Sparse-spike deconvolution based on adaptive step FISTA algorithm
PAN Shulin1, YAN Ke2, LI Lingyun3, JIANG Congyuan4, SHI Linguang3
1. School of Earth Science and Technology, Southwest Petroleum University, Chengdu, Sichuan 610500, China;
2. Southwest Oil & Gas Field Company, PetroChina, Chengdu, Sichuan 610051, China;
3. Research Institute of Geophysics, Shengli Oilfield Branch Co., SINOPEC, Dongying, Shandong 257000, China;
4. Department of Electrical and Electronic Engineering, Sichuan Vocational and Technical College, Suining, Sichuan 629000, China
Abstract：The optimal internal gradient step L can be searched by linear methods in the fast iterative shrinkage-thresholding algorithm (FISTA).But the step L can only be increased,which seriously affects the convergence of FISTA algorithm.In this paper,a sparse-spike deconvolution based on adaptive step FISTA algorithm is proposed.On the basis of FISTA algorithm,the step L is reduced appropriately before each iteration,and then the step L is found by a linear search to achieve the adaptive adjustment of L.In order to realize the algorithm theoretical converge,the auxiliary sequence of the conventional FISTA algorithm is modified by combining two consecutive L.Finally,the algorithm is converged.Theoretical model and field data tests show that the proposed method has better convergence and better anti-noise ability than the conventional FISTA algorithm,and obtain ideal inversion results of different signal-to-noise ratio data.
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