Correlation for Predicting Corrosivity of Crude Oils Using Proton Nuclear Magnetic Resonance and Chemometric Methods

• Published in: Energy & fuels Vol. 29; no. 11; pp. 7595 - 7600
• Main Authors: Mejia-Miranda, Carlos, Laverde, Dionisio, Molina V, Daniel
• Format: Journal Article
• Language: English
• Published: American Chemical Society 19.11.2015
• ISSN: 0887-0624; 1520-5029
• DOI: 10.1021/acs.energyfuels.5b01359

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 (1H 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 1H NMR-based correlation has better quality in predicting corrosivity of crude oils. The combination of 1H 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.