基于EWT-分量阈值与SVD的微震信号降噪方法

针对微震信号采集过程中存在大量不同频率的干扰信号，导致信号初至拾取难度大的问题，提出一种经验小波变换（EWT）结合分量阈值重构规则及奇异值分解（SVD）技术对微震信号进行降噪的方法。该方法利用EWT自适应分解和抗模态混叠的特点分解微震信号，得到各分量信号。对于高信噪比信号，选取相关系数大于0.3且方差贡献率大于15%的固有模态分量进行重构，具有较好的降噪效果；对于低信噪比信号，在高信噪比降噪方法的基础上利用SVD去除高频分量中的噪声，并与EWT分解出的低频有效分量进行重构。实验表明，对不同信噪比的构造信号与实际微震信号进行降噪，信噪比均得到明显改善；以修改的能量比法和分形维数法拾取实际微震降噪信号初至到时作为验证，拾取相对误差均小于1%，证明了本文降噪方法的有效性。

Micro-Seismic Signal Denoising Method Based on EWT-Component Threshold and SVD

In the process of micro-seismic signal acquisition,a large number of interference signals with different frequencies make it difficult to pick up the primary arrival of the signal.We propose a method based on empirical wavelet transform(EWT)combined with EWT component threshold reconstruction rule and singular value decomposition(SVD)technology for signal denoising.The component signals are obtained by the EWT method,which decomposes the micro-seismic signals with the characteristics of adaptive decomposition and conquering modal mixing.For the high signal-to-noise ratio signal,the reconstruction of inherent modal components with a correlation coefficient greater than 0.3 and a variance contribution rate greater than 15%has a better denoising effect.For the low signal-to-noise ratio signal,based on the high signal-to-noise ratio denoising method,we propose a new denoising method using SVD to denoise the high-frequency components and reconstructing with low-frequency effective components decomposed by EWT.Through experimental analysis,the signal-to-noise ratio of the construction signals with different signal-to-noise ratio and the actual micro-seismic signals are obviously improved.The modified energy ratio method and fractal dimension method are used to pick up the primary arrival of actual micro-seismic denoising signals for verification.The relative error of picking up is less than 1%.The test results show the effectiveness of the denoising method.