IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v282y2023ics036054422301753x.html
   My bibliography  Save this article

Pore structure evolution of Qingshankou shale (kerogen type I) during artificial maturation via hydrous and anhydrous pyrolysis: Experimental study and intelligent modeling

Author

Listed:
  • Liu, Bo
  • Mohammadi, Mohammad-Reza
  • Ma, Zhongliang
  • Bai, Longhui
  • Wang, Liu
  • Xu, Yaohui
  • Hemmati-Sarapardeh, Abdolhossein
  • Ostadhassan, Mehdi

Abstract

In this study, alterations in the pore structure of the Qingshankou shale during hydrous and anhydrous pyrolysis (HP and AHP) over wide ranges of temperature (300–450 °C) were studied to elucidate the role of water. Mineralogy of the original shale sample along with geochemical properties and pore structure after each step of artificial thermal maturation were analyzed using X-ray diffraction (XRD), Rock-Eval pyrolysis, and N2 adsorption, respectively. Complexity of pore structure was assessed via fractal dimension analysis followed by delineating different pore families in the samples' PSD curves. Next, four common artificial neural networks (ANNs) models were implemented along with Bayesian regularization (BR) and Levenberg-Marquardt (LM) optimization algorithms to model the N2 adsorption/desorption volume as thermal maturity progressed. Results showed that all samples represent Type IV hysteresis loop while the amount of N2 adsorption during HP was much higher than that of the AHP revealing the importance of water. Overall, the complexity of AHP samples’ pore structure was less than that of the HP since the count of pores with smaller pore width was reduced more during thermal progression. Deconvolution analysis showed that the original sample has eight pore families (7 in mesopore and 1 in the macropore range), while pore families with larger mean pore width were formed and expanded and pore families with smaller mean pore width were eliminated as thermal maturation progressed in both HP and AHP. Moreover, the average absolute percent relative error (AAPRE) of 3.74% for the entire data inferred that generalized regression neural network (GRNN) model was superior for the estimation of N2 volume adsorbed and desorbed. Finally, sensitivity analysis revealed that the relative pressure and pyrolysis method (AHP or HP) respectively had the strongest linear and non-linear relationships with the N2 adsorption/desorption volume. Collectively, this case confirmed the role that water plays in the evolution of pore structures throughout thermal maturation, which could be even more significant than temperature.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s036054422301753x
    DOI: 10.1016/j.energy.2023.128359
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422301753X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128359?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. Shi, Rui & Liu, Jishan & Wang, Xiaoming & Wei, Mingyao & Elsworth, Derek, 2021. "A critical analysis of shale laboratory permeability evolution data," Energy, Elsevier, vol. 236(C).
    2. 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).
    3. Medina, Federico Javier & Jausoro, Ignacio & Floridia Addato, María Alejandra & Rodriguez, María Jimena & Tomassini, Federico González & Caneiro, Alberto, 2022. "On the evaluation of Representative Elementary Area for porosity in shale rocks by Field Emission Scanning Electron Microscopy," Energy, Elsevier, vol. 253(C).
    4. Wei, Zijian & Sheng, J.J., 2022. "Changes of pore structures and permeability of the Chang 73 medium-to-low maturity shale during in-situ heating treatment," Energy, Elsevier, vol. 248(C).
    5. Lei, Jian & Pan, Baozhi & Guo, Yuhang & Fan, YuFei & Xue, Linfu & Deng, Sunhua & Zhang, Lihua & Ruhan, A., 2021. "A comprehensive analysis of the pyrolysis effects on oil shale pore structures at multiscale using different measurement methods," Energy, Elsevier, vol. 227(C).
