1887

Abstract

Summary

Rank reduction strategy as a basic method has been widely employed to reconstruct pre-stack multidimensional seismic data. Previous studies showing that properly sampled regular data can be embedded into a low-rank block Hankel or block Toeplitz matrix. Missing data will increase the rank of the matrix. Therefore, seismic data reconstruction can be posed as a rank reduction problem. In this paper, we introduce a new fast rank reduction algorithm named randomized QR decomposition to replace the classic Singular Value Decomposition (SVD) and

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/content/papers/10.3997/2214-4609.201701432
2017-06-12
2024-03-29
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References

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