基于CEEMD的自适应阈值随机噪声衰减  

Random noise attenuation using adaptive threshold denoising based on CEEMD

作　　者：代倩倩 张卫 李建浪[1,2] 杨浪 陈伟 DAI Qianqian;ZHANG Wei;LI Jianlang;YANG Lang;CHEN Wei(College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 430100, China;Key Laboratory of Exploration Technology for Oil and Gas Resources (Ministry of Education), Yangtze University, Wuhan 430100, China;Cooperative Innovation Center of Unconventional Oil and Gas, Yangtze University, Wuhan 430100, China)

机构地区：[1]长江大学地球物理与石油资源学院,武汉430100 [2]油气资源与勘探技术教育部重点实验室(长江大学),武汉430100 [3]长江大学非常规油气省部共建协同创新中心,武汉430100

出　　处：《中国科技论文》2022年第5期562-570,共9页China Sciencepaper

基　　金：国家自然科学基金资助项目(41804140)。

摘　　要：为了研究随机噪声压制,将完备集合经验模态分解(complete ensemble empirical mode decomposition,CEEMD)与自适应小波阈值去噪方法相结合,提出一种新的随机噪声衰减方法,引入归一化自相关函数分析,确定需要进行自适应小波阈值去噪的固有模态分量,重构各分量及剩余分量,得到去噪后的地震数据。在进行小波阈值处理时,根据不同层数和小波分解次数选取合适的自适应阈值;并且在传统软、硬阈值函数的基础上改进小波阈值函数,克服传统阈值函数存在的缺陷。数值模拟和实际资料结果表明,相较于常规方法,所提方法具有更好的随机噪音衰减效果。To study random noise attenuation,a new random noise attenuation method was proposed combined with complete ensemble empirical mode decomposition(CEEMD)and adaptive wavelet threshold denoising,which introduces normalized autocorrelation function to determine the intrinsic mode function(IMF)that denoised by wavelet threshold denoising method,and finally reconstructs the processed IMFs and residual component to obtain denoised seismic data.When processing,select the appropriate adaptive threshold according to the number of layers and wavelet decomposition times,and improve the threshold function on the basis of the traditional soft and hard threshold functions.This new threshold function overcomes the deficiencies of the traditional threshold functions.The experimental results of numerical simulation and real seismic data show that this method has better random noise attenuation effect than conventional methods.

关 键 词：地震噪音衰减 完备集合经验模态分解 固有模态函数 自适应小波阈值去噪 

分 类 号：P631[天文地球—地质矿产勘探]