Extended Natural Gas Characterization Method for Improved Predictions of Freeze-Out in LNG Production

Hassan A. Attalla (), Nour A. El-Emam, Tarek M. Aboul-Fotouh and Eric F. May ()
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Hassan A. Attalla: Mining and Petroleum Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo 11884, Egypt
Nour A. El-Emam: Mining and Petroleum Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo 11884, Egypt
Tarek M. Aboul-Fotouh: Mining and Petroleum Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo 11884, Egypt
Eric F. May: Fluid Science and Resources Division, The University of Western Australia, 35 Stirling Hwy, Crawley, Perth 6009, Australia

Energies, 2022, vol. 16, issue 1, 1-15

Abstract: The formation and the blockage of plant equipment such as heat exchangers by heavy hydrocarbon (HHC) solids is an inherent risk in cryogenic natural gas processing. The accuracy of the gas mixture’s compositional characterization significantly impacts the reliability of solid formaiton temperature predictions. Recently, we showed that complete characterization of the mixture is necessary to obtain accurate predictions of the melting temperature, as current methods based on pseudocomponent characterizations of HHCs are inadequate. Here, we present an improved method of characterizing HHCs that represents each pseudocomponent up to C 14+ by a paraffinic, isoparaffinic, naphthenic and aromatic (PINA) composition and allocates an associated defined component to represent these sub-fractions. This new, extended PINA-based characterization of HHC pseudocomponents is derived from 46 different pipeline natural gas samples, and the method is validated against three representative gas samples that were fully characterized. The melting temperatures of the three gas samples based on their full characterizations are 263.2 K (14.1 °F), 260.1 K (8.5 °F) and 248.3 K (−12.8 °F), respectively. Predictions made with the new method match these within (1 to 2) K, while previous correlation methods under-predict them by (10 to 20) K. The improved performance arises from (1) the selection of suitable discrete components to represent each PINA fraction within a pseudocomponent, (2) the more representative distribution of PINA fractions as a function of carbon number, and (3) the use of discrete components to represent the pseudocomponent’s thermodynamic properties in both the fluid and solid phases. These results show how the new characterization method can reliably predict HHC freeze-out conditions, particularly when a full compositional analysis is unavailable. Future research should aim to test the new method on natural gas samples from regions other than the US Gulf Coast.

Keywords: LNG—freeze-out—heavy hydrocarbons; pseudocomponent—compositional characterization; cryogenic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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