Abstract
Herein, a method to calculate the total sulfur concentration in petroleum samples from the chemometric modeling of data obtained by positive-ion atmospheric pressure photoionization Fourier transform ion cyclotron resonance mass spectrometry [(+) APPI FT-ICR MS] is described. Analysis by FT-ICR MS provides both a measurement of the total sulfur concentration and detailed molecular-level speciation of sulfur-containing compounds. A total of 30 crude oil samples ranging from 0.2 to 4.6 wt % sulfur were employed to train the sulfur prediction model. The ratios of the percent relative abundance (%RA) between the sulfur classes (Sx) and the hydrocarbon (HC) class were employed as variables for principal component analysis (PCA). The PCA results reveal a highly linear trend along the principal component with the highest explained variance (PC1). Analysis of the loadings plot reveals that the S1/HC ratio governs the trend in PC1. Values for PC2 are governed by S1/HC, S2/HC, and S3/HC ratios and provide the abili...
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