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Experimental investigation and intelligent modeling of pore structure changes in type III kerogen-rich shale artificially matured by hydrous and anhydrous pyrolysis

Author

Listed:
  • Liu, Bo
  • Mohammadi, Mohammad-Reza
  • Ma, Zhongliang
  • Bai, Longhui
  • Wang, Liu
  • Wen, Zhigang
  • Liu, Yan
  • Morta, Hem Bahadur
  • Hemmati-Sarapardeh, Abdolhossein
  • Ostadhassan, Mehdi

Abstract

The occurrence and enrichment of shale plays are highly controlled by pore characteristics of the formation. In this study, an immature sample rich in kerogen type III from the Damoguaihe formation, Hailar Basin in China is subjected to hydrous and anhydrous pyrolysis (HP and AHP) across an extensive temperature range (300–450 °C). Next, low-pressure N2 adsorption analysis was conducted on the pyrolyzate of each maturity stage to study the pore structures’ evolution during thermal maturity simulation. Moreover, deconvolution and fractal dimension analyses were implemented to study pore families and the complexity of pores within the shale samples. Finally, radial basis function (RBF) neural networks optimized by four evolutionary approaches were applied for modeling N2 adsorption data obtained from the HP and AHP samples. According to the results, the original shale sample and all pyrolyzates obtained with HP and AHP scenarios exhibited type IV isotherm with H3 hysteresis loops. As a whole, BET surface area, micro-, meso- and total pore volume of HP pyrolyzates were higher than AHP ones. The unheated shale sample had seven families containing three mesopore and four macropore groups. Although all pyrolyzates obtained from the pyrolysis had families with similar means, their pore volumes were entirely different, which proves that the pore structure of samples undergoes changes during thermal maturation and the presence of water can also enforce these changes. Both fractal dimensions showed a direct relationship with BET surface area and a negative correlation with the average pore diameter of shale samples. The RBF model optimized by differential evolution (DE) delivered a mean absolute percent relative error (MAPRE) value of 4.84% and determination coefficient (R2) of 0.9946 for the total data set, which outperforms other RBF models in predicting N2 adsorption/desorption tests of pyrolyzates. The outcome of sensitivity analysis suggested that the N2 adsorption/desorption behavior of the pyrolyzates was mostly affected by relative pressure and the pyrolysis type (HP or AHP). Ultimately, the results clearly revealed that the effect of water on the pores' alteration of shales with type III kerogen is greater than the effect of temperature or thermal maturity itself.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s036054422302193x
    DOI: 10.1016/j.energy.2023.128799
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    1. Yudong Zhang & Shuihua Wang & Genlin Ji, 2015. "A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-38, October.
    2. 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).
    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. 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.
    5. Vo Thanh, Hung & Zamanyad, Aiyoub & Safaei-Farouji, Majid & Ashraf, Umar & Hemeng, Zhang, 2022. "Application of hybrid artificial intelligent models to predict deliverability of underground natural gas storage sites," Renewable Energy, Elsevier, vol. 200(C), pages 169-184.
    6. 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).
    7. Wang, Tianyu & Tian, Shouceng & Li, Gensheng & Zhang, Liyuan & Sheng, Mao & Ren, Wenxi, 2021. "Molecular simulation of gas adsorption in shale nanopores: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    8. 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).
    9. Chen, Shangbin & Zhu, Yanming & Wang, Hongyan & Liu, Honglin & Wei, Wei & Fang, Junhua, 2011. "Shale gas reservoir characterisation: A typical case in the southern Sichuan Basin of China," Energy, Elsevier, vol. 36(11), pages 6609-6616.
    10. 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).
    11. 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).
    Full references (including those not matched with items on IDEAS)

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    Keywords

    Damoguaihe formation; Anhydrous and hydrous pyrolysis; N2 adsorption analysis; Deconvolution analysis; Fractal dimension; Artificial neural networks;
    All these keywords.

    JEL classification:

    • N2 - Economic History - - Financial Markets and Institutions

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