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Multiple prediction from incomplete data with the focused curvelet transform

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Title: Multiple prediction from incomplete data with the focused curvelet transform
Author: Herrmann, Felix J.
Subject Keywords incomplete data;curvelet;curvelet based recovery sparsity promoting inversion;CRSI;SRME;2D;3D;wavefield reconstruction
Issue Date: 2007
Publicly Available in cIRcle 2008-03-20
Publisher Society of Exploration Geophysicists
Citation: Herrmann, Felix J. 2007. Multiple prediction from incomplete data with the focused curvelet transform. SEG 77th Annual Meeting and Exposition.
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.
Affiliation: Earth and Ocean Sciences, Dept. of (EOS), Dept of
URI: http://hdl.handle.net/2429/601
Peer Review Status:

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