1887

Abstract

B035 Surface Related Multiple Prediction from Incomplete Data F.J. Herrmann* (University of British Columbia) SUMMARY Incomplete data unknown source-receiver signatures and free-surface reflectivity represent challenges for a successful prediction and subsequent removal of multiples. In this paper a new method will be represented that tackles these challenges by combining what we know about wavefield (de-)focussing by weighted convolutions/correlations and recently developed curvelet-based recovery by sparsity-promoting inversion (CRSI). With this combination we are able to leverage recent insights from wave physics towards a nonlinear formulation for the multiple-prediction problem that works for incomplete data and without detailed knowledge on the surface

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/content/papers/10.3997/2214-4609.201401490
2007-06-11
2020-10-31
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201401490
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