Four‐component surface‐consistent deconvolution

Abstract

When performing four‐component surface‐consistent deconvolution, it is assumed that the decomposition of amplitude spectra into source, receiver, offset, and common‐depth‐point components enables accurate deconvolution filters to be derived. However, relatively little effort has been put into the verification of this assumption. Some verification of the assumption is available by analyzing the results of the surface‐consistent decomposition of real seismic data. The surface‐consistent log‐amplitude spectra of land seismic data are able to provide convincing evidence that the source component collects effects of the source signature and near‐source structural effects, and that the receiver component collects receiver characteristics and near‐receiver structural effects. In addition, the offset component collects effects due to ground roll and average reflectivity, and the CDP component collects mostly random noise unless it is constrained to be smooth. Based on the results of this analysis, deconvolution filters should be constructed from the source and receiver components, while the offset and CDP components are discarded. The four‐component surface‐consistent decomposition can be performed efficiently by making use of a simple rearrangement of the Gauss‐Seidel matrix inversion equations. The algorithm requires just two passes through the prestack data volume, regardless of the sorted order of the data, so it is useful for both two‐dimensional and three‐dimensional (2-D and 3-D) data volumes.