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State-of-the-art modeling permeability of the heterogeneous carbonate oil reservoirs using robust computational approaches

机译:使用稳健的计算方法的非均相碳酸盐储层的最先进的建模渗透性

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The current study is aimed at developing straightforward and robust models for permeability prediction in heterogeneous carbonate oil reservoirs. Two heuristic methods including Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP) were utilized to model the formation permeability with respect to the static parameters including porosity, irreducible water saturation, and pore specific surface area. To do this, the required data points were assembled from the literature and were classified into the training and test data sets. After rigorous processing, two unique GMDH and GEP derived models were proposed for the first time for fulfilling the scope of this work. The validity of the new suggested models was examined by utilizing various statistical parameters integrated with visual analysis. Consequently, the results of the analysis reveal the high exactness of the aforementioned GMDH and GEP models by Average Absolute Relative Deviations (AARD %) of 37.15% and 16.55%, respectively. Implementing a comprehensive data and error assessment prove that GEP based model provides the most accurate forecast of permeability than all the available and generally published correlations for permeability. This is due to the fact that existing models are mainly developed for the sandstone reservoirs over a restricted range of parameters; whereas, the proposed tools are created for heterogeneous carbonate reservoirs over a comprehensive databank. The results of sensitivity analysis demonstrate the high impact value of irreducible water saturation and pore specific surface area on the modeling process. Moreover, the validity of the database and GEP modeling is verified by Williams' method, in which about 95% of data are located in a valid region. To end with, reliable methods for permeability calculation as the most eminent feature of the porous media are proposed here, which can be integrated with simulators or any modeling study dealing with fluid flow in heterogeneous carbonate reservoirs.
机译:目前的研究旨在为异均碳酸盐油藏的渗透预测发育直接和稳健的模型。包括数据处理(GMDH)和基因表达编程(GEP)的组方法包括群体方法的两个启发式方法,用于模拟相对于包括孔隙,不可缩短的水饱和度和孔比表面积的静态参数的形成渗透性。为此,从文献组装所需的数据点并被分类为培训和测试数据集。经过严格的处理后,首次提出了两个独特的GMDH和GEP衍生模型,以满足这项工作的范围。通过利用与可视分析集成的各种统计参数来检查新建议模型的有效性。因此,分析结果揭示了上述GMDH和GEP模型的高精度,平均绝对相对偏差(AARD%)分别为37.15%和16.55%。实施全面的数据和错误评估证明了基于GEP的模型提供了比所有可用的所有可用和通常公布的渗透性相关性的最准确的渗透性预测。这是由于现有模型主要为砂岩储层在受限制的参数范围内开发;虽然,所拟议的工具是在综合数据库上为异质碳酸盐储层而创建的。敏感性分析结果证明了不可缩短的水饱和度和孔隙特异性表面积的高冲击值。此外,威廉姆斯的方法验证了数据库和GEP建模的有效性,其中约95%的数据位于有效区域。为了结束,这里提出了作为多孔介质的最卓越特征的可靠性计算方法,其可以与模拟器或处理异质碳酸盐储层中的流体流动的任何建模研究集成。

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