Steam allocation for SAGD: Multi-pad multi-criteria short and long-term real-time performance management

Abstract

Optimizing steam allocation is critical for long-term performance goals in Steam-Assisted Gravity Drainage (SAGD) recovery. The steam supply mainly contributes to the economics, steam chamber conformance, greenhouse gas emissions, and ultimate bitumen recovery. Therefore, SAGD real-time optimization (RTO) must balance steam chamber development and economics to achieve long-term goals. However, in RTO, general-purpose optimization algorithms decide based on short-term responses, unlike long-term optimization processes. Using economic Key Performance Indicators (KPI) such as Net Present Value (NPV) in a single objective, the RTO determines the smallest amount of steam that results in the highest economic returns. Injecting a small amount of steam reduces steam chamber heat loss, growth, and long-term ultimate bitumen recovery. As a result, a suitable selection of critical KPIs is required to balance the development and economics of the steam chamber.This work presents a study of multiple combinations of SAGD KPIs for a multi-pad real-time steam allocation. The KPI combinations used in this study are NPV, cumulative steam-oil-ratio (cSOR), recovery factor (RF), and average pad temperature (aveTemp). A Box-Jenkins-based data-driven model simulates the SAGD recovery process, and a first principle simulator is used as a substitute for an actual reservoir. The Alternating Direction Method of Multipliers (ADMM) is proposed for multi and many-objective optimization for real-time steam allocation across multiple pads. A compromise programming approach guides the decision-makers choice of the optimum control setpoints of the non-dominated solutions on each horizon. At the end of three and half years of RTO, the optimal KPI combination is ranked based on the aggregated performance of NPV, cSOR, and RF of SAGD multi-pad steam allocation. A synthetic Western Canadian reservoir model with four pads and 33 well pairs developed from publicly available data is used for this study.The aggregated performance of this study's results showed that joint optimization of an economic and a steam chamber growth KPIs of two is better than a combination of three or four. The choice of the joint economic and steam chamber growth KPIs depends on the average pad temperature at the start of RTO to achieve optimal fluid balance in the long term. cSOR or NPV with RF joint KPI performs optimally at average pad temperatures above 90 °C, while cSOR or NPV with aveTemp below 90 °C at the start of RTO to achieve injected and produced fluid balance. Optimum economic return, recovery, and greenhouse gas emission of the SAGD process are achieved with cSOR KPI as the primary economic objective.