Dual Control of Permeability-Viscosity in Coalbed CO(2) Flow: Carbon Safety Supervision Assessment for Optimized Sequestration

煤层气CO₂流动渗透性-粘度双重控制:优化封存的碳安全监管评估

阅读:1

Abstract

Geological sequestration of CO(2) in coal seams is one of the effective methods to reduce carbon emissions. However, the combined effects of evolving CO(2) viscosity and the inherently low permeability of coal reservoirs can significantly inhibit CO(2) flow capacity, thereby affecting the overall storage efficiency. The dynamic dual-control mechanisms governing CO(2) migration in coal seams remain insufficiently understood. The analysis of dynamic dual-control weights influencing CO(2) flow behavior is focused on in this study. On this basis, a mathematical model is developed and numerical simulations are conducted. The model captures the transient evolution of CO(2) viscosity and the permeability of coal seams during the sequestration process and investigates the coupling relationship between CO(2) properties and coal seam permeability. Two mathematical decomposition methodsthe logarithmic decomposition method and the finite difference decomposition methodare employed to perform parameter decoupling analysis of CO(2) migration in coal seams. The dynamic coupling characteristics between permeability and viscosity are elucidated, and the dominant influence weights of their evolution on the CO(2) flow field are quantitatively evaluated. The study clarifies the stage-dependent control of fluid migration: permeability dominates initially, viscosity gains influence midstage, and both reach dynamic equilibrium over time. A dynamic dual-control weighting approach is proposed to optimize injection strategies, aiming to enhance CO(2) mobility and storage efficiency in an economically viable manner. The findings provide a theoretical basis for the accurate performance assessment of CO(2) sequestration in coal seams.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。