Application of Grid partitioning based Fuzzy inference system and ANFIS as novel approach for modeling of Athabasca bitumen and tetradecane mixture viscosity |
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Authors: | Pouya Bakhtiari Manesh Khalil Shahbazi Salman Shahryari |
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Affiliation: | 1. Department of Petroleum Engineering, Petroleum University of Technology, Ahwaz, Iran;2. Department of Petroleum Engineering, Islamic Azad University of Mahshahr, Mahshar, Iran |
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Abstract: | The heavy oil and bitumen reservoirs have effective role on supplying energy due to their availability in the world. The bitumen has extremely high viscosity so this type of reservoirs has numerous problems in production and trans- portation.one of the common approach for reduction of viscosity is injection of solvents such as tetradecane. In the present study the Grid partitioning based Fuzzy inference system was coupled with ANFIS to propose a novel algorithm for prediction of bitumen and tetradecane mixture viscosity in terms of pressure, temperature and weight fraction of the tetradecane. In the present study, the coefficients of determination for training and testing phases are determined as 0.9819 and 0.9525 respectively and the models are visualized and compared with experimental data in literature. According to the results the predicting method has acceptable accuracy for prediction of bitumen and tetradecane mixture viscosity. |
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Keywords: | bitumen tetradecane viscosity ANFIS predicting model heavy oil Grid partitioning based Fuzzy inference system |
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