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Multiple prediction from incomplete data with the focused curvelet transform Herrmann, Felix J.; Wang, Deli; Hennenfent, Gilles
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 |
501809 bytes
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Subject | |
Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2008-03-11
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Provider |
Vancouver : University of British Columbia Library
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Rights |
All rights reserved
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DOI |
10.14288/1.0107413
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URI | |
Affiliation | |
Citation |
Herrmann, Felix J., Wang, Deli, Hennenfent, Gilles. 2007. Multiple prediction from incomplete data with the focused curvelet transform. SEG International Exposition and 77th Annual Meeting.
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Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty; Graduate
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Copyright Holder |
Herrmann, Felix J.
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Aggregated Source Repository |
DSpace
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