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Combined denoising method based on curvelet transform and singular value decomposition

A singular value decomposition and curvelet transform technology, applied in the field of exploration geophysics, can solve problems such as poor effect of curved or crossed events, low calculation efficiency, and artifacts

Inactive Publication Date: 2016-02-10
CHINA PETROLEUM & CHEM CORP +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, they more or less have some deficiencies, including incomplete denoising, poor effect on curved or crossed events, artifacts, low calculation efficiency, etc. Each technology has its application limitations, so , it is necessary to study an effective denoising technique

Method used

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  • Combined denoising method based on curvelet transform and singular value decomposition
  • Combined denoising method based on curvelet transform and singular value decomposition
  • Combined denoising method based on curvelet transform and singular value decomposition

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Embodiment 1

[0048] Such as figure 1 as shown, figure 1 It is a flowchart of the joint denoising method based on curvelet transform and singular value decomposition of the present invention. In step 101, a seismic section that needs noise suppression is selected. The process goes to step 102.

[0049] In step 102, denoising processing is performed on the seismic section by using the curvelet transform threshold method. figure 2 It is the schematic diagram of the principle of the curvelet transform based on the joint denoising method of curvelet transform and singular value decomposition of the present invention. When utilizing the curvelet transform threshold method for denoising, the basic relationship of the curvelet transform in the frequency domain is represented by the following formula:

[0050]

[0051] In the formula: c(j,l,k) is the curvelet coefficient, j is the scale parameter, l is the angle parameter, k is the orientation parameter, is the input of the curvelet transfor...

Embodiment 2

[0064] In step 1, the curvelet transform is used to denoise with the threshold method. At this time, the basic relationship of the curvelet transform in the frequency domain is expressed by the following formula:

[0065]

[0066] In the formula: c(j,l,k) is the curvelet coefficient, j is the scale parameter, l is the angle parameter, k is the orientation parameter, f(x) is the input of the curvelet transform, for scale 2 -j , direction θ l , at of Qu Bo.

[0067] In step 1, the main method is as follows: first, perform curvelet forward transformation on the two-dimensional actual seismic records, transform it into the curvelet domain, and obtain multiple corresponding curvelet coefficients; then perform threshold processing on these curvelet coefficients, The curvelet coefficient greater than the threshold is regarded as the threshold corresponding to the effective signal, and is retained, and the curvelet coefficient smaller than the threshold is regarded as the curv...

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Abstract

The invention provides a seismic data combined denoising method based on curvelet transform and singular value decomposition. The combined denoising method based on curvelet transform and singular value decomposition comprises carrying out direction control and noise variance reduction through curvelet transform; partially flattening lineups through improved singular value decomposition, sequentially processing each data point and carrying out effective suppression on the noise of the whole seismic section; and combining the curvelet transform and singular value decomposition through quadtree decomposition. The technique, combined with good denoising effect of singular value decomposition and anisotropy and multi-scale characteristics of curvelet transform, can improve the signal to noise ratio of the seismic data, protect the effective signals while suppressing the random noise, can effectively remove image artifacts, and keep dynamical features of the seismic wave, and is an effective noise suppression technique.

Description

technical field [0001] The invention relates to the field of exploration geophysics, in particular to a joint denoising method based on curvelet transform and singular value decomposition in seismic data processing. Background technique [0002] In seismic data processing, denoising processing is a very critical link. The quality of denoising effect determines the quality of migration, stacking, and imaging, which in turn affects the subsequent seismic data inversion and interpretation. According to the different properties of noise, noise can be divided into two types: random noise and coherent noise. Currently commonly used seismic data denoising techniques include f-x predictive filtering, K-L transform, tau-p transform, coherence enhancement, polynomial fitting technology, singular value decomposition, curvelet transform, wavelet transform, etc. Various denoising techniques are used in actual data processing It has played a pivotal role and achieved good application res...

Claims

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Application Information

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IPC IPC(8): G01V1/36G01V1/32G01V1/28
Inventor 韩文功李红梅孙成禹冯德永张之涵梁鸿贤姚永强
Owner CHINA PETROLEUM & CHEM CORP
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