NDLI: Simultaneous and sequential approaches to joint optimization of well placement and control

Content Provider	Springer Nature Link
Author	Humphries, Thomas D. Haynes, Ronald D. James, Lesley A.
Copyright Year	2013
Abstract	Determining optimal well placement and control is essential to maximizing production from an oil field. Most academic literature to date has treated optimal placement and control as two separate problems; well placement problems, in particular, are often solved assuming some fixed flow rate or bottom-hole pressure at injection and production wells. Optimal placement of wells, however, does depend on the control strategy being employed. Determining a truly optimal configuration of wells thus requires that the control parameters be allowed to vary as well. This presents a challenging optimization problem, since well location and control parameters have different properties from one another. In this paper, we address the placement and control optimization problem jointly using approaches that combine a global search strategy (particle swarm optimization, or PSO) with a local generalized pattern search (GPS) strategy. Using PSO promotes a full, semi-random exploration of the search space, while GPS allows us to locally optimize parameters in a systematic way. We focus primarily on two approaches combining these two algorithms. The first is to hybridize them into a single algorithm that acts on all variables simultaneously, while the second is to apply them sequentially to decoupled well placement and well control problems. We find that although the best method for a given problem is context-specific, decoupling the problem may provide benefits over a fully simultaneous approach.
Starting Page	433
Ending Page	448
Page Count	16
File Format	PDF
ISSN	14200597
Journal	Computational Geosciences
Volume Number	18
Issue Number	3-4
e-ISSN	15731499
Language	English
Publisher	Springer International Publishing
Publisher Date	2013-09-22
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Production optimization Well placement Well control Particle swarm optimization Pattern search Joint optimization Black-box optimization Earth Sciences Geotechnical Engineering & Applied Earth Sciences Hydrogeology Mathematical Modeling and Industrial Mathematics Soil Science & Conservation
Content Type	Text
Resource Type	Article
Subject	Computers in Earth Sciences Computational Theory and Mathematics Computer Science Applications Computational Mathematics

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Hybrid differential evolution and particle swarm optimization for optimal well placement

Optimization of well placement by combination of a modified particle swarm optimization algorithm and quality map method

Well placement optimization subject to realistic field development constraints

A simultaneous perturbation stochastic approximation algorithm for coupled well placement and control optimization under geologic uncertainty

Generalized field-development optimization with well-control zonation

A variable-control well placement optimization for improved reservoir development

Joint optimization of oil well placement and controls

Application of a particle swarm optimization algorithm for determining optimum well location and type

Dimensionality reduction for production optimization using polynomial approximations

Simultaneous and sequential approaches to joint optimization of well placement and control

Similar Documents

Hybrid differential evolution and particle swarm optimization for optimal well placement

Optimization of well placement by combination of a modified particle swarm optimization algorithm and quality map method

Well placement optimization subject to realistic field development constraints

A simultaneous perturbation stochastic approximation algorithm for coupled well placement and control optimization under geologic uncertainty

Generalized field-development optimization with well-control zonation

A variable-control well placement optimization for improved reservoir development

Joint optimization of oil well placement and controls

Application of a particle swarm optimization algorithm for determining optimum well location and type

Dimensionality reduction for production optimization using polynomial approximations

Simultaneous and sequential approaches to joint optimization of well placement and control