Abstract：Sparse transformation based seismic data interpolation can efficiently provide reliable wavefield.However, fast and robust methods should be well developed to meet ever increasing computations and to reduce CPU time.In this paper, we propose a fast gradient projection method to restore seismic data based on curvelet transform.A smooth L1 norm optimization model is built and a gradient projection method is proposed to solve the new model.The orthogonality of curvelet transform is utilized to speed up the method.Numerical experiments reveal that the proposed method is much fast than the current most used sparse inverse methods and suitable for field data interpolation.
李欣, 杨婷, 孙文博, 王贝贝. 一种基于光滑L1范数的地震数据插值方法[J]. 石油地球物理勘探, 2018, 53(2): 251-256.
Li Xin, Yang Ting, Sun Wenbo, Wang Beibei. A gradient projection method for smooth L1 norm regularization based seismic data sparse interpolation. Oil Geophysical Prospecting, 2018, 53(2): 251-256.
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