IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v278y2023ipbs0360544223013853.html
   My bibliography  Save this article

Pore-scale lattice Boltzmann simulation of CO2-CH4 displacement in shale matrix

Author

Listed:
  • Wu, Jian
  • Gan, Yixiang
  • Shi, Zhang
  • Huang, Pengyu
  • Shen, Luming

Abstract

This study couples the Navier-Stokes and multicomponent advection-diffusion equations within the lattice Boltzmann method (LBM) to innovatively simulate the CO2–CH4 displacement in nanoporous shale matrix. In the LBM simulations of CO2 injection into heterogenous CH4-saturated nanoporous media, gas movements are modeled by two separate advection-diffusion lattices driven by the velocity solved from the third Navier-Stokes lattice. Langmuir adsorption kinetics is employed at the fluid-solid interfaces to simulate the mass exchange between the bulk free space and the solid matrix. Mass transfer inside the solid matrix is considered with adsorption and diffusion parameters obtained from molecular dynamics studies. CO2 adsorption and CH4 desorption are simulated simultaneously. The coupling scheme is successfully validated for advection, diffusion, and surface adsorption. Results show that the global mass transfer process is sensitive to intra-matrix diffusion. When the solid diffusion rate is ∼10−4 of the bulk one, selectivity can significantly impact the outflux concentration. Changing the CO2 adsorption rate constant 0.1–10 times nearly has no impact on gas adsorption in the solids. In comparison, the CH4 desorption rate constant strongly correlates to the CH4 desorption pathway. Increasing the particle size under a given porosity may benefit advection and lead to fast adsorption/desorption in the solids.

