Seismic fault enhancement method based on Ho-RPCA

A fault and ho-rpca technology, applied in the field of geophysical exploration, can solve problems such as poor continuity of faults, poor visibility, and low lateral resolution of faults

Inactive Publication Date: 2019-03-15
CHINA PETROLEUM & CHEM CORP +1
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Problems solved by technology

After the coherence calculation is performed on the original amplitude data volume, the SNR of the coherent volume obtained is still low, which reflects the low lateral resolution, poor visibility and poor continuity of the faults on the coherent slice.
For such a coherent body, whether it is manual interpretation or automatic interpretation of faults, it is very difficult

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  • Seismic fault enhancement method based on Ho-RPCA
  • Seismic fault enhancement method based on Ho-RPCA
  • Seismic fault enhancement method based on Ho-RPCA

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Embodiment Construction

[0063] In step 101, the input 3D coherent volume data is preprocessed, and the low-rank fault part and the sparse noise part are separated. Robust Principal Component Analysis (RPCA) is an extension of the compressive sensing theory on the matrix. The mathematical model of RPCA can be expressed as,

[0064] D=A+E (1-1)

[0065] If the coherent volume image is represented by D, since the fault is a regular planar structure in the coherent volume data, it corresponds to the low-rank part A. The noise components in the coherent body are more complex, which mainly includes Gaussian noise and coherent noise. Here is a brief description of coherent noise: its formation is related to the acquisition of seismic data and the pre-processing of data; coherent noise is often distributed near the fault plane in flocculent form, and its image gray value is lower than that of the fault image value; compared with Gaussian noise, the distribution of coherent noise is regular. Gaussian noise...

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Abstract

The invention provides a seismic fault enhancement method based on Ho-RPCA, which comprises the following steps of: 1, preprocessing input three-dimensional coherent volume data, and separating a low-rank fault part from a sparse noise part; 2, constructing an objective function based on Ho-RPCA; 3, solving the optimization problem through an alternating direction multiplier algorithm frame; 4, minimizing a tensor kernel norm, and using a kernel norm approximate solution based on tensor random singular value decomposition. The method enhances a coherent body from the angle of a tensor model, protects the high-dimensional characteristics of a coherent attribute body better, can better remove noise, improves the enhanced fault continuity, and can better enhance the fault information in the coherent body, and the overall effect is relatively ideal.

Description

technical field [0001] The invention relates to the technical field of geophysical prospecting, in particular to a Ho-RPCA-based seismic fault enhancement method. Background technique [0002] Seismic data collected by seismic exploration are usually three-dimensional or four-dimensional data volumes. Seismic data The data is composed of multiple seismic reflection waves corresponding to the surface coordinates of the work area, and each waveform will produce different waveform amplitudes due to the difference in geological characteristics of the reflection layer. Seismic data can provide sufficient physical basis for geological analysis and interpretation. The texture attribute extraction method of seismic data is an important means of seismic data interpretation. Among the many texture attribute extraction methods, the most representative is the coherent volume algorithm, which can identify faults by highlighting discontinuities in seismic data, thereby improving the eff...

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Application Information

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IPC IPC(8): G01V1/28G01V1/30
CPCG01V1/282G01V1/30
Inventor 宋明水王金铎王千军张曰静马波石好果徐佑德商丰凯陈林袁青
Owner CHINA PETROLEUM & CHEM CORP
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