In this paper, we present a nonlinear curvelet-based sparsity-promoting formulation for
three problems in seismic processing and imaging namely, seismic data regularization
from data with large percentages of traces missing; seismic amplitude recovery for subsalt
images obtained by reverse-time migration and primary-multiple separation, given
an inaccurate multiple prediction. We argue why these nonlinear formulations are beneficial.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/552 |
| Date | January 2007 |
| Creators | Herrmann, Felix J., Hennenfent, Gilles, Moghaddam, Peyman P. |
| 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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