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Seismic data processing with curvelets: a multiscale and nonlinear approach Herrmann, Felix J.
Description
In this abstract, we present a nonlinear curvelet-based sparsity-promoting formulation of a seismic processing flow, consisting of the following steps: seismic data regularization and the restoration of migration amplitudes. We show that the curvelet's wavefront detection capability and invariance under the migration-demigration operator lead to a formulation that is stable under noise and missing data.
Item Metadata
Title |
Seismic data processing with curvelets: a multiscale and nonlinear approach
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Creator | |
Contributor | |
Publisher |
Society of Exploration Geophysicists
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Date Issued |
2007
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Description |
In this abstract, we present a nonlinear curvelet-based sparsity-promoting formulation of a seismic processing flow, consisting of the following steps: seismic data regularization and the restoration of migration amplitudes. We show that the curvelet's wavefront detection capability and invariance under the migration-demigration operator lead to a formulation that is stable under noise and missing data.
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Extent |
5716560 bytes
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Subject | |
Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2008-03-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
All rights reserved
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DOI |
10.14288/1.0107416
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URI | |
Affiliation | |
Citation |
Herrmann, Felix J. 2007. Seismic data processing with curvelets: a multiscale and nonlinear approach. SEG 77th Annual Meeting and Exposition.
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Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Herrmann, Felix J.
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Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
All rights reserved