A Physics-Based Data-Driven Numerical Model for Reservoir History Matching and Prediction With a Field Application

作者:Zhao, Hui*; Kang, Zhijiang; Zhang, Xiansong; Sun, Haitao; Cao, Lin; Reynolds, Albert C.
来源:SPE Journal, 2016, 21(6): 2175-2194.
DOI:10.2118/173213-PA

摘要

We derive and implement an interwell-numerical-simulation model (INSIM), which can be used as a calculation tool to approximate the performance of a reservoir under waterflooding. In INSIM, the reservoir is characterized as a coarse model consisting of a number of interwell control units, where each unit has two specific parameters: transmissibility and control pore volume (PV). By solving the mass-material-balance and front-tracking equations for the control units, the interwell fluid rates and saturations are obtained so that phase-producing rates can be predicted. The ability of INSIM to predict water cut and phase rates is the most important innovation included in INSIM. INSIM is applied to perform history matching and to infer the interwell connectivity and geological characteristics. INSIM has a number of advantages. First, the model parameters estimated from history matching provide a relative characterization of interwell-formation properties. The model can handle changes in the flow directions caused by changing well rates, including shutting in wells or converting producers to injectors, whereas with the common correlation- based interwell-connectivity method, the well interactions are assumed to be fixed. Second, the previous methods, which have similar computational complexity to INSIM, can only provide the total liquid-production rate, whereas with our procedure, we can calculate the oil-and water-flow rates and hence history match water-cut data. Third, because we can calculate the oil-and water-flow rates, our method can be used for waterflooding optimization but with far-less computational effort than with the traditional method by use of a reservoir simulator.