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Full wavefield inversion with multiples; nonlinear Bayesian inverse multiple scattering theory beyond the Born approximation

Huang Xingguo
Full wavefield inversion with multiples; nonlinear Bayesian inverse multiple scattering theory beyond the Born approximation
Geophysics (December 2023) 88 (6): T289-T303

Abstract

Imaging earth's structures is fundamental to the earth's interior, yet how to reconstruct earth's heterogeneities using full-waveform inversion of full wavefield data that includes primary reflections and multiples remains enigmatic. I develop a nonlinear Bayesian approach for full-waveform inversion method with multiple scattering. Instead of using single scattering Born approximation to formulate the sensitivity kernels, I develop multiple scattering sensitivity kernels using multiple scattering-based Green's functions. It is based on the Lippmann-Schwinger integral and Marchenko methods, for which the Green's functions are retrieved from reflection data by solving a Marchenko equation. To estimate the uncertainty of velocities, I apply a Bayesian framework to the inverse problem. Our results indicate that the method does not depend on the earth's scattering potential and the full-waveform inversion method with multiple scattering is a good alternative approach to image the earth's structures.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 88
Serial Issue: 6
Title: Full wavefield inversion with multiples; nonlinear Bayesian inverse multiple scattering theory beyond the Born approximation
Author(s): Huang Xingguo
Affiliation: Jilin University, College of Instrumentation and Electrical Engineering, Changchun, China
Pages: T289-T303
Published: 202312
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 84
Accession Number: 2023-086376
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sects.
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2023, 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: 2023
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