Matrix and tensor completion for large-scale seismic interpolation: a comparative study

TitleMatrix and tensor completion for large-scale seismic interpolation: a comparative study
Publication TypeSINBAD Presentation
AuthorsOkan Akalin, Curt Da Silva, Rajiv Kumar, Ben Recht, Felix J. Herrmann
PublisherSINBAD
Year of Publication2013
Abstract

Owing to their high dimensionality, interpolating 3D seismic data volumes remains a computationally daunting task. In this work, we outline a comprehensive framework for sampling and interpolating such volumes based on the well-understood theory of Matrix and Tensor completion. This interpolation theory consists of three components major signal structure, structure-destroying sampling, and structure-restoring optimization. By viewing interpolation in the context of this theory, we are able to specify exactly when these approaches are expected to perform well. We also introduce structure-revealing transformations that promote the inherent low-rank structure in seismic data as well as a factorization approach that scales to large problem sizes. Our methods are able to handle large-scale data volumes more accurately and more quickly compared to other more ad-hoc approaches, as we will demonstrate. This is joint work with Curt Da Silva, Rajiv Kumar, Ben Recht, and Felix J. Herrmann.

KeywordsPresentation, private, SINBAD, SINBADFALL2013, SLIM
URLhttps://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2013/Fall/akalin2013SINBADmtc/akalin2013SINBADmtc.pdf
Citation Keyakalin2013SINBADmtc