Abstract: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.