Distributed Optimization and Control of Offshore Oil Production: The Intelligent Platform

Distributed Optimization and Control of Offshore Oil Production: The Intelligent Platform

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

0
No votes yet

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



Abstract

We describe a novel approach to distributed optimization and control of offshore oil production systems. The model incorporates a complex pipeline network. Oil and gas production systems are represented as a network of connected hierarchical structures of sub sea wells, manifolds and clusters. We consider multiphase flow of water, gas, and oil in the pipelines, and account for discrete switching and typical inflow characteristics of the sub sea wells. Network methods based on variational calculus provide a modeling framework for decentralized optimization and control. Conservation laws and the second law of thermodynamics combined with the passivity theory of nonlinear control lead to conditions for stability and optimality. We describe interconnections in networks through matrix representations that capture a network's topology. Control strategies are derived from the model, and stability and convergence to the optimal solution follows from the passivity conditions. The proposed distributed controller network can be seen as a special case of a Multi Agent System (MAS).
Content

We describe a novel approach to distributed optimization and control of offshore oil production systems. The model incorporates a complex pipeline network. Oil and gas production systems are represented as a network of connected hierarchical structures of sub sea wells, manifolds and clusters. We consider multiphase flow of water, gas, and oil in the pipelines, and account for discrete switching and typical inflow characteristics of the sub sea wells. Network methods based on variational calculus provide a modeling framework for decentralized optimization and control. Conservation laws and the second law of thermodynamics combined with the passivity theory of nonlinear control lead to conditions for stability and optimality. We describe interconnections in networks through matrix representations that capture a network's topology. Control strategies are derived from the model, and stability and convergence to the optimal solution follows from the passivity conditions. The proposed distributed controller network can be seen as a special case of a Multi Agent System (MAS).

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