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Application of fuzzy c-means algorithm as a novel method to predict density of mixtures of Athabasca bitumen and heavy n-alkane
Authors:Houman Darvish  Pejman Ghani  Mohsen Zare  Hesam Rezaei
Affiliation:1. Department of Petroleum Engineering, Marvdasht branch, Islamic Azad University, Marvdasht, Iran;2. Department of Petroleum Engineering, Fars Science and Research Branch, Islamic Azad University, Marvdasht, Iran
Abstract:The significant number of oil reservoir are bitumen and heavy oil. One of the approaches to enhance oil recovery of these types of reservoir is dilution of reservoir oil by injection of a solvent such as tetradecane into the reservoirs to modify viscosity and density of reservoir fluids. In this investigation, an effective and robust estimating algorithm based on fuzzy c-means (FCM) algorithm was developed to predict density of mixtures of Athabasca bitumen and heavy n-alkane as function of temperature, pressure and weight percent of the solvent. The model outputs were compared to experimental data from literature in different conditions. The coefficients of determination for training and testing datasets are 0.9989 and 0.9988. The comparisons showed that the proposed model can be an applicable tool for predicting density of mixtures of bitumen and heavy n-alkane.
Keywords:bitumen  tetradecane  fuzzy c-means  density  predicting model  EOR
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