石油物探2017，Vol.56Issue(6)：890-897,8.DOI:10.3969/j.issn.1000-1441.2017.06.015
一种改进的独立分量分析算法在大地电磁去噪中的应用
The application of an improved independent component analysis algorithm in magnetotelluric data denoising
摘要
Abstract
Combined with the wavelet analysis theory and blind source separation,an improved independent component analysis algorithm for magnetotelluric data denoising is proposed,which is based on the M-FastICA algorithm,an improvement on the FastICA algorithm.First,the multi-scale wavelet decomposition is performed to convert the observed signal from single channel to multiple channels,to meet the quantity demand of the independent component analysis.Then,the M-FastICA algorithm is adopted to process the multi-layer high frequency components extracted by wavelet decomposition.This process extracts the effective independent components and specific independent components.Then,the dynamic adaptive factor is introduced to limit the weight of the specific independent components and reduce the SNR influence in the observed data on the denoising process.Finally,the low frequency components of the wavelet and two types of independent components extracted using the M-FastICA algorithm together constitute the recovery signal.Simulation test results on an analog signal show that the denoising performance of the proposed method is better than the traditional wavelet threshold denoising method.The application test on field magnetotelluric observation data shows that both the apparent resistivity and phase curves are smoother and more stable than that before denoising.These results illustrate that the proposed method can effectively remove magnetotelluric noise.关键词
独立分量分析/小波分析/大地电磁/去噪/M-FastICA算法Key words
independent component analysis/wavelet analysis/magnetotelluric/denoising/M-FastICA algorithm分类
天文与地球科学引用本文复制引用
曹小玲,严良俊..一种改进的独立分量分析算法在大地电磁去噪中的应用[J].石油物探,2017,56(6):890-897,8.基金项目
国家自然科学基金(41274082,U1562109)、长江大学长江青年基金(2015cqn76)、长江大学重磁电勘探研究中心创新基金(7011201803xm)联合资助.This research is financially supported by the National Natural Science Foundation of China (Grant Nos.41274082,U1562109),the Yangtze Youth Fund in Yangtze university (Grant No.2015cqn76),and the Innovation Fund of Gravity-magnetic-electric exploration research center in Yangtze university (Grant No.7011201803xm). （41274082,U1562109）
