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3-D Migration Deconvolution

3-D Migration Deconvolution. Jianhua Yu, University of Utah Gerard T. Schuster, University of Utah. Jianxing Hu, GXT. Bob Estill, Unocal. Outline. Why Do Migration Deconvolution (MD) ?. Migration Deconvolution. Implementation of MD. Examples.

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3-D Migration Deconvolution

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  1. 3-D Migration Deconvolution Jianhua Yu, University of UtahGerard T. Schuster, University of Utah Jianxing Hu, GXT Bob Estill, Unocal

  2. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples Conclusions

  3. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples Conclusions

  4. Footprint Weak illumination Migration noise and artifacts Migration Noise Problems 0 Depth (km) 3.5

  5. Improving spatial resolution Enhancing illumination Purpose of MD Processing: Suppressing migration noise and artifacts

  6. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples Conclusions

  7. L is modeling operator Reflectivity Migrated image Migration: T M = L L R

  8. T -1 R = (L L ) M Goal: Reflectivity Migrated Section Design an improved MD filter MD is to eliminate the blurring influence in migration image by designing MD operator 3-D PRESTACK MD

  9. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples Conclusions

  10. Acquisition geometry information Velocity cube MD Implementation Steps: Step 1: Prepare traveltime table or Use migration timetable

  11. Y (km) N Depth Leveli L Depth (km) MD Implementation Steps: Step 2: Calculate the migration Green’s function

  12. Step 5: Repeat Steps 2-4 until the maximum depth is finished Step 4: Invert MD image at the depth Zi by solving linear equations MD Implementation Steps:

  13. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples : Synthetic data Conclusions

  14. 10 km 3X3 Sources; 11 X 11 Receivers dxshot=dyshot=1.5 km dxg=dyg=0.3 km 3-D Point Scatterer Model 3 km 3 km 0 0 Imaging: dx=dy=50 m dz=100 m

  15. 0 0 0 0 0 0 0 0 0 0 0 0 X (km) X (km) X (km) X (km) X (km) X (km) Y (km) Y (km) Y (km) Y (km) Y (km) Y (km) 3 3 3 3 3 3 3 3 3 3 3 3 MIG MD Depth Slices Z=1 km Z=3 km Z=5 km

  16. 0 0 0 0 0 0 0 0 0 0 0 0 X (km) X (km) X (km) X (km) X (km) X (km) Y (km) Y (km) Y (km) Y (km) Y (km) Y (km) 3 3 3 3 3 3 3 3 3 3 3 3 MIG MD Depth Slices Z=7 km Z=9 km Z=10 km

  17. 3.5 km 5 X 1 Sources; 11 X 7 Receivers Meandering Stream Model 2.5 km 2.5 km 0 0

  18. 0 X (km) 2.5 2.5 0 Y (km) Z=3.5 KM Mig Model MD

  19. 9 X5 Sources; 201 X 201 Receivers dxshot=dyshot=1 km 3-D SEG/EAGE Salt Model 12.2 km 12.2 km 0 0 Imaging: dx=dy=20 m

  20. 3-D SEG/EAGE Salt Model Y=7.12 km Y (km) X (km)

  21. Mig and MD ( z=1.4 km, negative polarity) X (km) X (km) 5 9.8 5 9.8 3 Y (km) 10 Mig MD

  22. Mig (z=1.2 km) MD (z=1.2 km) X (km) X (km) 5 9.8 5 9.8 3 Y (km) 10

  23. Mig (z=1.2 km) MD (z=1.2 km)

  24. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples: 2-D field data Conclusions

  25. X (km) 0 6 0 PS PSTM Image ( by Unocal) Time (s) 8

  26. X (km) 0 6 0 PSTMD PSTM(courtesy of Unocal) MD Time (s) 8

  27. X (km) 0 6 3 PSTM(courtesy of Unocal) PSTMD MD Time (s) 8

  28. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples: 3-D field data Conclusions

  29. : Sources : Receivers 3-D Land Field Data

  30. 3D PSTM (courtesy of Unocal) MD Inline Crossline 1.6 s

  31. MD 3D PSTM (courtesy of Unocal) Crossline 2.0 s

  32. Mig in Inline (Courtesy of Unocal) MD 3

  33. Mig MD Mig MD

  34. MD Mig (Courtesy of Unocal) Inline Number Inline Number 1 90 1 90 1 Crossline Number 300 (2 kft)

  35. Fault Fault

  36. MD Inline Number Inline Number 1 90 1 90 1 Crossline Number 265 Mig (Courtesy of Unocal) (3.6 kft)

  37. Mig (courtesy of Unocal) MD Inline Number 1 90 1 Inline Number 90 1.1 Depth (kft) 7.0 (Crossline=50)

  38. Mig (courtesy of Unocal) MD 1 90 1 90 1.1 Depth (kft) 8.0 (crossline 200)

  39. Crossline Number (Inline =50) 1 250 1.1 Depth (kft) Mig (Unocal) 7.0 1.1 MD 7.0

  40. Outline Why Do Migration Deconvolution (MD) ? Migration Deconvolution Implementation of MD Examples Conclusions

  41. Aperture width and filter length in designing MD filter are two key parameters Improve resolution and suppress migration artifacts MD cost is related with acquisition geometry Conclusions

  42. Acknowledgments • Thank Amramco, Unocal, and Chevron-Texaco for providing the data sets • The help and comments from Alan Leeds and George Yao are very appreciated • Thank 2002 UTAM sponsors for their financial support • http://utam.gg.utah.edu

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