3D seismic data de-noising approach based on Curvelet transform
Zhang Hua1, Chen Xiaohong2, Li Hongxing1, Huang Guangnan1, Chen Xiao1
1. Fundamental Science on Radioactive Geology and Exploration Technology Laboratory, East China University of Technology, Nanchang, Jiangxi 344000, China;
2. National Engineering Laboratory for Offshore Oil Exploration, China University of Petroleum(Beijing), Beijing 102249, China
Abstract：Most conventional de-noising methods are mainly used for 2D seismic data.However noise develops also in 3D data space.So these conventional methods do not work well in 3D seismic data processing.Therefore we choose multi-scale and multi-directional 2D Curvelet transform to eliminate noise in 3D seismic data.During the de-noising process,the time slice extracted from 3D seismic data is decomposed by the multi-scale and multi-directional Curvelet transform,and the idea of local threshold de-noising is introduced.We choose a suitable threshold factor for each scale after Curvelet transform,and then we can get the Curvelet coefficient of signals.At last,we process the inverse transform to reconstruct seismic signals using the extracted Curvelet coefficient,and achieve the purpose of de-noising.Test results on theoretical model and real data show that the proposed approach can well preserve seismic signals and achieve better de-noising compared with other methods.
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