Seismic signal restoration algorithm based on tensor nuclear norm regularization
A seismic signal and algorithm technology, applied in seismic signal processing and other directions, can solve problems such as the inability to make good use of multi-dimensional data correlation
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[0099] The present invention transforms the problem of restoring pre-stack seismic signals into the problem of tensor filling, utilizes the low rank property of seismic data tensors to construct tensor kernel norms, thereby effectively reconstructing missing seismic data. For solving the tensor filling problem, the present invention adopts the iterative decomposition method of ADMM, which extracts an unknown variable each time and fixes other variables, the calculation process is relatively simple, and the theoretical basis is strong. Compared with updating three parameters at a time, ADMM The algorithm converges faster and the effect is better. At the same time, for the constructed Hankel tensor nuclear norm, this paper proposes the HTR-SVD decomposition method based on the tensor random singular value decomposition (TR-SVD), and combines the truncation method of the matrix rank in the damped MSSA to construct the rank Damping cutoff selection method. The technical solutions...
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