Abstract：The projection on convex set (POCS) algorithm has been successfully applied to seismic data reconstruction, and it is flexible and simple.However, this algorithm must reconstruct data on a regular grid, and the actual collected data deviate from preset grid points due to obstacles and other factors, which results in poor reconstruction effects.Moreover, the convergence speed of the algorithm is only O(1/k).In order to solve these challenges, this paper builds a forward model of seismic data with non-uniform grids and derives a fast POCS (FPOCS) algorithm based on curvelet transform from the fast iterative shrinkage thresholding algorithm (FISTA).The FPOCS is a fast seismic data reconstruction method, which retains the computational simplicity of ite-rative shrinkage thresholding algorithm (ISTA) and has a global convergence speed of O(1/k2). Finally, the paper demonstrates the effectiveness of the proposed method through simulation and actual data.
董烈乾, 张慕刚, 汪长辉, 安学勇, 郭振兴, 范红光. 应用快速POCS算法的非均匀地震数据重建[J]. 石油地球物理勘探, 2023, 58(2): 334-339.
DONG Lieqian, ZHANG Mugang, WANG Changhui, AN Xueyong, GUO Zhenxing, FAN Hongguang. Reconstruction of non-uniformly sampled seismic data based on fast POCS algorithm. Oil Geophysical Prospecting, 2023, 58(2): 334-339.
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