Smart wells optimization with history matching

Smart wells are wells that have down hole instrumentation, such as sensors and valves, on the production tubing. These wells provide the ability for both down hole monitoring and control. Down hole monitoring can be achieved through the use of sensors while control is realized with down hole valves. Once a smart well is deployed, valves can be used to independently control each segment / branch of the well in a reactive mode, such as shutting off a zone once it starts producing water, or in a defensive mode, which requires the a priori determination of valve settings. Using the latter approach, which is the method applied in this work, valve settings are determined through an optimization procedure. We show with this procedure that well instrumentation can provide over 50% gain in cumulative oil recovery over the instrumented case for systems considered here in which the geology is assumed to be known. Because the geology is not known in real applications, we couple the valve optimization procedure with history matching techniques, in which we use idealized sensor data to update the reservoir description. Up to 90% of the gain attainable with known geology is achieved for the unconditionally and conditionally generated models considered. In addition, we show that it is beneficial to use multiple historymatched models for the optimization in some cases. This is because multiple history-matched models capture the geologic uncertainty better than single history-matched models. We also introduce efficient alternative procedures to improve the speed of the overall technique. These include the use of a Levenberg-Marquardt algorithm for the optimizations.