Abstract

For thermal technologies for heavy oil and oil sand reservoir extraction, such as cyclic steam stimulation and steam-assisted gravity drainage (SAGD), suboptimal steam conformance leads to recovery factors between 25-50%. Although preliminary research using Proportional-Integral-Derivative (PID) control in SAGD operations has proved beneficial towards steam conformance, PID control is responsive only to deviation from set-points and lacks constraint-handling capabilities. This results in suboptimal actuation signals that are sometimes unattainable. This paper summarizes research on a Model-Predictive-Controller (MPC) with proactive adjustments of steam injection rate. The steam injection rate was determined based on recursive parameter updates of a suitable time varying dynamic model describing the implicit relationship between the subcool temperature difference and the input heat rate, to achieve optimal steam conformance. Furthermore, the steam injection rate was constrained such that the pressure with which the steam impinged on the formation, called well bottom hole pressure (BHP), was below the formation fracture pressure of 4500 kPa at all times. The real time control study was made possible by establishing a bidirectional communication link between the Computer Modelling Group (CMG) STARS™, and MATLAB/Simulink software. The three-dimensional heterogeneous reservoir model, developed in STARS™ acted as a virtual plant and the MPC, developed in MATLAB/Simulink, acted as an onsite controller. Results show 35.7% improvement in oil recovery and a more efficient cumulative steam-to-oil ratio (cSOR) profile in comparison to the base case of steam injection at a constant BHP of 4000 kPa.

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