Proactive Optimization of Oil Recovery in Multilateral Wells Using Real Time Production Data

Abstract

AbstractSmart wells provide great potential to improve the recovery from hydrocarbon resources. Smart wells provide the ability to control uncertainties associated with reservoir heterogeneity. One example is to mitigate unexpected water production due to fractures and hence increase the ultimate recovery. This is achieved by selectively controlling production from multiple laterals. Due to subsurface communication between laterals that have different productivity indices, it is difficult in practice to optimize production from smart wells. The optimization of smart wells involves adjusting parameters including the settings of the downhole inflow control valves (ICV) that act as subsurface chokes.This paper focused on the reservoir engineering aspects of finding the optimum ICV configuration that optimizes reservoir performance parameters such as recovery factor and net present value. Also, the work studied the effect of heterogeneity, mainly fractures, on the optimization process. This paper also proposes a technique to quantify the effect of fractures on the optimization process and to provide recommendations of further analysis.Genetic algorithm (GA) was used as the main optimization engine to find the optimum ICV configuration. The GA was accompanied by a data library (proxy) to reduce the number of required simulation runs. A commercial reservoir simulator was used as the objective function evaluator that assesses the outcome of candidate ICV configurations.Several examples are presented to show the improvement in reservoir performance made using the optimization process. These examples include a synthetic model, and a real onshore model. Various objective functions were optimized such as water cut, and net present value.