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Comprehensive evaluation of the organic-rich saline lacustrine shale in the Lucaogou Formation, Jimusar sag, Junggar Basin, NW China

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  • Cao, Yan
  • Jin, Zhijun
  • Zhu, Rukai
  • Liu, Kouqi
  • Bai, Jianing

Abstract

To explore a comprehensive evaluation method for saline lacustrine shale, samples were collected from the shale strata of the Lucaogou Formation in the Jimusar Sag, Junggar Basin. Organic geochemical and mineralogical parameters were assessed through TOC evaluation, rock pyrolysis, and XRD. Quantitative analysis of pore structure was achieved using a combined low-pressure N2 adsorption and mercury intrusion. Optical microscopy and FE-SEM analyzed macerals and pore morphology, respectively, while 2D NMR identified varied hydrogen-containing components in the shale. The findings revealed predominance of inorganic pores in saline lacustrine shale strata, with a lower occurrence of organic pores. The saline lacustrine sediments were in the late stage of oil generation. The siltstone and type III3 carbonate felsic shale displayed an abundance of type II1 organic matter, low vitrinite and inertinite contents, high macroporous volumes and surface areas, and they possessed a high content and fluidity of free oil, despite being lower maturity (0.85%

Suggested Citation

  • Cao, Yan & Jin, Zhijun & Zhu, Rukai & Liu, Kouqi & Bai, Jianing, 2024. "Comprehensive evaluation of the organic-rich saline lacustrine shale in the Lucaogou Formation, Jimusar sag, Junggar Basin, NW China," Energy, Elsevier, vol. 294(C).
  • Handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224005589
    DOI: 10.1016/j.energy.2024.130786
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    References listed on IDEAS

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    1. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "U.S. shale oil production and WTI prices behaviour," Energy, Elsevier, vol. 141(C), pages 12-19.
    2. Zhang, Xiang & Wei, Bing & You, Junyu & Liu, Jiang & Wang, Dianlin & Lu, Jun & Tong, Jing, 2021. "Characterizing pore-level oil mobilization processes in unconventional reservoirs assisted by state-of-the-art nuclear magnetic resonance technique," Energy, Elsevier, vol. 236(C).
    3. Wang, Qiang & Song, Xiaoxing & Li, Rongrong, 2018. "A novel hybridization of nonlinear grey model and linear ARIMA residual correction for forecasting U.S. shale oil production," Energy, Elsevier, vol. 165(PB), pages 1320-1331.
    4. Liu, Yazhou & Zeng, Jianhui & Qiao, Juncheng & Yang, Guangqing & Liu, Shu'ning & Cao, Weifu, 2023. "An advanced prediction model of shale oil production profile based on source-reservoir assemblages and artificial neural networks," Applied Energy, Elsevier, vol. 333(C).
    5. Saif, Tarik & Lin, Qingyang & Butcher, Alan R. & Bijeljic, Branko & Blunt, Martin J., 2017. "Multi-scale multi-dimensional microstructure imaging of oil shale pyrolysis using X-ray micro-tomography, automated ultra-high resolution SEM, MAPS Mineralogy and FIB-SEM," Applied Energy, Elsevier, vol. 202(C), pages 628-647.
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