环境噪声的强低频特征及其压制方法  

Strong low-frequency characteristics of environmental noise and its suppression methods

作　　者：王鹏飞[1] 李国发[1] 熊金良[2] 李皓 左黄金 WANG PengFei;LI GuoFa;XIONG JinLiang;LI Hao;ZUO HuangJin(China University of Petroleum(Beijing),Beijing 102249,China;Dagang Oilfield Company,CNPC,Tianjin 300280,China;University of Electronic Science and Technology of China,Huzhou 313001,China;Research Institute of BEG,CNPC,Zhuozhou 072751,China)

机构地区：[1]中国石油大学(北京),北京102249 [2]中国石油天然气股份有限公司大港油田分公司,天津300280 [3]电子科技大学长三角研究院(湖州),湖州313001 [4]东方地球物理勘探有限责任公司研究院,涿州072751

出　　处：《地球物理学报》2025年第4期1521-1532,共12页Chinese Journal of Geophysics

基　　金：CNPC物探重点实验室项目(2022DQ0604-03);国家自然科学基金面上课题(42074141)联合资助。

摘　　要：低频信号在地震勘探中具有不可替代的作用.本文所开展的野外环境噪声调查表明:环境噪声的频率成分并非白噪分布,其低频端具有更强的能量.环境噪声的这种强低频特征降低了常规方法对低频信号的恢复能力.为此,本文提出了一种基于不同频段空间预测滤波算子映射关系的低频信号恢复方法.其基本思想是,首先计算信噪比较高频段的空间预测滤波算子,然后,基于不同频段空间预测滤波算子的映射关系,由信噪比较高频段的空间预测滤波算子构建低频端的滤波算子.最后,将该预测滤波算子作用在低频地震记录上,避免强低频噪声对预测滤波算子估算精度的影响,提高低频信号的恢复精度.模型数据和实际数据的测试分析表明了本文方法的可行性和有效性.Low frequency signals play an irreplaceable role in seismic exploration.The field environmental noise survey conducted in this article shows that the frequency component of environmental noise is not white noise distribution,and its low-frequency end has stronger energy.The strong low-frequency characteristics of environmental noise reduce the ability of conventional methods to recover low-frequency signals.Therefore,this article proposes a low-frequency signal recovery method based on the mapping relationship of spatial prediction filtering operators in different frequency bands.The basic idea is to first calculate the spatial prediction filter operator for the high frequency band of the signal-to-noise ratio,and then,based on the mapping relationship of spatial prediction filter operators for different frequency bands,construct the low-frequency filter operator from the spatial prediction filter operator for the high frequency band of the signal-to-noise ratio.Finally,the predictive filtering operator is applied to low-frequency seismic records to avoid the impact of strong low-frequency noise on the estimation accuracy of the predictive filtering operator and improve the recovery accuracy of low-frequency signals.The testing and analysis of model data and actual data demonstrate the feasibility and effectiveness of the proposed method.

关 键 词：环境噪声 频率特性 空间预测滤波 噪声衰减 信号恢复 

分 类 号：P631[天文地球—地质矿产勘探]