Low-rank representation of omnidirectional subsurface extended image volumes

TitleLow-rank representation of omnidirectional subsurface extended image volumes
Publication TypeSINBAD Presentation
AuthorsGraff-Kray, M, Rajiv Kumar, Felix J. Herrmann
PublisherSINBAD
Year of Publication2017
Abstract

Extended image volumes are an important migration tool in seismic exploration. However the computation and the storage of omnidirectional subsurface extended image volumes are usually prohibitive. That is why some solutions have been already proposed for instance by focusing on horizontal offsets only. In our work, we will consider a linear algebra approach to deal with the low-rank representation of extended image volumes with full offsets. We will never build entirely the resulting matrix but get only actions of it on well-chosen probing vectors, based on Low-Rank decomposition or randomized SVD. This representation allows us to have access to all the energy of the extended image volume matrix and still limits the storage of the information and the computational cost.

KeywordsPresentation, private, SINBAD, SINBADFALL2017, SLIM
URLhttps://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2017/Fall/graff2017SINBADFlrp/graff2017SINBADFlrp.pdf
URL1

https://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2017...

Citation Keygraff2017SINBADFlrp