Seismic data compression and reconstruction method

Abstract

The invention relates to a seismic data compression and reconstruction method. The seismic data compression and reconstruction method comprises the following steps: firstly, carrying out wavelet transformation on seismic data to increase the compressibility of the seismic data; secondly, constructing a measurement matrix capable of being realized by hardware according to a chaos sequence; carryingout compression observation on the seismic data subjected to the wavelet transformation by utilizing a chaotic measurement matrix; finally, improving a Bayesian wavelet tree structure compressed sensing reconstruction algorithm; recovering complete seismic data by utilizing an improved BTSWCS-vb algorithm. According to the seismic data compression and reconstruction method, the result of an actual data test shows that compared with a common random measurement matrix, the chaotic measurement matrix is convenient to be realized by the hardware; a plurality of chaotic measurement matrixes are adopted so that real-time compression with the seismic data compression ratio of 0.2 to 0.55 can be realized and the influence, caused by the chaos measurement matrixes, especially a Logistic sequence matrix, on a reconstruction effect, is also very good; the improved reconstruction algorithm, namely the BTSWCS-vb algorithm, is adopted so that the reconstruction precision is improved and the reconstruction time is remarkably shortened.

Description

technical field [0001] The invention relates to a seismic data processing method, in particular to a seismic data compression and reconstruction method based on an improved Bayesian compressed sensing algorithm. Background technique [0002] The real-time recovery of massive data in the process of geological exploration has brought great challenges to existing seismographs, which is also the most important factor restricting the development of seismographs. In particular, with the continuous deepening of seismic exploration, the seismic exploration data continues to expand, which puts great pressure on the sampling and wireless transmission speed of the seismograph, the storage capacity of the memory, and the processing speed of the computer. Through the key technology of compressed sensing theory, the seismic data is compressed in the lower computer in real time, and the data is transmitted to the upper computer. When seismic data interpretation is required, the upper compu...

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Problems solved by technology

[0006] Although the above existing technologies can be used for seismic data compression and reconstruction, the compression factor in common compression algorithms is at the cost of loss of signal accuracy, and the degree of data compression directly affects the reconstruction effect, and the demands of real-time compression and high-precision reconstruction cannot be simultaneously Satisfy

And in view of the fact that the compression process pays more attention to real-time performance and the reconstruction process pays more attention to accuracy, the common compression and reconstruction algorithms cannot meet the real-time compression of seismic exploration systems and the demand for high-precision reconstruction of original data

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