    6. Zeng, Fang & Dong, Chunmei & Lin, Chengyan & Tian, Shansi & Wu, Yuqi & Lin, Jianli & Liu, Binbin & Zhang, Xianguo, 2022. "Pore structure characteristics of reservoirs of Xihu Sag in East China Sea Shelf Basin based on dual resolution X-ray computed tomography and their influence on permeability," Energy, Elsevier, vol. 239(PD).
    7. Gou, Qiyang & Xu, Shang & Hao, Fang & Yang, Feng & Shu, Zhiguo & Liu, Rui, 2021. "The effect of tectonic deformation and preservation condition on the shale pore structure using adsorption-based textural quantification and 3D image observation," Energy, Elsevier, vol. 219(C).
    8. Jiang, Yongdong & Luo, Yahuang & Lu, Yiyu & Qin, Chao & Liu, Hui, 2016. "Effects of supercritical CO2 treatment time, pressure, and temperature on microstructure of shale," Energy, Elsevier, vol. 97(C), pages 173-181.
    9. He, Qianyang & Li, Delu & Sun, Qiang & Wei, Baowei & Wang, Shaofei, 2022. "Main controlling factors of marine shale compressive strength: A case study on the cambrian Niutitang Formation in Dabashan Mountain," Energy, Elsevier, vol. 260(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. Liu, Bo & Mohammadi, Mohammad-Reza & Ma, Zhongliang & Bai, Longhui & Wang, Liu & Wen, Zhigang & Liu, Yan & Morta, Hem Bahadur & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2023. "Experimental investigation and intelligent modeling of pore structure changes in type III kerogen-rich shale artificially matured by hydrous and anhydrous pyrolysis," Energy, Elsevier, vol. 282(C).
    2. Liu, Bo & Mohammadi, Mohammad-Reza & Ma, Zhongliang & Bai, Longhui & Wang, Liu & Xu, Yaohui & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2023. "Pore structure characterization of solvent extracted shale containing kerogen type III during artificial maturation: Experiments and tree-based machine learning modeling," Energy, Elsevier, vol. 283(C).
    3. Wang, Chao & Liu, Bo & Mohammadi, Mohammad-Reza & Fu, Li & Fattahi, Elham & Motra, Hem Bahadur & Hazra, Bodhisatwa & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2024. "Integrating experimental study and intelligent modeling of pore evolution in the Bakken during simulated thermal progression for CO2 storage goals," Applied Energy, Elsevier, vol. 359(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. Liu, Bo & Mohammadi, Mohammad-Reza & Ma, Zhongliang & Bai, Longhui & Wang, Liu & Wen, Zhigang & Liu, Yan & Morta, Hem Bahadur & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2023. "Experimental investigation and intelligent modeling of pore structure changes in type III kerogen-rich shale artificially matured by hydrous and anhydrous pyrolysis," Energy, Elsevier, vol. 282(C).
    2. Liu, Bo & Mohammadi, Mohammad-Reza & Ma, Zhongliang & Bai, Longhui & Wang, Liu & Xu, Yaohui & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2023. "Pore structure characterization of solvent extracted shale containing kerogen type III during artificial maturation: Experiments and tree-based machine learning modeling," Energy, Elsevier, vol. 283(C).
    3. Wang, Chao & Liu, Bo & Mohammadi, Mohammad-Reza & Fu, Li & Fattahi, Elham & Motra, Hem Bahadur & Hazra, Bodhisatwa & Hemmati-Sarapardeh, Abdolhossein & Ostadhassan, Mehdi, 2024. "Integrating experimental study and intelligent modeling of pore evolution in the Bakken during simulated thermal progression for CO2 storage goals," Applied Energy, Elsevier, vol. 359(C).
    4. Pan, Bin & Yin, Xia & Yang, Zhengru & Ghanizadeh, Amin & Debuhr, Chris & Clarkson, Christopher R. & Gou, Feifei & Zhu, Weiyao & Ju, Yang & Iglauer, Stefan, 2024. "Real-time imaging of oil shale pyrolysis dynamics at nanoscale via environmental scanning electron microscopy," Applied Energy, Elsevier, vol. 363(C).
    5. 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).
    6. Wei, Jianguang & Yang, Erlong & Li, Jiangtao & Liang, Shuang & Zhou, Xiaofeng, 2023. "Nuclear magnetic resonance study on the evolution of oil water distribution in multistage pore networks of shale oil reservoirs," Energy, Elsevier, vol. 282(C).
