3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform
Zhang Hua1, Chen Xiao-Hong2, and Zhang Luo-Yi1
1. State Key Laboratory Breeding Base of Nuclear Resources and Environment, East China University of Technology, Nanchang 330013, China.
2. National Engineering Laboratory for Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing 102249, China.
Abstract Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.
This research work was sponsored by the National Natural Science Foundation of China (Nos. 41304097 and 41664006), the Natural Science Foundation of Jiangxi Province (No. 20151BAB203044), the China Scholarship Council (No. 201508360061), and Distinguished Young Talent Foundation of Jiangxi Province (2017).
Cite this article:
. 3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform[J]. APPLIED GEOPHYSICS, 2017, 14(1): 87-95.
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2017, Vol. 14 
