Seismic trace interpolation via sparsity promoting reweighted algorithms

TitleSeismic trace interpolation via sparsity promoting reweighted algorithms
Publication TypeSINBAD Presentation
AuthorsHassan Mansour
PublisherSINBAD
Year of Publication2012
Abstract

Missing-trace interpolation aims to reconstruct regularly sampled wavefields from periodically sampled data with gaps caused by physical constraints. While transform-domain sparsity promotion has proven to be an effective tool to solve this recovery problem, current recovery techniques make no use of a priori information on the transform-domain coefficients. To overcome these vulnerabilities in solving the recovery problem for large-scale problems, we propose recovery by weighted one-norm minimization, which exploits correlations between locations of significant coefficients of different partitions, e.g., shot records, common-offset gathers, or frequency slices, of the acquired data. Moreover, in situations where no prior support estimate is available, we propose the WSPGL1 algorithm that outperforms standard $\ell_1$ minimization in finding sparse solutions to underdetermined linear systems of equations. Our algorithm is a modification of the SPGL1 algorithm and enjoys better sparse recovery performance at no additional computational cost. We illustrate the improved recovery using WSPGL1 for randomly subsampled seismic traces.

KeywordsPresentation, SINBAD, SINBADFALL2012, SLIM
URLhttps://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2012/Fall/mansour2012SINBADsti/mansour2012SINBADsti_pres.pdf
Citation Keymansour2012SINBADsti