High-Temperature Solvent Injection for Heavy-Oil Recovery From Oil Sands: Determination of Optimal Application Conditions Through Genetic Algorithm

Summary Our recent experimental studies on superheated solvent injection for heavy-oil recovery showed that when a solvent is injected into the reservoir, the process is highly sensitive to pressure and temperature. The effects of these parameters on the recovery factor (RF) are accentuated when the operating conditions are closer to the saturation curve of the solvent injected. This paper investigates this process and formulates the optimal field-scale application conditions that yield the maximum profit, as a continuation of previous work. To achieve this, a hypothetical field-scale numerical model was constructed, and the key parameters identified through the aforementioned sensitivity analysis were incorporated. Then, the injection process was simulated for a two-horizontal injection/production pattern. An optimization study was performed to identify the relative contributions of the effective parameters (pressure, temperature, and injection rate) and to propose an optimal application scheme with a genetic algorithm (GA). The critical pressure and temperature yielding maximum production and highest profit considering solvent retrieval were defined for different injection rates and application scenarios. Our results indicate that, at the end of the hot solvent-injection process, an important volume of solvent is left in the reservoir, and its volume depends on the injection–production scheme selected. Nevertheless, if the project is performed under appropriately selected operational parameters (obtained through the optimization processes) and followed by the proper process to retrieve the solvent from the reservoir (low-temperature steam or hot-water applications), it can make the hot solvent-injection process profitable.