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Thermal recovery of coalbed methane: Modeling of heat and mass transfer in wellbores

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  • Nie, Bin
  • Sun, Sijia

Abstract

Coalbed methane (CBM) reservoirs have the characteristics of low porosity, low permeability, strong heterogeneity and high content of adsorbed gas. A large number of studies have shown that the adsorption performance of coalbed methane reservoirs on methane is significantly affected by temperature. Therefore, heat injection development of coalbed methane reservoirs has received extensive attention. This paper takes the superheated steam (SS) flow in the wellbore after fracturing the coalbed methane reservoir as the research object, and establishes a mathematical model of the SS flow. The model consists of momentum conservation equation and energy conservation equation as the main control equation, combined with auxiliary models to form a complete mathematical model. In this paper, the discrete method is used to obtain the numerical solution of the model, and then the influence of the injection parameters on the SS flow is analyzed. The research conclusions of this paper have reference significance for the development of coalbed methane reservoirs with SS injection. This study found that: (a) When the injection rate is low enough (0.2 kg/s in this paper), the effect of gravity on SS pressure is stronger than that of pressurized gas; (b) When the steam injection speed is within a certain range (0.5 kg/s in this example), the pressure of the SS first decreases and then increases, forming a U shape; (c) The SS temperature increases with increasing of injection rate. During this period, the Joule-Thompson effect replaces the heat loss effect as the main factor controlling the temperature drop of the SS; (d) In order to maintain the development advantages of SS, the SS should still have a certain degree of superheat at the bottom of the well. Therefore, the steam injection speed should not be too high (eg 0.2 kg/s in this article); (e) Therefore, with the increase of SS pressure inside the wellbore, the temperature value decreases due to the influence of Joule Thompson effect, resulting in the continuous decrease of superheat degree.

Suggested Citation

  • Nie, Bin & Sun, Sijia, 2023. "Thermal recovery of coalbed methane: Modeling of heat and mass transfer in wellbores," Energy, Elsevier, vol. 263(PD).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222027852
    DOI: 10.1016/j.energy.2022.125899
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    References listed on IDEAS

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    Cited by:

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    4. Fu, Shenguang & Wang, Liang & Li, Shuohao & Ni, Sijia & Cheng, Yuanping & Zhang, Xiaolei & Liu, Shimin, 2024. "Re-thinking methane storage mechanism in highly metamorphic coalbed reservoirs — A molecular simulation considering organic components," Energy, Elsevier, vol. 293(C).
    5. Ji, Bingnan & Pan, Hongyu & Pang, Mingkun & Pan, Mingyue & Zhang, Hang & Zhang, Tianjun, 2023. "Molecular simulation of CH4 adsorption characteristics in bituminous coal after different functional group fractures," Energy, Elsevier, vol. 282(C).
    6. Wang, Huaijing, 2023. "Modeling of multiple thermal fluid circulation in horizontal section of wellbores," Energy, Elsevier, vol. 282(C).
    7. Wei, Jianguang & Liang, Shuang & Zhang, Dong & Li, Jiangtao & Zhou, Runnan, 2023. "Frozen core experimental study on oil-water distribution characteristics at different stages of water flooding in low permeability oil reservoirs," Energy, Elsevier, vol. 278(PB).
    8. Wei, Jianguang & Zhou, Xiaofeng & Shamil, Sultanov & Yuriy, Kotenev & Yang, Erlong & Yang, Ying & Wang, Anlun, 2024. "High-pressure mercury intrusion analysis of pore structure in typical lithofacies shale," Energy, Elsevier, vol. 295(C).
    9. Cheng, Ming & Fu, Xuehai & Chen, Zhaoying & Liu, Ting & Zhang, Miao & Kang, Junqiang, 2023. "A new approach to evaluate abandoned mine methane resources based on the zoning of the mining-disturbed strata," Energy, Elsevier, vol. 274(C).
    10. Zhang, Hewei & Shen, Jian & Wang, Geoff & Li, Kexin & Fang, Xiaojie & Jing, Qu, 2023. "Differential heat transfer characteristics of coal macerals and their control mechanism: At the mesoscale," Energy, Elsevier, vol. 280(C).
    11. Min, Chao & Wen, Guoquan & Gou, Liangjie & Li, Xiaogang & Yang, Zhaozhong, 2023. "Interpretability and causal discovery of the machine learning models to predict the production of CBM wells after hydraulic fracturing," Energy, Elsevier, vol. 285(C).

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