Elastic least-squares reverse time migration

Zongcai Feng, Gerard T. Schuster

Research output: Contribution to journalArticlepeer-review

138 Scopus citations

Abstract

We use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P- and S-wave impedances. Elastic LSRTMsolves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and amplitude balancing, fewer artifacts, and less crosstalk compared with the elastic RTM images. The images are also better focused and have better reflector continuity for steeply dipping events compared to the acoustic LSRTM images. Similar to conventional leastsquares migration, elastic LSRTM also requires an accurate estimation of the P- and S-wave migration velocity models. However, the problem remains that, when there are moderate errors in the velocity model and strong multiples, LSRTMwill produce migration noise stronger than that seen in the RTM images.
Original languageEnglish (US)
Pages (from-to)S143-S157
Number of pages1
JournalGEOPHYSICS
Volume82
Issue number2
DOIs
StatePublished - Mar 8 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research is supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. Z. Feng would also like to thank G. Dutta and B. Guo for their help. The computation resource provided by the KAUST Supercomputing Laboratory is greatly appreciated. We are very grateful to Jerry Harris and Robert Langan for the use of the crosswell data set.

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