Structure Preserving Regularization for Multitrace Sparse Deconvolution

Abstract

Summary In reflectivity inversion problems, due to complicated structures and low signal-to-noise ratio (SNR) of input seismic traces, the conventional sparse deconvolution method is normally not able to provide the results that can clearly characterize the geology structure. One of the reasons is that the inversion process is performed on a trace-by-trace basis, and as a result the continuity along reflectors in seismic images may be deteriorated. In this paper, we develop a multichannel algorithm to perform this inversion process, where a multichannel precondition filter is incorporated into the conventional sparse deconvolution method and the information of adjacent traces is applied during the inversion process. Numerical experiments have verified the validity and feasibility of this method by field data, showing that the reflectivity profiles obtained using the proposed method can have an improved lateral continuity and clearer structure.