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Seismic imaging and processing with curvelets Herrmann, Felix J.; Hennenfent, Gilles; Moghaddam, Peyman P.
Abstract
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.
Item Metadata
| Title |
Seismic imaging and processing with curvelets
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| Creator | |
| Contributor | |
| Publisher |
European Association of Geoscientists & Engineers
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| Date Issued |
2007
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| Description |
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.
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| Extent |
967654 bytes
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| Subject | |
| Genre | |
| Type | |
| File Format |
application/pdf
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| Language |
eng
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| Date Available |
2008-03-10
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
All rights reserved
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| DOI |
10.14288/1.0107404
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| URI | |
| Affiliation | |
| Citation |
Herrmann, Felix J., Hennefent, Gilles, Moghaddam, Peyman P.
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| Peer Review Status |
Unreviewed
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| Scholarly Level |
Faculty; Graduate; Other
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| Copyright Holder |
Herrmann, Felix J.
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| Aggregated Source Repository |
DSpace
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All rights reserved