Optimal wavelet basis selection method for wavelet threshold denoising of pre-stack seismic data

Abstract

The invention discloses an optimal wavelet basis selection method for wavelet threshold denoising of pre-stack seismic data, which selects an optimal wavelet basis by comparing the local similarity of pre-stack seismic data and a wavelet basis function, and comprises the following steps that well bypass seismic wavelets are extracted, and a wave impedance curve is obtained by means of logging information; a reflection coefficient sequence is obtained through the wave impedance curve, well bypass seismic records are synthesized through convolution of the reflection coefficient sequence and the well bypass seismic wavelets, and then the correlation coefficient of the synthesized well bypass seismic records and the wavelet basis function is calculated to select the optimal wavelet basis. According to the method, the optimal wavelet basis is selected by comparing the local similarity of the synthetic seismic record and the wavelet basis function, the influence of a threshold function and a decomposition scale is eliminated, and only one single variable exists. According to the technical scheme, only well bypass seismic channel data and conventional logging data are needed, and the method has the advantages of being simple, convenient and accurate.

Description

technical field [0001] The present application relates to the technical field of seismic data processing, in particular to a method for selecting an optimal wavelet base for pre-stack seismic data wavelet threshold denoising. Background technique [0002] Pre-stack seismic data contain rich geological information, but the actually collected pre-stack seismic data usually contain a lot of noise. The existence of these noises seriously affects the signal-to-noise ratio of seismic data and the accuracy of seismic data processing and interpretation. Wavelet threshold is a transform developed from Fourier transform to obtain detailed information in time domain. It has the characteristics of multi-resolution and multi-scale, and has natural advantages in the field of signal processing. Wavelet threshold is to separate multiple sub-band signals from seismic records containing noise, set the coefficients of sub-band signals whose main component is noise to zero, and retain and enha...

AI Technical Summary

Problems solved by technology

Based on this method to select the optimal wavelet base, without considering the influence of the threshold function and decomposition scale, and not following the principle of single variable, it is difficult to select the real optimal wavelet base

In addition, due to the huge amount of pre-stack seismic data information, the above-mentioned optimal wavelet base selection method has a huge amount of calculation, which requires a lot of computer time, labor and time.

Images