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 multi-channel 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 multi-channel matching pursuit. We proposed a structure-adapted matching pursuit method that uses 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 using the least-squares principle. This DTW-based, structure-adapted, multi-channel, least-squares matching pursuit would improve the robustness and accuracy of the seismic trace decomposition.

Improvement and Application of Hale’s Dynamic Time Warping Algorithm

“…The DTW algorithm is improved by combining the Euclidean distance of the seismic trace with the first time derivative of the seismic trace. Based on the principle of least squares, the amplitudes of all the extracted wavelets are updated synchronously, which improves the robustness and accuracy of seismic trace decomposition [30].…”