2. Crosscorrelation Migration of Free-Surface Multiples in RVSP Data Jianming Sheng University of Utah February, 2001

3. Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

4. Objective Validate the feasibility of crosscorrelation migration for RVSP data; Image the reflectivity distribution without knowing the source position. (Schuster and Rickett, 2000)

5. Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

6. Crosscorrelation Migration Principle Asymptotic analysis Key steps

7. Principle of CCM S G’ G X Crosscorrelogram

8. Principle of CCM S G’ G X Virtualsource Imaging condition

9. Asymptotic Analysis Migration image Trial image point Crosscorrelograms

10. Asymptotic Analysis Under stationary phase condition D irect G host Negligible contribution from: D irect Contribution from: Contribution from: G host Contribution from: Contribution from: G host D irect Reflection coefficient

11. Asymptotic Analysis CCM image gives the reflectivity distribution except contaminated by artifacts up to order

12. Key Steps of CCM Step 1: Bandpass filter and other preprocess; Step 2: Dip filter; Step 5: Migrate the crosscorrelograms. Step 3: Generate crosscorrelograms; Step 4: Filter aliasing in crosscorrelograms;

13. Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

14. Numerical Examples Three-layered modelThree-layered model Exxon’s Friendswood RVSP dataExxon’s Friendswood RVSP data

15. RECEIVERS 91.4 m 182.8 m V1 = 762 m/s V3 = 1372 m/s V2 = 1067 m/s SOURCES Three-Layered Model 98 shots 24 traces per shot

16. 1st-CRG 0 150 300 Depth (m) 0 150 300 Depth (m) 0 0.8 0.6 0.2 0.4 0 0.8 0.6 0.2 0.4 Time (sec.) Dip-filtered Before dip-filtered Direct Primary Ghost

17. 1st-CSG0 0.8 0.6 0.2 0.4 Time (sec.) 0 0.8 0.6 0.2 0.4 0 60 120 180 Offset (m) Shot Gather Crosscorrelogram Pseudo-Shot Gather D G High-order Ghost

18. Crosscorrelation migration image 0 90 180 Offset (m) 0 150 300 Depth (m) True Reflectors

19. RECEIVERS SOURCES Exxon’s Friendswood RVSP Data 98 shots 23 traces per shot 9.1 m 304.8 m 7.6 m 365.7 m

20. Exxon’s Friendswood RVSP Data 0 200 300 Depth (m) 100 ReflectivityWell-log CCM

21. Exxon’s Friendswood RVSP Data 0 180 360 0 12 24 Offset (m) Depth (m) CCM image

22. Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

23. Summary Asymptotic analysis shows that CCM is capable of imaging the reflectivity distribution;Asymptotic analysis shows that CCM is capable of imaging the reflectivity distribution; The results of synthetic and Exxon’s Friendswood RVSP data validate the feasibility of CCM.The results of synthetic and Exxon’s Friendswood RVSP data validate the feasibility of CCM.

24. Further Work To attenuate the artifacts generated by CCM;To attenuate the artifacts generated by CCM; To deal with the amplitude preservation problem.To deal with the amplitude preservation problem.

25. Acknowledgment I thank the sponsors of the 2000 University of Utah Tomography and Modeling /Migration (UTAM) Consortium for their financial support.