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Comparison of Poststack MD Depth Slices

X (km). X (km). 10. 10. 8. 8. 6. 6. 4. 4. 6. 6. Y (km). Y (km). 8. 8. Comparison of Poststack MD Depth Slices. Kirchhoff Image. MD Image. 4. 4. 6. 6. 8. 8. 10. 10. 1. 1. Depth (km). Depth (km). 4. 4. Comparison of Prestack Migration and MD Images. X (km).

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Comparison of Poststack MD Depth Slices

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  1. X (km) • X (km) • 10 • 10 • 8 • 8 • 6 • 6 4 4 • 6 • 6 • Y (km) • Y (km) • 8 • 8 Comparison of Poststack MD Depth Slices • Kirchhoff Image • MD Image

  2. 4 • 4 • 6 • 6 • 8 • 8 • 10 • 10 • 1 • 1 • Depth (km) • Depth (km) • 4 • 4 Comparison of Prestack Migration and MD Images • X (km) • Prestack Kirchhoff Migration Image of • a North Sea Data Set • X (km) • MD Image

  3. Prestack Migration Deconvolution Jianxing Hu University of Utah

  4. Outline • Methodology • Theory and implementation • Numerical Tests • Synthetic and field data tests • Conclusions

  5. Modeling and Migration Forward Modeling: Model Space Green’s Function Reflectivity Wavelet Seismic data Migration: Data Space Migrated Image Seismic Data

  6. Relation of Migrated Image and Reflectivity Distribution Model Space Where: Data Space Denote as the migration Green’s Function

  7. Reflectivity Modulated by Migration Green’s Function Model Space

  8. Migration Deconvolution Model Space Model Space --- reference position of migration Green’s function

  9. Traveltime Table Migration Green’s function Methodology Calculate migration Green’s function Recording geometry & migrated image dimension + Velocity Model

  10. Apply migration deconvolution filter to the stacked prestack migration image RTM RTM 6 6 5 5 1 1 2 2 Depth (km) Depth (km) 3 3 Offset(km) Offset(km) Methodology Deconvolved Image Migration Image 5 Pseudo-Convolution

  11. Recording Geometry & migrated image dimension + Prestackmigration Green’s function Difference between Poststack MD and Prestack MD Zero-offset trace location & migrated image dimension + Velocity Model Traveltime Table Poststackmigration Green’s function

  12. MD Implementation Entire Migrated Image Cube Division Parts Image Layers Y X Z

  13. MD Scheme for Marine Survey Partitioned Image Cube Smaller Traveltime Table Computing Nodes

  14. MD Scheme for 3-D Land Survey Partitioned Image Cube Smaller Traveltime Table Computing Nodes Problem: Lose Far-Offset Traces

  15. Subdivide the migration image area and use multi- reference migration Green’s function to account for lateral velocity variation and far-field artifacts Multi-Reference migration Green’s function Lateral Velocity Variation

  16. Outline • Methodology • Numerical Tests • Conclusions

  17. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set (Canadian Foothills) • 3-D SEG/EAGE salt model • 3-D West Texas data set

  18. Recording Geometry 5 X 5 Sources; 21 X 21 Receivers Wavelet frequency 50 Hz (0, 1km) (0, 0) (1km, 1km) (1km, 0) Point scatterer

  19. Prestack KM vs. Prestack MD Y X Y Y X X Y X

  20. Prestack KM vs. Poststack MD Y X Y Y X X Y X

  21. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set (Canadian Foothills) • 3-D SEG/EAGE salt model • 3-D West Texas data set

  22. Recording Geometry 5 X 5 Sources; 21 X 21 Receivers Wavelet frequency 50 Hz (0, 1 km) (0, 0) (1 km,1 km) (1 km, 0) A river channel

  23. Meandering River Model X (m) 0 1000 0 Depth (m) 1000

  24. X (m) 0 1000 0 Depth (m) 1000 Kirchhoff Migration Image

  25. X (m) 0 1000 0 Depth (m) 1000 MD Image

  26. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set (Canadian Foothills) • 3-D SEG/EAGE salt model • 3-D West Texas data set

  27. 0 km 20 km 0 km 4 km • Prestack Migration Image X(km) 0 km • 20 km 0 km Depth (km) 4 km • Deconvolved Migration Image X(km) Depth (km)

  28. Zoom View of KM and MD 3 3 7 7 X (km) X (km) 2 2 Depth (km) Depth (km) 3 3 4 4 Prestack KM Prestack MD

  29. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set (Canadian Foothills) • 3-D SEG/EAGE salt model • 3-D West Texas data set

  30. X(km) 10 0 5 0 2 Depth (km) 6 Husky Prestack Migration Image 4

  31. X(km) 10 0 5 0 2 Depth (km) 6 Velocity Model for Husky Data 7000 Velocity (m/s) 3200

  32. X(km) 10 0 5 0 2 Depth (km) 6 MD with 3 reference positions

  33. X(km) 10 0 5 0 2 Depth (km) 6 MD with 20 reference positions

  34. KM Image MD Image 3 references MD Image 20 references

  35. X(km) 10 0 5 0 2 Depth (km) 6 MD with 20 reference positions A

  36. 5 9 X(km) 1 KM Depth (km) 3 5 X(km) 9 1 MD Depth (km) 3

  37. X(km) 10 0 5 0 2 Depth (km) 6 MD with 20 reference positions B

  38. 11 14 X(km) 1 KM Depth (km) 3 11 X(km) 14 1 MD Depth (km) 3

  39. X(km) 10 0 5 0 2 Depth (km) 6 MD with 20 reference positions C

  40. 10 X(km) 14 2 KM Depth (km) 5 10 X(km) 14 2 MD Depth (km) 5

  41. 10 X(km) 14 2 KM Depth (km) Whitening & Bandpass 5 10 X(km) 14 2 MD Depth (km) 5

  42. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set • 3-D SEG/EAGE salt model • 3-D West Texas data set

  43. SEG/EAGE Salt Model

  44. Y (km) 5 8 0 0 Depth (km) 2 2 4 4 Y (km) 5 8 KM Inline (97,Y) Section MD Inline (97,Y) Section

  45. X (km) X (km) 8 8 11 11 0 0 2 2 4 4 Depth (km) KM Crossline (X,97) Section MD Crossline (X,97) Section

  46. Depth Slices Y (km) Y (km) 5 5 8 8 8 8 X (km) X (km) 11 11 KM MD Y (km) 5 8 Y (km) 5 8 8 8 600 m X (km) X (km) 11 11 800 m

  47. Numerical Tests • 3-D point scatterer model • 3-D meandering stream model • 2-D SEG/EAGE overthrust model • 2-D Husky data set • 3-D SEG/EAGE salt model • 3-D West Texas data set

  48. Velocity Model for West Texas Data X (kft) 0 15 0 20 Velocity (kft/s) Depth(kft) 14 6

  49. West Texas Data X (kft) 0 10 4 8 Depth (kft) KM Inline Section (X,93) 12 16

  50. X (kft) 0 10 4 8 Depth (kft) 12 16 West Texas Data KM Crossline Section (93,Y)

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