Issue 65, 2020, Issue in Progress

Analysis of Xinjiang asphaltenes using high precision spectroscopy

Abstract

Asphaltenes are known for causing flow assurance problems in numerous oil fields. In this study we present a comparative spectroscopic analysis of Xinjiang heavy oil asphaltenes as part of ongoing research for an environmentally friendly and cheap chemical inhibitor. The goal is to predict the internal morphology of these asphaltenes through comparative analysis using high precision spectroscopy. Fourier transform infrared spectroscopy (FTIR), proton-nuclear magnetic resonance (H-NMR) and electrospray ionization Fourier transform ion cyclotron resonance combined with mass spectroscopy were used in this analysis. Several studies have demonstrated the enormous potential of these techniques to characterize hydrocarbons. Here we comparatively apply these techniques to characterize Xinjiang asphaltenes with reference to earlier imaging studies with atomic force and scanning tunneling microscopy to assign a structure to these asphaltenes. Results revealed the nature of the asphaltenes to be polycyclic, aromatic with both heteroatomic and metallic content. Thirteen basic and eleven non-basic/acidic nitrogen compounds fused within the aromatic network were identified. The mass distribution is in the range between 100–800 Da. H-NMR revealed various structural parameters (aromaticity and degree of unsaturation) and together with FTIR various functional groups were identified that include: ethers, sulphides, amides and sulfoxides. The predicted structures are consistent with the “island” and “aryl linked core” models.

Graphical abstract: Analysis of Xinjiang asphaltenes using high precision spectroscopy

Article information

Article type
Paper
Submitted
25 Aug 2020
Accepted
18 Oct 2020
First published
27 Oct 2020
This article is Open Access
Creative Commons BY license

RSC Adv., 2020,10, 39425-39433

Analysis of Xinjiang asphaltenes using high precision spectroscopy

X. Qiyong, K. Wyclif, P. Jingjun, R. Xiong, W. Deng, S. Zhang, J. Guo and Y. Yang, RSC Adv., 2020, 10, 39425 DOI: 10.1039/D0RA07278H

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