Seismic Denoising Based on the Modified Particle Swarm Optimization-Independent Component Analysis
详细信息
- 责任者：Zhang Yinxue (College of Information and Control Engineering ; China University of Petroleum (East China) ; Qingdao 266580 ; China) ; Tian Xuemin
- 刊名：Oil Geophysical Prospecting
- 出版年：2012
- 卷期：47(1)
- 关键词：地震勘探 ; seismic exploration
- 页码：p.56-62
- 图表：4 illus., 1 table, 20 refs.
- 分类号：1600
- issnNo：ISSN1000-7210
- isbnNo：CN13-1095/TE
摘要
A modified independent component analysis(ICA) approach based on the chaos particle swarm optimization(PSO) is proposed in this paper in order to improve prestack seismic denoising on the basis of the fixed step size ICA.This method utilizes the chaos PSO algorithm to adjust the step size function of relative gradient ICA,and it can reduce the residual error of ICA.On the other hand,a nonli-nearly decreasing inertia weight(NDIW) is proposed to improve the capability of global and local search of PSO.The trial results for synthetic and shot gather data show that the proposed ICA method works pretty well on removing random noise with very little seismic signal loses compared to other approaches.In addition,the proposed method can obtain high signal-to-noise ratio(SNR) data.
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