Wigner higher-order spectrum seismic signal spectral decomposition method based on matching pursuit

Abstract

Provided is a Wigner higher-order spectrum seismic signal spectral decomposition method based on matching pursuit. The method is characterized by, to begin with, reading a seismic section and selecting the atom type; then, selecting seismic data; carrying out complex seismic trace analysis of the signal and carrying out global search on the scale factor to determine an initial parameter set of atoms; carrying out local search on the parameter set to find out the atom most matched with the signal; calculating the diagonal slice spectrum of the Wigner higher-order spectrum of the most matched atom; calculating the residual error of the signal projected in the direction of the most matched atom, and taking the residual error as a new decomposition signal; and carrying out summation on the diagonal slice spectrums of the Wigner higher-order spectrums of the atoms obtained through decomposition, taking the sum as Wigner higher-order spectrum time-frequency spectrum of the seismic data, and cutting a single frequency slice; and obtaining spectral decomposition result by carrying out the same method on all seismic data. The cross terms of the Wigner higher-order spectrum are removed by utilizing the matching pursuit method, so that the earthquake spectral decomposition result having higher time-frequency aggregativeness can be obtained; and the method can provide more accurate information for the follow-up seismic reservoir prediction and fluid identification.

Description

technical field [0001] The invention belongs to the field of non-stationary signal time-frequency analysis and seismic signal processing, and in particular relates to a Wigner high-order spectrum seismic signal spectrum decomposition method based on matching pursuit. Background technique [0002] Spectral decomposition is a seismic signal interpretation technique that decomposes seismic data into the time-frequency domain, thereby revealing that the time-frequency domain contains useful hydrocarbon-bearing information. Several studies have demonstrated the utility of this method for reservoir interpretation and prediction, such as reservoir thickness estimation, stratigraphic interpretation, and fluid identification. Traditional spectral decomposition methods, such as short-time Fourier transform, calculate the time-frequency distribution of signals by introducing window functions, so the time-frequency resolution is limited by the corresponding window functions, which canno...

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Problems solved by technology

However, the Wigner higher-order spectrum also has the same problem of cross-interference terms as WVD

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