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Evolving ANFIS model to estimate density of bitumen-tetradecane mixtures

机译:不断发展的ANFIS模型来估计沥青 - 四烷混合物密度

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摘要

Recent investigations have proved more worldwide availability of heavy crude oil resources such as bitumen than those with conventional crude oil. Diluting the bitumen through injection of solvents including tetradecane into such reservoirs to decrease the density and viscosity of bitumen has been found to be an efficient enhanced oil recovery approach. This study focuses on introducing an effective and robust density predictive method for Athabasca bitumen-tetradecane mixtures against pressure, temperature and solvent weight percent through implementation of adaptive neuro-fuzzy interference system technique. The emerged results of proposed model were compared to experimentally reported and correlation-based density values in different conditions. Values of 0.003805 and 1.00 were achieved for mean square error and R-2, respectively. The developed model is therefore regarded as a highly appropriate tool for the purpose of bitumen-tetradecane mixture density estimation.
机译:最近的调查证明,与传统原油相比,沥青等重质原油资源在世界范围内的可用性更高。通过向此类储层注入包括十四烷在内的溶剂来稀释沥青,以降低沥青的密度和粘度,已被发现是一种有效的提高原油采收率的方法。本研究旨在通过实施自适应神经模糊干扰系统技术,针对压力、温度和溶剂重量百分比,介绍一种有效且稳健的阿萨巴斯卡沥青-十四烷混合物密度预测方法。在不同条件下,将所提出模型的结果与实验报告和基于相关性的密度值进行了比较。均方误差和R-2的值分别为0.003805和1.00。因此,开发的模型被认为是估算沥青-十四烷混合物密度的非常合适的工具。

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