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 STARS TM (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. V C 2018 American Institute of Chemical Engineers AIChE J, 00: 000-000, 2018

Experiments on Steam Injection into Preformed Steam Chambers of Various Shapes for Maximum Condensate Recovery

“…It is important to note that, perhaps due to the seminal works of Butler [1][2][3][4], many theoretical and experimental works have reported steam injection in terms of volume flow rates (see, for instance, [7,11,14,22,23]). However, to measure gas flow using a volumetric flow meter, temperature and pressure measurement are required, along with the gas density, to convert the volumetric flow into mass flow.…”