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Preprint
Article
Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain
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A peer-reviewed article of this preprint also exists.
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Abstract
Full-waveform seismic data inversion has given rise to hope for the simultaneous and automated execution of tomography and imaging by solving a nonlinear least-squares optimization problem. As previously recognized, brute force minimization by classical methods is hopeless if the data lacks low temporal frequencies. The article developed a reliable numerical method for recovering smooth velocity using model space decomposition. We present realistic synthetic examples to test the presented algorithm.
Keywords:
Subject: Environmental and Earth Sciences - Atmospheric Science and Meteorology
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Submitted:
25 November 2020
Posted:
26 November 2020
You are already at the latest version
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A peer-reviewed article of this preprint also exists.
This version is not peer-reviewed
Submitted:
25 November 2020
Posted:
26 November 2020
You are already at the latest version
Alerts
Abstract
Full-waveform seismic data inversion has given rise to hope for the simultaneous and automated execution of tomography and imaging by solving a nonlinear least-squares optimization problem. As previously recognized, brute force minimization by classical methods is hopeless if the data lacks low temporal frequencies. The article developed a reliable numerical method for recovering smooth velocity using model space decomposition. We present realistic synthetic examples to test the presented algorithm.
Keywords:
Subject: Environmental and Earth Sciences - Atmospheric Science and Meteorology
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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