Reconstruction of seismic data with least squares inversion based on nonuniform fast Fourier transform
基于非均匀快速傅里叶变换的最小二乘反演地震数据重建

Reconstruction of uneven seismic data is a crucial step of the analyzing and processing of the data. In this paper, a least squares inversion based on nonuniform fast Fourier transform is proposed, which can reconstruct both uneven and alias seismic data. The algorithm of nonuniform fast Fourier transform is used to do Fourier transform of uneven data. An adaptive DFT weighted norm regularization constraint is used during the reconstruction. The inverse problem is solved by the preconditioning conjugate gradient method, which makes the solutions stable and convergence quick. Experimental results on theoretical model and raw uneven seismic data show that the proposed method is fast, efficient and applicable.