Applying Grid partitioning based Fuzzy inference system as novel algorithm to predict Asphaltene precipitation. (16th February 2018)

• Record Type: Journal Article
• Authors: Zanbouri, Hosein; Ashtari Larki, Saeed; Bemani, Amin; Shokrollahzadeh Behbahani, Hassan
• Is Part Of: Petroleum science and technology. Volume 36:Number 4(2018)
• Page Start: 302
• Page End: 307
• Publication Date: 2018-02-16
• Subjects: Asphaltene -- precipitation -- predicting model -- deposition -- optimization; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2017.1421971
• Languages: English
• ISSNs: 1091-6466

Abstract

ABSTRACT: Asphaltene precipitation is one of challenging problems in petroleum and chemical engineering so the importance of investigation of Asphaltene precipitation is clear. The asphaltene deposition effects on wellbore plugging, wettability alteration and facility damages. In order to solve these problems, a novel investigation based on Grid partitioning based Fuzzy inference system algorithm to predict precipitated asphaltene in terms of dilution ratio, temperature and carbon number of precipitant was developed. The predicting algorithm performance was evaluated statistically and graphically. The coefficients of determination (R 2 ) for training and testing phases 0.9973 and 0.9900 respectively which confirm the great accuracy and high potential of predicting algorithm for estimation of precipitated asphaltene so this algorithm can be used as high accurate and simple software for prediction of asphaltene behavior in crude oil.