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Coherence-weighted Wavepath Migration for Teleseismic Data

Coherence-weighted Wavepath Migration for Teleseismic Data. J. Sheng, G. T. Schuster, K. L. Pankow, J. C. Pechmann, and R. L. Nowack. University of Utah. Feb. 5, 2004. Motivation. Given: Teleseismic data. Goal: Local crustal structure. Solution I: Receiver function (RF). Principle of RF.

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Coherence-weighted Wavepath Migration for Teleseismic Data

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  1. Coherence-weighted Wavepath Migration for Teleseismic Data J. Sheng, G. T. Schuster, K. L. Pankow, J. C. Pechmann, and R. L. Nowack University of Utah Feb. 5, 2004

  2. Motivation Given: Teleseismic data Goal: Local crustal structure Solution I: Receiver function (RF)

  3. Principle of RF Green’s fun. Instrument Source history Vertical Comp. Radial (Langston, 1977, 1979) P PS Moho P

  4. pPs pSs pPp Moho Problems • Other phases generate artifacts

  5. Motivation Given: teleseismic data Goal: local crustal structure Solution I: Receiver function (RF) Solution II: Xcorrelogram mig. (Xmig)

  6. Principle of Xmig Ghost P-wave Direct P-wave

  7. Problems • Incident angle usually > 30 deg. • Irregular spacing • Low frequency and long source • history

  8. Motivation Given: teleseismic data Goal: local crustal structure Solution I: Receiver function (RF) Solution II: Xcorrelogram mig. (Xmig) Solution III: Coherence-weighted WM

  9. Outline Coherence-weighted WM Synthetic Test Earthquake Data Summary

  10. Coherence-weighted WM Step 1: Calculate radial and vertical RF • zero-phase traces b. source wavelet c. deconvolution

  11. Step 1: Calculate radial and vertical RF Coherence-weighted WM Step 2: Migrate RF and obtain ps, pPs, and pPp images

  12. P S X’ X’ X’ X X X Wavepath Migration R Plane wave Mps(x)=RRF(TS-TP) MpPs(x)=RRF(TS+TP) MpPp(x)=VRF(2TP)

  13. Step 1: Calculate radial and vertical RF Step 2: Migrate RF and obtain ps, pPs, and pPp images Coherence-weighted WM Step 3: Coherence weight

  14. Coherence-weighted WM ps pPs pPp 0 Depth (km) 60 0 220 0 220 0 220 Distances (km) Distances (km) Distances (km) 0 MCW=W*Mps Depth (km) 60 0 220 Distances (km)

  15. Outline Coherence-weighted WM Synthetic Test Earthquake Data Summary

  16. 0 Depth (km) 60 0 Distances (km) 220 Synthetic Model

  17. Parameters (Synthetic) • Plane P-wave incident at 40 deg. • 221 Stations with 1km spacing • Source peak frequency 0.6 Hz

  18. Synthetic Seismogram 0 Traveltime (sec.) 70 Vertical Radial

  19. Radial RF (Synthetic) 0 Traveltime (sec.) 20

  20. Vertical RF (Synthetic) 0 Traveltime (sec.) 20

  21. 0 Depth (km) 60 0 220 Distances (km) ps Image (Synthetic)

  22. 0 Depth (km) 60 0 220 Distances (km) pPs Image (Synthetic)

  23. 0 Depth (km) 60 0 220 Distances (km) pPp Image (Synthetic)

  24. 0 Depth (km) 60 0 220 Distances (km) CW Image (Synthetic)

  25. Outline Coherence-weighted WM Synthetic Test Earthquake Data Summary

  26. Earthquake Data

  27. Station Map 41.8 Great Salt Lake Latitude (deg.) 39.8 -113.5 -110.5 Longitude (deg.)

  28. 50 sec. 50 sec. 50 Processing Parameters 120 Time (sec.) Passband: 0.2~0.6 Hz 200 Water-level: 0.001 270

  29. 0 Time (sec.) 20 0 200 Distances (km) Radial RF

  30. 0 Time (sec.) 20 0 200 Distances (km) Vertical RF

  31. 0 Depth (km) 60 0 200 Distances (km) ps Image

  32. 0 Depth (km) 60 0 200 Distances (km) pPs Image

  33. 0 Depth (km) 60 0 200 Distances (km) pPp Image

  34. 0 Depth (km) 60 0 200 Distances (km) CW Image

  35. Outline Coherence-weighted WM Synthetic Test Earthquake Data Summary

  36. Summary • ps, pPs, and pPp arrivals in RF can be migrated • to provide a different perspective. • CWWM can combine three images to correctly • image the reflector with attenuated artifacts. • This method can image the Moho at the depth • consistent with previous studies.

  37. Acknowledgment I thank the sponsors of the 2003 UTAM Consortium for their financial support .

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