基于优化聚类的人工源电磁法数据信噪分离方法  

Noise separation of CSEM data based on improved clustering method

作　　者：胡艳芳 刘子杰[2,3] 李帝铨[2,3] 张贤[2,3] 索光运 HU YanFang;LIU ZiJie;LI DiQuan;ZHANG Xian;SUO GuangYun(School of Microelectronics and Physics,Hunan University of Technology and Business,Changsha 410205,China;Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University),Ministry of Education,Changsha 410083,China;School of Geosciences and Info-Physics,Central South University,Changsha 410083,China)

机构地区：[1]湖南工商大学微电子与物理学院,长沙410205 [2]有色金属成矿预测与地质环境监测教育部重点实验室(中南大学),长沙410083 [3]中南大学地球科学与信息物理学院,长沙410083

出　　处：《地球物理学报》2024年第1期394-408,共15页Chinese Journal of Geophysics

基　　金：国家重点研发计划(2018YFC0807802);国家自然科学基金面上项目(41874081);湖南省教育厅科学研究重点项目(22A0457);湖南省自然科学基金青年基金项目(2023JJ40222);有色金属成矿预测与地质环境监测教育部重点实验室(中南大学)开放基金项目(2022YSJS05);中南大学研究生自主探索创新项目(2022ZZTS0306)资助。

摘　　要：为了降低强电磁干扰对人工源电磁法(Controlled Source Electromagnetic Method,CSEM)有效信号的影响,改善CSEM实测数据处理结果因人而异且效率低的不足,本文针对CSEM有效信号周期性特征提出了一种加权自适应带宽均值漂移聚类(Weighted Adaptive Bandwidth Mean-Shift Clustering,WAB-MSC)信噪分离方法.首先在传统均值漂移聚类(Mean-Shift Clustering,MSC)算法的基础上增加核函数,降低处理结果对带宽选择的敏感度,提高算法的稳健性;其次结合实测CSEM数据的分布特征提出了一种基于局部密度梯度的带宽估计方法,实现了自适应带宽选择;最后通过仿真数据与实测数据对本文方法进行了验证,结果表明:本文方法能有效消除强电磁干扰对CSEM数据的影响,最大程度保留受噪声影响较小或未受噪声影响的数据,提高数据信噪比,降低强干扰噪声对CSEM初始资料的影响程度,获得更为真实的地电响应模型,为后续数据处理提供保障.In this paper,to reduce human factors and improve inefficiencies in Controlled Source Electromagnetic Method(CSEM) data processing,we present a noise separation method based on the Weighted Adaptive Bandwidth Mean-Shift Clustering(WAB-MSC) to suppress the strong electromagnetic interference in CSEM.Firstly,the kernel function is added to the traditional Mean-Shift Clustering(MSC) algorithm to reduce the sensitivity of the bandwidth selection,which can improve the robustness of the algorithm.Then,with the distribution characteristics of measured CSEM data,we proposed a bandwidth estimation method based on local density gradient to realize adaptive bandwidth selection.Finally,to verify our proposed method,the simulation signals composited by different noise types and pseudo-random signals are tested.Results show that our proposed method can effectively suppress the strong electromagnetic interference on CSEM data,which maximizes the retention of valid data and improves the signal-to-noise ratio of the data.Moreover,once the influence of strong interference noise on CSEM raw data has been effectively reduced,the apparent resistivity curves become smooth and continuous.The processing results provide a guarantee for obtaining a real geoelectric response model and subsequent data processing.

关 键 词：人工源电磁法 强电磁干扰 信噪分离 自适应 聚类算法 

分 类 号：P631[天文地球—地质矿产勘探]