Parallel algorithm of seismic signal frequency compensation based on CUDA

被引：0

作者：

Zhang Q. ^{[1
,2
,3
]}

Zhang J. ^{[1
]}

Lei Q. ^{[1
]}

Peng B. ^{[1
,2
]}

Liu S. ^{[1
,2
]}

机构：

[1] School of Computer Science, Southwest Petroleum University, Chengdu

[2] State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University), Chengdu

[3] School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu

来源：

Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2022年 / 57卷 / 05期

关键词：

Compressed sensing; CUDA; Frequency compensation; Parallel computing;

D O I：

10.13810/j.cnki.issn.1000-7210.2022.05.025

中图分类号：

学科分类号：

摘要：

The frequency compensation algorithm of seismic signals based on compressed sensing can effectively broaden the spectrum of seismic signals and improve the resolution of seismic data. Although the algorithm has a good frequency-broadening effect, it has low time efficiency in the face of high-dimensional and large-scale seismic data. Analysis shows that the bottleneck of the algorithm lies in massive algebraic operations for the reflection coefficient and convolution operations in signal reconstruction. Therefore, a parallel scheme based on CUDA is proposed for parallel optimization of the algorithm. Firstly, the organization form of seismic data is changed to make it more efficient and more suitable for parallel processing. Then, the serial code for computing the reflection coefficient is reconstructed, and a large number of lightweight threads of GPU are called by CUDA to parallelize the algebraic operations. Finally, the convolution calculation method of time-domain signals is changed by the convolution theorem, and the convolution operation of two time-domain signals is converted to the frequency domain by the cufft library function. The results reveal that the parallel algorithm achieves four times the overall speedup of the serial algorithm on the PC side on the premise of ensuring computational accuracy. © 2022, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.

引用

页码：1241 / 1249

页数：8

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