1 / 54

Migration velocity analysis by recursive wavefield extrapolation

Migration velocity analysis by recursive wavefield extrapolation. Paul Sava & Biondo Biondi Stanford University SEP. Motivation. Wave-equation MVA (WEMVA). Band-limited Multi-pathing Resolution Born approximation small anomaly Rytov approximation phase unwrapping.

nadine-morse
Download Presentation

Migration velocity analysis by recursive wavefield extrapolation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Migration velocity analysis by recursive wavefield extrapolation Paul Sava & Biondo Biondi Stanford University SEP paul@sep.stanford.edu

  2. Motivation paul@sep.stanford.edu

  3. Wave-equation MVA (WEMVA) Band-limited Multi-pathing Resolution Born approximation small anomaly Rytov approximation phase unwrapping paul@sep.stanford.edu

  4. Wave-equation MVA (WEMVA) WE tomography data space WE MVA image space paul@sep.stanford.edu

  5. Outline • WEMVA overview • Born image perturbation • Differential image perturbation • Example paul@sep.stanford.edu

  6. A tomography problem paul@sep.stanford.edu

  7. WEMVA: main idea paul@sep.stanford.edu

  8. Born approximation paul@sep.stanford.edu

  9. WEMVA: objective function Linear WEMVA operator slownessperturbation image perturbation (known) slowness perturbation (unknown) image perturbation paul@sep.stanford.edu

  10. WEMVA: objective function paul@sep.stanford.edu

  11. Fat ray: GOM example paul@sep.stanford.edu

  12. Outline • WEMVA overview • Born image perturbation • Differential image perturbation • Example paul@sep.stanford.edu

  13. “Data” estimate paul@sep.stanford.edu

  14. Prestack Stolt residual migration r R0 R • Background image R0 • Velocity ratio r paul@sep.stanford.edu

  15. Prestack Stolt residual migration r R0 R • Image perturbation paul@sep.stanford.edu

  16. Born approximation paul@sep.stanford.edu

  17. Residual migration: the problem Correct velocity Incorrect velocity Zero offset image Zero offset image Angle gathers Angle gathers paul@sep.stanford.edu

  18. Born approximation paul@sep.stanford.edu

  19. Outline • WEMVA overview • Born image perturbation • Differential image perturbation • Example paul@sep.stanford.edu

  20. Differential image perturbation Image difference Image differential Computed Measured paul@sep.stanford.edu

  21. Differential image perturbation R Rr R0 r r0 r paul@sep.stanford.edu

  22. Phase perturbation Df +3p +2p +p 0 r -p -2p paul@sep.stanford.edu

  23. Differential image perturbation paul@sep.stanford.edu

  24. Born approximation paul@sep.stanford.edu

  25. Example: background image Zero offset image Background image Angle gathers paul@sep.stanford.edu

  26. Example: differential image Zero offset image Differential image Angle gathers paul@sep.stanford.edu

  27. Example: slowness inversion Image perturbation Slowness perturbation paul@sep.stanford.edu

  28. Example: updated image Updated image Updated slowness paul@sep.stanford.edu

  29. Example: correct image Correct image Correct slowness paul@sep.stanford.edu

  30. Outline • WEMVA overview • Born image perturbation • Differential image perturbation • Example paul@sep.stanford.edu

  31. Field data example • North Sea • Salt environment • Subset • One non-linear iteration • Migration (background image) • Residual migration (image perturbation) • Slowness inversion (slowness perturbation) • Slowness update (updated slowness) • Re-migration (updated image) depth location paul@sep.stanford.edu

  32. depth location depth paul@sep.stanford.edu

  33. depth velocity ratio velocity ratio paul@sep.stanford.edu

  34. depth location depth paul@sep.stanford.edu

  35. depth location location paul@sep.stanford.edu

  36. depth location location paul@sep.stanford.edu

  37. depth location depth paul@sep.stanford.edu

  38. depth location depth paul@sep.stanford.edu

  39. Summary • MVA • Wavefield extrapolation methods • Born linearization • Differential image perturbations • Key points • Band-limited (sharp velocity contrasts) • Multi-pathing (complicated wavefields) • Resolution (frequency redundancy) paul@sep.stanford.edu

  40. paul@sep.stanford.edu

  41. MVA information (a) g g x x z z paul@sep.stanford.edu

  42. MVA information (b) g g x x z z paul@sep.stanford.edu

  43. MVA information (c) w w g g paul@sep.stanford.edu

  44. WEMVA cost reduction Full image Offset focusing Spatial focusing Frequency Normal incidence image Spatial focusing “fat” rays w w g g paul@sep.stanford.edu

  45. Another example paul@sep.stanford.edu

  46. Example: correct model Zero offset image Angle gathers paul@sep.stanford.edu

  47. Example: background model Zero offset image Angle gathers paul@sep.stanford.edu

  48. Example: correct perturbation Zero offset image Angle gathers paul@sep.stanford.edu

  49. Example: differential perturbation Zero offset image Angle gathers paul@sep.stanford.edu

  50. Example: perturbations comparison Correct Difference Differential paul@sep.stanford.edu

More Related