Abstract
Based on the analysis and generalization of literature data, results of the classification of difficult to recover oil selected from Uzen, Zhetibay, Kalamkas, Karakudyk and Karamandybas oil fields of Kazakhstan using fuzzy cluster analysis are presented. Classification of types of difficult to recover oil is considered according to a set of features, including content of sulfur, chlorides, oil density, oil viscosity, permeability of occurrence conditions. Analysis of the classification results of difficult to recover reserves was performed, which showed the need to divide the total sample (set) into homogeneous groups according to a set of classification criteria, for which fuzzy cluster analysis is most suitable. A parameter characterizing the quality of oil is proposed.
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Karazhanova, M.K., Zhetekova, L.B., Aghayeva, K.K. (2020). Quality Assessment of Oil that Difficult to Recover Based on Fuzzy Clustering and Statistical Analysis. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M., Sadikoglu, F. (eds) 10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions - ICSCCW-2019. ICSCCW 2019. Advances in Intelligent Systems and Computing, vol 1095. Springer, Cham. https://doi.org/10.1007/978-3-030-35249-3_32
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DOI: https://doi.org/10.1007/978-3-030-35249-3_32
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