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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
Creator
Herrmann, Felix J.
Contributor
University of British Columbia. Seismic Laboratory for Imaging and Modeling
Publisher
Society of Exploration Geophysicists
Date Issued
2007
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.
Extent
5716560 bytes
Subject
Migration demigration; Curvelet; Seismic data; Regularization; Restoration; Migration amplitudes; Nonlinear; Curvelet domain sparsity; Smoothness; Overfitting; 2D; 2-D
Genre
Presentation
Type
Text; Still Image
File Format
application/pdf
Language
eng
Date Available
2008-03-20
Provider
Vancouver : University of British Columbia Library
Rights
All rights reserved
DOI
10.14288/1.0107416
URI
http://hdl.handle.net/2429/600
Affiliation
Science, Faculty of; Earth and Ocean Sciences, Department of
Citation
Herrmann, Felix J. 2007. Seismic data processing with curvelets: a multiscale and nonlinear approach. SEG 77th Annual Meeting and Exposition.
Peer Review Status
Unreviewed
Scholarly Level
Faculty
Copyright Holder
Herrmann, Felix J.
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