A compositional reservoir simulation study was performed to investigate enhanced oil recovery and sequestration of carbon dioxide. Maximizing profit from oil recovery and maximizing the amount of carbon dioxide stored in the reservoir are competing goals and both will be important in the future. Both depend on large number of parameters and the strategy used to flood the reservoir. A very large number of simulations are required to understand and evaluate different strategies for each reservoir and for each realization of the properties of a particular reservoir. In this study the effects of variety of flood design variables on both EOR and sequestration objectives were investigated in sandstone and carbonate reservoirs separately. Experimental design and the method of response surfaces were used as tools to perform this study in a systematic and efficient way. Design parameters such as well spacing, different injection and production schemes, various well control techniques, and different mobility control methods were selected for study. By applying fractional factorial design and D-optimal methods, simulation cases were selected to study the effect of the parameters for each scenario. The amount of CO2 stored at the end of the oil recovery process and the net present value of the each sensitivity case were considered as the two decision criteria. Economic analysis for all of these cases were performed based on the necessity to account for CO2 storage factors such as capture and transportation costs, and possible CO2 tax credits for storage. Response surface analysis was utilized to determine the best strategy based upon these decision criteria for different type of the reservoirs. The result using this approach was similar to the result from an exhaustive simulation study, but took much less computation time and effort. An approach that is both realistic and feasible, such as the one used in this study, will be needed for future simulation studies because of the increasing importance of CO2 geological storage, the extremely wide variety of reservoir conditions of potential interests, the need to understand and reduce uncertainties, the need to find better operational strategies, and the uncertainty in future economic and regulatory incentives.

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