The collection of seismic data in field surveys is often affected by uncontrollable factors such as terrain,resulting in irregular and missing seismic data.In order to not compromise the sub-sequent seismic data processing,it is necessary to reconstruct the missing seismic data.However,traditional reconstruction algorithms often have slow convergence rates.To address this issue,a new joint operator is proposed,which combines the fast threshold iterative method with the linear Breg-man method.This combination further improves the efficiency of the algorithm on the basis of the ac-celeration of fast threshold iteration method,resulting in a fast and high-precision reconstruction method.During the reconstruction process,the curvelet domain is used as the sparse transform do-main,and the hard thresholding function and exponential threshold model are employed.Theoretical data simulations and practical data verification demonstrate that compared to traditional seismic data reconstruction methods,this method achieves significant improvements in reconstruction quality and efficiency.Additionally,this method exhibits certain noise robustness.By leveraging the efficient convergence of the fast threshold iterative method,the reconstruction speed is further accelerated.
关键词
地震数据重建/稀疏反演/快速阈值迭代法/线性Bregman方法/曲波变换
Key words
seismic data reconstruction/sparse inversion/fast threshold iteration method/Linear Bregman method/curvelet transform
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