Fractured Reservoirs History Matching based on Proxy Model and Intelligent Optimization Algorithms

In this paper, a new robust approach based on least square support vector machine (lssvm) as a proxy model is used for an automatic fractured reservoir history matching. the proxy model is made to model the history match objective function (mismatch values) based on the history data of the field. this model is then used to minimize the objective function through particle swarm optimization (pso) and imperialist competitive algorithm (ica). this procedure leads to matching of history of the field in which a set of reservoir parameters is used. the final sets of parameters are then applied for the full simulation model to validate the technique. the obtained results showed that due to high speed and need for little data sets, lssvm is the best tool to build a proxy model. also the comparison of pso and ica showed that pso is less time-consuming and more effective.