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First Arrival Traveltime and Waveform Inversion of Refraction Data

First Arrival Traveltime and Waveform Inversion of Refraction Data

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First Arrival Traveltime and Waveform Inversion of Refraction Data

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  1. First Arrival Traveltime and Waveform Inversion of Refraction Data Jianming Sheng and Gerard T. Schuster University of Utah October, 2002

  2. Outline • Motivation • First arrival traveltime and waveform inversion • Numerical examples • Summary

  3. Motivation Given: Traveltime and waveform of CDP refraction data Goal: High resolution tomogram Problem: Can waveform tomography provide better resolution than ray-based tomography?

  4. Ray-based Tomography vs. Full Waveform Inversion Efficient and robust Ray-based tomography Resolution limited by high-freq. assumption No high-freq. limitation Full waveform tomography Slow convergence and local minima problem

  5. First-arrival Traveltime and Waveform Inversion Efficient and robust Ray-based traveltime tomography Initial model No high-freq. limitation First-arrival waveform inversion Better convergence and mild nonlinear

  6. Outline • Motivation • First arrival traveltime and waveform inversion • Numerical examples • Summary

  7. First Arrival Traveltime and Waveform Inversion • Step 1: Preprocessing the raw data: band-pass, 3D to 2D transform, trace normalization • Step 2: Picking first-arrival traveltimes and muting out other waves except first arrivals

  8. First arrival traveltime tomography • Step 3: Minimizes traveltime residual Initial model

  9. Observed Predicted Misfit function • Step 4: First arrival waveform inversion

  10. Multigrid Tomography Dynamic smoothing scheme • Traveltime tomography: (to attack local minima problem) (Nemeth, T., Normark, E. and Qin, F., 1992)

  11. Outline • Motivation • First arrival traveltime and waveform inversion • Numerical examples • Summary

  12. Numerical Examples • Synthetic data I: Three-layer • Synthetic data II: WesternGeco (Blind test) • Redmond mine survey data

  13. 0 2500 1958 20 Depth (m) 1416 40 873 331 60 0 100 200 (m/s) Distance (m) Synthetic Model I Suggested by Konstantin Osypov Source Freq. 60 Hz Avg. Velocity 2400 m/s Source Wavelength 40 m

  14. 0 2500 1958 20 Depth (m) 1416 40 m 40 873 331 60 0 100 200 (m/s) Distance (m) Synthetic Model I

  15. Synthetic Data I • Synthetic data set was calculated • by 2-D FD acoustic wave equation • solver • Twenty-one shots and 51 traces • per shot were used. • Computational grid dimension was • 401*121.

  16. Synthetic Shot Gather -80 120 Offset (m) 0.0 Time (sec.) 0.1 Air Wave

  17. 0 2500 1958 20 Depth (m) 1416 40 873 331 60 0 100 200 (m/s) Distance (m) Traveltime Tomogram

  18. 0 2500 1958 20 Depth (m) 1416 40 873 331 60 0 100 200 (m/s) Distance (m) Synthetic Model I

  19. 2.0 Traveltime Residual (sec.) 1.0 0.0 1 30 Iterations Traveltime Residual

  20. 0 2500 1958 20 Depth (m) 1416 40 873 331 60 0 100 200 (m/s) Distance (m) Waveform Tomogram

  21. 0 2500 1958 20 Depth (m) 1416 40 873 331 60 0 100 200 (m/s) Distance (m) Synthetic Model I

  22. 12,000 8,000 Waveform Residual 4,000 0 Waveform Residual 1 30 Iterations

  23. Numerical Examples • Synthetic data I: Three-layer • Synthetic data II: WesternGeco (Blind test) • Redmond mine survey data

  24. True Velocity Model Horizontal distance (km) 0.0 26 0.0 1000 m/s 2050~2500 m/s Depth (km) 1.0

  25. True Density Model Horizontal distance (km) 0.0 26 0.0 Depth (km) 1.0

  26. Recorded CSG # 150 -3000 Offset (m) 3000 0.0 Time (sec.) 2.0

  27. Guessed Density Model 3400 Density (kg/m3) 1400 5000 1000 Velocity (m/s)

  28. Source Wavelet 400 0 Amplitude -600 0.0 Time (sec.) 0.25

  29. Waveform Matching Offset (m) -50 -25 Amplitude 0 25 50 0.0 Time (sec.) 0.2

  30. Traveltime Tomogram m/s Horizontal distance (km) 0.0 26 0.0 2712 2284 Depth (km) 1856 1428 1.0 1000

  31. Traveltime Tomogram m/s Horizontal distance (km) 5.0 8.75 0.0 2409 0.1 2057 Depth (km) 0.2 1705 1352 0.3 0.4 1000

  32. Waveform Tomogram m/s Horizontal distance (km) 5.0 8.75 0.0 2700 0.1 2275 Depth (km) 0.2 1850 1425 0.3 0.4 1000

  33. Migration section Horizontal distance (km) 5.0 8.75 0.0 0.1 Depth (km) 0.2 0.3 0.4

  34. Predicted CSG #150 -3000 Offset (m) 3000 0.0 Time (sec.) 2.0

  35. Recorded CSG # 150 -3000 Offset (m) 3000 0.0 Time (sec.) 2.0

  36. Numerical Examples • Synthetic data I: Three-layer • Synthetic data II: WesternGeco (Blind test) • Redmond mine survey data

  37. Salt Diapir Data • Thirty-one shots and 120 traces • total 3188 traveltimes picked. • Shot interval: 20 m • geophone interval 5 m • Source frequency 40 Hz. • Record length 1 sec. • sample interval 0.5 millisecond .

  38. 0 Time (sec.) 0.2 120 1 Geophone # CSG for Field Data After Preprocessing

  39. 0 Time (sec.) 0.2 120 1 Geophone # CSG for Field Data After Muting

  40. Wavelet Extracted 0 Time (sec.) 0.1

  41. 5500 0 20 m 4500 3500 55 m Depth (m) 2500 Tunnel SALT 1500 500 130 (m/s) 0 590 Distance (m) Traveltime Tomogram

  42. 2.0 Traveltime Residual (sec.) 1.0 0.0 Traveltime Residual 1 30 Iterations

  43. 5500 0 20 m 4500 3500 55 m Depth (m) 2500 Tunnel SALT 1500 500 130 (m/s) 0 590 Distance (m) Waveform Tomogram

  44. 5500 0 20 m 4500 3500 55 m Depth (m) 2500 Tunnel SALT 1500 500 130 (m/s) 0 590 Distance (m) Traveltime Tomogram

  45. 6,000 4,000 Waveform Residual 2,000 0 Waveform Residual 1 30 Iterations

  46. 0 Time (sec.) 0.2 120 1 Geophone # Predicted CSG

  47. 0 Time (sec.) 0.2 120 1 Geophone # CSG for Salt Data After Muting

  48. Logarithmic Amplitude Vs. Offset 2 0 Synthetic Log10 Amplitude -2 Observed -4 0 Offset (m) 400

  49. Problems Seismic attenuation Surface wave noise Source wavelet inversion & objective function