Determination of Saturates, Aromatics, and Polars in Crude Oil by 13C NMR and Support Vector Regression with Variable Selection by Genetic Algorithm

Abstract

The contents of saturates, aromatics, and polars in crude oil were determined using carbon-13 nuclear magnetic resonance spectroscopy (13C NMR) associated with support vector regression (SVR) and a genetic algorithm (GA) for the simultaneous selection of spectral variables and SVR model parameters. The developed models presented prediction sample errors of 4.4% (w/w) for saturates, 4.3% (w/w) for aromatics (w/w), and 3.7% (w/w) for polars. These results are acceptable for the petroleum industry, considering that the error obtained by the standard methodology is 5% (w/w), which is the maximum value of variation allowed in SARA analysis. The proposed methodology made these determinations using small amounts of samples (approximately 2 mL) in a relatively short time (approximately 2 h).