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Surface Wave Prediction and Subtraction by Interferometry + Deconvolution

Surface Wave Prediction and Subtraction by Interferometry + Deconvolution. Yanwei Xue Feb. 7, 2008. Outline. Motivation 2D Interferometry + Deconvolution Theory and Field Data Test 3D Proposed Algorithm and Field Data Test Conclusions & the Road Ahead. Motivation.

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Surface Wave Prediction and Subtraction by Interferometry + Deconvolution

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  1. Surface Wave Prediction and Subtraction by Interferometry + Deconvolution Yanwei Xue Feb. 7, 2008

  2. Outline • Motivation • 2D Interferometry + Deconvolution Theory and Field Data Test • 3D Proposed Algorithm and Field Data Test • Conclusions & the Road Ahead

  3. Motivation • Problem: Find a better way to predict and remove surface waves by interferometry • Background: • Interferometric Prediction (Dong, 2005) • Interferometry + NLF prediction (Xue, 2006) • Solution:Inteferometry + Deconvolution

  4. Outline • Motivation • 2D Interferometry + Deconvolution Theory and Field Data Test • 3D Proposed Algorithm and Field Data Test • Conclusions & the Road Ahead

  5. u (s,g) u (s,g’) u(g,g’) g g’ g g’ S 2D Interferometric Surface Wave Prediction U(s|g,ω)= W(s,ω)G(s|g) U(s|g’,ω)= W(s,ω)G(s|g’) C(g |g’,ω)=|W(s,ω)| G(g|g’) Using crosscorrelation D(g |g’)= G(g|g’) Using deconvolution W(s,ω) U(g|g’,ω)= D(g|g’) U(s|g’,ω)= W(s,ω)G(s|g’)

  6. Input data d Interferometry + Deconvolution prediction G Predicted d Source wavelet ^ ^ ^ d = d Least squares subtraction d= min || d – d || ^ ^ ^ 2 ^ Output data d no yes Basic workflow Window the surface waves out Surface waves removed completely?

  7. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 2D Field Data Test Raw Data vs 1st Prediction Original Data Interferometric prediction of 1st Iteration

  8. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 Raw Data vs 1st Removal Original Data Result after 1st Iteration

  9. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 3rd Removal vs 1st Removal Result after 1st Iteration Result after 3rd Iteration

  10. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 Raw Data vs 3rd Removal Result after 3rd Iteration Original Data

  11. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 Raw Data vs Removed SW Original Data Surface Waves Removed

  12. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 Interferometry + Deconvolution vs Interferometry + NLF Result of Interferometry + Deconvolution Result of Interferometry + NLF

  13. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 3600 3600 SW by Interferometry + Deconvolution vs by Interferometry + NLF Surface Waves Removed by Interferometry + NLF Surface Waves Removed by Interferometry + Deconvolution

  14. Outline • Motivation • 2D Interferometry + Deconvolution Theory and Field Data Test • 3D Proposed Algorithm and Field Data Test • Conclusions & the Road Ahead

  15. S2 S1 S3 Challenge for 3D Extension l2 l3 l1 l1 l2 2D: l2 - l1 = l3 3D: l2 - l1 < l3

  16. Proposed 3D Interferometry

  17. S1 S2 S3 z z Physical Meaning

  18. Acquisition Geometry 0 Receiver Interval Inline: 60 m Crossline: 260 m 42 receivers per line Y (m) Source Interval Inline: 60 m Crossline: 260 m Total 708 Shots 4000 0 4000 X (m) 3D Test with CREWES Field Data

  19. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 2500 2500 Interferometric Test of Line 4 predicted Original

  20. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 2500 2500 Interferometric Test of Line 2 predicted Original

  21. 0 0 Time (s) Time (s) 2.0 2.0 0 0 X (m) X (m) 2500 2500 Interferometric Test of Line 1 predicted Original

  22. Outline • Motivation • 2D Interferometry + Deconvolution Theory and Field Data Test • 3D Proposed Algorithm and Field Data Test • Conclusions & the Road Ahead

  23. Summary • I developed and tested a 2D nterferometry + Deconvolution prediction scheme for surface wave removal • Results of Interferometry + Deconvolution were compared with the results of Interferometry + NLF • I proposed and tested a 3D extension of this workflow , but did not get the expected result.

  24. The Road Ahead • Improve the ability of Interferometry + Deconvolution to separate noise from signal • Use a denser data set to improve our 3D test

  25. Thanks!

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