Most investigations showed that the prevalent thermodynamic models are incapable of predicting asphaltene precipitation without extensive data fitting. This is primarily due to lack of knowledge of the asphaltene properties, its complex nature and the large number of parameters affecting precipitation. Hece, several authors tried to generate a simple and universe mathematical model in order to predict the amount of asphaltene precipitation. In spite of these efforts, the authors only considered temperature and type of solvents as the effective parameters in generating their scaling equations. The major disadvantage of these models is their inability in predicting the amount of asphaltene precipitation for different crude oils. Therefore, this deficiency contradicts to the universality of these models. In this work by performing experimental tests on different crude oils and analyzing their properties such as GOR, Resin to Asphaltene ratio, mole percent of plus fractions and residual oil density, a new scaling equation was developed for the predicting of asphaltene precipitation of different crude oil samples. The developed correlation can be used to estimate the amount of precipitated asphaltene at different dilution ratios and the onset dilution ratio of precipitation. The new scaling correlation has been validated with another experimental precipitation data generated after developing the scaling correlation.

You can access this article if you purchase or spend a download.