Ideal seismic spectrum decomposition method based on variable phase ricker wavelet matching tracking

Abstract

The invention discloses an ideal seismic spectrum decomposition method based on variable phase ricker wavelet matching tracking. The method comprises the following steps of firstly, constructing a variable phase ricker wavelet library; then, according to a matching tracking method, calculating a matching wavelet and a corresponding amplitude coefficient, and multiplying the amplitude coefficient by a wavelet atom and taking as a sub-signal obtained through decomposition; and then, carrying out Fourier transform on the sub-signal corresponding to a single reflection interface, calculating the amplitude spectrum and the rotational phase spectrum of an interface reflection seismic wave, and placing a Fourier transform spectrum at corresponding delay time; and finally, acquiring an ideal timefrequency spectrum decomposition result. The time-frequency decomposition result comprises the two parts of an amplitude spectrum and a rotational phase spectrum, and the rotational phase spectrum canprovide richer geological and reservoir information. The amplitude spectrum decomposition result accurately reflects the delay time of a seismic wavelet arriving at an interface and energy distribution along with a frequency change, is not limited by a uncertainty principle limit, has a super high time resolution and a frequency resolution and is an ideal time-frequency spectrum for a seismic signal.

Description

technical field [0001] The invention belongs to the field of oil and gas geophysical exploration, and in particular relates to an ideal ground spectrum decomposition method based on phase-variable Lake wavelet matching and tracking. Background technique [0002] Seismic spectral decomposition technology converts the time-domain seismic signals to the time-frequency domain for analysis, and can obtain richer stratigraphic information from seismic data. It has been widely used in determining the thickness of strata, interpreting sedimentary facies, and detecting oil and gas. [0003] Common seismic spectrum decomposition methods mainly include linear time-frequency analysis, bilinear time-frequency analysis and adaptive time-frequency analysis. The linear time-frequency analysis method is the kernel function decomposition method, which uses the window function to realize the time-frequency locality of the signal, mainly including short-time Fourier transform (STFT), continuous...

AI Technical Summary

Problems solved by technology

However, compared with the actual seismic wavelet, the redundancy of the zero-phase Lake wavelet library is poor, and it is necessary to construct a variable-phase Lake wavelet

At the same time, in the actual seismic records, there are not only linear phase changes caused by time delay, but also phase rotation caused by thin layers, velocity dispersion and energy attenuation, while conventional matching tracking (whether zero-phase or non-zero-phase radar Gramlets, real or complex domain matching pursuits) do not consider the rotational phase spectrum separately

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