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SURFACE WAVE ELIMINATION BY INTERFEROMETRY AND ADAPTIVE SUBTRACTION

SURFACE WAVE ELIMINATION BY INTERFEROMETRY AND ADAPTIVE SUBTRACTION. YANWEI XUE University of Utah. Outline. Surface Wave Problem & Remedy Theory of Interferometric Filtering 2D Field Data Results 3D Field Data Results Conclusions. Problem: Surface waves blur the seismograms.

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SURFACE WAVE ELIMINATION BY INTERFEROMETRY AND ADAPTIVE SUBTRACTION

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  1. SURFACE WAVE ELIMINATION BY INTERFEROMETRY AND ADAPTIVE SUBTRACTION YANWEI XUE University of Utah

  2. Outline • Surface Wave Problem & Remedy • Theory of Interferometric Filtering • 2D Field Data Results • 3D Field Data Results • Conclusions

  3. Problem: Surface waves blur the seismograms. A seismogram with surface waves and reflections Reflection waves 0 Time (s) Surface waves 2.0 Receiver (m) 0 7200 surf ref = d + d d Solution: Filter the surface waves by Non-Linear Filter (NLF) and interferometric method

  4. Outline • Surface Wave Problem & Remedy • Theory of Interferometric Prediction • 2D Field Data Results • 3D Field Data Results • Conclusions

  5. Near-OffsetSurf. Wave Mid-OffsetSurf. Wave Near-OffsetSurf. Wave A B A B B A A B A B B A B A Prediction of Surface Waves

  6. Basic Strategy ^ s Input data d d Interferometric prediction ^ ^ ^ d s ^ ^ ^ Least squares subtraction r No Output data Yes Surface waves are removed completely?

  7. 0 Time (s) 2.0 Receiver (m) 0 3600 Nonlinear Local Filter

  8. Outline • Surface Wave Problem & Remedy • Theory of Interferometric Filtering • 2D Field Data Results • 3D Field Data Results • Conclusions

  9. 0 Time (s) 2.0 Receiver (m) 0 3600 Raw Data

  10. 0 Time (s) 2.0 Receiver (m) 0 3600 Remove Surface Waves by NLF

  11. 0 Time (s) 2.0 Receiver (m) 0 3600 Remove Surface Waves by Int.+NLF

  12. 0 Time (s) 2.0 Receiver (m) 0 3600 Raw Data

  13. 0 Time (s) 2.0 Receiver (m) 0 3600 Remove Surface Waves by F-K

  14. 0 Time (s) 2.0 Receiver (m) 0 3600 Remove Surface Waves by Int.+NLF

  15. 0 Time (s) 2.0 Receiver (m) 0 3600 Surface Waves Predicted by F-K

  16. 0 Time (s) 2.0 Receiver (m) 0 3600 Surface Waves Predicted by Int.+NLF

  17. Outline • Surface Wave Problem & Remedy • Theory of Interferometric Filtering • 2D Field Data Results • 3D Field Data Results • Conclusions

  18. 0 0 Time (s) Time (s) 4.0 4.0 0 0 Receiver(m) 5000 Receiver (m) 5000 Line 9 Before and After Removal of Surface Waves

  19. 0 0 Time (s) Time (s) 4.0 4.0 0 0 Receiver (m) 5000 Receiver (m) 5000 Line 11 Before and After Removal of Surface Waves

  20. 0 0 Time (s) Time (s) 4.0 4.0 0 0 Receiver (m) 5000 Receiver (m) 5000 Line 13 Before and After Removal of Surface Waves

  21. 0 0 Time (s) Time (s) 4.0 4.0 0 0 Receiver (m) 5000 Receiver (m) 5000 Line 14 Before and After Removal of Surface Waves

  22. Outline • Surface Wave Problem & Remedy • Theory of Interferometric Filtering • 2D Field Data Results • 3D Field Data Results • Conclusions

  23. Conclusions • This approach is effective for surface wave removal in both 2D and 3D cases. • Advantages: • Better than FK method for irregular acquisition geometry. • No need for a near surface velocity model. • Limitations: • Sensitive to the choice of NLF parameters. • Parameter selection can be expensive. • Future Work: • Eliminate need for non-linear local filter. • More tests on 3D data.

  24. Acknowledgement I thank the sponsors of 2006 UTAM consortium for their financial support.

  25. THANKS!

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