Seismic deconvolution by atomic decomposition: a parametric approach with sparseness constraints

TitleSeismic deconvolution by atomic decomposition: a parametric approach with sparseness constraints
Publication TypeJournal Article
Year of Publication2005
AuthorsFelix J. Herrmann
JournalIntegrated Computer-Aided Engineering
Volume12
Number1
Page69-90
Month01
PublisherIOS Press
ISSN1069-2509
Keywordsdeconvolution, Modelling, Processing, SLIM
Abstract

In this paper an alternative approach to the blind seismic deconvolution problem is presented that aims for two goals namely recovering the location and relative strength of seismic reflectors, possibly with super-localization, as well as obtaining detailed parametric characterizations for the reflectors. We hope to accomplish these goals by decomposing seismic data into a redundant dictionary of parameterized waveforms designed to closely match the properties of reflection events associated with sedimentary records. In particular, our method allows for highly intermittent non-Gaussian records yielding a reflectivity that can no longer be described by a stationary random process or by a spike train. Instead, we propose a reflector parameterization that not only recovers the reflector’s location and relative strength but which also captures reflector attributes such as its local scaling, sharpness and instantaneous phase-delay. The first set of parameters delineates the stratigraphy whereas the second provides information on the lithology. As a consequence of the redundant parameterization, finding the matching waveforms from the dictionary involves the solution of an ill-posed problem. Two complementary sparseness-imposing methods Matching and Basis Pursuit are compared for our dictionary and applied to seismic data.

URLhttp://dl.acm.org/citation.cfm?id=1238980.1238986
URL1

https://slim.gatech.edu/Publications/Public/Journals/IntegratedComputerA...

Citation Keyherrmann2005ICAEsdb