Heavy-Oil Surrogate Formulation Based on FT-ICR MS Analysis

• Published in: Energy & fuels 2023-11, Vol.37 (21), p.16354-16367
• Main Authors: Guevara, Edwin, Alabbad, Mohammed, Chatakonda, Obulesu, Kloosterman, Jeffrey W., Middaugh, Joshua, Zhang, Wen, Emwas, Abdul-Hamid, Sarathy, S. Mani
• Format: Article
• Language: English
• Subjects: Traditional Fossil Fuels
• ISSN: 0887-0624; 1520-5029
• DOI: 10.1021/acs.energyfuels.3c02134

Surrogate molecules are commonly employed to represent complex mixtures to predict properties and develop chemical kinetic models. The objective of a surrogate formulation is to emulate the chemical and physical properties of a complex matrix by using either a single molecule or multiple molecules. The proposed surrogate molecule’s chemical kinetic model can be used to simulate the behavior of oil in various scenarios, such as pyrolysis and oxidation. However, creating surrogates for heavy oils demands a meticulous characterization involving numerous chemical analytical techniques, which are not only resource-intensive but also time-consuming, with their interpretation posing challenges. This study introduces a novel approach to formulate surrogate molecules for heavy oils, specifically relying on high-resolution mass spectrometry. This method facilitates the creation of one or more surrogate molecules for residual oils in a semiautomatic manner. The foundation of this methodology lies in the derivation of structure descriptors from FT-ICR MS data. The presented approach is explained in detail and successfully applied to identify both single surrogate molecules and multicomponent surrogate molecules within two residual oils obtained from Saudi Arabia. The results show that the surrogates obtained can effectively approximate the elemental composition and align well with estimated functional groups using nuclear magnetic resonance. Additionally, these surrogate molecules can predict physical properties, such as heating values, for both oils through quantitative structural property calculations. This study is expected to streamline the process of estimating surrogate molecules for heavy oils without the need for multiple analytical techniques. Consequently, this will reduce the time, cost, and subjectivity associated with conventional approaches.