Fluid Phase Equilibria 354 (2013) 177–184 Contents lists available at SciVerse ScienceDirect Fluid Phase Equilibria jou rn al h om epage: www.elsevier.com/locate/fluid Asphaltene precipitation due to natural depletion of reservoir: Determination using a SARA fraction based intelligent model Abdolhossein Hemmati-Sarapardeh a,b , Reza Alipour-Yeganeh-Marand b , Ali Naseri b , Anoush Safiabadi b , Farhad Gharagheizi c,d , Poorandokht Ilani-Kashkouli c,d , Amir H. Mohammadi e,c,∗ a Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran b Department of Petroleum Engineering, Amirkabir University of Technology, Tehran, Iran c Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa d Department of Chemical Engineering, Buinzahra Branch, Islamic Azad University, Buinzahra, Iran e Institut de Recherche en Génie Chimique et Pétrolier (IRGCP), Paris Cedex, France a r t i c l e i n f o Article history: Received 10 February 2013 Received in revised form 31 May 2013 Accepted 5 June 2013 Available online 14 June 2013 Keywords: Asphaltene precipitation Reservoir fluid PVT Model Support vector machine Leverage approach a b s t r a c t Precipitation of asphaltene leads to rigorous problems in petroleum industry such as: wettability alter- ations, relative permeability reduction, blockage of the flow with additional pressure drop in wellbore tubing, upstream process facilities and surface pipelines. Experimentally determination of the asphal- tene precipitation is costly and time consuming. Therefore, searching for some other quick and accurate methods for determination of the asphaltene precipitation is inevitable. The objective of this communi- cation is to present a reliable and predictive model namely, the least – squares support vector machine (LSSVM) to predict the asphaltene precipitation. This model has been developed and tested using 157 series of experimental data for 32 different crude oils from a number of Iranian oil reservoirs. The ranges of data used to develop the model cover many of Iranian oil reservoirs PVT data and consequently the developed model could be reliable for prediction of other Iranian oil reservoirs’ samples. Statistical and graphical error analysis have been carried out to establish the adequacy and accuracy of the model. The results show that the developed model provides predictions in good agreement with experimental data. Furthermore, it is illustrated that the proposed method is capable of simulating the actual physical trend of the asphaltene precipitation with variation of pressure. Finally, the Leverage approach, in which the statistical Hat matrix, Williams plot, and the residuals of the model results lead to identification of the likely outliers, has been performed. Fortunately, all the experimental data seem to be reliable except five. Thus, the developed model could be reliable for prediction of the asphaltene precipitation in its applica- bility domain. This model can be implemented in any reservoir simulator software and it provides enough accuracy and performance over the existing methods. © 2013 Elsevier B.V. All rights reserved. 1. Introduction Crude oil consists of a complex mixture of hydrocarbons and other components with a wide range of molecular weights. In general, from a physicochemical point of view, it can be catego- rized into four main fractions including saturates, aromatics, resins and asphaltenes (SARA) [1–7]. Among these four ones, the lat- ter have the highest molecular weight and aromatic content, and ∗ Corresponding author at: Institut de Recherche en Génie Chimique et Pétrolier (IRGCP), Paris Cedex, France. E-mail address: a.h.m@irgcp.fr (A.H. Mohammadi). furthermore, it is the most complicated fraction which alone con- tains more than 100,000 different molecules [5,8–11]. Asphaltene is insoluble in normal alkanes such as n-heptane and n-pentane; however, it is soluble in some aromatic solvents for instance toluene, benzene and pyridine [12–17]. Due to variations in tem- perature, pressure and composition of the oil, asphaltene may precipitate out of the solution. Part of the variations in these param- eters which causes severe precipitation problems in oil or natural gas reservoirs arises from the enhanced oil recovery processes such as CO 2 injection, natural gas injection and microbial EOR [18–24]. The precipitation of asphaltene leads to rigorous problems in petroleum reservoirs, production and processing facilities, and even in gas and gas condensate operations; such as: wettability 0378-3812/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fluid.2013.06.005