Recent results in curvelet-based primary-multiple separation: application to real data
Title | Recent results in curvelet-based primary-multiple separation: application to real data |
Publication Type | Conference |
Year of Publication | 2007 |
Authors | Deli Wang, Rayan Saab, Ozgur Yilmaz, Felix J. Herrmann |
Conference Name | SEG Technical Program Expanded Abstracts |
Publisher | SEG |
Keywords | Presentation, SEG, SLIM |
Abstract | In this abstract, we present a nonlinear curvelet-based sparsity-promoting formulation for the primary-multiple separation problem. We show that these coherent signal components can be separated robustly by explicitly exploting the locality of curvelets in phase space (space-spatial frequency plane) and their ability to compress data volumes that contain wavefronts. This work is an extension of earlier results and the presented algorithms are shown to be stable under noise and moderately erroneous multiple predictions. \copyright2007 Society of Exploration Geophysicists |
URL | https://slim.gatech.edu/Publications/Public/Conferences/SEG/2007/wang07SEGrri/wang07SEGrri.pdf |
DOI | 10.1190/1.2792986 |
Presentation | |
Citation Key | wang2007SEGrri |