PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 1, 2026Journal of energy resources technology.1 citations

A Numerical Method for Predicting Liquid Loading of Condensate Gas Wells

View Full Paper
CXChuan XieYPYu Xin PangYHYongbo Hu

Key Points

  • The aim is to accurately predict the onset of liquid loading in condensate gas wells to optimize production.
  • Developed a CFD approach using the Euler-Euler Multi Fluid VOF model.
  • Applied Schiller-Naumann and Brackbill-CSF models to assess interactions among gas, water, and oil.
  • Conducted experiments to validate numerical results against pressure gradient measurements.
  • Evaluated the numerical model against field-measured data sets.
  • Numerical model accuracy improved to over 90%.
  • Significant agreement between numerical and experimental results.
  • Method effectively eliminates human bias in liquid loading diagnosis.

Abstract

Abstract Condensate gas wells always experience three phases (gas-water-condensate oil) flow in the wellbore, the interaction between each phase more complicate, which aggravate the liquid loading causes severe production decline. Accurately predicting the onset of liquid loading is significant in gas well production optimization. Significant efforts have been made to model liquid-loading behavior. However, few mechanistic models are capable of easily and accurately tackling the complicated flow behavior of gas-water-condensate oil three phases in the vertical wells. Based on the liquid film reversal, this study proposes an CFD approach to calculate the onset of liquid loading for condensate gas wells. First, the Euler-Euler Multi Fluid VOF model is applied to simulate the liquid film flow behavior, and the Schiller-Naumann and Brackbill-CSF model calculate the interactive effects between gas-water-oil three phases. Then, experiments are conducted to validate the numerical results, the numerical results agreed well when compared with experimental results, regarding pressure gradient measurements and critical velocity predictions. Finally, the numerical method has been evaluated against field-measured data set. The numerical method not only Improve model accuracy to over 90%, but also eliminates human bias, providing a robust tool for liquid loading diagnosis in condensate wells.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Xie et al. (2026) studied this question.

synapsesocial.com/papers/69a3d8d8ec16d51705d3007ehttps://doi.org/10.1115/1.4071252
Ask AI
Helpful
Bookmark
Share
View Full Paper