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Local MVA for VSP Data Progress Report

Local MVA for VSP Data Progress Report. Sanzong Zhang, Xin Wang and Xian Xiao Jan. 7, 2010. Outline. Local VSP Migration Local VSP MVA Challenges Numerical Examples Future Work Acknowledgements. Local VSP Migration. Conventional VSP Migration. s. s. g. Forward. Backward ‏.

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Local MVA for VSP Data Progress Report

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  1. Local MVA for VSP DataProgress Report Sanzong Zhang, Xin Wang and Xian Xiao Jan. 7, 2010

  2. Outline • Local VSP Migration • Local VSP MVA • Challenges • Numerical Examples • Future Work • Acknowledgements

  3. Local VSP Migration

  4. Conventional VSP Migration s s g Forward Backward‏ x

  5. Defocusing in VSP Migration s Errors in the overburden and salt body velocity model g x Defocusing

  6. Limitations in VSP Migration • Overburden or salt velocity model is required, but hard to build. • Errors due to imperfect velocity models.

  7. Local VSP Migration s R(g’|s) g’ x T(g|s) g

  8. Imaging Condition (1) Crosscorrelation imaging condition (2) Deconvolution imaging condition

  9. Steps of Local VSP Migration (a) VSP data: P(g|s)=T(g|s)+R(g|s) s g R(g|s)‏ (b) Backward reflection (c) Backward transmission x T(g|s)‏ T(x|s)= G(x|g)*T(g|s)‏ R(x|s)= G(x|g)*R(g|s)‏ g g s g g R(g|s)‏ x x T(g|s)‏ (d) Crosscorrelation g R(g|s)‏ m(x)= R(x|s)*T(x|s)‏ s x s

  10. Benefits • Local VSP migration is oriented to our target . • Only a local velocity model near the well is needed. • Complex overburden and salt body are avoided. • Source statics are automatically accounted for. • Immune to salt-related interbed cross-talk. • Fast and easy to perform.

  11. Local MVA for VSP Data

  12. Local VSP MVA (LVM)‏ • LVM combines VSP migration and velocity model updating • LVM is based on the local VSP migration obtained by using reflected and transmitted waves. • Depth residuals from common image gathers (CIGs) are transferred to traveltime residuals. • Traveltime tomography is used to update the local velocity model near the well.

  13. Challenges in Local VSP MVA

  14. Comparison of Three Migration Methods in Local VSP MVA.

  15. Depth Residuals CIGs using the background velocity model 2000m/s.

  16. Numerical Examples

  17. Sigsbee P-wave Velocity Model m/s 0 4500 279 shots, interval of 45.7m Depth (km)‏ 150 receivers, Interval of 30m 1500 9.2 Offset (km)‏ 12.5 -12.5

  18. Pressure component of a common receiver gather for the receiver at the depth of 4.6 km

  19. Local VSP Migration Results True model Migration image 4.6 d f Depth (km)‏ d f = fault 9.2 -3 Offset (km)‏ 3 d = diffractor

  20. Marine 2D Offset VSP data Source @150 m offset @600 m offset @1500 m offset 0 Depth (m)‏ 2800 m Salt 82 receivers with 15.3-m interval 3200 m 4878 1829 0 Offset (m)‏

  21. Velocity Profile P Wave 0 Incorrect velocity model Depth (m)‏ 2800 m Salt 3200 m 4500 0 5000 Velocity (m/s)‏

  22. Z-Component VSP Data 2652 Reflected P Salt Depth (m)‏ Direct P 3887 1.2 3.0 Traveltime (s)‏

  23. 150 m offset Without deconvolution With deconvolution 3.3 Depth (km)‏ 3.9 Offset (m)‏ Offset (m)‏ 0 100 0 100

  24. 600 m offset Without deconvolution With deconvolution 3.3 Depth (km)‏ 4.4 Offset (m)‏ Offset (m)‏ 0 600 0 600

  25. 1500 m offset Without deconvolution With deconvolution 3.3 Depth (km)‏ 4.4 Offset (m)‏ Offset (m)‏ 0 600 0 600

  26. Future work • Method to recognize minor depth • residuals • Conversion between depth residual • and time residual • Interactive velocity updating based • on time residual tomography

  27. Acknowledgements • Thanks to the 2009 sponsors of UTAM Consortium for their support. • Thanks to Jerry for providing me excellent working conditions at KAUST. • Thanks to Xian Xiao for providing me his data and code.

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