Migration of viscoacoustic data using acoustic reverse time migration with hybrid deblurring filters

Yuqing Chen, Bowen Guo, Gerard T. Schuster

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Viscoacoustic migration can significantly compensate for the amplitude loss and phase distortion in migration images computed from highly attenuated data. However, solving the viscoacoustic wave equation requires a significant amount of storage space and computation time, especially for least-squares migration methods. To mitigate this problem, we used acoustic reverse time migration (RTM) instead of viscoacoustic migration to migrate the viscoacoustic data and then we correct the amplitude and phase distortion by hybrid deblurring filters in the image domain. Numerical tests on synthetic and field data demonstrate that acoustic RTM combined with hybrid deblurring filters can compensate for the attenuation effects and produce images with high resolution and balanced amplitudes. This procedure requires less than one-third of the storage space and is [Formula: see text] times faster compared with the viscoacoustic migration, but at the cost of mildly reduced accuracy. Here, [Formula: see text] represents the number of iterations used for least-squares migration method. This method can be extended to 3D migration at even a greater cost saving.
Original languageEnglish (US)
Pages (from-to)S127-S136
Number of pages1
JournalGeophysics
Volume84
Issue number3
DOIs
StatePublished - 2019

Bibliographical note

KAUST Repository Item: Exported on 2021-07-09
Acknowledgements: The research reported in this paper was 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. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST. We thank them for providing the computational resources required for carrying out this work. We also thank Exxon for the Friendswood crosswell data.

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