Prestack seismic texture analysis method based on gradient co-occurrence matrix

Abstract

The invention discloses a prestack seismic texture analysis method based on a gradient co-occurrence matrix. The method comprises the following steps of S1, acquiring four-dimensional data V to be analyzed from prestack seismic data D; S2, defining a gradient computation direction (formula) and defining a four-dimensional sub-data set (formula); S3, establishing a four-dimensional sub-data set S with the size of T*NI*NC*No by taking a line (:, i, j, k) formed by T sample points in the V as the center, and computing the gradient of each point in the S in sequence in order to obtain a gradient matrix M; and S4, constructing a gradient co-occurrence matrix G based on the gradient matrix, and computing texture feature attributes based on the gradient co-occurrence matrix G. On the basis of a gray level co-occurrence matrix, gradient information is added, and some statistical quantities are extracted from the gradient co-occurrence matrix to reflect the textural features, and the texture analysis method has the advantages that the signal resolution is improved, and the noise influence is reduced.

Description

Technical field [0001] The invention belongs to the technical field of seismic analysis, and particularly relates to a pre-stack seismic texture analysis method based on a gradient co-occurrence matrix. Background technique [0002] After years of development, exploration seismology has become a discipline for detecting underground geological structures and exploring underground resources such as oil, natural gas and shale gas in different regions. First of all, based on the reflection, refraction, and diffraction characteristics of seismic waves on the surface of different media, the land uses the method of shooting or controllable seismic sources to excite seismic waves. Because different geological structures have different effects on the reflection, refraction and diffraction of seismic waves, and the loss of excited seismic waves is different, this makes the seismic waves that eventually return to the ground different. Therefore, the returned seismic waves carry information...

AI Technical Summary

Problems solved by technology

For pre-stack seismic data, the use of gray-level co-occurrence matrix to describe texture features can not improve resolution and reduce the influence of noise

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