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 effects.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/551 |
| Date | January 2007 |
| Creators | Herrmann, Felix J. |
| Publisher | European Association of Geoscientists & Engineers |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | text |
| Rights | Herrmann, Felix J. |
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