基于Shearlet变换的非局部均值地震噪声压制

在地震勘探中,由于野外地震数据采集环境及仪器性能本身的限制,采集到地震信号中不可避免地会混入较强的噪声,极大影响后续处理、解释工作。而近几年,多尺度几何分析方法以其独特优势成为压制噪声的研究热点,本文提出在Shearlet域中引入非局部均值算法对地震噪声进行压制,该算法首先对地震信号进行非下采样Shearlet变换,然后采用非局部均值法对分解后系数子集进一步处理,并采用8个Sobel算子近似表示全方向结构,对权重函数进行改进,最后对系数进行Shearlet反变换,得到去噪后的地震信号。实验结果表明相比于传统非局部均值法,该联合算法能有效地压制随机噪声,同时对弱同相轴具有更好的保护作用,在地震资料处理中具有良好的实用性。

Seismic noise suppression using non-local means algorithm based on the Shearlet transform

Owing to the limitations of both the field environment for seismic data acquisition and the performance of instruments,the seismic signals collected in seismic exploration are inevitably mixed with strong noise,thus greatly affecting the subsequent processing and interpretation.In recent years,multi-scale geometric analysis methods have become an important topic in noise suppression owing to their unique advantages.This study proposed suppressing the seismic noise using a non-local mean (NLM) algorithm in the Shearlet domain.First,the non-subsampled Shearlet transform (NSST) was performed for seismic signals.Then,the decomposed coefficient subset was further processed using the NLM method,and the weight function was improved by using eight Sobel operators to approximate the omnidirectional structure.Finally,the inverse Shearlet transform was performed for the coefficients to obtain the denoised seismic signals.Experimental results show that this combined algorithm can effectively suppress the random noise and preserve the weak events,thus showing high practicability in the seismic data processing.