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Multiple prediction from incomplete data with the focused curvelet transform Herrmann, Felix J.
Abstract
Incomplete data represents a major challenge for a successful prediction and subsequent removal of multiples. In this paper, a new method will be represented that tackles this challenge in a two-step approach. During the first step, the recenly developed curvelet-based recovery by sparsity-promoting inversion (CRSI) is applied to the data, followed by a prediction of the primaries. During the second high-resolution step, the estimated primaries are used to improve the frequency content of the recovered data by combining the focal transform, defined in terms of the estimated primaries, with the curvelet transform. This focused curvelet transform leads to an improved recovery, which can subsequently be used as input for a second stage of multiple prediction and primary-multiple separation.
Item Metadata
Title |
Multiple prediction from incomplete data with the focused curvelet transform
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Creator | |
Contributor | |
Publisher |
Society of Exploration Geophysicists
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Date Issued |
2007
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Description |
Incomplete data represents a major challenge for a successful prediction and subsequent removal of multiples. In this paper, a new method will be represented that tackles this challenge in a two-step approach. During the first step, the recenly developed curvelet-based recovery by sparsity-promoting inversion (CRSI) is applied to the data, followed by a prediction of the primaries. During the second high-resolution step, the estimated primaries are used to improve the frequency content of the recovered data by combining the focal transform, defined in terms of the estimated primaries, with the curvelet transform. This focused curvelet transform leads to an improved recovery, which can subsequently be used as input for a second stage of multiple prediction and primary-multiple separation.
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Extent |
4096109 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 |
10.14288/1.0107420
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URI | |
Affiliation | |
Citation |
Herrmann, Felix J. 2007. Multiple prediction from incomplete data with the focused curvelet transform. 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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Rights
All rights reserved