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Adaptive Grid Reverse-Time Migration

Adaptive Grid Reverse-Time Migration. Yue Wang. Outline. Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions. Problem. Kirchhoff migration is not optimal for complex velocity model. Marmousi Model. 0. Depth (km). Low-velocity wedge. 3.

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Adaptive Grid Reverse-Time Migration

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  1. Adaptive Grid Reverse-Time Migration Yue Wang

  2. Outline Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions

  3. Problem Kirchhoff migration is not optimal for complex velocity model.

  4. Marmousi Model 0 Depth (km) Low-velocity wedge 3 0 9 Distance (km)

  5. Problem Kirchhoff migration Using first arrival time Difficulty in imaging

  6. Problem Reverse-Time Migration RTM) Using multi-arrival time Image complex structure Expensive

  7. Solution Variable grid size Variable time step Fast RTM

  8. Objective Develop fast reverse time migration for land and marine multi-component data

  9. Outline  Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions

  10. Reverse Time Operator A 2-4 staggered-grid FD solver Elastic wave equation

  11. Variable Grid Size Low velocity High velocity Depth Distance

  12. Variable Grid Size Fine grid (dx dz) Coarse grid (3dx 3dz) z

  13. Variable Grid Size Fine grid Use wave equation to propagate waves Coarse grid

  14. Variable Time Step coarse grid, fine time step Depth coarse grid, coarse time step Distance

  15. dt dt dt 3 dt t Variable Time Step z

  16. t Variable Time Step Fine time step Use wave equation to propagate waves Coarse time step z

  17. Variable Time Step Falk et al. (1998, Geophys. Pros. ): 1. Non-staggered-grid FD 2. 2x time step change

  18. Variable Time Step The new method : 1. Staggered-grid FD 2. 3x time step change

  19. No artificial reflections Time t2 Amplitude Depth Numerical Results Time t1 Amplitude Depth Fine time step Coarse time step

  20. Outline  Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions

  21. Salt Model 0 Depth (km) 2.7 0 4.5 Distance (km)

  22. Velocity Profile P S 0 0 Depth (km) Depth (km) 2.7 2.7 1.5 4 0 2 Velocity (km/s) Velocity (km/s)

  23. Velocity Profile P S Fine grid size Fine time step 0 Coarse grid size Coarse time step Depth (km) 2.7 1.5 4 0 2 Velocity (km/s) Velocity (km/s)

  24. Horizontal Vertical Normal Stress 0 Shot Gather Time (s) 2 0.9 Distance (km) 3.6 0.9 Distance (km) 3.6 0.9 Distance (km) 3.6

  25. 0 Kirchhoff Migration Depth (km) 2.5 0.45 4.05 Distance (km)

  26. 0 Kirchhoff Migration Depth (km) 2.5 0.45 4.05 Distance (km)

  27. 0 Reverse Time Migration Depth (km) 2.5 0.45 4.05 Distance (km)

  28. 0 Reverse Time Migration Depth (km) 2.5 0.45 4.05 Distance (km)

  29. Outline Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions 

  30. Radial Component Vertical Component Processed CSG 0 Time (s) 2.7 0 80 0 80 Trace Number Trace Number

  31. Common Offset Gather(Vertical Component) 0 Depth (km) Signal/Noise Ratio High 4 0 27 Distance (km)

  32. Common Offset Gather(Radial Component) 0 Depth (km) Signal/Noise Ratio Low 4 0 27 Distance (km)

  33. Kirchhoff Migration(Vertical Component) 0 Depth (km) 4 0 27 Distance (km)

  34. Kirchhoff Migration(Radial Component) 0 Depth (km) 4 0 27 Distance (km)

  35. RTM 0 Depth (km) 4 0 27 Distance (km)

  36. RTM KM Comparison 0 Depth (km) 4 0 27 0 27 Distance (km) Distance (km)

  37. Outline Motivation and Objective Reverse Time Methodology Salt Dome Model Test Field Data Test Conclusions and Future Work 

  38. Conclusions Variable RTM 10 times faster than standard RTM Migrates Land and marine multi-component data Use primary and multiple reflections for imaging

  39. Acknowledgement We are grateful to the 1999 sponsors of the UTAM consortium for the financial support

  40. Radial Component Vertical Component Raw CSG 0 Time (s) 2.7 0 80 0 80 Trace Number Trace Number

  41. Main Processing Flow Geometry assignment, datuming and so on Trace editing Surface wave attenuation, amplitude balancing P-velocity analysis S-velocity analysis Relative gain compensation, surface velocity estimation KM RTM

  42. 0 Shallow Velocity Depth (km) 0.4 0 27 Distance (km)

  43. Future Work Apply the RTM scheme for data set with more complex structures.

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