Pressure-volume-temperature analysis of Caspian oil to improve the analytical delumping procedure
DOI:
https://doi.org/10.15587/1729-4061.2024.297769Keywords:
delumping, pseudo-component, plus fraction, BIP, EoS, PVT, K-value, Caspian oilAbstract
Compositional modeling of the reservoir isn’t complete without calculations of phase equilibrium and is a complex process involving many calculations. In nature, hydrocarbons don’t occur as separate components, they’re mainly mixtures. When modeling the reservoir composition for phase equilibrium calculations, in order to reduce computational costs, in practice, hydrocarbon mixtures are grouped into pseudo-components. The number of grouped pseudo-components varies from 4 to 10. This grouping process is called lumping. However, when crude oil comes to the surface, it’s important to know its detailed composition, since mixtures grouped into pseudo-components don’t allow you to know this. In this regard, modeling of the detailed composition of hydrocarbons is the main tool for understanding the detailed phase separation and design of surface facilities. In practice, this process is called delumping. In the case of this process, the detailed composition of the fluid is presented and the amount reaches up to 36 components, sometimes more. The delumping process, due to the precise separation of heavy plus fractions into carbons with single ordinal numbers (C7, C8, etc.), makes it possible to clearly recognize non-zero BIP’s in the equation of state.
The new analytical approach has not previously been applied to the oils of the Caspian region, so this approach has an important role for the oil industry in the Caspian region. Analytical delumping in this paper was done to improve the PVT modeling. This paper presents the results of PVT research of Caspian oil and presents a comparison of analytical and numerical methods of delumping. As a result of the study, it was found that the analytical approach is in excellent agreement with experimental data and data from software such as PVTsim
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Copyright (c) 2024 Jamilyam Ismailova, Ayaulym Baibekova, Dinara Delikesheva, Aibek Abdukarimov, Alfiya Khussainova
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