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

Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

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

Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

Crosscorrelation Migration Principle Asymptotic analysis Key steps

Principle of CCM S G’ G X Crosscorrelogram

Principle of CCM S G’ G X Virtualsource Imaging condition

Asymptotic Analysis Migration image Trial image point Crosscorrelograms

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

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

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;

Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

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

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

1st-CRG Depth (m) Depth (m) Time (sec.) Dip-filtered Before dip-filtered Direct Primary Ghost

1st-CSG Time (sec.) Offset (m) Shot Gather Crosscorrelogram Pseudo-Shot Gather D G High-order Ghost

Crosscorrelation migration image Offset (m) Depth (m) True Reflectors

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

Exxon’s Friendswood RVSP Data Depth (m) 100 ReflectivityWell-log CCM

Exxon’s Friendswood RVSP Data Offset (m) Depth (m) CCM image

Outline ObjectiveObjective Crosscorrelation migrationCrosscorrelation migration Numerical examplesNumerical examples SummarySummary

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.

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.

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