Customized CRS regularization strategies for improved migration results

Common-Reflector-Surface processing (CRS) generally improves the signal-to-noise ratio of a data set. In addition, it is the best available algorithm to regularize data in any domain such as shot-receiver or azimuth/offset domain. In seismic data processing, there are multiple prestack migration algorithms around which may require input data optimized in both, data quality and spatial sampling depending on the selected migration approach. CRS processing can help in both, improving the overall input data quality as well as its sampling in order to reduce migration artefacts and thus improve the seismic image. This is demonstrated at both, a Kirchhoff migration and a Reverse Time Migration (RTM). Kirchhoff migration usually operates in the offset domain and for that reason shows less artefacts if a fully offset regularized data set is input. In this particular example, the data was separated into six azimuth classes which were independently offset regularized by CRS in order to better image faults according to their orientation. The azimuth/offset regularized data was then prestack migrated for each azimuth class. An RTM requires shot gather input. Here, we use a shot-receiver regularization to both, improve the signal-to-noise ratio, and suppress migration artefacts at locations with decreased shot-receiver coverage.