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Comparison of KM and MD

0 km. 0 km. 4 km. 4 km. Comparison of KM and MD. Poststack Migration Image. 0 km. 15 km. Deconvolved Migration Image. 0 km. 15 km. 5. 1. Comparison of RTM and MD Images. RTM. MD. 6. 6. 5. 1. 2. 2. Depth (km). Depth (km). 3. 3. X(km). X(km). X (km). X (km). 10. 10. 8.

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Comparison of KM and MD

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  1. 0 km 0 km 4 km 4 km Comparison of KM and MD • Poststack Migration Image • 0 km • 15 km • Deconvolved Migration Image 0 km 15 km

  2. 5 • 1 Comparison of RTM and MD Images RTM MD • 6 • 6 • 5 • 1 • 2 • 2 • Depth (km) • Depth (km) • 3 • 3 • X(km) • X(km)

  3. 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. Time-Migration Deconvolution Jianxing Hu University of Utah

  5. Outline • Problem • Formation of migration image • Solution • Time-migration deconvolution • Numerical Tests • Synthetic and field data tests • Conclusions

  6. Footprint Amplitude distortion Migration noise and artifacts The Problems • Migration Noise • Recording Footprint • Poor Resolution • Amplitude Distortion • 0 km • 15 km 0 Time (s) 2

  7. Seismograph Source Formation of Migration Image Receivers Point Reflector

  8. Seismograph Migration Response Point Reflector Migration Image

  9. Continue Reflector Migration Image Seismograph Dip Reflection Layer

  10. Migration Response Continue Reflector Migration Image Seismograph Dip Reflection Layer

  11. Outline • Problem • Solution • Numerical Tests • Conclusions

  12. Solution Apply the principle of migration deconvolution to time-migration section

  13. Relation of Migrated Image • and Reflectivity Distribution Model Space where is point scatterer migration response and defined as “migration Green’s function”

  14. Assumption Migration Green’s function is lateral shift invariant: -- 1-D velocity model with an lateral invariant recording geometry and aperture Model Space

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

  16. Lateral Velocity Variation • Lateral Velocity Variation • Finite recording geometry Distance Depth

  17. 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

  18. Outline • Problem • Solution • Numerical Tests • Conclusions

  19. Numerical Tests • 2-D SEG/EAGE overthrust model • 2-D Mobil marine data from the North Sea

  20. X (km) 0 0 Time (s) Time (s) 2 2 0 km 15 km KM 0 km 15 km MD

  21. 6 6 8 8 10 10 0.5 0.5 1.0 1.0 Zoom Views X (km) X (km) Time (s) KM MD

  22. X (km) 0 0 Time (s) Time (s) 2 2 0 km 15 km KM 0 km 15 km MD

  23. 6 6 8 8 10 10 0.5 0.5 1.0 1.0 Zoom Views X (km) X (km) Time (s) KM MD

  24. Numerical Tests • 2-D SEG/EAGE overthrust model • 2-D Mobil marine data from the North Sea

  25. X (km) 0 25 0 Time (s) 4 6 Velocity Model 2500 Velocity (m/s) 1500

  26. X (km) 0 25 0 Time (s) 4 6 Time Migration Image

  27. KM MD 0 Time (s) 4 6 Migration Deconvolution Image X (km) 0 25

  28. KM MD X(km) X(km) 14 14 18 18 2 2 Time (s) Time (s) 2.7 2.7

  29. Spike Decon MD X(km) X(km) 14 14 18 18 2 2 Time (s) Time (s) 2.7 2.7

  30. Whitening Filtering MD X(km) X(km) 14 14 18 18 2 2 Time (s) Time (s) 2.7 2.7

  31. KM MD 0 Time (s) 4 6 Migration Deconvolution Image X (km) 0 25

  32. KM MD X(km) X(km) 10 10 14 14 1 1 Time (s) Time (s) 1.8 1.8

  33. Spike Decon MD X(km) X(km) 10 10 14 14 1 1 Time (s) Time (s) 1.8 1.8

  34. Whitening Filtering MD X(km) X(km) 10 10 14 14 1 1 Time (s) Time (s) 1.8 1.8

  35. KM MD 0 Time (s) 4 6 Migration Deconvolution Image X (km) 0 25

  36. KM MD X(km) X(km) 20 20 24 24 1.5 1.5 Time (s) Time (s) 2.3 2.3

  37. Spike Decon MD X(km) X(km) 20 20 24 24 1.5 1.5 Time (s) Time (s) 2.3 2.3

  38. Whitening Filtering MD X(km) X(km) 20 20 24 24 1.5 1.5 Time (s) Time (s) 2.3 2.3

  39. Outline • Motivation • Solution • Numerical Tests • Conclusions

  40. Works on 2-D synthetic and field poststack time migration data, improve resolution, mitigate some migration artifacts Subdivision method is able to account for lateral-velocity variations and attenuate some far-field artifacts A post-migration processing: Cost 2X Conclusions

  41. Apply time-migration deconvolution to prestack time migration data Future Work Test time-migration deconvolution algorithm on 3D synthetic and field poststack migration data

  42. Acknowledgement I thank the members of Utah Tomography and Modeling /Migration (UTAM) Consortium for their financial support

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