IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v278y2023ics036054422301174x.html
   My bibliography  Save this article

Gas production from shale reservoirs with bifurcating fractures: A modified quadruple-domain model coupling microseismic events

Author

Listed:
  • Micheal, Marembo
  • Yu, Hao
  • Meng, SiWei
  • Xu, WenLong
  • Huang, HanWei
  • Huang, MengCheng
  • Zhang, HouLin
  • Liu, He
  • Wu, HengAn

Abstract

Many fracture branches are generated during hydraulic fracturing to form complex fracture networks and the majority of the gas in the unstimulated region (USR) is left unexploited. Traditional models usually overlook the key effect of bifurcating fracture morphology on gas production from hydraulically stimulated shale formation. Understanding the interaction behavior between the matrix system and the bifurcating fractures is important for exploiting shale reservoirs. In this regard, a modified quadruple-domain model with both the stimulated region (SR) and the USR, is established. The SR contains the bifurcating hydraulic fractures (BHF) which are captured by the Lindenmayer system (L-system) algorithm based on the coupling with microseismic events. Meanwhile, the effects of single layer and multiple layer sorption on gas transport are included in the new dynamic permeability equation. The model is validated against results from the experiment, field data, and numerical simulations. The results demonstrate that the initial axiom, bifurcating distance, deviation angle, and number of iterations have a significant influence on the morphology of the BHF and subsequently control its growth leading to complex network. BHF complexity, natural fracture geometry, and the amount of sorption gas simultaneously determine the flow behavior and cumulative production performance.

Suggested Citation

  • Micheal, Marembo & Yu, Hao & Meng, SiWei & Xu, WenLong & Huang, HanWei & Huang, MengCheng & Zhang, HouLin & Liu, He & Wu, HengAn, 2023. "Gas production from shale reservoirs with bifurcating fractures: A modified quadruple-domain model coupling microseismic events," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s036054422301174x
    DOI: 10.1016/j.energy.2023.127780
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422301174X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127780?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. Gao, Qi & Han, Songcai & Cheng, Yuanfang & Shi, Xian & Yan, Chuanliang & Han, Zhongying, 2022. "Flow-coupled-geomechanical modelling of CO2 transport in depleted shale from a microscopic perspective," Energy, Elsevier, vol. 257(C).
    2. Niu, Wente & Sun, Yuping & Zhang, Xiaowei & Lu, Jialiang & Liu, Hualin & Li, Qiaojing & Mu, Ying, 2023. "An ensemble transfer learning strategy for production prediction of shale gas wells," Energy, Elsevier, vol. 275(C).
    3. 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).
    4. Yang, Run & Liu, Xiangui & Yu, Rongze & Hu, Zhiming & Duan, Xianggang, 2022. "Long short-term memory suggests a model for predicting shale gas production," Applied Energy, Elsevier, vol. 322(C).
    5. Hu, Yuhao & Liu, Guannan & Luo, Ning & Gao, Feng & Yue, Fengtian & Gao, Tao, 2022. "Multi-field coupling deformation of rock and multi-scale flow of gas in shale gas extraction," Energy, Elsevier, vol. 238(PA).
    6. Tian, Zhenhua & Wei, Wei & Zhou, Shangwen & Sun, Chenhao & Rezaee, Reza & Cai, Jianchao, 2022. "Impacts of gas properties and transport mechanisms on the permeability of shale at pore and core scale," Energy, Elsevier, vol. 244(PA).
    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. Xing, Zhihao & Yao, Jun & Liu, Lei & Sun, Hai, 2024. "Efficiently reconstructing high-quality details of 3D digital rocks with super-resolution Transformer," Energy, Elsevier, vol. 300(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).
    3. 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).

