Abstract:

Seismic data from piedmont areas typically suffers from low signal-to-noise ratio (SNR), making it challenging to pick residual velocity fields and causing difficulties in iterative convergence of the depth domain velocity field to its optimal value. All these factors impede accurate migration and imaging of the seismic data from piedmont areas. By using the interpolation techniques in five-dimensional data regularization, the data from the original common midpoint (CMP) gathers prior to migration were reconstructed. By altering observation system, the bin attributes were enhanced to improve the SNR of the seismic data for iterative inversion of the pre-stack depth migration (PSDM) velocity field. To ensure the fidelity of the migrated data, the high-SNR CMP gathers obtained from data interpolation were used solely as inputs for the iterative inversion of the depth domain velocity field, while the original CMP gathers were preserved for the final PSDM imaging. This method enables fast and accurate iterative convergence of the depth domain velocity field. The actual application demonstrates that the method is highly feasible, and yields accurate final migrated velocity field through iterative updates and well-aligned reflections of migrated seismic profiles. This method provides a valuable reference for PSDM velocity modeling in the piedmont areas.

Key words: piedmont, seismic data processing, five-dimensional data regularization, data interpolation, CMP gather, depth domain velocity inversion, PSDM