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Least-squares extended reverse time migration with randomly sampled space shifts

Yang Jizhong, Yunyue Elita Li, Liu Yuzhu and Jingjing Zong
Least-squares extended reverse time migration with randomly sampled space shifts
Geophysics (November 2020) 85 (6): S357-S369

Abstract

Because the velocity errors are inevitable in field data applications, direct implementation of conventional least-squares reverse time migration (LSRTM) would generate defocused migration images. Extending the model domain has the potential to preserve the data information, and reducing the extended model could provide a final image with more continuous subsurface structures for geologic interpretation. However, the computational cost and the memory requirement would be increased significantly compared to conventional LSRTM. To obtain an inversion image with better quality than conventional LSRTM, while maintaining the same computational cost and memory requirement, we have introduced random space shifts in LSRTM. The key point is to perform implicit model extension and immediate model reduction within each iteration of the inversion procedure. To be robust against the random noise during the random sampling process, we formulate the inverse problem based on a correlation objective function. Numerical examples on a simple layered model, the Marmousi model, and the SEAM model demonstrate that even when the bulk velocity errors are up to 10%, we still obtain reasonable results for subsurface geologic interpretation.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 85
Serial Issue: 6
Title: Least-squares extended reverse time migration with randomly sampled space shifts
Affiliation: Tongji University, Laboratory of Marine Geology, Shanghai, China
Pages: S357-S369
Published: 202011
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 53
Accession Number: 2021-010461
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 1 table, sects.
Secondary Affiliation: National University of Singapore, SGP, Singapore
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2021, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 2021
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