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Knowledge about stability of asphaltene, determined by difference index, is of significant interest because of the many problems associated with asphaltene precipitation. This study followed two parallel fuzzy strategies for estimating refractive index (RI) of crude oil and refractive index of crude oil at onset of asphaltene precipitation (PRI) from Sara fraction data. Predicted RI and PRI were then utilized for easy and fast diagnosis of asphaltene stability by dint of calculating difference index (or ΔRI = RI – PRI). The experimental data reported in the literature have been used for model developing and checking. An acceptable agreement between fuzzy predicted values and experimental data confirmed the power of fuzzy logic technique in prediction of RI, PRI, and consequent ΔRI. In this study, ΔRI was not predicted directly mainly for two reasons. First, RI and PRI contain invaluable information themselves and predicting them fulfills the need for these information when they are desired. Second, dividing the problem into two simpler parts and solving them separately enhances the terminal accuracy of prediction. Although the regression accuracy for ΔRI was not completely satisfied, the classification accuracy for discriminating between stable and unstable situations was 100%.
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Gholami et al. (2013) studied this question.
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