IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6326-d1230013.html
   My bibliography  Save this article

Large-Scale Ex Situ Tests for CO 2 Storage in Coal Beds

Author

Listed:
  • Marian Wiatowski

    (Department of Energy Saving and Air Protection, Central Mining Institute, Plac Gwarków 1, 40-166 Katowice, Poland)

  • Krzysztof Kapusta

    (Department of Energy Saving and Air Protection, Central Mining Institute, Plac Gwarków 1, 40-166 Katowice, Poland)

  • Kamil Stańczyk

    (Department of Acoustics, Electronics and IT Solutions, Central Mining Institute, Plac Gwarków 1, 40-166 Katowice, Poland)

  • Marcin Szyja

    (Department of Energy Saving and Air Protection, Central Mining Institute, Plac Gwarków 1, 40-166 Katowice, Poland)

  • Shakil Masum

    (Geoenvironmental Research Centre, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Sivachidambaram Sadasivam

    (Geoenvironmental Research Centre, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Hywel Rhys Thomas

    (Geoenvironmental Research Centre, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

Abstract

This publication discusses the experiments and findings of project ROCCS (Establishing a Research Observatory to Unlock European Coal Seams for Carbon Dioxide Storage), which aimed to investigate the potential for carbon dioxide storage in coal seams. The project involved large-scale ex situ laboratory tests, where CO 2 was injected into an experimental coal seam using a high-pressure reactor at the Central Mining Institute in Poland. The reactor simulated underground conditions, and the experimental coal seam measured 3.05 m in length with a cross-section of 0.4 × 0.4 m. Parameters such as gas flow, temperatures, and pressures were monitored during the experiments. In the study conducted, the sorption capacity of coal from the Polish mine “Piast-Ziemowit” for CO 2 , at a sorption pressure of 30 bar, was determined to be 4.8% by weight relative to the raw coal mass. The data collected from these ex situ tests can support the design of a potential commercial-scale CO 2 storage installation.

Suggested Citation

  • Marian Wiatowski & Krzysztof Kapusta & Kamil Stańczyk & Marcin Szyja & Shakil Masum & Sivachidambaram Sadasivam & Hywel Rhys Thomas, 2023. "Large-Scale Ex Situ Tests for CO 2 Storage in Coal Beds," Energies, MDPI, vol. 16(17), pages 1-14, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6326-:d:1230013
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6326/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6326/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enbin Liu & Xudong Lu & Daocheng Wang, 2023. "A Systematic Review of Carbon Capture, Utilization and Storage: Status, Progress and Challenges," Energies, MDPI, vol. 16(6), pages 1-48, March.
    2. Maria Wetzel & Christopher Otto & Min Chen & Shakil Masum & Hywel Thomas & Tomasz Urych & Bartłomiej Bezak & Thomas Kempka, 2023. "Hydromechanical Impacts of CO 2 Storage in Coal Seams of the Upper Silesian Coal Basin (Poland)," Energies, MDPI, vol. 16(7), pages 1-24, April.
    3. Vo Thanh, Hung & Yasin, Qamar & Al-Mudhafar, Watheq J. & Lee, Kang-Kun, 2022. "Knowledge-based machine learning techniques for accurate prediction of CO2 storage performance in underground saline aquifers," Applied Energy, Elsevier, vol. 314(C).
    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. Fang, Huihuang & Sang, Shuxun & Wang, Zhangfei & Guo, Jinran & Liu, Huihu & Xu, Hongjie & Chen, Rui, 2024. "Numerical analysis of temperature effect on CO2 storage capacity and CH4 production capacity during the CO2-ECBM process," Energy, Elsevier, vol. 289(C).
    2. Dahai, He & Zhihong, Yin & Lin, Qin & Yuhong, Li & Lei, Tian & Jiang, Li & Liandong, Zhu, 2024. "The application of magical microalgae in carbon sequestration and emission reduction: Removal mechanisms and potential analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    3. Nafees Ali & Xiaodong Fu & Umar Ashraf & Jian Chen & Hung Vo Thanh & Aqsa Anees & Muhammad Shahid Riaz & Misbah Fida & Muhammad Afaq Hussain & Sadam Hussain & Wakeel Hussain & Awais Ahmed, 2022. "Remote Sensing for Surface Coal Mining and Reclamation Monitoring in the Central Salt Range, Punjab, Pakistan," Sustainability, MDPI, vol. 14(16), pages 1-26, August.
    4. Wenjin Chen & Jun Zhang & Feng Li & Ruoyi Zhang & Sennan Qi & Guoqing Li & Chong Wang, 2023. "Low Carbon Economic Dispatch of Integrated Energy System Considering Power-to-Gas Heat Recovery and Carbon Capture," Energies, MDPI, vol. 16(8), pages 1-19, April.
    5. Vo Thanh, Hung & Sheini Dashtgoli, Danial & Zhang, Hemeng & Min, Baehyun, 2023. "Machine-learning-based prediction of oil recovery factor for experimental CO2-Foam chemical EOR: Implications for carbon utilization projects," Energy, Elsevier, vol. 278(PA).
    6. Ahmed M. Nassef, 2023. "Improving CO 2 Absorption Using Artificial Intelligence and Modern Optimization for a Sustainable Environment," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    7. Yi, Jun & Qi, ZhongLi & Li, XiangChengZhen & Liu, Hong & Zhou, Wei, 2024. "Spatial correlation-based machine learning framework for evaluating shale gas production potential: A case study in southern Sichuan Basin, China," Applied Energy, Elsevier, vol. 357(C).
    8. Mithran Daniel Solomon & Marcel Scheffler & Wolfram Heineken & Mostafa Ashkavand & Torsten Birth-Reichert, 2024. "Pipeline Infrastructure for CO 2 Transport: Cost Analysis and Design Optimization," Energies, MDPI, vol. 17(12), pages 1-21, June.
    9. Kanakaraj Aruchamy & Athinarayanan Balasankar & Subramaniyan Ramasundaram & Tae Hwan Oh, 2023. "Recent Design and Synthesis Strategies for High-Performance Supercapacitors Utilizing ZnCo 2 O 4 -Based Electrode Materials," Energies, MDPI, vol. 16(15), pages 1-36, July.
    10. Aliyon, Kasra & Rajaee, Fatemeh & Ritvanen, Jouni, 2023. "Use of artificial intelligence in reducing energy costs of a post-combustion carbon capture plant," Energy, Elsevier, vol. 278(PA).
    11. William Ampomah & Anthony Morgan & Desmond Ofori Koranteng & Warden Ivan Nyamekye, 2024. "CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects," Energies, MDPI, vol. 17(17), pages 1-57, August.
    12. Fangshu Cui & Sheng Qin & Jing Zhang & Mengwei Li & Yuanhao Shi, 2022. "A Hybrid Method for Prediction of Ash Fouling on Heat Transfer Surfaces," Energies, MDPI, vol. 15(13), pages 1-15, June.
    13. Ming Yue & Quanqi Dai & Haiying Liao & Yunfeng Liu & Lin Fan & Tianru Song, 2024. "Prediction of ORF for Optimized CO 2 Flooding in Fractured Tight Oil Reservoirs via Machine Learning," Energies, MDPI, vol. 17(6), pages 1-20, March.
    14. Chen, Siyuan & Liu, Jiangfeng & Zhang, Qi & Teng, Fei & McLellan, Benjamin C., 2022. "A critical review on deployment planning and risk analysis of carbon capture, utilization, and storage (CCUS) toward carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    15. 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.

    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:gam:jeners:v:16:y:2023:i:17:p:6326-:d:1230013. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.