Derivative-free optimization for generalized oil field development

Placeholder Show Content

Abstract/Contents

Abstract
Given the substantial costs and potential rewards associated with petroleum field development and reservoir management, it is essential that these operations be performed as close to optimally as possible. This work presents numerical methods for field development optimization where the goal is to simultaneously determine the optimal number and type of new wells, the sequence in which they should be drilled, as well as their corresponding locations and (time-varying) controls. The optimization is posed as a mixed-integer nonlinear programming (MINLP) problem and involves categorical, integer-valued, and real-valued variables. The formulation handles bound, linear, and nonlinear constraints; the latter are treated using filter-based techniques. Noninvasive derivative-free approaches are applied for the optimizations. Methods considered include Mesh Adaptive Direct Search (MADS, a local pattern search method), Particle Swarm Optimization (PSO, a heuristic global search method) and a PSO-MADS hybrid. Single and biobjective optimization example cases are presented. These cases involve well control optimization, joint well placement and control, and generalized full-field development problems. Significant improvement over base-case field development plans is demonstrated in all cases and the PSO-MADS hybrid procedure is shown to outperform its component methods. It is concluded that, although demanding in terms of computation, the methodology presented here is applicable for realistic petroleum field development and reservoir management.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Isebor, Obiajulu Joseph
Associated with Stanford University, Department of Energy Resources Engineering.
Primary advisor Durlofsky, Louis
Thesis advisor Durlofsky, Louis
Thesis advisor Aziz, Khalid
Thesis advisor Mukerji, Tapan, 1965-
Advisor Aziz, Khalid
Advisor Mukerji, Tapan, 1965-

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Obiajulu Joseph Isebor.
Note Submitted to the Department of Energy Resources Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2013.
Location electronic resource

Access conditions

Copyright
© 2013 by Obiajulu Joseph Isebor
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

Also listed in

Loading usage metrics...