A stochastic quasi-Newton McMC method for uncertainty quantification of full-waveform inversion

TitleA stochastic quasi-Newton McMC method for uncertainty quantification of full-waveform inversion
Publication TypePresentation
Year of Publication2014
AuthorsZhilong Fang, Chia Ying Lee, Felix J. Herrmann
KeywordsPresentation, SINBAD, SINBADSPRING2014, SLIM
Abstract

In this work, we present a fast McMC method using the stochastic l-BFGS Hessian to quantify the uncertainty of full-waveform inversion. Using the stochastic l-BFGS Hessian, we do not need the assumption that the Hessian of data misfit is low rank and we also reduce the computational cost of estimating the Hessian. Numerical result shows the capability of this fast McMC method.

URLhttps://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2014/Spring/fang2014SINBADsqn/fang2014SINBADsqn.pdf
Citation Keyfang2014SINBADsqn