Petroleomics by High-Resolution Mass Spectrometry: Review and Outlook

High Resolution Image Download MS PowerPoint Slide Petroleum is a complex matrix, with its physical and thermodynamic properties, as well as mixture behavior, primarily dependent on its constituents and their relative quantities. Adequate characterization of crude oil constituents is indispensable for determining its thermodynamic behavior and is of great importance for all stages of its value chain from reserve estimation to projects for production, lifting, transportation, refining, and distribution of its derivatives. Consequently, there is significant interest in conducting in-depth studies of its composition. High-resolution mass spectrometers have been employed universally to analyze petroleum, giving rise to the field of petroleomics. High-field techniques such as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and Orbitrap MS are fundamental in petroleomics studies. Nevertheless, the high resolution of these instruments introduces certain sample variations and spectral alignment challenges. To address these limitations, data processing methodologies have been developed to align, concatenate, and correct baseline distortions in the spectra of complex matrices. This article aimed to conduct a systematic investigation of the development of chemometrics (multivariate analysis, machine learning, or artificial intelligence) in petroleomics applied to high-resolution instruments such as FT-ICR MS and Orbitrap MS.