One-step data-domain least-squares reverse time migration

Abstract
Least-squares reverse time migration (LSRTM) is an iterative inversion algorithm for estimating the broadband-wavenumber reflectivity model. Although it produces superior results compared with conventional reverse time migration (RTM), LSRTM is computationally expensive. We have developed a one-step LSRTM method by considering the demigrated and observed data to design a deblurring preconditioner in the data domain using the Wiener filter. For the Wiener filtering, we further use a stabilized division algorithm via the Taylor expansion. The preconditioned observed data are then remigrated to obtain a deblurred image. The total cost of this method is about two RTMs. Through synthetic and real data experiments, we see that one-step LSRTM is able to enhance image resolution and balance source illumination at low computational costs.

Citation
Liu Q, Peter D (2018) One-step data-domain least-squares reverse time migration. GEOPHYSICS 83: R361–R368. Available: http://dx.doi.org/10.1190/geo2017-0622.1.

Acknowledgements
We are grateful to editors S. Operto and A. Chen and reviewers M. Wong, L. Xu, and an anonymous reviewer for improving the initial manuscript. The research reported in this publication is supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research under award no. UAPN#2605-CRG4. For computer time, this research used the resources of the Information Technology Division and Extreme Computing Research Center at KAUST.

Publisher
Society of Exploration Geophysicists

Journal
GEOPHYSICS

DOI
10.1190/geo2017-0622.1

Additional Links
https://library.seg.org/doi/10.1190/geo2017-0622.1

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