Sparse least-squares reverse time migration using seislets

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• 作者：Gaurav Dutta ^{gaurav.dutta@kaust.edu.sa}
• 关键词：Least-squares reverse time migration ; Seislets ; Sparsity ; Dip-constrained preconditioner
• 刊名：Journal of Applied Geophysics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：136
• 期：Complete
• 页码：142-155
• 全文大小：4815 K
• 卷排序：136

文摘

I present a LSRTM method using seislets as basis functions for the reflectivity. An optimization problem is formulated that promotes sparsity in the inverted image in the seislet domain. Sparse LSM using seislets can mitigate the migration artifacts from undersampled or noisy data. A huge savings in the computational cost can be obtained from the proposed methodology.