Key team members:
Team lead: Assoc. Prof. John Bagterp Jørgensen, DTU Compute. A Post Doc and a PhD student will be recruited to solve the challenges regarding optimization and control.
Integration of reservoir, well, and facilities operation is needed in reservoir management for the overall optimisation of the production.
In this WP we will research numerical methods for optimal control and Nonlinear Model Predictive Control (NMPC) to develop Closed-Loop Reservoir Management (CLRM) software that can potentially be used for improving the oil recovery from oil reservoirs by water flooding.
This final work package integrates the results from the other three WPs and integrates the control and optimisation processes.
Different objective functions can be chosen to simultaneously maximize the value of the oil production and manage risks. The key novelty investigated here builds upon recent research results of risk management by a risk-return objective function known from portfolio management in financial engineering. The results demonstrate that this approach may be superior to existing approaches in making financial risk management of oil production feasible. The major task in this WP is to test the hypothesis that a return-risk bi-criterion objective function for an ensemble of reservoir models will be superior to the existing models and thus attractive for reservoir managements worldwide.