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Seismic signal completion method based on synchronous sparse low-rank tensor completion model

A seismic signal and completion technology, applied in seismic signal processing, seismology, measurement devices, etc., to achieve accurate and efficient recovery, improve sparsity and low rank

Active Publication Date: 2020-06-30
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0017] The main purpose of the present invention is to provide a seismic signal completion method based on a synchronous sparse low-rank tensor completion model, aiming to solve the above technical problems existing in existing methods

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  • Seismic signal completion method based on synchronous sparse low-rank tensor completion model
  • Seismic signal completion method based on synchronous sparse low-rank tensor completion model
  • Seismic signal completion method based on synchronous sparse low-rank tensor completion model

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Embodiment Construction

[0067] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

[0068] The present invention first describes the tensor completion problem in the field:

[0069] Given a linear measurement result vector of length M y=R M There is the following linear mapping relationship: y m =m >=(vec(A m )) T ,vec(X),1≤m≤M, where Is an unknown tensor with tubal-rank r, Is the perceptual tensor, and then define a linear mapping operator Then the tensor perception problem can be described as: looking for a tensor Make it satisfy y=H(X), and minimize the tubal-rank of tensor X. The problem of tensor completion is to complete the missing part of the tensor by observing a sm...

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Abstract

The invention discloses a seismic signal completion method based on a synchronous sparse low-rank tensor completion model. The method includes preprocessing four-dimensional earthquakes, establishing a tensor completion model, and adopting a truncated tensor kernel norm regularization method The objective function of the tensor completion model is constructed, and the objective function of the constructed tensor completion model is solved by using the non-exact augmented Lagrangian multiplier method. The invention transforms the tensor to be restored into the Curvelet transform domain by establishing a tensor model based on the transform domain to improve its sparsity and low rank, and combines the ADMM algorithm to realize accurate and efficient recovery of four-dimensional missing seismic data.

Description

Technical field [0001] The invention belongs to the technical field of seismic data reconstruction, and specifically relates to a seismic signal completion method based on a synchronous sparse low-rank tensor completion model. Background technique [0002] As we enter the 21st century, the global economy has entered a new period of development, and all walks of life have increasingly strong demand for energy. However, new energy has not been able to replace the core position of oil and natural gas in the energy system. With the rapid development of the global economy, all countries are heavily dependent on oil and natural gas, and their demand is increasing. The domestic consumption of oil and natural gas, a resource related to people's livelihood, has reached hundreds of millions of tons. [0003] Although our country has a large land area, compared with the Middle East, our country is not in the oil belt. Only parts of Tibet are on the tail of the global oil belt. This has result...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01V1/28G01V1/30
CPCG01V1/28G01V1/282G01V1/30
Inventor 钱峰张仓仓胡光岷
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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