Off-the-grid low-rank matrix recovery: seismic data reconstruction

TitleOff-the-grid low-rank matrix recovery: seismic data reconstruction
Publication TypeConference
Year of Publication2016
AuthorsOscar Lopez, Rajiv Kumar, Ozgur Yilmaz, Felix J. Herrmann
Conference NameCanadian Mathematical Society Summer Meeting
Month06
KeywordsCMS, matrix completion, matrix sensing, nonuniform discrete Fourier transform, nuclear-norm, Seismic data Interpolation
Abstract

This talk discusses a modified low-rank matrix recovery work-flow that admits unstructured observations. By incorporating a regularization operator which accurately maps structured data to unstructured data, into the nuclear-norm minimization problem, this approach is able to compensate for data irregularity. Furthermore, by construction this formulation yields output that is supported on a structured grid. Recovery error bounds are established for the methodology with matrix sensing and matrix completion numerical experiments including applications to seismic trace interpolation to demonstrate the potential of the approach.

Notes

(CMS, Edmonton, Alberta)

Presentation

https://slim.gatech.edu/Publications/Public/Conferences/CMS/2016/lopez20...

Citation Keylopez2016CMSogl