Accelerating oil-water subsurface flow simulation through reduced-order modeling and advances in nonlinear analysis

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Abstract/Contents

Abstract
Reservoir simulation is an important tool for understanding and predicting subsurface flow and reservoir performance. In applications such as production optimization and history matching, thousands of simulation runs may be required. Therefore, proxy methods that can provide approximate solutions in much shorter times can be very useful. Reduced-order modeling (ROM) methods are a particular type of proxy procedure that entail a reduction of the number of unknown variables in the nonlinear equations. This dissertation focuses on two of the most promising proper orthogonal decomposition (POD)-based ROM methods, POD-TPWL and POD-DEIM. A separate (non-ROM) technique to accelerate nonlinear convergence for oil-water problems is presented in the appendix.

Description

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 2018; ©2018
Publication date 2018; 2018
Issuance monographic
Language English

Creators/Contributors

Author Jiang, Rui
Degree supervisor Durlofsky, Louis
Degree supervisor Tchelepi, Hamdi
Thesis advisor Durlofsky, Louis
Thesis advisor Tchelepi, Hamdi
Thesis advisor Volkov, Oleg
Degree committee member Volkov, Oleg
Associated with Stanford University, Department of Energy Resources Engineering.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Rui (Forest) Jiang.
Note Submitted to the Department of Energy Resources Engineering.
Thesis Thesis Ph.D. Stanford University 2018.
Location electronic resource

Access conditions

Copyright
© 2018 by Rui Jiang
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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