The aim of this work was to demonstrate that the average chemical structure of the asphaltenes of a crude oil sample is unique compared with crudes of other wells from the Colorado Oil field, Colombia. Six crude oils extracted from several depths (from 2112 to 6178 ft) were studied; these crude oils have a very critical problem of deposition of paraffins and very low concentrations of asphaltenes (<1% w/w), although asphaltenes have been found with them in the organic deposits. To research this problem, first, we studied the chemical structure of asphaltenes; this information will be used in the future to understand the influence of asphaltene chemical structure on the crystallization of paraffins in waxy crude oils. The Colorado asphaltenes were characterized by nuclear magnetic resonance (NMR), mass spectrometry (MS), X-ray diffraction (XRD), and Raman spectroscopy to determine their main structural parameters. Average molecular parameters (AMPs) were analyzed using matrix plot, cluster analysis, and principal component analysis; it was demonstrated that the average molecular structures of asphaltenes differed from each other, and a cluster scatterplot suggests that there are four types of asphaltenes in the crude oils from the Colorado Oil field. The more extreme structural differences were between the asphaltenes of the crude oils obtained from the top sand and the bottom sand.

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In our previous articles (Energy & Fuels 2017, 31, 133−139 and Energy & Fuels 2017, 31, 8997−9005), it was presented that the asphaltenes of the Colorado field have different chemical structures, and these change the properties of crystallization of the paraffins. In this paper, we present a new way to understand the effects of the chemical structure of the asphaltenes on crude oil rheology, which includes correlating the average molecular parameters (AMPs) and the concentration of the asphaltenes with rheological properties using chemometric methods such as the partial least squares method. The asphaltenes were separated from six crude oil samples (average °API of 38) and were characterized using nuclear magnetic resonance to determine their main molecular parameters. Rheological properties including viscosity, yield stress, and gel temperature were experimentally determined for each of the crude oil samples and their respective maltenes. The results of a multivariate analysis show that the AMPs of the asphaltenes that cause the greatest effects are the ratio of peripheral aromatic carbons to aromatic carbons (C p /C ar ) and pericondensed aromatic carbons (C aaa ), which increase the gel temperature among maltenes and crude oils. The concentration of the asphaltenes (C oasf ) contributes to decreasing this property. An increase in the yield stress is mainly caused by the aliphatic chains of the asphaltenes (n) and the molecular weight (M w ), whereas C oasf causes decrease on the yield stress. Finally, the change in viscosity at 20 °C is increased by C p /C ar and is decreased by C oasf and paraffinic carbons (C s ).

Naphthenic acids and sulfur compounds cause corrosion problems in the crude distillation units. Their heterogeneity in the concentration and reactivity makes it difficult to predict the corrosivity of crude oils. In this paper, the areas of resonance signals belonging to 12 chemical shift regions of the proton nuclear magnetic resonance ( 1 H NMR) spectra of crude oils were correlated with the corrosion rate of AISI SAE 1005 carbon steel using a partial least squares regression. The corrosion rates were determined by weight loss tests at 350 °C for 12 h. In addition, a correlation to calculate the corrosion rate based only on the acidity and sulfur percentage of crude oils was proposed for the same crude oil samples. A statistical comparison of the proposed correlations indicates that the 1 H NMR-based correlation has better quality in predicting corrosivity of crude oils. The combination of 1 H NMR spectroscopy with chemometric techniques provides a fast alternative method for quantitative prediction of the corrosion rate at typical operation temperatures of crude distillation units.

Various methods were developed to predict the stability of Colombian crude oils, in which the integral areas of the resonance signals from 12 regions of 1 H nuclear magnetic resonance (NMR) spectra of 29 widely different crude oils were correlated with the stability parameter of Heithaus (P o ) and the colloidal instability index (CII). Correlations between the NMR spectra and properties were obtained using partial least-squares (PLS) regression and multiple linear regression (MLR). The prediction models for P o and CII by PLS had coefficients of determination (R 2 ) of >98 and >99%, respectively, while the crossvalidation values (CV, q 2 ) ranged from 89 to 90%, respectively. The models obtained from MLR showed a high adjusted R 2 (R 2 ad ) for P o and a lower R 2 ad for CII. The R 2 values of the prediction models for P o ranged from 97 to 98%. The use of these predictive methods is faster, more environmentally friendly, and less expensive than conventional methods. Of the set of crude oils used in this study, it was observed that the crude oils with a low tendency to precipitate asphaltenes are those with a high aromatic content and low paraffin content because they exhibited a very low CII and a very high peptizing power for asphaltenes, P o . Considering the relationship between the asphaltene content and P o and CII, asphaltenes cannot be considered negative factors for the stability of some crude oils.