Removing density effects in LS-RTM with a low-rank matched filter

TitleRemoving density effects in LS-RTM with a low-rank matched filter
Publication TypeConference
Year of Publication2018
AuthorsMengmeng Yang, Rajiv Kumar, Rongrong Wang, Felix J. Herrmann
Conference NameSEG Technical Program Expanded Abstracts
Page4251-4255
Month10
Keywordsdensity effect, Least square, low rank, SEG
Abstract

Least-squares reverse-time migration faces difficulties when it inverts the data containing strong components related to density variation with velocity-only Born modeling operator. The strong density perturbation will be inverted as strong dummy velocity perturbations, which influence the amplitudes and phase of the velocity perturbations in the inverted model. The traditional method is to invert the additional density variations by developing Born operator with respect to both density and velocity or modify the image condition. In this work, we develop a matched-filter based LS-RTM for velocity-only Born modeling operator, which removes the artifacts in the imaging created by the strong density variation. This method doesn't call for extra work of finite difference stencil and is more general. In the experiment part, we use a complex discontinuous layered medium with strong density variations at the ocean bottom, and show the efficacy of the propose formulation.

Notes

(SEG, Anaheim)

URLhttps://www.slim.eos.ubc.ca/Publications/Public/Conferences/SEG/2018/yang2018SEGrde/yang2018SEGrde.html
DOI10.1190/segam2018-2997814.1
Presentation

https://www.slim.eos.ubc.ca/Publications/Public/Conferences/SEG/2018/yan...

Citation Keyyang2018SEGrde