Version 1
: Received: 25 November 2020 / Approved: 26 November 2020 / Online: 26 November 2020 (10:42:47 CET)
How to cite:
Cheverda, V. Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain. Preprints2020, 2020110663. https://doi.org/10.20944/preprints202011.0663.v1
Cheverda, V. Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain. Preprints 2020, 2020110663. https://doi.org/10.20944/preprints202011.0663.v1
Cheverda, V. Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain. Preprints2020, 2020110663. https://doi.org/10.20944/preprints202011.0663.v1
APA Style
Cheverda, V. (2020). Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain. Preprints. https://doi.org/10.20944/preprints202011.0663.v1
Chicago/Turabian Style
Cheverda, V. 2020 "Elastic Full-Waveform Inversion Using Migration‑Based Depth Reflector Representation in the Data Domain" Preprints. https://doi.org/10.20944/preprints202011.0663.v1
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.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.