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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