With increasing world demand for energy, more attention has been given to the exploitation of the huge resources present in the form of heavy oil and bitumen. Co-injection of solvent with steam has shown to be promising in enhancing oil rates as well as in reduction of energy and water consumption with lower environmental impacts. Commercial numerical simulators are very time consuming to model and optimize the hybrid thermal-solvent oil recovery process. Semi-analytical models may be used to estimate production rates and thermal efficiency of the process in much less time compared to the numerical reservoir simulators.
This dissertation is composed of three parts, including convective mixing, gravity drainage of heavy oil and bitumen, and energy balance, all for the steam-solvent recovery process. A linear stability analysis is presented for double-diffusive convection in a horizontal and homogenous porous medium saturated with bitumen exposed to high temperature and solvent concentration. A new and more general criterion is obtained for occurrence of natural convection, considering variation of fluid viscosity and density with temperature and solvent concentration. Results show that the onset of convection is delayed for a fluid with variable viscosity. For the second part, steady-state and unsteady-state semi-analytical models are developed to predict the oil flow rate in steam-solvent assisted recovery process. Butler’s model for SAGD is modified to account for the effect of solvent co-injected with steam, considering the transverse dispersion and concentration-dependent molecular diffusion. Both models are validated against CMG-STARS™ thermal simulator. The oil rate predictions with selected solvents are in agreement with reported experimental data. In third part, equations are derived for energy consumption of the steam-solvent process for evaluation of thermal efficiency and SOR for each model.
The results from this dissertation will help to select a proper solvent for a given reservoir and bitumen properties, in terms of the oil production rate and energy efficiency. The proposed model may be used to find the optimal operation parameters, leading to an efficient design of a steam-solvent recovery process that utilizes less water and reduces the amount of energy and gas emissions per barrel of oil produced.