1. 3-D Prestack Migration Deconvolution Bob Estill ( Unocal) Jianhua Yu (University of Utah)

2. Why 3-D Prestack MD ? Outline Migration Deconvolution Examples Conclusions Synthetic and field data

3. Why 3-D Prestack MD? Outline Migration Deconvolution Examples Conclusions Synthetic and field data

4. Limited recording aperture Aliasing problem Multi-illumination angles More 3-D prestack data Why 3-D Prestack MD

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

6. Purpose of 3-D MD: Improving spatial resolution Enhancing illumination Suppressing migration noise and artifacts

7. Migration Deconvolution Outline Why 3D Prestack MD ? Examples Conclusions Synthetic and field data

8. m’ = L d T Migration: but d = L m Migrated image Data L m Migration image = Blurred image of true reflectivity model m L is modeling operator Reflectivity

9. T m = (L L ) m’ 3-D Prestack MD Reflectivity Design an improved MD filter Migrated Section An improved MD operator aims at improving the stability of MD filter

10. Examples Migration Deconvolution Outline Conclusions Synthetic and field data Why 3D Prestack MD?

11. Examples Migration Deconvolution Outline Conclusions Synthetic and field data Why 3D Prestack MD?

12. Recording Geometry : Sources : Receivers

13. Recording Geometry 10 KM

14. 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) MIG MD Z=1 km Z=3 km Z=5 km Depth Slices

15. 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) MIG MD Z=7 km Z=9 km Z=10 km Depth Slices

16. 0 2.5 km 0 Meandering Stream Model 2.5 km 5 X 1 Sources; 11 X 7 Receivers

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

18. 0 12.2 km 0 3-D SEG/EAGE Salt Model 12.2 km 9 X5 Sources; dxshot=dyshot=1 km 201 X 201 Receivers Imaging: dx=dy=20 m

19. 3-D SEG/EAGE Salt Model Y=3.12 km X (km)Y (km)

20. Mig and MD ( Inline, negative polarity) X (km) 0.4 3.6 Depth (km) 5.29.45.29.4 X (km) MDMig

21. 3-D SEG/EAGE Salt Model X (km)Y (km) Y=7.12 km

22. Mig and MD ( y=7.12 km, negative polarity) X (km) 0.4 3.6 Depth (km) 59.85 X (km) MDMig

23. 3-D SEG/EAGE Salt Model X=8.12 km X=6.12 km

24. Mig and MD (x=6.12 km, negative polarity) Y (km) 0.4 3.6 Depth (km) 5105 Y (km) MDMig

25. 3-D SEG/EAGE Salt Model 1.4 km

26. Mig and MD ( z=1.4 km, negative polarity) X (km) 3 10 Y (km) 59.85 X (km) MDMig

27. 3-D SEG/EAGE Salt Model 1.2-1.4 km

28. MD (z=1.2 km)Mig (z=1.2 km) X (km) 3 10 Y (km) 59.85 X (km)

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

30. MD (z=1.4 km)Mig (z=1.4 km) X (km) 3 10 Y (km) 59.85 X (km)

31. Migration Deconvolution Outline Examples Conclusions Synthetic and field data Why 3D Prestack MD?

32. Unocal Alaska 3-D Data : Receivers : Sources

33. Horizontal Slice at 1.2 s Inline Crossline 3D PSTM (courtesy of Unocal)MD

34. 1.6 s Inline Crossline Horizontal Slice at 1.6 s 3D PSTM (courtesy of Unocal)MD

35. 2.0 s Crossline Horizontal Slice at 2.0 s 3D PSTM (courtesy of Unocal)MD

36. 2.0 s Inline Crossline Horizontal Slice at 2.4 s 3D PSTM (courtesy of Unocal)MD

37. 3 Mig in Inline (Courtesy of Unocal) MD

38. Mig MD Mig MD

39. Migration Deconvolution Outline Why 3D Prestack MD? Examples Conclusions Synthetic and field data

40. Conclusions Improve resolution and mitigate some migration artifacts Suitable for Kirchhoff and Wave equation migration images Poststack MD processing = Postmig (up to Prestack MD processing <= Premig

41. Conclusions Improve resolution and mitigate some migration artifacts Suitable for Kirchhoff and Wave equation migration images Poststack MD processing = Postmig Prestack MD processing <= Premig ( relative with the specific MD filter )

42. Acknowledgments Thank Bob Estill and Unocal for providing the proprietary data set and the careful guidance of Unocal people in processing and interpreting Unocal Alaska dataThank Bob Estill and Unocal for providing the proprietary data set and the careful guidance of Unocal people in processing and interpreting Unocal Alaska data Thank 2002 UTAM sponsors for the financial supportThank 2002 UTAM sponsors for the financial support