Structure-adapted Multichannel Matching Pursuit for Seismic Trace Decomposition

Abstract

While the single-channel matching pursuit decomposes a seismic trace into a series of wavelets, the multichannel matching pursuit examines the lateral coherence of the seismic traces as a constraint to improve the lateral continuity of the decomposition. However, the presence of structures in the subsurface negatively affects the performance of the multichannel matching pursuit. We proposed a structure-adapted matching pursuit method that combines with a dynamic time-warping (DTW) algorithm to estimate the similarity between adjacent seismic traces and extract an optimal wavelet along the dip plane. This structure-adapted implementation would significantly speed up the convergence of the decomposition process. We modified the DTW algorithm by combining the Euclidean distance of the seismic trace and the first-order temporal derivative of the seismic trace. We also updated the amplitudes of all extracted wavelets simultaneously based on the least-squares principle. This DTW-based, structure-adapted, least-squares, multichannel matching pursuit method would improve the robustness and accuracy of seismic trace decomposition.