Applying FCM-ANFIS algorithm as a novel computational method for prediction of viscosity of bitumen and heavy alkane mixture |
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| Authors: | Mohammad Hosein Emami Baghdadi Houman Darvish Hosein Zanbouri Karim Rouhibakhsh |
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| Affiliation: | 1. Department of Petroleum Engineering, Marvdasht branch, Islamic Azad University, Marvdasht, Iran;2. Department of Instrumentation and Automation Engineering, Petroleum University of Technology, Ahwaz, Iran;3. Department of Petroleum Engineering, School of chemical, petroleum and Gas Eng., Shiraz University, Shiraz, Iran |
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| Abstract: | Recently the studies expressed that the noticeable number of oil reservoirs in all over the world are heavy oil and bitumen reservoirs. So the importance of enhancement of oil recovery (EOR) processes for heavy oil and bitumen reservoirs is highlighted. The Dilution of the reservoir fluid by solvents such as tetradecane is one of well-known methods for these types of reservoirs which effects oil recovery by decreasing viscosity. In the present study, Fuzzy c-means (FCM) algorithm was coupled with Adaptive neuro-fuzzy inference system (ANFIS) to predict viscosity of bitumen and tetradecane in terms of temperature, pressure and weight percent of tetradecane. The coefficients of determination for training and testing steps were calculated such as 0.9914 and 0.9613. The comparison of results and experimental data expressed that FCM-ANFIS algorithm has great potential for estimation of viscosity of bitumen and tetradecane. |
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| Keywords: | bitumen enhanced oil recovery FCM-ANFIS tetradecane viscosity |
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