Simulation of numerical reservoir models with thousands and millions of grid blocks may consume a significant amount of time\nand effort, even when high performance processors are used. In cases where the simulation runs are required for sensitivity analysis,\ndynamic control, and optimization, the act needs to be repeated several times by continuously changing parameters. This makes it\neven more time-consuming. Currently, proxy models that are based on response surface are being used to lessen the time required\nfor running simulations during sensitivity analysis and optimization. Proxy models are lighter mathematical models that run faster\nand perform in place of heavier models that require large computations. Nevertheless, to acquire data for modeling and validation\nand develop the proxy model itself, hundreds of simulation runs are required. In this paper, a system identification based proxy\nmodel that requires only a single simulation run and a properly designed excitation signal was proposed and evaluated using a\nbenchmark case study. The results show that, with proper design of excitation signal and proper selection of model structure,\nsystem identification based proxy models are found to be practical and efficient alternatives for mimicking the performance of\nnumerical reservoir models. The resulting proxy models have potential applications for dynamic well control and optimization.
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