Combination of the common reflection surface-based prestack data regularization and reverse time migration: Application to real land data

Abstract

The application of reverse time migration (RTM) to land seismic data is still a great challenge due to its low quality, low signal-to-noise ratio, irregular spatial sampling, acquisition gaps, and missing traces. Therefore, prior to the application of this kind of depth migration, the input prestack data must be judiciously preconditioned; that is, it must be interpolated, regularized, and enhanced. There are several Fourier-based methods for seismic data preconditioning, but for 2D real land data, as we will show, the regularization of prestack data based on the common reflection surface (CRS) method provides high-quality enhanced preconditioned data, which is suitable for prestack depth migration and velocity model building. We have determined the successful application of RTM to onshore seismic data, revealing the great potential of combining RTM and CRS-based prestack data regularization. We apply this processing combination to real land data with low quality and irregular spatial sampling, from geologically complex areas with the presence of diabase sills and steeply dipping reflectors. Normally, it is very difficult to extract the wavelet of the seismic source from this type of low-quality onshore data because the reflection events are hidden or mixed with noise, and, because of this, RTM migration is often applied using artificial sources (e.g., a Ricker wavelet), which can introduce ringy side lobes in the reflectors. Therefore, we develop a practical algorithm for wavelet determination from the power spectrum of the CRS regularized prestack data, and we apply it successfully in the RTM migration. We develop applications of our prestack data preconditioning based on CRS followed by RTM for two 2D onshore seismic lines from the Tacutu and Parnaiba basins, Brazil. Comparisons with standard Kirchhoff depth migration reveal that the combination of CRS followed by wavelet extraction and then RTM improves the quality and resolution of the final migrated images.