Real‐time multivariable model predictive control for steam‐assisted gravity drainage

Abstract

Thermal recovery techniques, such as steam‐assisted gravity drainage (SAGD), are used to recover the majority of the crude bitumen, in Western Canada. However, suboptimal production techniques have led to a large carbon footprint and a subsequent search for more efficient extraction techniques, than open loop manual control. This article summarizes research on the comparison of performance of a novel multi‐input multioutput (MIMO) model predictive controller (MPC) with steam trap and oil rate controls with a multi‐input single output (MISO) MPC with only steam trap control. An appropriate system identification technique was also used for periodic model update in compliance with changing system behavior. The real‐time control study was made possible by establishing a bidirectional communication between computer modeling group STARSTM (virtual reservoir) and MATLAB (onsite controller) software. The results show a 171% improvement in oil recovery for the novel MIMO MPC over the MISO MPC. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3034–3041, 2018