Centered Differential Waveform Inversion with Minimum Support Regularization

Vladimir Kazei, Tariq Ali Alkhalifah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Time-lapse full-waveform inversion has two major challenges. The first one is the reconstruction of a reference model (baseline model for most of approaches). The second is inversion for the time-lapse changes in the parameters. Common model approach is utilizing the information contained in all available data sets to build a better reference model for time lapse inversion. Differential (Double-difference) waveform inversion allows to reduce the artifacts introduced into estimates of time-lapse parameter changes by imperfect inversion for the baseline-reference model. We propose centered differential waveform inversion (CDWI) which combines these two approaches in order to benefit from both of their features. We apply minimum support regularization commonly used with electromagnetic methods of geophysical exploration. We test the CDWI method on synthetic dataset with random noise and show that, with Minimum support regularization, it provides better resolution of velocity changes than with total variation and Tikhonov regularizations in time-lapse full-waveform inversion.
Original languageEnglish (US)
Title of host publication79th EAGE Conference and Exhibition 2017
PublisherEAGE Publications
ISBN (Print)9789462822177
DOIs
StatePublished - May 26 2017

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