Rank minimization via alternating optimization: seismic data interpolation

TitleRank minimization via alternating optimization: seismic data interpolation
Publication TypeConference
Year of Publication2015
AuthorsOscar Lopez, Rajiv Kumar, Felix J. Herrmann
Conference NameEAGE Annual Conference Proceedings
Month06
OrganizationUBC
KeywordsEAGE, interpolation, low-rank, matrix completion
Abstract

Low-rank matrix completion techniques have recently become an effective tool for seismic trace interpolation problems. In this talk, we consider an alternating optimization scheme for nuclear norm minimization and discuss the applications to large scale wave field reconstruction. By adopting a factorization approach to the rank minimization problem we write our low-rank matrix in bi-linear form, and modify this workflow by alternating our optimization to handle a single matrix factor at a time. This allows for a more tractable procedure that can robustly handle large scale, highly oscillatory and critically subsampled seismic data sets. We demonstrate the potential of this approach with several numerical experiments on a seismic line from the Nelson 2D data set and a frequency slice from the Gulf of Mexico data set.

Notes

(EAGE, Madrid)

URLhttps://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2015/lopez2015EAGErma/lopez2015EAGErma.html
DOI10.3997/2214-4609.201413453
Presentation

https://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2015/lo...

Citation Keylopez2015EAGErma