Reconstruction of seismic data via tensor completion

Author

Kreimer, Nadia ; Sacchi, Mauricio D.

Author_Institution

Dept. of Phys., Univ. of Alberta, Edmonton, AB, Canada

fYear

2012

fDate

5-8 Aug. 2012

Firstpage

29

Lastpage

32

Abstract

We describe the use of a higher-order singular value decomposition (HOSVD) in the reconstruction of seismic volumes. Seismic data in the frequency - space domain are represented via a 4-th order tensor. We present an iterative algorithm that permits to simultaneously de-noise and recover missing observations. The algorithm assumes that 4D spatial data can be represented by a low-rank tensor computed via the Higher-Order Singular Value Decomposition (HOSVD).

Keywords

iterative methods; signal denoising; signal reconstruction; singular value decomposition; tensors; 4D spatial data; 4th order tensor; HOSVD; frequency-space domain; higher-order singular value decomposition; iterative algorithm; low-rank tensor; seismic data reconstruction; seismic volume reconstruction; tensor completion; Approximation methods; Frequency domain analysis; Image reconstruction; Matrix decomposition; Signal to noise ratio; Singular value decomposition; Tensile stress; Multi-dimensional Seismic Data Regularization; Tensor Completion;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing Workshop (SSP), 2012 IEEE

Conference_Location

Ann Arbor, MI

ISSN

pending

Print_ISBN

978-1-4673-0182-4

Electronic_ISBN

pending

Type

conf

DOI

10.1109/SSP.2012.6319687

Filename

6319687