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Investigation of CH4/CO2 competitive adsorption-desorption mechanisms for enhanced shale gas production and carbon sequestration using nuclear magnetic resonance

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  • Zhou, Guangzhao
  • Duan, Xianggang
  • Chang, Jin
  • Bo, Yu
  • Huang, Yuhan

Abstract

Understanding the competitive adsorption-desorption mechanisms in shale is of fundamental significance for enhancing CH4 recovery and CO2 sequestration. This study adopted nuclear magnetic resonance to reveal the influence of CO2 on adsorption-desorption behaviors of CH4 in plug-sized samples. Three distinctive peaks were observed in the transverse relaxation time (T2) spectrum of a CH4-saturated sample, which indicated the adsorbed CH4 (0.1 ms < T2 < 1 ms), free state CH4 in pores (2 ms < T2 < 30 ms) and free state CH4 in fractures (100 ms < T2 < 1000 ms). When CH4 reached adsorption equilibration under 20 MPa, the total T2 signals of adsorbed CH4, free state CH4 in pores and free state CH4 in fractures were 565.3, 591.5 and 306.6 p. u., respectively. Subsequently, CO2 was pumped into the CH4-saturated sample under 22 MPa. When CO2–CH4 completed the competitive adsorption process, T2 signals decreased from 565.3 to 396.6 p. u. for adsorbed CH4, increased from 591.5 to 707.3 p. u. for free state CH4 in pores, and increased from 306.6 to 359.5 p. u. for free state CH4 in fractures. Afterwards, the desorption of shale sample began. CH4 concentration decreased from 79% to 55% while CO2 concentration increased from 21% to 45%. Finally, the total desorption rate of adsorbed CH4 (65%) was much higher than that without introducing CO2 (25%–40%).

Suggested Citation

  • Zhou, Guangzhao & Duan, Xianggang & Chang, Jin & Bo, Yu & Huang, Yuhan, 2023. "Investigation of CH4/CO2 competitive adsorption-desorption mechanisms for enhanced shale gas production and carbon sequestration using nuclear magnetic resonance," Energy, Elsevier, vol. 278(PB).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223013580
    DOI: 10.1016/j.energy.2023.127964
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    1. Kuang, Yangmin & Zhang, Lunxiang & Zheng, Yanpeng, 2022. "Enhanced CO2 sequestration based on hydrate technology with pressure oscillation in porous medium using NMR," Energy, Elsevier, vol. 252(C).
    2. Mei, Yingdan & Liu, Wenbo & Wang, Jianliang & Bentley, Yongmei, 2022. "Shale gas development and regional economic growth: Evidence from Fuling, China," Energy, Elsevier, vol. 239(PC).
    3. Liu, Jia & Xue, Yi & Fu, Yong & Yao, Kai & Liu, Jianqiang, 2023. "Numerical investigation on microwave-thermal recovery of shale gas based on a fully coupled electromagnetic, heat transfer, and multiphase flow model," Energy, Elsevier, vol. 263(PE).
    4. Zhang, Tong & Tang, Ming & Ma, Yankun & Zhu, Guangpei & Zhang, Qinghe & Wu, Jun & Xie, Zhizheng, 2022. "Experimental study on CO2/Water flooding mechanism and oil recovery in ultralow - Permeability sandstone with online LF-NMR," Energy, Elsevier, vol. 252(C).
    5. Huang, Liang & Ning, Zhengfu & Wang, Qing & Zhang, Wentong & Cheng, Zhilin & Wu, Xiaojun & Qin, Huibo, 2018. "Effect of organic type and moisture on CO2/CH4 competitive adsorption in kerogen with implications for CO2 sequestration and enhanced CH4 recovery," Applied Energy, Elsevier, vol. 210(C), pages 28-43.
    6. Wang, Lian & Yao, Yuedong & Wang, Kongjie & Adenutsi, Caspar Daniel & Zhao, Guoxiang & Lai, Fengpeng, 2022. "Hybrid application of unsupervised and supervised learning in forecasting absolute open flow potential for shale gas reservoirs," Energy, Elsevier, vol. 243(C).
    7. Nguyen-Le, Viet & Shin, Hyundon, 2022. "Artificial neural network prediction models for Montney shale gas production profile based on reservoir and fracture network parameters," Energy, Elsevier, vol. 244(PB).
    8. Shi, Wenrui & Zhang, Chaomo & Jiang, Shu & Liao, Yong & Shi, Yuanhui & Feng, Aiguo & Young, Steven, 2022. "Study on pressure-boosting stimulation technology in shale gas horizontal wells in the Fuling shale gas field," Energy, Elsevier, vol. 254(PB).
    9. Xu, WenLong & Yu, Hao & Micheal, Marembo & Huang, HanWei & Liu, He & Wu, HengAn, 2023. "An integrated model for fracture propagation and production performance of thermal enhanced shale gas recovery," Energy, Elsevier, vol. 263(PA).
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    2. Shasha Sun & Shiwei Huang & Feng Cheng & Wenhua Bai & Zhaoyuan Shao, 2023. "Geological Characteristics and Challenges of Marine Shale Gas in the Southern Sichuan Basin," Energies, MDPI, vol. 16(15), pages 1-20, August.

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