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A limited number of laboratory and field evidences showed that steam-solvent coinjection can lead to a higher oil production rate, higher ultimate oil recovery, and lower steam-oil ratio, compared with steam-only injection. However, a critical question still remains unanswered: Under what circumstances the above mentioned benefits can be obtained when steam and solvent are coinjected? To answer this question requires a detailed knowledge of the mechanisms involved in coinjection and reflection of this knowledge to its numerical simulation. Our earlier studies demonstrated that the determining factors for improved oil production rates are relative positions to the temperature and solvent fronts, the steam and solvent contents of the chamber at its interface with reservoir bitumen, and solvent diluting effects on the mobilized bitumen just ahead of the chamber edge. Then, the key mechanisms for improved oil displacement are solvent propagation, solvent accumulation at the chamber edge, and phase transition. This paper deals with this unanswered question by deriving a systematic workflow for selecting an optimum solvent and its concentration in coinjection of a single-component solvent with steam. The optimization considers the oil production rate, ultimate oil recovery, and solvent retention in situ. Multiphase behavior of water-hydrocarbon mixtures in the chamber is explained in detail analytically and numerically. The proposed workflow is applied to simulation of the Senlac SAP pilot project to investigate reasons for its success. Results show that an optimum volatility of solvent can be typically observed in terms of the oil production rate for given operation conditions. This optimum volatility occurs as a result of the balance between two factors affecting the oil mobility along the chamber edge; i.e., reduction of the chamber-edge temperature and superior dilution of oil in coinjection of more volatile solvent with steam. It is possible to maximize oil recovery while minimizing solvent retention in situ by controlling the concentration of a given coinjection solvent. Initiation of coinjection right after achieving the inter-well communication enables the enhancement of oil recovery early in the process. Subsequently, the solvent concentration should be gradually decreased until it becomes zero for the final period of the coinjection. Simulation case studies show the validity of the oil recovery mechanisms described.

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Steam-Assisted Gravity Drainage (SAGD) is a widely used thermal recovery technique in western Canada. Use of numerical simulators, although successful in history-matching and performance prediction of the process, is extremely time consuming for field-scale optimization purposes. Therefore, analytical and semi-analytical models are desirable tools for quick field-wide performance forecast. The first theoretical study of SAGD was conducted by Butler et al. (1981). An elegant analytical model was developed to estimate the oil production rate of a laterally spreading steam chamber, assuming a steady-state mode of thermal conduction beyond the advancing steam front. This model has been the basis for all other SAGD analytical/semi-analytical studies. The model was later modified by Butler and Stephens (1981) and Butler (1985) to overcome the shortcomings of the steady-state heat transfer assumption. The majority of the analytical models of SAGD to date, assume that steam chamber has reached the over-burden from the start of the process and that it can only grow sideways. In real applications, however, steam chamber will rise vertically during its early stages of development. Therefore, these models are not capable of capturing the physics of the vertical growth phase adequately and their estimations of the oil production rate and steam oil ratio (SOR) may be questionable. A uniform steam chamber development during the vertical growth is crucial to an efficient SAGD process during the rest of the project's lifetime. Therefore, it is important to have a reliable estimation of the performance of this phase. In this work, the unsteady-state SAGD model of Butler (1985) has been modified to include the vertical growth phase. Darcy's law and material balance were combined to estimate the oil production rate and steam chamber growth. Energy balance was then used to estimate SOR. Validation of the estimations for oil production rate, steam chamber shape and SOR from this new model against the results of fine-scale numerical simulation indicates that the model has successfully captured the primary physics of the vertical growth phase. The model also predicts a more accurate in-situ distribution of thermal energy and SOR compared to the original model of Butler (1985). A closed form solution is possible for oil production rate, chamber height and SOR under some simplifying assumptions during the vertical growth phase; however, a numerical approach is required beyond this phase. The mathematics are simple enough to allow coding with simple computer programs to yield quick realistic field-scale performance predictions.

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