Real-time compression and high-precision reconstruction method of seismic data in wavelet domain based on compressive sensing

Abstract

The invention relates to a wavelet domain seismic data real-time compression and high-precision reconstruction method based on compressed sensing. The wavelet domain seismic data real-time compression and high-precision reconstruction method comprises the steps of: firstly, carrying out sparse representation on a microseismic signal in a wavelet domain; secondly, constructing a chaos Bernoulli measurement matrix (CBMM) by utilizing a Logistic chaotic sequence, and performing compressed observation on the sparsely-represented microseismic signal by using the chaos Bernoulli measurement matrix; and finally, adopting a Bayesian wavelet tree structure tree structure reconstruction method (BTSWCS), and recovering complete original data. Actual contrast experimental results show that the compression time can be shortened to 10<-5> s by using the wavelet domain seismic data real-time compression and high-precision reconstruction method for compressing data with total sampling points being 2<8>, that is, if a sampling rate of a seismometer is 1 KSPS, the CBMM measurement matrix can realize real-time compression on the acquired 0.25 s data basically. The wavelet domain seismic data real-time compression and high-precision reconstruction method increases a PSNR value by at least 5 dB, significantly improves the peak signal to noise ratio when compared with the greedy algorithm, and reduces reconstruction errors.

Description

technical field [0001] The invention relates to a processing method of microseismic data, in particular to a method for real-time compression and high-precision reconstruction of seismic data in wavelet domain based on compressed sensing. Background technique [0002] Real-time data transmission is the most important factor restricting the development of cable-free storage seismographs. With the continuous deepening of seismic exploration, seismic exploration is developing in the direction of multi-dimensional, multi-component and high-resolution, which makes the seismic exploration data continue to expand, and the sampling and wireless transmission speed of the cable-free seismograph, the storage capacity of the memory and the processing of the computer Speed ​​creates extreme stress. Through reasonable compression processing of seismic data, the real-time processing speed can be improved, and the performance of wireless communication data transmission of seismographs can ...

AI Technical Summary

Problems solved by technology

[0006] Although the above existing technologies can be used for compression and reconstruction of microseismic signals, due to the particularity of geophysical data, it is required to keep the original appearance of the data as much as possible during data acquisition. However, these data compression methods cannot be used in the data acquisition stage. Data is operated, but one or a small number of sampled data cannot be processed, and the data stream cannot be compressed in real time, and decoding is purely an inverse operation of encoding. The compression factor is at the cost of losing signal accuracy, and it is impossible to reduce the compression ratio at the same time. , to reduce the reconstruction error

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