Joint inversion of reflectivity and background subsurface components

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Reverse-time migration constituted the ultimate solution for imaging geologically complex areas. Nowadays, it represents the main engine behind sophisticated imaging techniques, such as linearized waveform inversion, migration velocity analysis, and full-waveform inversion. The latter is arguably the most ambitious attempt to obtain a complete and accurate picture of the subsurface. Unfortunately, it is vulnerable to cycle-skipping. Strategies to attack this problem include better acquisition, data processing, and different implementations of the full-waveform inversion algorithm. In this thesis, I propose a joint inversion of the subsurface reflectivity and the subsurface background component as different parameter sets, rather than being combined as in full-waveform inversion. During the early stages of my research, I posed the problem as a linear optimization problem. However, this approach does not have the expected properties. A nonlinear scheme corrected the problem. I test the method in synthetic 2D data and a 3D ocean-bottom node dataset from the Gulf of Mexico.


Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2020; ©2020
Publication date 2020; 2020
Issuance monographic
Language English


Author Cabrales Vargas, Alejandro
Degree supervisor Biondi, Biondo, 1959-
Thesis advisor Biondi, Biondo, 1959-
Thesis advisor Clapp, Robert G. (Robert Graham)
Thesis advisor Harris, Jerry M
Degree committee member Clapp, Robert G. (Robert Graham)
Degree committee member Harris, Jerry M
Associated with Stanford University, Department of Geophysics


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Alejandro Cabrales Vargas.
Note Submitted to the Department of Geophysics.
Thesis Thesis Ph.D. Stanford University 2020.
Location electronic resource

Access conditions

© 2020 by Alejandro Cabrales Vargas
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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