C-wave analysis (Module 03-CW)

1. C-wave analysis (Module 03-CW) • 4C introduction • Isotropic processing • Anisotropic processing I – Early developments • Anisotropic processing II – Recent advances • Anisotropic processing in practice • More data examples • Converted-wave splitting (CWS) analysis • CWS in practice

2. A Proposed Workflow for Heavy Oil Reservoir Characterization Using Multicomponent Seismic Data R.R. Kendall*, P.F. Anderson, L. Chabot & F.D. Gray - Veritas

3. Outline • The Problem (lithology identification) • Integrated Multicomponent Workflow • Acquisition • Processing • Petrophysics • AVO/Inversion • Multi-Attribute/Neural Network • Reservoir models • Conclusions

4. The Problem – Lithology Identification Mud Plug

5. Good SAGD Pair Bad SAGD Pair SAGD - Steam Assisted Gravity Drainage Red – Injector Green - Producer

6. SAGD technology for Bitumen recovery

7. Outline • The Problem (lithology identification) • Integrated Multicomponent Workflow • Acquisition • Processing • AVO/Inversion • Multi-Attribute/Neural Network (EMERGE) • Reservoir models • Conclusions

8. Sensor Die Mixed Signal ASIC Geo Meca MEMS Sensors & Accelerometers

9. DSU3

10. What’s Changed? • New Systems Designed For Multicomponent • Improved Field Operations • Improved Quality • Point Receiver 3 FDU’s ~ DSU3 Triphone

11. Field Operations – System Deployment • Deployed in shallow hole • - significantly improved coupling • - reduced noise • Tilt (inclination) • will not cause signal degradation

12. Tilt Correction (VOR) Before Tilt CorrectionH1 = 90 o H2 = 115 oV = 25 o After Tilt CorrectionH1 = 90 o H2 = 90 oV = 0 o

13. 5 5 0 0 -5 -5 -10 -10 Amplitude Response in dB Laser Amplitude Response in dB -15 Vibrometer -15 -20 Geophone -20 -25 -25 MEMS -30 -30 1 10 100 1 10 100 Frequency (Hz) Frequency (Hz) Low Frequency Response Geophone & MEMS simultaneously shaken MEMS sensor maintains dynamic range at extreme low frequencies

14. Phase Response MEMS MEMS

15. High Resolution P-wave Data

16. Amplitude Spectrum Comparison MEMS Geophone

17. Wavelet Transform – Peak @ 100 Hz

18. Wavelet Transform – Peak @ 200 Hz

19. Wavelet Transform – Peak @ 300 Hz

20. Vertical Component - Raw Shot

21. Brute Rec Stack: LW static 550cdp

22. 550cdp Receiver Stack: only LW statics corrected

23. 550cdp Receiver Stack: LW and SW statics

24. 90 S 11 -7 P Statics – P vs S -75

25. Vp/Vs from PS Velocity Analysis 5.0 2.5 1.0

26. VSH estimation (EMERGE)

27. Flow Chart Processing Analysis Petrophysical Analysis PP Data (SAGE) Well Logs analyzed and evaluated to provide edited curves for inversions/EMERGE as well as to determine which attributes should aid in identification of shale content within the reservoir Processing PP data using conventional methods (decon, NMOZ, etc.) Output: PP-Stack PP-Gathers Registration Velocity & static info from PP processing feeds into PS Processing Correlate well logs to PP- & PS stack (ProMC) Use wells to guide horizon picking (Tornado) Estimate phase of seismic data (ProMC) Register PS-stack to PP-time PS Data (SAGE) Use stacking velocities from PP data for PSNMOZ correction of gathers and Shot-side statics in processing of PS data. Output: VpVs Ratio Volume PS- volumes in PP time Output: PS-Stack w/ CCP-binning PP-Gathers w/ CCP-binning

28. 1 1 1 1 Fault Fault Fault Fault Structure Structure Structure 2 2 2 2 Dip Dip Dip Structure Dip 3 Structure and Stratigraphy PS PP PP in PP time PS in PP time

29. Dipole or VSP (to the surface)

30. • Sand • Shale Core Integration  (Gpa-g/cc) Gas Sand Coal  (Gpa-g/cc) Petrophysical Rock Properties for Seismic Attribute Prediction Formation Evaluation

31. List of Attributes Input • PP: • Stack (plus various attributes) • Rp (plus various attributes) • Rs (plus various attributes) • Rd (plus various attributes) • Acoustic Impedance (inversion of PP-Stack) • P-Impedance (inversion of Rp) • S-Impedance (inversion of Rs) • Density (inversion of Rd) • Lambda*Rho • Mu*Rho • PS: • CCP Stack (plus various attributes) • Rs (plus various attributes) • Rd (plus various attributes) • Pseudo-S Impedance (inversion of PS-CCP Stack) • S-Impedance • Density • Other: • VpVs from Registration

32. Review • PP and PS data (acquisition and processing) • Registration • AVO Attributes Calculated • PP: Rp, Rs, Rd • PS: Rs, Rd • AVO Attributes Inverted • PP: AI, SI, RHOB • PS: SI, RHOB • Note that PS inversion were done in PS time to avoid wavelet-distortion effects of registration process • All above attributes loaded into EMERGE™ plus: • VpVs ratio from horizon-based registration • PP and PS Stacks • Inversions of PP and PS Stacks • Etc.

33. OB1 Map A’ A

34. OB1 – Calculated VSH VSH

35. OB2 Map B’ B

36. OB2 – Calculated VSH VSH

37. OB3 Map C’ C

38. OB3 – Calculated VSH VSH C C’ Blind Test

39. VSH w/ RHOB (DEV-6 – DEV) VSH 0.25

40. Reservoir Model and Simulation

41. Conclusions • Heavy oil is one of the world’s major crude oil deposits (~15%). • Devised an integrated workflow • Multicomponent • Acquisition • Processing • Interpretation and inversion • Reservoir model • We have shown that this integrated method can accurately estimate Vsh from seismic data using Multi-attribute Regression • PS Attributes made significant contribution to Multi-attribute Regression for VSH (4 of 9)