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Seismic data processing with curvelets: a multiscale and nonlinear approach.

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Title: Seismic data processing with curvelets: a multiscale and nonlinear approach.
Author: Herrmann, Felix J.; Wang, Deli; Hennenfent, Gilles; Moghaddam, Peyman P.
Subject Keywords curvelet transform;incomplete data;seismic;sparsity;mixing;noise
Issue Date: 2007
Publicly Available in cIRcle 2008-03-10
Publisher Society of Exploration Geophysicists
Citation: Herrmann,Felix J.,Wang, Deli, Hennenfent, Gilles, Moghaddam, Peyman P. 2007. Seismic data processing with curvelets: a multiscale and nonlinear approach. SEG International Exposition and 77th Annual Meeting.
Abstract: 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.
Affiliation: Earth and Ocean Sciences, Dept. of (EOS), Dept of
URI: http://hdl.handle.net/2429/557
Peer Review Status:

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