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Seismic data decomposition into spectral components using regularized nonstationary autoregression

Sergey Fomel
Seismic data decomposition into spectral components using regularized nonstationary autoregression
Geophysics (November 2013) 78 (6)

Abstract

Seismic data can be decomposed into nonstationary spectral components with smoothly variable frequencies and smoothly variable amplitudes. To estimate local frequencies, I use a nonstationary version of Prony's spectral analysis method defined with the help of regularized nonstationary autoregression. To estimate local amplitudes of different components, I fit their sum to the data using regularized nonstationary regression. Shaping regularization ensures stability of the estimation process and provides controls on smoothness of the estimated parameters. Potential applications of the proposed technique include noise attenuation, seismic data compression, and seismic data regularization.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 78
Serial Issue: 6
Title: Seismic data decomposition into spectral components using regularized nonstationary autoregression
Author(s): Fomel, Sergey
Affiliation: University of Texas at Austin, Bureau of Economic Geology, Austin, TX, United States
Pages: O69-O76
Published: 201311
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 37
Accession Number: 2014-004375
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sects.
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201404
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