Scholarlink

<p>The multicomponent thermal fluid (MTF) process is a pivotal technology for enhancing heavy oil recovery. However, its injection often triggers particle migration and deposition within reservoirs, leading to permeability impairment, reduced displacement efficiency, and potential wellbore blockages. This study investigates the particle migration mechanisms during MTF-assisted heavy oil displacement, employing a combined approach of numerical simulation and physical modeling. To account for electrically enhanced thermal methods, the analysis extends to heating effects on fluid rheology, as electrical heating can directly regulate fluid viscosity and injection rate, which are the dominant factors controlling particle migration dynamics. Utilizing the geological data from Block M of a specific oilfield, a porous media model featuring “wormhole” structures was constructed using the radius expansion method. A rheological model for the MTF-heavy oil system was developed, integrating viscosity-temperature profiles and PVT data, with particle migration simulated via the CFD-DEM coupling method. The research elucidates the impact mechanisms of key operational parameters, including injection rate, fluid viscosity (influenced by thermal input), and particle density. A predictive mathematical model for particle migration distance was established and validated. Results indicate that the factors affecting migration distance are ranked in the following order: fluid injection rate &gt; fluid viscosity &gt; particle density &gt; porosity &gt; particle diameter. Injection rate, fluid viscosity, and porosity exhibit a positive correlation with migration distance, whereas particle density and diameter show a negative correlation. By linking thermal fluid dynamics to parameters controllable in electrically assisted heating processes, this study provides theoretical guidance for optimizing operation parameters of electrically assisted MTF recovery and mitigating reservoir damage induced by particle migration. The findings offer significant insights for promoting the efficient development of heavy oil resources, particularly in the context of hybrid thermal-electrical recovery technologies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Particle migration dynamics in heavy oil recovery using multicomponent thermal fluid: an integrated simulation study with implications for electrical heating applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月29日

查看全文
  • Haizhong Yang,
  • Zhipeng Li,
  • Tian Zhou,
  • Zetao Sun,
  • Hui Xu,
  • Zhuwei Tao,
  • Shengda Zhang

摘要

The multicomponent thermal fluid (MTF) process is a pivotal technology for enhancing heavy oil recovery. However, its injection often triggers particle migration and deposition within reservoirs, leading to permeability impairment, reduced displacement efficiency, and potential wellbore blockages. This study investigates the particle migration mechanisms during MTF-assisted heavy oil displacement, employing a combined approach of numerical simulation and physical modeling. To account for electrically enhanced thermal methods, the analysis extends to heating effects on fluid rheology, as electrical heating can directly regulate fluid viscosity and injection rate, which are the dominant factors controlling particle migration dynamics. Utilizing the geological data from Block M of a specific oilfield, a porous media model featuring “wormhole” structures was constructed using the radius expansion method. A rheological model for the MTF-heavy oil system was developed, integrating viscosity-temperature profiles and PVT data, with particle migration simulated via the CFD-DEM coupling method. The research elucidates the impact mechanisms of key operational parameters, including injection rate, fluid viscosity (influenced by thermal input), and particle density. A predictive mathematical model for particle migration distance was established and validated. Results indicate that the factors affecting migration distance are ranked in the following order: fluid injection rate > fluid viscosity > particle density > porosity > particle diameter. Injection rate, fluid viscosity, and porosity exhibit a positive correlation with migration distance, whereas particle density and diameter show a negative correlation. By linking thermal fluid dynamics to parameters controllable in electrically assisted heating processes, this study provides theoretical guidance for optimizing operation parameters of electrically assisted MTF recovery and mitigating reservoir damage induced by particle migration. The findings offer significant insights for promoting the efficient development of heavy oil resources, particularly in the context of hybrid thermal-electrical recovery technologies.