In this work, we present the control and optimization of a network consisting of two gas-lifted oil wells, a common pipeline-riser system and a separator. The gas-lifted oil wells may be open-loop unstable. The regulatory layer stabilizes the system by cascade control of wellhead pressure measurements without needing bottom hole sensing devices. An economic Nonlinear Model Predictive Control (NMPC) based on the Multiple Shooting (MS) formulation is applied for optimization of the network operations. The optimization layer thus provides optimal settings for the regulatory controllers. The control structure has been validated by using the realistic OLGA simulator as the process, and using simplified models for Kalman filtering and the NMPC de...
In offshore production systems for oil and gas, the wells are usually controlled manually, while the...
Increasingly the upstream oil & gas industry is using active flow control (e.g. feedback loops) or p...
peer reviewedIn oil production platforms, processes are nonlinear and prone to modeling errors, as t...
As oil reserves become scarcer, oil production and recovery must be enhanced. The gas lift is one of...
As oil reserves become scarcer, oil production and recovery must be enhanced. The gas lift is one of...
This paper considers the optimal operation of an oil and gas production network by formulating it as...
Control and optimization of an oil production network based on gas-lift is a difficult task with cha...
In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share g...
The topic of this paper is the application of nonlinear model predictive control (NMPC) for optimizi...
Recent years advances within well deployment and instrumentation technology offers huge potentials f...
This thesis covers methods for optimization of oil production in three time-scales. In the long-term...
The concept of Real-Time Production Optimization is a key for improving operational performance and ...
The present Master's Thesis describes a further development of a Network Solver that checks if a cer...
This work studies the steady-state optimization of a Gas Lift Oil Well Network. The optimization app...
This paper illustrates the potential of nonlinear model-based control applied for stabilization of u...
In offshore production systems for oil and gas, the wells are usually controlled manually, while the...
Increasingly the upstream oil & gas industry is using active flow control (e.g. feedback loops) or p...
peer reviewedIn oil production platforms, processes are nonlinear and prone to modeling errors, as t...
As oil reserves become scarcer, oil production and recovery must be enhanced. The gas lift is one of...
As oil reserves become scarcer, oil production and recovery must be enhanced. The gas lift is one of...
This paper considers the optimal operation of an oil and gas production network by formulating it as...
Control and optimization of an oil production network based on gas-lift is a difficult task with cha...
In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share g...
The topic of this paper is the application of nonlinear model predictive control (NMPC) for optimizi...
Recent years advances within well deployment and instrumentation technology offers huge potentials f...
This thesis covers methods for optimization of oil production in three time-scales. In the long-term...
The concept of Real-Time Production Optimization is a key for improving operational performance and ...
The present Master's Thesis describes a further development of a Network Solver that checks if a cer...
This work studies the steady-state optimization of a Gas Lift Oil Well Network. The optimization app...
This paper illustrates the potential of nonlinear model-based control applied for stabilization of u...
In offshore production systems for oil and gas, the wells are usually controlled manually, while the...
Increasingly the upstream oil & gas industry is using active flow control (e.g. feedback loops) or p...
peer reviewedIn oil production platforms, processes are nonlinear and prone to modeling errors, as t...