IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v258y2022ics0360544222017492.html
   My bibliography  Save this article

A relative permeability model considering nanoconfinement and dynamic contact angle effects for tight reservoirs

Author

Listed:
  • Tian, Weibing
  • Wu, Keliu
  • Chen, Zhangxin
  • Gao, Yanling
  • Li, Jing
  • Wang, Muyuan

Abstract

With a sharp reduction in conventional oil and gas resources, tight oil and gas resources have attracted great interest in the petroleum industry. Relative permeability plays an important role in modeling fluid flow in tight reservoirs. Here, considering the nanoconfinement effects (abnormal viscosity effect (AVE) and slip effect) and dynamic contact angle (DCA) effect, a relative permeability model for tight reservoirs is proposed. The results show that the proposed model can accurately describe the relative permeability in tight reservoirs. As the AVE of water or oil increases, the relative permeability of water decreases, while the relative permeability of oil hardly changes for rocks with an average pore radius of 298 nm and decreases for the ones with an average pore radius of 49 nm. As the slip length of oil increases, the relative permeabilities of both water and oil decrease. As the DCA effect increases, the relative permeability of water increases, while the relative permeability of oil is unchanged. With a decrease in the pore size, the nanoconfinement effects on relative permeability become more notable, while the DCA effect on relative permeability becomes smaller. This work is of great significance to the development of tight reservoirs.

Suggested Citation

  • Tian, Weibing & Wu, Keliu & Chen, Zhangxin & Gao, Yanling & Li, Jing & Wang, Muyuan, 2022. "A relative permeability model considering nanoconfinement and dynamic contact angle effects for tight reservoirs," Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:energy:v:258:y:2022:i:c:s0360544222017492
    DOI: 10.1016/j.energy.2022.124846
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222017492
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.124846?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, H.D. & Chen, Y. & Ma, G.W., 2020. "Effects of capillary pressures on two-phase flow of immiscible carbon dioxide enhanced oil recovery in fractured media," Energy, Elsevier, vol. 190(C).
    2. Cai, Mingyu & Su, Yuliang & Elsworth, Derek & Li, Lei & Fan, Liyao, 2021. "Hydro-mechanical-chemical modeling of sub-nanopore capillary-confinement on CO2-CCUS-EOR," Energy, Elsevier, vol. 225(C).
    3. Psaltis, Steven & Farrell, Troy & Burrage, Kevin & Burrage, Pamela & McCabe, Peter & Moroney, Timothy & Turner, Ian & Mazumder, Saikat, 2015. "Mathematical modelling of gas production and compositional shift of a CSG (coal seam gas) field: Local model development," Energy, Elsevier, vol. 88(C), pages 621-635.
    4. Zhao, Yuechao & Zhang, Yuying & Lei, Xu & Zhang, Yi & Song, Yongchen, 2020. "CO2 flooding enhanced oil recovery evaluated using magnetic resonance imaging technique," Energy, Elsevier, vol. 203(C).
    5. Jeong, Gu Sun & Lee, Jaehyoung & Ki, Seil & Huh, Dae-Gee & Park, Chan-Hee, 2017. "Effects of viscosity ratio, interfacial tension and flow rate on hysteric relative permeability of CO2/brine systems," Energy, Elsevier, vol. 133(C), pages 62-69.
    6. Suekane, Tetsuya & Soukawa, Shingo & Iwatani, Satoshi & Tsushima, Shoji & Hirai, Shuichiro, 2005. "Behavior of supercritical CO2 injected into porous media containing water," Energy, Elsevier, vol. 30(11), pages 2370-2382.
    7. Ajayi, Temitope & Awolayo, Adedapo & Gomes, Jorge S. & Parra, Humberto & Hu, Jialiang, 2019. "Large scale modeling and assessment of the feasibility of CO2 storage onshore Abu Dhabi," Energy, Elsevier, vol. 185(C), pages 653-670.
    8. De Silva, G.P.D. & Ranjith, P.G. & Perera, M.S.A. & Dai, Z.X. & Yang, S.Q., 2017. "An experimental evaluation of unique CO2 flow behaviour in loosely held fine particles rich sandstone under deep reservoir conditions and influencing factors," Energy, Elsevier, vol. 119(C), pages 121-137.
    9. Wang, Yanji & Li, Hangyu & Xu, Jianchun & Liu, Shuyang & Wang, Xiaopu, 2022. "Machine learning assisted relative permeability upscaling for uncertainty quantification," Energy, Elsevier, vol. 245(C).
    10. Wang, Jinkai & Feng, Xiaoyong & Wanyan, Qiqi & Zhao, Kai & Wang, Ziji & Pei, Gen & Xie, Jun & Tian, Bo, 2022. "Hysteresis effect of three-phase fluids in the high-intensity injection–production process of sandstone underground gas storages," Energy, Elsevier, vol. 242(C).
    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. Tian, Weibing & Wu, Keliu & Feng, Dong & Gao, Yanling & Li, Jing & Chen, Zhangxin, 2023. "Dynamic contact angle effect on water-oil imbibition in tight oil reservoirs," Energy, Elsevier, vol. 284(C).
    2. 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.

