In oil and gas industry, quick decisions on reservoir management have a huge impact on business success. Reservoir simulation is used as a typical tool to predict field performance and analyze uncertainties for assistance on decision making. Nevertheless, history matching, as a critical step of reservoir simulation, typically requires running a numerical simulation model repeatedly with different parameter settings, which is a huge computational cost, especially for complicated geological models with numerous grid cells. For reservoir engineers, how to achieve efficient reservoir simulation by taking full advantage of field data without compromise on the simulation time is a big concern.

In this work, Smart Proxy, as a relative new proxy model type, is proposed to investigate the feasibility of fastening history matching process as an alternative. Smart Proxy is an ensemble of Artificial Intelligence and Data Mining (AI&DM) technologies that are able to learn and replicate the behavior of reservoir simulation model with high accuracy. It can be developed off line and put online for automatic history matching at high speed such that a single run can be performed in a fraction of a second (Mohaghegh 2006).

This paper presents the Smart Proxy generation and its implementation in a real oilfield simulation case named SACROC Unit. It essentially involves detailing numerical reservoir simulation and Smart Proxy generation for a naturally fractured carbonate numerical simulation model with highly complicated development stages. The developed Smart Proxy is implemented to perform automatic history matching in the designated study area of SACROC Unit. The efficient history matching has been proven to be successfully accomplished using Smart Proxy simulation. Tremendous time and efforts have been saved without any compromise on simulation accuracy compared with that of traditional numerical reservoir simulation method.

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