重庆大学学报(英文版)2018,Vol.17Issue(4) :162-170.

The improved ICA algorithm and its application in the seismic data denoising

QIN Fei-long LIU Jian YAN Wen-yong
重庆大学学报(英文版)2018,Vol.17Issue(4) :162-170.

The improved ICA algorithm and its application in the seismic data denoising

QIN Fei-long 1LIU Jian 2YAN Wen-yong2
扫码查看

作者信息

  • 1. Department of Information and Computing Science, Chengdu Technological University, Chengdu 611730, P. R. China;College of Mathematics and Science, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
  • 2. School of Materials Engineering, Chengdu Technological University, Chengdu 611730, P. R. China
  • 折叠

Abstract

The field seismic data is disturbed by the interferential information, which has low signal to noise ratio (SNR). That is disadvantage for seismic data interpretation. So it is important to remove the noise of seismic data. Independent component analysis (ICA) can remove most of the noise interference. However, ICA has some defects in noise reduction, because it needs some conditions that seismic data is independent reciprocally for denoising. To solve these defects, this paper proposes an improved ICA algorithm to noise reduction. Through simulation experiments, it can be obtained that the best decomposition levels of the new algorithm is 3. At last, the proposed improved ICA is applied to deal with the actual seismic data. The results show that it can effectively eliminate most of seismic noise such as random noise, linear interference, surface waves, and so on.The improved ICA is not only easy to denoising, but also has excellent mathematical theoretical properties.

Key words

seismic data/improved ICA/wavelet transform/denoising

引用本文复制引用

基金项目

Funded by the Project of China Geological Survey(1212010916040)

Sichuan Science and Technology Program(2017JY0051)

Sichuan Science and Technology Program(2018GZ0200)

出版年

2018
重庆大学学报(英文版)
重庆大学

重庆大学学报(英文版)

影响因子:0.02
ISSN:1671-8224
被引量3
参考文献量1
段落导航相关论文