    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. Wang, Zengding & Liu, Tengyu & Liu, Shanchao & Jia, Cunqi & Yao, Jun & Sun, Hai & Yang, Yongfei & Zhang, Lei & Delshad, Mojdeh & Sepehrnoori, Kamy & Zhong, Junjie, 2024. "Adsorption effects on CO2-oil minimum miscibility pressure in tight reservoirs," Energy, Elsevier, vol. 288(C).
    2. Wang, Yanwei & Dai, Zhenxue & Chen, Li & Shen, Xudong & Chen, Fangxuan & Soltanian, Mohamad Reza, 2023. "An integrated multi-scale model for CO2 transport and storage in shale reservoirs," Applied Energy, Elsevier, vol. 331(C).
    3. 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).
    4. 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).
    5. Zhao, Li & Guanhua, Ni & Yan, Wang & Hehe, Jiang & Yongzan, Wen & Haoran, Dou & Mao, Jing, 2022. "Semi-homogeneous model of coal based on 3D reconstruction of CT images and its seepage-deformation characteristics," Energy, Elsevier, vol. 259(C).
    6. 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).
    7. Wang, Han & Zhang, Mingshan & Xia, Xuanzhe & Tian, Zhenhua & Qin, Xiangjie & Cai, Jianchao, 2024. "Lattice Boltzmann prediction of CO2 and CH4 competitive adsorption in shale porous media accelerated by machine learning for CO2 sequestration and enhanced CH4 recovery," Applied Energy, Elsevier, vol. 370(C).
    8. 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).
    9. Niu, Wente & Lu, Jialiang & Sun, Yuping & Zhang, Xiaowei & Li, Qiaojing & Cao, Xu & Liang, Pingping & Zhan, Hongming, 2024. "Techno-economic integration evaluation in shale gas development based on ensemble learning," Applied Energy, Elsevier, vol. 357(C).
    10. 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).
    11. Huang, Xianfu & Zhao, Ya-Pu, 2023. "Evolution of pore structure and adsorption-desorption in oil shale formation rocks after compression," Energy, Elsevier, vol. 278(PA).
    12. Zhou, Aitao & Li, Jingwen & Gong, Weili & Wang, Kai & Du, Changang, 2023. "Theoretical and numerical study on the contribution of multi-hole arrangement to coalbed methane extraction," Energy, Elsevier, vol. 284(C).
    13. Donghuan Han & Tongwen Jiang & Wei Xiong & Shusheng Gao & Huaxun Liu & Liyou Ye & Wenqing Zhu & Weiguo An, 2024. "A New Method for Calculating the Influx Index in Gas-Drive Reservoirs: A Case Study of the Kela-2 Gas Field," Energies, MDPI, vol. 17(5), pages 1-23, February.
    14. Zhou, Guangzhao & Guo, Zanquan & Sun, Simin & Jin, Qingsheng, 2023. "A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction," Applied Energy, Elsevier, vol. 344(C).
    15. Gou, Liangjie & Yang, Zhaozhong & Min, Chao & Yi, Duo & Li, Xiaogang & Kong, Bing, 2024. "A novel domain adaptation method with physical constraints for shale gas production forecasting," Applied Energy, Elsevier, vol. 371(C).
    16. Zhiyu Li & Zhengdong Lei & Weijun Shen & Dmitriy A. Martyushev & Xinhai Hu, 2023. "A Comprehensive Review of the Oil Flow Mechanism and Numerical Simulations in Shale Oil Reservoirs," Energies, MDPI, vol. 16(8), pages 1-23, April.
    17. Yang, Hongmin & Kang, Ningning & Chen, Xiangjun & Liu, Yuan, 2023. "Exploring the inhibitory effect of H2O on CO2/CH4 adsorption in coal: Insights from experimental and simulation approaches," Energy, Elsevier, vol. 284(C).
    18. Tao Wang & Shuangjian Li & Jian Gao & Xuepeng Zhang & Miao Chen, 2024. "Stochastic Risk Assessment Framework of Deep Shale Reservoirs by a Deep Learning Method and Random Field Theory," Sustainability, MDPI, vol. 16(23), pages 1-20, December.
    19. Xiaoyu Ju & Xiaodong Zhao & Boyu Zhou & Ruixue Zhang & Xinyu Wu & Dafa Guo, 2023. "Identification of Reservoir Water-Flooding Degrees via Core Sizes Based on a Drip Experiment of the Zhenwu Area in Gaoyou Sag, China," Energies, MDPI, vol. 16(2), pages 1-14, January.
    20. Qin, Xiangjie & Wu, Jinsui & Xia, Yuxuan & Wang, Han & Cai, Jianchao, 2024. "Multicomponent image-based modeling of water flow in heterogeneous wet shale nanopores," Energy, Elsevier, vol. 298(C).

    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:c:s036054422301174x. 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.