(125e) Optimal Flow Control for Oil Production Under Gas Coning Conditions in Oil-Rim Reservoirs
Motivated by these considerations, we propose a model-based control framework to maximize the oil production from the oil-rim reservoir during the super-critical phase. For this purpose, we first develop a first principles model to describe the gas-coning behavior, particularly the spatiotemporal evolution of GOR and GOC, which is determined by the oil extraction rate. Second, the data generated from the high-fidelity model is used to construct a reduced-order model (ROM). The ROM is used to design a Kalman filter that will utilize the real-time measurements at the wellbore to estimate GOR and GOC at the locations where the measurements are not available. Third, model predictive control (MPC) theory is applied in the receding horizon fashion for the design of a feedback control system that manipulates the oil extraction rate at the wellbore to maximize the net present value (NPV) of the produced oil in the super-critical phase. In the controller, we will explicitly consider practical constraints such as the actuator limitation and a limit on GOR for economically-feasible operations. Lastly, the developed feedback control system will be compared with the traditional back-stepping methods during the super-critical phase.
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