Application of novel ANFIS-PSO approach to predict asphaltene precipitation. (17th January 2018)

• Record Type: Journal Article
• Authors: Keybondorian, Ebrahim; Taherpour, Alireza; Bemani, Amin; Hamule, Touba
• Is Part Of: Petroleum science and technology. Volume 36:Number 2(2018)
• Page Start: 154
• Page End: 159
• Publication Date: 2018-01-17
• Subjects: asphaltene -- precipitation -- ANFIS-PSO -- predicting model -- optimization; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2017.1411948
• Languages: English
• ISSNs: 1091-6466

Abstract

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 R 2, AARD and RMSE for the total data are 0.90309, 9.4908 and 7.9468. They showed the predicting algorithm performed in acceptable manner so a high accurate and simple tool was proposed to predict the precipitated asphaltene as function of Dilution ration, temperature and carbon number of precipitants.