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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:最近的调查已经证明了更全世界的重质原油资源,如沥青,而不是传统原油。 通过将沥青注射稀释沥青,包括四烷成的这种储存器以降低沥青的密度和粘度被发现是一种有效的增强的采油方法。 本研究侧重于通过实施自适应神经模糊干扰系统技术来引入Athabasca沥青 - 四癸烷混合物的有效和鲁棒的密度预测方法,通过实施自适应神经模糊干扰系统技术。 将所提出的模型的出现结果与在不同条件下通过实验报告和基于相关的密度值进行比较。 对于平均方误差和R-2,达到0.003805和1.00的值。 因此,开发的模型被认为是一种非常适当的工具,用于沥青 - 四烷混合密度估计。

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