    7. Huang, HanWei & Yu, Hao & Xu, WenLong & Lyu, ChengSi & Micheal, Marembo & Xu, HengYu & Liu, He & Wu, HengAn, 2023. "A coupled thermo-hydro-mechanical-chemical model for production performance of oil shale reservoirs during in-situ conversion process," Energy, Elsevier, vol. 268(C).
    8. Cui, Ziang & Sun, Mengdi & Mohammadian, Erfan & Hu, Qinhong & Liu, Bo & Ostadhassan, Mehdi & Yang, Wuxing & Ke, Yubin & Mu, Jingfu & Ren, Zijie & Pan, Zhejun, 2024. "Characterizing microstructural evolutions in low-mature lacustrine shale: A comparative experimental study of conventional heat, microwave, and water-saturated microwave stimulations," Energy, Elsevier, vol. 294(C).
    9. Abelly, Elieneza Nicodemus & Yang, Feng & Ngata, Mbega Ramadhani & Mwakipunda, Grant Charles & Shanghvi, Eric Richard, 2024. "A field study of pore-network systems on the tight shale gas formation through adsorption-desorption technique and mercury intrusion capillary porosimeter: Percolation theory and simulations," Energy, Elsevier, vol. 302(C).
    10. Xu, HengYu & Yu, Hao & Fan, JingCun & Xia, Jun & Liu, He & Wu, HengAn, 2022. "Formation mechanism and structural characteristic of pore-networks in shale kerogen during in-situ conversion process," Energy, Elsevier, vol. 242(C).
    11. Tian, Shifeng & Zhou, Junping & Xian, Xuefu & Gan, Quan & Yang, Kang & Zheng, Yi & Deng, Guangrong & Zhang, Fengshou, 2023. "Impact of supercritical CO2 exposure time on the porosity and permeability of dry and wet shale: The influence of chemo-mechanical coupling effects," Energy, Elsevier, vol. 270(C).
    12. 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).
    13. Yin, Hong & Zhou, Junping & Xian, Xuefu & Jiang, Yongdong & Lu, Zhaohui & Tan, Jingqiang & Liu, Guojun, 2017. "Experimental study of the effects of sub- and super-critical CO2 saturation on the mechanical characteristics of organic-rich shales," Energy, Elsevier, vol. 132(C), pages 84-95.
    14. Wang, Chongyang & Zhang, Dongming & Liu, Chenxi & Pan, Yisha & Jiang, Zhigang & Yu, Beichen & Lin, Yun, 2023. "Deformation and seepage characteristics of water-saturated shale under true triaxial stress," Energy, Elsevier, vol. 284(C).
    15. Jin, Lu & Hawthorne, Steven & Sorensen, James & Pekot, Lawrence & Kurz, Bethany & Smith, Steven & Heebink, Loreal & Herdegen, Volker & Bosshart, Nicholas & Torres, José & Dalkhaa, Chantsalmaa & Peters, 2017. "Advancing CO2 enhanced oil recovery and storage in unconventional oil play—Experimental studies on Bakken shales," Applied Energy, Elsevier, vol. 208(C), pages 171-183.
    16. 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).
    17. Zhou, Junping & Tian, Shifeng & Zhou, Lei & Xian, Xuefu & Yang, Kang & Jiang, Yongdong & Zhang, Chengpeng & Guo, Yaowen, 2020. "Experimental investigation on the influence of sub- and super-critical CO2 saturation time on the permeability of fractured shale," Energy, Elsevier, vol. 191(C).
    18. Chengkai Fan & Qi Li & Jianli Ma & Duoxing Yang, 2019. "Fiber Bragg grating‐based experimental and numerical investigations of CO2 migration front in saturated sandstone under subcritical and supercritical conditions," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 9(1), pages 106-124, February.
    19. 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).
    20. 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).

    More about this item

    Keywords

    Qingshankou shale; Hydrous and anhydrous pyrolysis; N2 adsorption; Deconvolution analysis; Fractal dimension; Artificial neural networks;
    All these keywords.

    JEL classification:

    • N2 - Economic History - - Financial Markets and Institutions

    Statistics

    Access and download statistics

    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:282:y:2023:i:c:s036054422301753x. 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.