Seismic Data Interpolation and Denoising Using SVD-free Low-rank Matrix Factorization

Rajiv Kumar, A. Aravkin, H. Mansour, B. Recht, F. Herrmann
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引用次数: 15

Abstract

Recent developments in rank optimization have allowed new approaches for seismic data interpolation and denoising. In this paper, we propose an approach for simultaneous seismic data interpolation and denoising using robust rank-regularized formulations. The proposed approach is suitable for large scale problems, since it avoids SVD computations by using factorized formulations. We illustrate the advantages of the new approach using a seismic line from Gulf of Suez and 5D synthetic seismic data to obtain high quality results for interpolation and denoising, a key application in exploration geophysics.
基于无奇异值分解的低秩矩阵分解的地震数据插值与去噪
等级优化的最新发展为地震数据插值和去噪提供了新的方法。本文提出了一种利用鲁棒秩正则化公式进行地震数据插值和去噪的方法。该方法通过因式分解避免了奇异值分解的计算,适用于大规模问题。我们利用苏伊士湾的地震线和5D合成地震数据说明了新方法的优点,可以获得高质量的插值和去噪结果,这是勘探地球物理的关键应用。
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