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This work presents a novel multiobjective optimization model for bitumen upgrading operations. The proposed model considers five basic upgrading stages; which are the base of any bitumen/heavy oil upgrading operation. These stages include: primary distillation, vacuum distillation, cracking, hydrotreating, and blending. The model includes different processing units per upgrading stage. Each unit includes a set of operating modes; which are defined in terms of particular products yield and energy requirements. The proposed model takes into account two competing objective functions that must be minimized: 1) operating energy costs, and 2) associated CO2 emissions. The optimization approach seeks for the optimal bitumen upgrading configuration by selecting the most suitable upgrading steps based on their corresponding unit’s operating modes. This is done to obtain a particular type of synthetic crude oil (SCO) blend according to composition specifications. The problem was modeled as a mixed-integer nonlinear program (MINLP) using the GAMS modeling system. The model was validated using historical data of the Canadian heavy oil industry. The results show that the proposed model is a practical tool to (1) select and plan the most suitable bitumen upgrading configuration according to product specifications, (2) determine the upgrading energy costs, (3) and mitigate CO2 emissions.

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