Decision Making Under Uncertainty in EOR: Applying the Least Squares MonteCarlo Method in Chemical EOR Implementation

Abstract

AbstractThis study introduces a decision making evaluation method for flexibility in chemical EOR. The method aims to capture the effects of dynamic uncertainties both technical and economic and produce a near-optimal policy with respect to these uncertainties as they vary with time. The evaluation method used was the Least-Squares MonteCarlo(LSM) method which is best suited for evaluating flexibility in project implementation. The decision analysed was that of finding the best time to initiate surfactant flooding during the life time of a field under uncertainty. The study was conducted on two reservoir models: 3-D homogeneous model and a 2-D heterogeneous model. The technical uncertainties considered were the residual oil saturation to the surfactant flood, surfactant adsorption and reservoir heterogeneity while the main economic uncertain parameters considered were oil price, surfactant cost and water injection and production costs. The results show that the LSM method provides a decision making tool that was able to capture the value of flexibility in surfactant flooding implementation. The LSM method provides great insight into the effect of uncertainty on decision making which can help mitigate adverse circumstances should they arise. The results found that the optimal policy obtained was reliable and that heterogeneity does affect the optimal policy. It was also possible to consider the value of information using this method.