Powered by OpenAIRE graph
Found an issue? Give us feedback
Physics of Fluidsarrow_drop_down
Physics of Fluids
Article . 2023 . Peer-reviewed
Data sources: Crossref
addClaim

Research on transient composition tracking in natural gas condensate pipeline networks

Authors: Shangfei Song; Di Fan; Yijia Fan; Bing Yan; Bohui Shi; Shengnan Zhang; Xiaofang Lv; +3 Authors

Research on transient composition tracking in natural gas condensate pipeline networks

Abstract

Offshore pipelines are hailed as the “lifeline” of an offshore oil and gas production system and are essential for offshore oil and gas development. Component tracing technologies for the oil and gas multiphase transmission pipeline networks need to be urgently developed to predict the fluid composition changes in pipeline networks. Instead of assuming the fluid components are constant, we consider they varied with flow. The component conservation equations and a phase change model are established. The equation of state of the fluid is adopted to determine the equilibrium state of each component in real time. Considering the macroscopic flow calculation, microscopic fluid components, and phase equilibrium, the component tracking algorithm is established for natural gas condensate pipeline networks, which can dynamically track the fluid composition in pipeline networks and calculate the phase exchange amount and related flow parameters in real time. Three case studies are performed to verify the effectiveness of the algorithm. These findings are of great practical significance for understanding the gas–liquid two-phase flow in pipeline networks, promoting further engineering applications of component tracking on pipeline networks.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!