Economic optimization of EOR processes using knowledge-based system: Case studies

The main challenge of Enhanced Oil Recovery (EOR) processes at the prevaili ng low oil prices is to reduce the cost. An optimization methodology, combi ned with an economic model, is implemented into an expert system for optimi zing the net present value of full field development with an EOR process. T he approach is automated and combines an economic package and existing nume rical 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 r eservoir characteristics, (2) prepare appropriate input data sets to design the selected EOR process using existing numerical simulators, and (3) appl y 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 pr ocess might be profitable. The project profitability measures were used as the decisionmaking variables in an iterative approach to optimize the desig n of the EOR process. The economic analysis is based on the estimated recov ery, residual oil in-place, oil price, and operating costs. Two case studie s are presented for two reservoirs that have already been produced to their economic limits and are potential candidates for surfactant/polymer floodi ng, and carbon-dioxide flooding, respectively, or otherwise subject to aban donment. The effect of several design parameters on the project profitabili ty of these EOR processes was investigated.