Data driven Gradient Sampling for seismic inversion

TitleData driven Gradient Sampling for seismic inversion
Publication TypeSINBAD Presentation
AuthorsMathias Louboutin, Felix J. Herrmann
PublisherSINBAD
Year of Publication2017
Abstract

We present in this work an extension of the Gradient Sampling algorithm presented at the last EAGE in Paris. We previously showed the potential of this algorithm playing with implicit time-shifts to represent the wavefield of a slightly perturbed velocity model. We introduce an extension where the weights of the Gradient Sampling algorithm are obtained with the solve of data-based quadratic subproblem instead of at random. The update direction is the a more accurate representation of the true Gradient Sampling update direction.

KeywordsPresentation, private, SINBAD, SINBADFALL2017, SLIM
URLhttps://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2017/Fall/louboutin2017SINBADFddg/louboutin2017SINBADFddg.pdf
URL1

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

Citation Keylouboutin2017SINBADFddg