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    Application of novel ANFIS-PSO approach to predict asphaltene precipitation

    , Article Petroleum Science and Technology ; Volume 36, Issue 2 , 2018 , Pages 154-159 ; 10916466 (ISSN) Keybondorian, E ; Taherpour, A ; Bemani, A ; Hamule, T ; Sharif University of Technology
    Taylor and Francis Inc  2018
    Abstract
    Asphaltene precipitation is known as one of the challenging problems in petroleum industries which have significant effects on production such as formation damage and wellbore plugging. To solve this problem, calculation of precipitated asphaltene becomes highlighted so in the present study a novel approach is proposed based on ANFIS algorithm to estimate precipitated asphaltene in terms of dilution ration, carbon number of precipitants and temperature. The particle swarm optimization (PSO) method is applied to optimize ANFIS algorithm parameters. The proposed model was evaluated based on statistical parameters and the calculated R2, AARD and RMSE for the total data are 0.90309, 9.4908 and...