ECONOMIC OPTIMIZATION OF EOR PROCESSES USING KNOWLEDGE-BASED SYSTEM: CASE STUDIES

The main challenge of Enhanced Oil Recovery (EOR) processes at the prevailing low oil prices is to reduce the cost. An optimization methodology, combined with an economic model, is implemented into an expert system for optimizing the net present value of full field development with an EOR process. The approach is automated and combines an economic package and existing numerical reservoir simulators to optimize the design of a selected EOR process using sensitivity analysis. The EOR expert system includes three stages of consultations: (1) select an appropriate EOR process on the basis of the reservoir characteristics, (2) prepare appropriate input data sets to design the selected EOR process using existing numerical simulators, and (3) apply the discounted-cash-flow methods to the optimization of the selected EOR process to find out under what conditions at current oil prices this EOR process might be profitable. The project profitability measures were used as the decision-making variables in an iterative approach to optimize the design of the EOR process. The economic analysis is based on the estimated recovery, residual oil in-place, oil price, and operating costs. Two case studies are presented for two reservoirs that have already been produced to their economic limits and are potential candidates for surfactant/polymer flooding, and carbon-dioxide flooding, respectively, or otherwise subject to abandonment. The effect of several design parameters on the project profitability of these EOR processes was investigated.