A data processing method and device for surface wave dispersion curve

Abstract

The invention provides a data processing method and a data processing device for a surface wave dispersion curve. The method comprises the steps of selecting target seismic traces in to-be-processed seismic data in a frequency domain; determining an adjacent seismic trace number threshold and a phase difference threshold of the target seismic traces; totally selecting M adjacent seismic traces in the target seismic traces; respectively calculating phase differences between the M adjacent seismic traces and the target seismic traces at each reference frequency point; determining the number of the seismic traces in which the phase difference on the reference frequency point is larger than the phase difference threshold; and determining whether the corresponding reference frequency point is an added frequency point of the surface wave dispersion curve. By means of the data processing method and the data processing device, the noise part in a frequency-phase-speed frequency dispersion spectrum can be effectively eliminated, thereby effectively improving precision of the surface wave dispersion curve which is obtained from the frequency-phase-speed frequency dispersion spectrum.

Description

technical field [0001] The present application relates to the technical field of seismic data processing, in particular to a data processing method and device for surface wave dispersion curves. Background technique [0002] In seismic data processing technology, inversion of near-surface structure using surface waves is a common technique for stratigraphic structure analysis. The near-surface inversion using surface waves mainly includes two processing stages. The first processing stage is to perform surface wave dispersion analysis and generate surface wave dispersion curves; the second processing stage is to use the generated surface wave dispersion curves to perform Inversion of near-surface structures. Therefore, the accuracy of this inversion processing method depends on the accuracy of surface wave dispersion analysis. Obtaining higher-precision surface wave dispersion curves is the key to improving the accuracy of inversion results. [0003] In the prior art, in o...

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Problems solved by technology

However, during the accumulation process, since the seismic data includes other nonlinear seismic waves besides the linear surface wave, the phase difference between these seismic waves and the phase of the surface wave is relatively large, which will cause the surface wave accumulation result to be distorted. Interference, causing the frequency-phase velocity dispersion spectrum to contain noise parts, thereby reducing the accuracy of the picked-up surface wave dispersion curve

[0004] There are at least the following problems in the prior art: In the prior art, when the seismic data is accumulated, the seismic data contains nonlinear seismic waves, and the phase difference between the nonlinear seismic waves and the surface waves is relatively large, which will cause serious damage to the surface wave accumulation results. Interference, causing the frequency-phase velocity dispersion spectrum to contain noise parts, which in turn leads to low precision of the surface wave dispersion curve picked up from the frequency-phase velocity dispersion spectrum

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