Applications of smart proxies for subsurface modeling

作者：SHAHKARAMI Alireza,MOHAGHEGH Shahab

摘要：Using artificial intelligence(AI) and machine learning(ML) techniques, we developed and validated the smart proxy models for history matching of reservoir simulation, sensitivity analysis, and uncertainty assessment by artificial neural network(ANN). The smart proxy models were applied on two cases, the first case study investigated the application of a proxy model for calibrating a reservoir simulation model based on historical data and predicting well production while the second case study investigated the application of an ANN-based proxy model for fast-track modeling of CO2 enhanced oil recovery, aiming at the prediction of the reservoir pressure and phase saturation distribution at injection stage and post-injection stage. The prediction effects for both cases are promising. While a single run of basic numerical simulation model takes hours to days, the smart proxy model runs in a matter of seconds, saving 98.9% of calculating time. The results of these case studies demonstrate the advantage of the proposed workflow for addressing the high run-time, computational time and computational cost of numerical simulation models. In addition, these proxy models predict the outputs of reservoir simulation models with high accuracy.

发文机构：Saint Francis University West Virginia University

关键词：smartproxymodelingreservoirsimulationmachinelearningartificialneuralnetworkhistorymatchingsensitivityanalysisoptimizationtechnologyCO2EOR

分类号： TP18[自动化与计算机技术—控制理论与控制工程]TE311[石油与天然气工程—油气田开发工程]