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Sparse sampling method in seismic data regularization

A seismic data, sparse sampling technology, applied in seismic signal processing and other directions, can solve problems such as incompleteness, lack of seismic traces, irregularity, etc.

Inactive Publication Date: 2015-03-18
CHINA PETROLEUM & CHEM CORP +1
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Problems solved by technology

In addition, it is also possible that the original acquisition data itself is incomplete and irregular, lacking seismic traces / shots

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  • Sparse sampling method in seismic data regularization
  • Sparse sampling method in seismic data regularization
  • Sparse sampling method in seismic data regularization

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[0048] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0049] The purpose of the present invention is to design a random sparse acquisition scheme of seismic traces satisfying the Bernoulli distribution aiming at the technical problem of seismic data regularization. This method is used to re-sample the collected seismic data or directly collect a small amount of seismic trace data in the field, and then process the indoor compressed sensing technology to obtain complete seismic data to realize the regularization of seismic data. It provides a way to obtain complete data for areas where regular seismic data cannot be obtained, which can increase the number of stacking and improve the quality of seismic imaging. Collecting only part of the data can also save collection costs.

[0050] The method of the invention is one of the three key technologies that need to be solved by applying the compressed sensing technology to rea...

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Abstract

The invention provides a sparse sampling method in seismic data regularization and belongs to the field of seismic exploration data regularization. The method includes the following steps: (1) obtaining a seismic signal sparse expression: selecting Curvelet conversion as a seismic signal sparse expression; (2) designing a random seismic channel sparse sampling scheme which meets Bernoulli distribution; (3) applying the sampling scheme obtained through step (2) to carry out resampling on original seismic data so that undersampled seismic data which meets a Bernoulli distribution rule is formed; (4) applying a restructuring algorithm to generate complete reconstruction data. Through use of the method, a complete seismic channel reconstruction result can be obtained through fewer seismic channels in a compressed sensing method.

Description

technical field [0001] The invention belongs to the field of regularization of seismic exploration data, and in particular relates to a sparse sampling method in regularization of seismic data. Background technique [0002] Seismic data regularization is an important step in seismic signal processing, and it is also a research hotspot in seismic data processing in recent years. Compressed sensing technology, which has received extensive attention in recent years, has been applied to the regularization of seismic data, which can effectively regularize irregular data volumes. [0003] Compressed sensing (CS for short) theory and technology is a new signal acquisition, encoding and decoding theory between mathematics and information science proposed by American scientists in 2006 based on signal sparsity or compressibility. This theory breaks through the limitation that traditional signal acquisition must satisfy the Shannon / Nyquist sampling theorem, and can reconstruct the or...

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Application Information

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IPC IPC(8): G01V1/28
Inventor 蔡瑞赵群杨丽周中彪
Owner CHINA PETROLEUM & CHEM CORP
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