Seismic noise suppression using non-local means algorithm based on the Shearlet transform
WANG Jin-Gang1,2(), AN Yong1,2(), XU Zhen-Wang3
1. State Key Laboratory of Petroleum Resource and Prospecting,China University of Petroleum,Beijing 102249,China 2. College of Geophysics,China University of Petroleum,Beijing 102200,China 3. Research Institute of Petroleum Exploration and Development,Liaohe Oilfield Company,PetroChina,Panjin 124010,China
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.
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WANG Jin-Gang, AN Yong, XU Zhen-Wang. Seismic noise suppression using non-local means algorithm based on the Shearlet transform. Geophysical and Geochemical Exploration, 2023, 47(1): 199-207.
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