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Self-adaption curvelet threshold value earthquake denoising method based on local variance analysis

A local variance and self-adaptive technology, applied in the field of petroleum exploration, can solve the problem of losing effective information, etc., and achieve the effect of better denoising ability and authentic denoising ability

Inactive Publication Date: 2014-04-09
CHINA UNIV OF PETROLEUM (BEIJING)
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Problems solved by technology

This method ignores the different characteristics of the curvelet coefficients at different scales, and processing with the same threshold will inevitably lose effective information

Method used

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  • Self-adaption curvelet threshold value earthquake denoising method based on local variance analysis
  • Self-adaption curvelet threshold value earthquake denoising method based on local variance analysis
  • Self-adaption curvelet threshold value earthquake denoising method based on local variance analysis

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Embodiment 1

[0052] An adaptive curvelet threshold seismic denoising method based on local analysis of variance, comprising the following steps:

[0053] Step 1: Perform curvelet transform on seismic data to obtain curvelet transform coefficients;

[0054] Step 2: Use the standard deviation of the curvelet coefficient at the finest scale to determine the standard deviation of random noise in the time domain, and calculate the standard deviation of noise at each scale and angle in the curvelet domain;

[0055] Step 3: Use the noise standard deviation of the noisy signal at each scale and angle, combined with local variance analysis, to calculate the standard deviation of the effective signal;

[0056] Step 4: Use the standard deviation of the noise obtained above and the effective signal to establish a threshold and perform soft threshold processing;

[0057] Step 5: Perform curvelet inverse transformation to obtain the denoising result in the time domain.

[0058] Further, the curvelet t...

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Abstract

The invention provides a self-adaption curvelet threshold value earthquake denoising method based on local variance analysis. According to the method, on the basis that deep analysis is conducted on the characteristics of a curvelet coefficient on different scales and at different angles, a self-adaption threshold value technology is provided so that effective separation of a signal and noise can be achieved at any angle, protection conducted on non-noise components is enhanced with the help of local variance information of a curvelet area, and therefore damage to the effective signal especially the weak signal can be reduced. Practices on synthetic seismogram and land seismic data prove that the actual denoising effect of a threshold value iteration method is not ideal, the denoising effect of the method is more real and effective, and the method has the unique advantages in the aspects of noise attenuation and detail protection.

Description

technical field [0001] The invention belongs to the field of petroleum exploration, in particular to an adaptive curve wave threshold seismic denoising method based on local variance analysis. Background technique [0002] Seismic data denoising runs through the whole process of seismic data acquisition, processing and interpretation, and high signal-to-noise ratio is the primary task of seismic data digital processing. With the development of seismic exploration technology, conventional seismic data denoising methods are increasingly unable to meet the needs of current high-precision exploration. The limitations of traditional denoising technology have prompted the continuous development of seismic data denoising technology, and the content of denoising technology Rich. [0003] Curvelet transform is a directional multi-scale transform, which introduces directional parameters on the basis of wavelet transform, which can provide a more sparse representation for straight lin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/36
Inventor 孙学凯孙赞东
Owner CHINA UNIV OF PETROLEUM (BEIJING)
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