A nonlinear sparsity promoting formulation and algorithm for full waveform inversion

TitleA nonlinear sparsity promoting formulation and algorithm for full waveform inversion
Publication TypeConference
Year of Publication2011
AuthorsAleksandr Y. Aravkin, James V. Burke, Felix J. Herrmann, Tristan van Leeuwen
Conference NameEAGE Annual Conference Proceedings
Month05
OrganizationEAGE
KeywordsEAGE, Full-waveform inversion, Optimization
Abstract

Full Waveform Inversion (FWI) is a computational procedure to extract medium parameters from seismic data. FWI is typically formulated as a nonlinear least squares optimization problem, and various regularization techniques are used to guide the optimization because the problem is illposed. In this paper, we propose a novel sparse regularization which exploits the ability of curvelets to efficiently represent geophysical images. We then formulate a corresponding sparsity promoting constrained optimization problem, which we call Nonlinear Basis Pursuit Denoise (NBPDN) and present an algorithm to solve this problem to recover medium parameters. The utility of the NBPDN formulation and efficacy of the algorithm are demonstrated on a stylized cross-well experiment, where a sparse velocity perturbation is recovered with higher quality than the standard FWI formulation (solved with LBFGS). The NBPDN formulation and algorithm can recover the sparse perturbation even when the data volume is compressed to 5 % of the original size using random superposition.

URLhttps://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2011/aravkin11EAGEnspf/aravkin11EAGEnspf.pdf
Presentation

https://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2011/ar...

URL1

http://earthdoc.eage.org/publication/publicationdetails/?publication=50199

Citation Keyaravkin2011EAGEnspf