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Shearlet transformation-based seismic data reconstruction method

A seismic data, sparse transformation technology, applied in the field of exploration geophysics, can solve the problems of poor data reconstruction effect, low computational efficiency, missing data reconstruction, etc., and achieve good data reconstruction effect.

Inactive Publication Date: 2017-04-26
CHINA UNIV OF PETROLEUM (EAST CHINA)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These methods use the knowledge of multi-scale geometric analysis and can use the geometric features of the image to reconstruct missing data, but they have the disadvantages of low computational efficiency and poor reconstruction effect on some data.

Method used

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  • Shearlet transformation-based seismic data reconstruction method
  • Shearlet transformation-based seismic data reconstruction method
  • Shearlet transformation-based seismic data reconstruction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0028] Example 1 (Specific reconstruction of seismic simulation observation data with a missing degree of 20%).

[0029] Such as figure 1 As shown, a seismic data reconstruction method based on Shearlet transform includes the following steps:

[0030] Step 1. Input the observed seismic data, select the seismic data to be reconstructed, and analyze the characteristics of the seismic data;

[0031] Step 2: Establish the corresponding measurement matrix M and sampling matrix R according to the observed seismic data y. The measurement matrix M is the basis corresponding to the occurrence of data measurement. It samples the complete data to obtain data with missing channels, so that the sampling point is The seismic data of the data remains unchanged, and the seismic data at non-sampling points is empty. Perform shearlet transformation on the observed seismic data y to obtain the sparse transformation matrix S T =a,s,t > , Where the shear wave function ψ a,s,t =a -3 / 4 ψ(D -1 B -1 ), a∈R...

Embodiment 2

[0046] Embodiment 2 is the specific reconstruction of the seismic simulation observation data with a 50% missing degree.

[0047] See Example 1 for specific reconstruction steps.

Embodiment 3

[0048] Embodiment 3 is the specific reconstruction of noisy seismic simulation observation data with missing parts.

[0049] See Example 1 for specific reconstruction steps.

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Abstract

The invention provides a Shearlet transformation-based seismic data reconstruction method. According to the method, data comprising missing seismic traces can be reconstructed based on Shearlet transformation and sparse signal theories. Observation data is input, positions of the missing traces are analyzed, and a sampling matrix of the data is obtained; a measurement matrix and a Shearlet transformation matrix are determined; a model matrix is obtained based on the measurement matrix, the sampling matrix and the Shearlet transformation matrix; a most sparse solution is obtained based on a sparse promotion inversion algorithm; reverse sparse transformation is carried out, and reconstructed seismic data is obtained; the reconstructed seismic data is output and saved. Random missing data can be effectively recovered via the Shearlet transformation-based seismic data reconstruction method, complete and regular reconstructed data can be obtained, and strong technical support can be provided for subsequent seismic data processing and interpretation.

Description

Technical field [0001] The invention relates to the field of exploration geophysics, in particular to a seismic data reconstruction method based on Shearlet transformation. Background technique [0002] The integrity and regularity of seismic data have a significant impact on the later data processing and interpretation. However, in actual field collection, the data is often incomplete and irregular due to the influence of restrictive factors such as irregular terrain, building occlusion and economic benefits. Therefore, how to effectively improve the accuracy of data processing results through reconstruction, so as to meet the production needs, makes the seismic data reconstruction method a very important part of seismic data processing. Due to the need for data integrity and regularity, many different seismic data reconstruction methods have been proposed. Such as missing built-in zero-value channels, transplanting adjacent seismic channels, and ignoring missing sampling poin...

Claims

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Application Information

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IPC IPC(8): G01V1/28
CPCG01V1/28
Inventor 唐杰孙成禹王浩
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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