,000 ft The shale is fractured by the pressure induced in the well 10,000 ft Based on graphic by Al Granberg

5. CGGV North American Experience More than 40 projects and 18,000 km2 Utica Horn River 2009 – 2 projects 178 Sq km + 2D Regional 2009 - 2011 8 Projects 1155 sq km Marcellus Montney 2007 - 2011 5 Projects 726 sq km 2008 - 2011 6 Projects 1405 sq km Woodford Bakken 2010 - 2011 13 Projects 6920 sq km 2009 - 3 Projects 457 sq km Picenace / Uinta Eagle Ford Haynesville Barnett 2009 - 2011 2 Projects 5607 sq km 2006 - 2008 3 Projects +440 sq km 2007 – 8 Projects +500 sq km 2010 - 1 Project 340 sq km

6. CGGV in Shale Resource Exploration Feasibility study & survey design Data acquisition Processing & Imaging Fracture / stress characterization & rock properties Sweet spot prediction with well-calibrated attributes Microseismic fracture monitoring Calibration with well data – correlation with production data • Integrated solutions for Unconventional Resources • Full suite of tools and technologies • From prediction to monitoring • Calibration & correlation with well data

7. Tri-Parish Line Case Study Generating Geomechanical Properties and Sweet Spot Identification for optimum driling

8. Shale Plays: Questions? Shale Type Ductile or Britle Gas Content TOC, Bulk Volume of Gas Fracture Fracture Type, Direction and Length Validation

9. Shale Plays: Seismic Driven Answers?

10. Shale Plays: Seismic Workflow

11. Haynesville Shale: Bulk Volume Gas Bulk Volume Gas = Total Porosity x (1–Water Saturation)

12. Stress Analysis Workflow Hooke’s Law / Linear Slip Theory H V h V h H Patent Pending Seismic AzAVO Terms E – Young’ s Modulus n – Poisson’s Ratio ZN – Normal Compliance

13. Differential Horizontal Stress Ratio (DHSR) H - h H DHSR shmin sHmax shmin = Closure Stress Pressure sHmax Patent Pending • 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

14. Cross-plot DHSR vs. Young’s Modulus Ductile Brittle Differential Horizontal Stress Ratio Static Young’s Modulus Aligned Fractures will form (YELLOW) Fracture Swarms will occur (GREEN) Ductile (RED)

15. DHSR platelets overlaying Young’s Modulus BRITTLE H - h H DHSR Plate orientation: direction of maximum horizontal stress Map colour: derived Young’s modulus

16. Volumetric Interpretation Aligned Fractures (YELLOW) Fracture Swarms (GREEN) Ductile (RED)

17. Probable Zones of Better Hydraulic Fractures Probability: Zones of better hydraulic fractures (random pattern) High Percentage of Hydraulic Fractures H- h H Bottom of HVL Low

18. Multi-Attribute Analysis Highlighting Potential Good Production Areas High Low

19. 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 compared with WEST EAST The direction of maximum horizontal stress predicted from the seismic observations matched the corresponding core stress measurements to within 5%.

20. 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

21. Conclusions • Environment • Water access • Proppant access • Leakage prevention • Financial • Well costs reduced • Well performance enhanced • Return On Investment • SEISMIC can help!

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

23. Differential Horizontal Stress Ratio (DHSR) shmin sHmax shmin= Closure Stress H - h H Pressure sHmax • 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

24. DHSR and Young’s Modulus Crossplot DHSR E E E: Young’s Modulus