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Prestack seismic data reconstruction and denoising by orientation-dependent tensor decomposition

Quezia Cavalcante and Milton J. Porsani
Prestack seismic data reconstruction and denoising by orientation-dependent tensor decomposition
Geophysics (February 2021) 86 (2): V107-V117

Abstract

Multidimensional seismic data reconstruction and denoising can be achieved by assuming noiseless and complete data as low-rank matrices or tensors in the frequency-space domain. We have adopted a simple and effective approach to interpolate prestack seismic data that explores the low-rank property of multidimensional signals. The orientation-dependent tensor decomposition represents an alternative to multilinear algebraic schemes. Our method does not need to perform any explicit matricization, only requiring calculation of the so-called covariance matrix for one of the spatial dimensions. The elements of such a matrix are the inner products between the lower dimensional tensors in a convenient direction. The eigenvalue decomposition of the covariance matrix provides the eigenvectors for the reduced-rank approximation of the data tensor. This approximation is used for recovery and denoising, iteratively replacing the missing values. Synthetic and field data examples illustrate the method's effectiveness for denoising and interpolating 4D and 5D seismic data with randomly missing traces.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 86
Serial Issue: 2
Title: Prestack seismic data reconstruction and denoising by orientation-dependent tensor decomposition
Affiliation: Universidade Federal da Bahia, Centro de Pesquisa em Geofisica e Geologia, Salvador, Brazil
Pages: V107-V117
Published: 202102
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 48
Accession Number: 2021-022977
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Annotation: Includes appendices
Illustration Description: illus.
Secondary Affiliation: Instituto Nacional de Ciencias e Tecnologia em Geofisica do Petroleo, BRA, Brazil
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2021, 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: 2021
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