    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. Zhang, Xue & Su, Yuliang & Li, Lei & Da, Qi'an & Hao, Yongmao & Wang, Wendong & Liu, Jiahui & Gao, Xiaogang & Zhao, An & Wang, Kaiyu, 2022. "Microscopic remaining oil initiation mechanism and formation damage of CO2 injection after waterflooding in deep reservoirs," Energy, Elsevier, vol. 248(C).
    2. Hao, Yongmao & Li, Zongfa & Su, Yuliang & Kong, Chuixian & Chen, Hong & Meng, Yang, 2022. "Experimental investigation of CO2 storage and oil production of different CO2 injection methods at pore-scale and core-scale," Energy, Elsevier, vol. 254(PB).
    3. An, Qiyi & Zhang, Qingsong & Li, Xianghui & Yu, Hao & Yin, Zhanchao & Zhang, Xiao, 2022. "Accounting for dynamic alteration effect of SC-CO2 to assess role of pore structure on rock strength: A comparative study," Energy, Elsevier, vol. 260(C).
    4. Mahmoodpour, Saeed & Amooie, Mohammad Amin & Rostami, Behzad & Bahrami, Flora, 2020. "Effect of gas impurity on the convective dissolution of CO2 in porous media," Energy, Elsevier, vol. 199(C).
    5. Ren, Bo & Trevisan, Luca, 2020. "Characterization of local capillary trap clusters in storage aquifers," Energy, Elsevier, vol. 193(C).
    6. Procesi, M. & Cantucci, B. & Buttinelli, M. & Armezzani, G. & Quattrocchi, F. & Boschi, E., 2013. "Strategic use of the underground in an energy mix plan: Synergies among CO2, CH4 geological storage and geothermal energy. Latium Region case study (Central Italy)," Applied Energy, Elsevier, vol. 110(C), pages 104-131.
    7. Zhang, Xue & Li, Lei & Su, Yuliang & Da, Qi'an & Fu, Jingang & Wang, Rujun & Chen, Fangfang, 2023. "Microfluidic investigation on asphaltene interfaces attempts to carbon sequestration and leakage: Oil-CO2 phase interaction characteristics at ultrahigh temperature and pressure," Applied Energy, Elsevier, vol. 348(C).
    8. 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).
    9. Meiheriayi Mutailipu & Qingnan Xue & Tao Li & Yande Yang & Fusheng Xue, 2023. "Thermodynamic Properties of a Gas–Liquid–Solid System during the CO 2 Geological Storage and Utilization Process: A Review," Energies, MDPI, vol. 16(21), pages 1-30, October.
    10. 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).
    11. Buttinelli, M. & Procesi, M. & Cantucci, B. & Quattrocchi, F. & Boschi, E., 2011. "The geo-database of caprock quality and deep saline aquifers distribution for geological storage of CO2 in Italy," Energy, Elsevier, vol. 36(5), pages 2968-2983.
    12. 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).
    13. Chen, Hao & Liu, Xiliang & Zhang, Chao & Tan, Xianhong & Yang, Ran & Yang, Shenglai & Yang, Jin, 2022. "Effects of miscible degree and pore scale on seepage characteristics of unconventional reservoirs fluids due to supercritical CO2 injection," Energy, Elsevier, vol. 239(PC).
    14. Li, Weicheng & Vaziri, Vahid & Aphale, Sumeet S. & Dong, Shimin & Wiercigroch, Marian, 2021. "Energy saving by reducing motor rating of sucker-rod pump systems," Energy, Elsevier, vol. 228(C).
    15. Wang, Jieming & Wang, Jinkai & Xu, Shujuan & Wu, Rui & Lv, Jian & Li, Zhi & Li, Chun & Zhang, Jinliang & Zhao, Lei & Xie, Jun & Zhang, Jianguo, 2022. "A novel mode for “three zones” collaborative reconstruction of underground gas storage and its application to large, low-permeability lithologic gas reservoirs," Energy, Elsevier, vol. 253(C).
    16. Zhang, Decheng & Ranjith, P.G. & Perera, M.S.A. & Zhang, C.P., 2020. "Influences of test method and loading history on permeability of tight reservoir rocks," Energy, Elsevier, vol. 195(C).
    17. Shakouri, Sina & Mohammadzadeh-Shirazi, Maysam, 2023. "Modeling of asphaltic sludge formation during acidizing process of oil well reservoir using machine learning methods," Energy, Elsevier, vol. 285(C).
    18. Fathy, Mohammad & Kazemzadeh Haghighi, Foojan & Ahmadi, Mohammad, 2024. "Uncertainty quantification of reservoir performance using machine learning algorithms and structured expert judgment," Energy, Elsevier, vol. 288(C).
    19. Zhang, Tong & Ming, Tang & Yuan, Liang & Zhu, Guangpei & Zhang, Cun & Liu, Yang & Li, Yanfang & Wang, Wen & Yang, Xin, 2023. "Experimental study on stress-dependent multiphase flow in ultra-low permeability sandstone during CO2 flooding based on LF-NMR," Energy, Elsevier, vol. 278(PA).
    20. Xiangyu Wang & Lei Zhang, 2022. "Experimental Study on Permeability Evolution of Deep Coal Considering Temperature," Sustainability, MDPI, vol. 14(22), pages 1-17, 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:258:y:2022:i:c:s0360544222017492. 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.