SummaryAn integrated modeling of the cyclic steam stimulation (CSS) at the Peace River heavy-oil/oil-sand deposits in Alberta, Canada, is challenging because of the presence of compositional gradient, faulting, and bottomwater pockets, and the variations in the oil viscosity, rock dilation, fracturing, and the pay-zone-thickness variation. Both gravity and viscosity are marked by declining quality with depth, biodegradation, and compartmentalization.The high oil viscosity and low water mobility at Peace River cause low initial injectivity. High injectivity during the CSS is achieved by high-pressure injection to fail the formation mechanically and trigger fracturing and pore deformation. Moreover, the pore dilation/recompaction triggers relative permeability hysteresis.History matching of high steam injectivities is challenging when reasonable fracture lengths and rock compressibilities are used. To match injectivities, most reservoir simulations have used either a larger compressibility (“spongy-rock” approach) or long fractures. The spongy-rock approach predicts a steady increase in injection pressure, whereas during the early time of the injection cycles, injection pressures increase and then level off for most of the cycle.We describe the enhancements made in an iteratively coupled geomechanical–flow model to incorporate the modeling of both pore deformation and relative permeability hysteresis to match the injection pressures, steam injectivity, and oil/water productions from CSS at Peace River that are otherwise difficult to reproduce. The geomechanical model explains surface heave and high injectivity caused by dilation attributable to shear failure, increase in pore pressure/formation compressibility, and decrease in effective stress. A dilation pressure is specified, below which the behavior is elastic and above which a higher compressibility is used. Above a maximum porosity, further dilation is not permitted. Also, the hysteresis model calculates gridblock relative permeabilities that lie on or between the imbibition/drainage curves, making it possible to use the laboratory-derived two-phase oil–water relative permeabilities and still match the field-measured water- and oil-production volumes.By combining an iteratively coupled reservoir–geomechanical model for the CSS with stochastic workflows, including the Latin-hypercube design (LHD) and response-surface methodology (RSM), the impacts of dilation/recompaction factors (fracturing pressure, maximum injection pressure, dilation pressure, recompaction pressure, and formation compressibility) are quantified through history matching the field results and automated stochastic sensitivity analysis and uncertainty assessment.
Read full abstract