Parallel Dantzig–Wolfe decomposition for real-time optimization—Applied to a complex oil field

Parallel Dantzig–Wolfe decomposition for real-time optimization—Applied to a complex oil field

This page is a publication and represents journal papers, conference papers and proceedings etc.

5
Average: 5 (1 vote)

1 users have rated this content. We would love to have your vote as well. Log in and rate!



Abstract

This paper studies Dantzig–Wolfe decomposition for real-time optimization of process systems with a decentralized structure. The idea is to improve computational efficiency and transparency of a solution. The contribution lies in the application of the Dantzig–Wolfe method which allows us to efficiently decompose an optimization problem into parts. Moreover, we show how the algorithm can be parallelized for even higher efficiency. The nonlinear system is modeled by piecewise linear models with the added benefit that error bounds can be computed. In this context alternative parameterizations are discussed. The properties of the method are studied by applying it to a model of a complex petroleum field with severe production optimization challenges due to rate dependent gas-coning wells. The model resembles the Troll west oil rim, a huge gas and oil field on the Norwegian Continental shelf. Finally, the paper discusses workflows in production optimization as a means to explain how the proposed methodology can be applied in practice.
Content

This paper studies Dantzig–Wolfe decomposition for real-time optimization of process systems with a decentralized structure. The idea is to improve computational efficiency and transparency of a solution. The contribution lies in the application of the Dantzig–Wolfe method which allows us to efficiently decompose an optimization problem into parts. Moreover, we show how the algorithm can be parallelized for even higher efficiency. The nonlinear system is modeled by piecewise linear models with the added benefit that error bounds can be computed. In this context alternative parameterizations are discussed.

 The properties of the method are studied by applying it to a model of a complex petroleum field with severe production optimization challenges due to rate dependent gas-coning wells. The model resembles the Troll west oil rim, a huge gas and oil field on the Norwegian Continental shelf.

 Finally, the paper discusses workflows in production optimization as a means to explain how the proposed methodology can be applied in practice.

Other key information

207 results
Below, you will find related content (content tagged with same topic(s) as this publication)
Content type: Presentation page for handbook

Integrated Planning in Oil & Gas Industry

Designing and Cultivating IPL Practices

5
Content type: Publication

Integrated production optimization of oil fields with pressure and routing constraints: The Urucu field

This is scientific publications written in collaboration with the IO Center

5
Content type: Publication

Integrated Reservoir Modelling of the Norne Field

Volume Visualization/Seismic Attribute,Structural and Property Modeling

0
Content type: Publication

Integrating Networked Process Systems to Solve Dynamic Optimization Problems

This is a scientific publication written in collaboration with the IO Center.

0
Content type: Publication

Integration by Infrastructuring: The Case of Subsea Environmental Monitoring in Oil and Gas Offshore Operations

Development of ICT solutions for performing real-time subsea environmental monitoring during oil and gas offshore operations

0
Content type: Presentation page for handbook

Interdisciplinary decision making in production optimization

Handbook in interdisciplinary decision making in production optimization.

0
Content type: Topic page

Interdisciplinary Risk Assessment in Integrated Operations

Addressing Human and Organisational Factors in Major Accident Loss Prevention

0
Content type: Project

IO 1 - IO Teamwork and Capabilities (Phase 2)

Distributed collaboration, IO leadership and capability development

0
Content type: Project

IO 3 - Proactive Management of Safety and Environment (Phase 2)

Applying IO-related solutions to prevent major accidents

0
Content type: Project

IO 4 - Production Optimization and Subsurface IO (Phase 2)

Production Optimization and Subsurface IO is a project with focus on using models and predictions to enhance utilization of oil fields.

0

Pages