Abstract：Due to factors such as terrain conditions or acquisition costs,acquired seismic data may be incomplete or irregularly distributed,which affects subsequent seismic data analysis.Therefore,it is important to reconstruct seismic data with high precision before the data processing.The fixed point continuation algorithm is a very effective reconstruction method based on the minimization of nuclear norm.However,it is based on singular value decomposition (the computation complexity of singular value decomposition is O(mn min(m,n)),where m and n are the dimension of the matrix).Therefore,it will take a long time to solve the problem when the dimension of the matrix is high.Using PROPACK is one of conventional acceleration ways,which can reduce the computation complexity to O(rmn),where r means the rank of observed matrix.But this way still takes a long time.To overcome this issue,an improved fast fixed point continuation algorithm is proposed in this paper,which uses the block Krylov iterative approximate singular value decomposition algorithm and subspace multiplexing technique to reduce the computation complexity of singular value decomposition to O(mc min(m,c)),where (c<m,n),c∈R+).Experiments on simulating data and field seismic data show that the proposed algorithm provides much better performance than the conventional algorithm in the computation time with a reasonable signal to noise ratio.
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