IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v294y2024ics0360544224005589.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224005589
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2024.130786?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. Monge, Manuel & Gil-Alana, Luis A. & PĂ©rez 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.
    Full references (including those not matched with items on IDEAS)

    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. Zhou, Xiaofeng & Wei, Jianguang & Zhao, Junfeng & Zhang, Xiangyu & Fu, Xiaofei & Shamil, Sultanov & Abdumalik, Gayubov & Chen, Yinghe & Wang, Jian, 2024. "Study on pore structure and permeability sensitivity of tight oil reservoirs," Energy, Elsevier, vol. 288(C).
    2. Zhou, Wei & Li, Xiangchengzhen & Qi, ZhongLi & Zhao, HaiHang & Yi, Jun, 2024. "A shale gas production prediction model based on masked convolutional neural network," Applied Energy, Elsevier, vol. 353(PA).
    3. Gil-Alana, Luis A. & Dadgar, Yadollah & Nazari, Rouhollah, 2020. "An analysis of the OPEC and non-OPEC position in the World Oil Market: A fractionally integrated approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    4. Ding, Song & Tao, Zui & Zhang, Huahan & Li, Yao, 2022. "Forecasting nuclear energy consumption in China and America: An optimized structure-adaptative grey model," Energy, Elsevier, vol. 239(PA).
    5. Zhang, Shuo & Song, Shengyuan & Zhang, Wen & Zhao, Jinmin & Cao, Dongfang & Ma, Wenliang & Chen, Zijian & Hu, Ying, 2023. "Research on the inherent mechanism of rock mass deformation of oil shale in-situ mining under the condition of thermal-fluid-solid coupling," Energy, Elsevier, vol. 280(C).
    6. Xinyu Han & Rongrong Li, 2019. "Comparison of Forecasting Energy Consumption in East Africa Using the MGM, NMGM, MGM-ARIMA, and NMGM-ARIMA Model," Energies, MDPI, vol. 12(17), pages 1-24, August.
    7. Bouteska, Ahmed & Hajek, Petr & Fisher, Ben & Abedin, Mohammad Zoynul, 2023. "Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. Wang, Qiang & Jiang, Feng, 2019. "Integrating linear and nonlinear forecasting techniques based on grey theory and artificial intelligence to forecast shale gas monthly production in Pennsylvania and Texas of the United States," Energy, Elsevier, vol. 178(C), pages 781-803.
    9. Afees Adebare Salisu & Idris A. Adediran, 2018. "The U.S. Shale Oil Revolution and the Behavior of Commodity Prices," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 3(1), pages 27-53, September.
    10. Li, Shaohua & Wang, Xin & Wang, Sijia & Zhang, Yi & Chen, Cong & Jiang, Lanlan & Wang, Lei & Liang, Fei & Sun, Hongjun & Song, Yongchen, 2024. "Optimizing oil recovery with CO2 microbubbles: A study of gas composition," Energy, Elsevier, vol. 302(C).
    11. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    12. Wang, Ziwei & Qin, Yong & Shen, Jian & Li, Teng & Zhang, Xiaoyang & Cai, Ying, 2022. "A novel permeability prediction model for coal based on dynamic transformation of pores in multiple scales," Energy, Elsevier, vol. 257(C).
    13. Yang Su & Ming Zha & Keyu Liu & Xiujian Ding & Jiangxiu Qu & Jiehua Jin, 2021. "Characterization of Pore Structures and Implications for Flow Transport Property of Tight Reservoirs: A Case Study of the Lucaogou Formation, Jimsar Sag, Junggar Basin, Northwestern China," Energies, MDPI, vol. 14(5), pages 1-20, February.
    14. Wenzhou Du & Yue Wang & Xuelin Liu & Lulu Sun, 2018. "Study on Low Temperature Oxidation Characteristics of Oil Shale Based on Temperature Programmed System," Energies, MDPI, vol. 11(10), pages 1-12, September.
    15. Jin, Xu & Wang, Xiaoqi & Yan, Weipeng & Meng, Siwei & Liu, Xiaodan & Jiao, Hang & Su, Ling & Zhu, Rukai & Liu, He & Li, Jianming, 2019. "Exploration and casting of large scale microscopic pathways for shale using electrodeposition," Applied Energy, Elsevier, vol. 247(C), pages 32-39.
    16. Zhineng Hu & Jing Ma & Liangwei Yang & Liming Yao & Meng Pang, 2019. "Monthly electricity demand forecasting using empirical mode decomposition-based state space model," Energy & Environment, , vol. 30(7), pages 1236-1254, November.
    17. Saif, Tarik & Lin, Qingyang & Gao, Ying & Al-Khulaifi, Yousef & Marone, Federica & Hollis, David & Blunt, Martin J. & Bijeljic, Branko, 2019. "4D in situ synchrotron X-ray tomographic microscopy and laser-based heating study of oil shale pyrolysis," Applied Energy, Elsevier, vol. 235(C), pages 1468-1475.
    18. 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).
    19. Niu, Daming & Sun, Pingchang & Ma, Lin & Zhao, Kang'an & Ding, Cong, 2023. "Porosity evolution of Minhe oil shale under an open rapid heating system and the carbon storage potentials," Renewable Energy, Elsevier, vol. 205(C), pages 783-799.
    20. Ahmad, Shakil, 2021. "Does COVID-19 effects the United States crude oil imports price?," Economic Consultant, Roman I. Ostapenko, vol. 33(1), pages 57-67.

    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:294:y:2024:i:c:s0360544224005589. 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.