Decision analysis under uncertainty for smart well deployment

Downhole inflow control devices allow for the flexible operation of nonconventional wells. In this paper, a method for determining the optimal performance of smart wells, i.e., wells containing downhole inflow control devices, is presented. The method entails the use of a gradient-based optimization technique in conjunction with a reservoir simulator. The optimization accounts for uncertain geology as well as the risk of failure of the control devices. A decision analysis approach is presented to determine whether or not to deploy smart completions in light of these uncertainties. The overall optimization technique is applied to several example problems involving geological models with multiple geostatistical realizations and with different reliability scenarios for the control devices. It is shown that there is significant variation in the level of improvement attainable using inflow control devices and that this improvement varies with both the valve reliability and the particular geological realization. Decision-making techniques are used to quantify the benefits obtained using optimized smart wells under different risk attitudes.