Suggested Citation

  • Wu, Jian & Gan, Yixiang & Shi, Zhang & Huang, Pengyu & Shen, Luming, 2023. "Pore-scale lattice Boltzmann simulation of CO2-CH4 displacement in shale matrix," Energy, Elsevier, vol. 278(PB).
  • Handle: RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223013853
    DOI: 10.1016/j.energy.2023.127991
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223013853
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.127991?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Hui & Chen, Li & Qu, Zhiguo & Yin, Ying & Kang, Qinjun & Yu, Bo & Tao, Wen-Quan, 2020. "Modeling of multi-scale transport phenomena in shale gas production — A critical review," Applied Energy, Elsevier, vol. 262(C).
    2. Chen, Lei & Huang, Ding-Bin & Wang, Shan-You & Nie, Yi-Nan & He, Ya-Ling & Tao, Wen-Quan, 2019. "A study on dynamic desorption process of methane in slits," Energy, Elsevier, vol. 175(C), pages 1174-1180.
    3. Yang, Xue & Chen, Zeqin & Liu, Xiaoqiang & Xue, Zhiyu & Yue, Fen & Wen, Junjie & Li, Meijun & Xue, Ying, 2022. "Correction of gas adsorption capacity in quartz nanoslit and its application in recovering shale gas resources by CO2 injection: A molecular simulation," Energy, Elsevier, vol. 240(C).
    4. Qin, Chao & Jiang, Yongdong & Zuo, Shuangying & Chen, Shiwan & Xiao, Siyou & Liu, Zhengjie, 2021. "Investigation of adsorption kinetics of CH4 and CO2 on shale exposure to supercritical CO2," Energy, Elsevier, vol. 236(C).
    5. Yan, Min & Zhou, Ming & Li, Shugang & Lin, Haifei & Zhang, Kunyin & Zhang, Binbin & Shu, Chi-Min, 2021. "Numerical investigation on the influence of micropore structure characteristics on gas seepage in coal with lattice Boltzmann method," Energy, Elsevier, vol. 230(C).
    6. Xie, Weidong & Wang, Meng & Chen, Si & Vandeginste, Veerle & Yu, Zhenghong & Wang, Hua, 2022. "Effects of gas components, reservoir property and pore structure of shale gas reservoir on the competitive adsorption behavior of CO2 and CH4," Energy, Elsevier, vol. 254(PB).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ren, Jitian & Xiao, Wenlian & Pu, Wanfen & Tang, Yanbing & Bernabé, Yves & Cheng, Qianrui & Zheng, Lingli, 2024. "Characterization of CO2 miscible/immiscible flooding in low-permeability sandstones using NMR and the VOF simulation method," Energy, Elsevier, vol. 297(C).
    2. Kasala, Erasto E. & Wang, Jinjie & Lwazi, Hussein M. & Nyakilla, Edwin E. & Kibonye, John S., 2024. "The influence of hydraulic fracture and reservoir parameters on the storage of CO2 and enhancing CH4 recovery in Yanchang formation," Energy, Elsevier, vol. 296(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Jian & Shen, Luming & Huang, Pengyu & Gan, Yixiang, 2023. "Selective adsorption and transport of CO2–CH4 mixture under nano-confinement," Energy, Elsevier, vol. 273(C).
    2. Xie, Weidong & Wang, Hua & Vandeginste, Veerle & Chen, Si & Gan, Huajun & Wang, Meng & Yu, Zhenghong, 2023. "Thermodynamic and kinetic affinity of CO2 relative to CH4 and their pressure, temperature and pore structure sensitivity in the competitive adsorption system in shale gas reservoirs," Energy, Elsevier, vol. 277(C).
    3. Pang, Mingkun & Zhang, Tianjun & Ji, Xiang & Wu, Jinyu & Song, Shuang, 2022. "Measurement of the coefficient of seepage characteristics in pore-crushed coal bodies around gas extraction boreholes," Energy, Elsevier, vol. 254(PA).
    4. Qin, Chao & Jiang, Yongdong & Zhou, Junping & Zuo, Shuangying & Chen, Shiwan & Liu, Zhengjie & Yin, Hong & Li, Ye, 2022. "Influence of supercritical CO2 exposure on water wettability of shale: Implications for CO2 sequestration and shale gas recovery," Energy, Elsevier, vol. 242(C).
    5. Xuhua Gao & Junhong Yu & Xinchun Shang & Weiyao Zhu, 2023. "Investigation on Nonlinear Behaviors of Seepage in Deep Shale Gas Reservoir with Viscoelasticity," Energies, MDPI, vol. 16(17), pages 1-23, August.
    6. Qin, Chao & Jiang, Yongdong & Cao, Mengyao & Zhou, Junping & Song, Xiao & Zuo, Shuangying & Chen, Shiwan & Luo, Yahuang & Xiao, Siyou & Yin, Hong & Du, Xidong, 2023. "Experimental study on the methane desorption-diffusion behavior of Longmaxi shale exposure to supercritical CO2," Energy, Elsevier, vol. 262(PA).
    7. Liu, Bo & Mohammadi, Mohammad-Reza & Ma, Zhongliang & Bai, Longhui & Wang, Liu & Xu, Yaohui & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2023. "Pore structure evolution of Qingshankou shale (kerogen type I) during artificial maturation via hydrous and anhydrous pyrolysis: Experimental study and intelligent modeling," Energy, Elsevier, vol. 282(C).
    8. Li, Bo & Yu, Hao & Xu, WenLong & Huang, HanWei & Huang, MengCheng & Meng, SiWei & Liu, He & Wu, HengAn, 2023. "A multi-physics coupled multi-scale transport model for CO2 sequestration and enhanced recovery in shale formation with fractal fracture networks," Energy, Elsevier, vol. 284(C).
    9. Yang, Jinghua & Wang, Min & Wu, Lei & Liu, Yanwei & Qiu, Shuxia & Xu, Peng, 2021. "A novel Monte Carlo simulation on gas flow in fractal shale reservoir," Energy, Elsevier, vol. 236(C).
    10. Liu, Huang & Yao, Desong & Yang, Bowen & Li, Huashi & Guo, Ping & Du, Jianfen & Wang, Jian & Yang, Shuokong & Wen, Lianhui, 2022. "Experimental investigation on the mechanism of low permeability natural gas extraction accompanied by carbon dioxide sequestration," Energy, Elsevier, vol. 253(C).
    11. Wenchao Liu & Yuejie Yang & Chengcheng Qiao & Chen Liu & Boyu Lian & Qingwang Yuan, 2023. "Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs," Energies, MDPI, vol. 16(5), pages 1-30, March.
    12. Wang, Ziwei & Qin, Yong & Shen, Jian & Li, Teng & Zhang, Xiaoyang & Cai, Ying, 2022. "A novel permeability prediction model for coal based on dynamic transformation of pores in multiple scales," Energy, Elsevier, vol. 257(C).
    13. Dai, Xuguang & Wei, Chongtao & Wang, Meng & Ma, Ruying & Song, Yu & Zhang, Junjian & Wang, Xiaoqi & Shi, Xuan & Vandeginste, Veerle, 2023. "Interaction mechanism of supercritical CO2 with shales and a new quantitative storage capacity evaluation method," Energy, Elsevier, vol. 264(C).
    14. Yongzan, Wen & Guanhua, Ni & Xinyue, Zhang & Yicheng, Zheng & Gang, Wang & Zhenyang, Wang & Qiming, Huang, 2023. "Fine characterization of pore structure of acidified anthracite based on liquid intrusion method and Micro-CT," Energy, Elsevier, vol. 263(PA).
    15. Golsanami, Naser & Jayasuriya, Madusanka N. & Yan, Weichao & Fernando, Shanilka G. & Liu, Xuefeng & Cui, Likai & Zhang, Xuepeng & Yasin, Qamar & Dong, Huaimin & Dong, Xu, 2022. "Characterizing clay textures and their impact on the reservoir using deep learning and Lattice-Boltzmann simulation applied to SEM images," Energy, Elsevier, vol. 240(C).
    16. Bowen Ling & Hasan J. Khan & Jennifer L. Druhan & Ilenia Battiato, 2020. "Multi-Scale Microfluidics for Transport in Shale Fabric," Energies, MDPI, vol. 14(1), pages 1-23, December.
    17. Wei, Jianguang & Fu, Lanqing & Zhao, Guozhong & Zhao, Xiaoqing & Liu, Xinrong & Wang, Anlun & Wang, Yan & Cao, Sheng & Jin, Yuhan & Yang, Fengrui & Liu, Tianyang & Yang, Ying, 2023. "Nuclear magnetic resonance study on imbibition and stress sensitivity of lamellar shale oil reservoir," Energy, Elsevier, vol. 282(C).
    18. Fargalla, Mandella Ali M. & Yan, Wei & Deng, Jingen & Wu, Tao & Kiyingi, Wyclif & Li, Guangcong & Zhang, Wei, 2024. "TimeNet: Time2Vec attention-based CNN-BiGRU neural network for predicting production in shale and sandstone gas reservoirs," Energy, Elsevier, vol. 290(C).
    19. Tian, He & Li, Zhonghui & Liu, Zhi & Yin, Shan & Niu, Yue & Zhang, Quancong & Chen, Dong, 2024. "Visual characterization of coal gas desorption using infrared radiation," Energy, Elsevier, vol. 289(C).
    20. Tao Zhang & Shuyu Sun, 2021. "Thermodynamics-Informed Neural Network (TINN) for Phase Equilibrium Calculations Considering Capillary Pressure," Energies, MDPI, vol. 14(22), pages 1-16, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223013853. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.