In recent years, several Steam Assisted Gravity Drainage (SAGD) projects have proven effective for the recovery of heavy oil and bitumen and Expanding Solvent (ES) SAGD pilot projects have shown positive indications of improved performance. This paper presents the results of a simulation study performed to investigate important aspects of the ES-SAGD process. In an ES-SAGD process, a solvent is added to the injected steam that remains in the vapor phase in the SAGD steam chamber and condenses along the walls of the steam chamber. Thus the solvent will have enough time to dissolve/disperse in the bitumen in the mobile zone before steam condensation occurs. Because the solvent blends with the bitumen, it significantly lowers (up to 5 fold) the oil viscosity. This process has the potential to accelerate recovery with less steam requirement per barrel of oil produced. The important factors that control the performance of the ES-SAGD process are the solvent type, concentration, operating pressure and the injection strategy. Results of sensitivity studies performed on each of these aspects are presented with conclusions and recommendations for operating strategy. Frequently, in heavy oil recovery processes, shear dilation has been reported as a mechanism that enhances the fluid conductivity of the reservoir medium. Even though dilation is typically adjusted as a history matching variable, one of the main problems encountered with that procedure is the huge disparity in production rates that result depending on whether the process is carried out at high or low operating pressures. The capability and limitations of the geomechanical constitutive relations used to model permeability variations with reservoir pressure, built in to the thermal simulator used for the study were explored. It is concluded that dilation is an important factor for SAGD performance at high operating pressure. In order to history match the performance of such projects, it is necessary to increase the porosity and/or permeability within a heterogeneous model and dynamic dilation factor was found to play a crucial role in matching the early time data.