Effective workflow for optimization of intelligent well completions

Abstract

Intelligent wells provide the ability for monitoring and control of downhole environment of the wells. Downhole monitoring is achieved through sensors while control is realized with downhole valves. Recovery from intelligent wells can be improved by proper selection of candidate wells/fields and optimizing the number, location and performance of the installed Interval Control Valves. Design criteria, however, suffer from incomplete understanding of the precise determination of these parameters, their interaction and combined effects. Having known the candidate well, we presented a new workflow to optimize the number, location and performance of Interval Control Valves as the main element of intelligent wells. This is a very computationally demanding and time consuming task; therefore a proxy model is developed and applied to speed up the process. Primary evaluations show that optimization of each parameter independently is not the best practice because of their interrelation and combined effects on objective function. An integrated optimization approach is therefore developed in which all the Interval Control Valves' parameters are optimized together during the process. Considerable improvement in cumulative oil production and control of produced water is achieved by applying this method on real field data.