IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i6p1608-d516675.html
   My bibliography  Save this article

Impact of Mineral Reactive Surface Area on Forecasting Geological Carbon Sequestration in a CO 2 -EOR Field

Author

Listed:
  • Wei Jia

    (Energy & Geoscience Institute, University of Utah, Salt Lake City, UT 84108, USA
    Department of Civil & Environmental Engineering, University of Utah, Salt Lake City, UT 84112, USA)

  • Ting Xiao

    (Energy & Geoscience Institute, University of Utah, Salt Lake City, UT 84108, USA
    Department of Civil & Environmental Engineering, University of Utah, Salt Lake City, UT 84112, USA)

  • Zhidi Wu

    (Energy & Geoscience Institute, University of Utah, Salt Lake City, UT 84108, USA
    Department of Civil & Environmental Engineering, University of Utah, Salt Lake City, UT 84112, USA)

  • Zhenxue Dai

    (College of Construction Engineering, Jilin University, Changchun 130026, China)

  • Brian McPherson

    (Energy & Geoscience Institute, University of Utah, Salt Lake City, UT 84108, USA
    Department of Civil & Environmental Engineering, University of Utah, Salt Lake City, UT 84112, USA)

Abstract

Mineral reactive surface area (RSA) is one of the key factors that control mineral reactions, as it describes how much mineral is accessible and can participate in reactions. This work aims to evaluate the impact of mineral RSA on numerical simulations for CO 2 storage at depleted oil fields. The Farnsworth Unit (FWU) in northern Texas was chosen as a case study. A simplified model was used to screen representative cases from 87 RSA combinations to reduce the computational cost. Three selected cases with low, mid, and high RSA values were used for the FWU model. Results suggest that the impact of RSA values on CO 2 mineral trapping is more complex than it is on individual reactions. While the low RSA case predicted negligible porosity change and an insignificant amount of CO 2 mineral trapping for the FWU model, the mid and high RSA cases forecasted up to 1.19% and 5.04% of porosity reduction due to mineral reactions, and 2.46% and 9.44% of total CO 2 trapped in minerals by the end of the 600-year simulation, respectively. The presence of hydrocarbons affects geochemical reactions and can lead to net CO 2 mineral trapping, whereas mineral dissolution is forecasted when hydrocarbons are removed from the system.

Suggested Citation

  • Wei Jia & Ting Xiao & Zhidi Wu & Zhenxue Dai & Brian McPherson, 2021. "Impact of Mineral Reactive Surface Area on Forecasting Geological Carbon Sequestration in a CO 2 -EOR Field," Energies, MDPI, vol. 14(6), pages 1-22, March.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1608-:d:516675
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/6/1608/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/6/1608/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ting Xiao & Brian McPherson & Richard Esser & Wei Jia & Zhenxue Dai & Shaoping Chu & Feng Pan & Hari Viswanathan, 2020. "Chemical Impacts of Potential CO 2 and Brine Leakage on Groundwater Quality with Quantitative Risk Assessment: A Case Study of the Farnsworth Unit," Energies, MDPI, vol. 13(24), pages 1-14, December.
    2. You, Junyu & Ampomah, William & Sun, Qian, 2020. "Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework," Applied Energy, Elsevier, vol. 279(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eusebius J. Kutsienyo & Martin S. Appold & Martha E. Cather, 2023. "Investigation of the Effect of Injected CO 2 on the Morrow B Sandstone through Laboratory Batch Reaction Experiments: Implications for CO 2 Sequestration in the Farnsworth Unit, Northern Texas, USA," Energies, MDPI, vol. 16(12), pages 1-22, June.
    2. Zhang, Xiaoying & Ma, Funing & Yin, Shangxian & Wallace, Corey D & Soltanian, Mohamad Reza & Dai, Zhenxue & Ritzi, Robert W. & Ma, Ziqi & Zhan, Chuanjun & Lü, Xiaoshu, 2021. "Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review," Applied Energy, Elsevier, vol. 303(C).

    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. Abdoli, B. & Hooshmand, F. & MirHassani, S.A., 2023. "A novel stochastic programming model under endogenous uncertainty for the CCS-EOR planning problem," Applied Energy, Elsevier, vol. 338(C).
    2. Bocoum, Alassane Oumar & Rasaei, Mohammad Reza, 2023. "Multi-objective optimization of WAG injection using machine learning and data-driven Proxy models," Applied Energy, Elsevier, vol. 349(C).
    3. Jin, Wencheng & Atkinson, Trevor A. & Doughty, Christine & Neupane, Ghanashyam & Spycher, Nicolas & McLing, Travis L. & Dobson, Patrick F. & Smith, Robert & Podgorney, Robert, 2022. "Machine-learning-assisted high-temperature reservoir thermal energy storage optimization," Renewable Energy, Elsevier, vol. 197(C), pages 384-397.
    4. Shaoping Chu & Hari Viswanathan & Nathan Moodie, 2023. "Legacy Well Leakage Risk Analysis at the Farnsworth Unit Site," Energies, MDPI, vol. 16(18), pages 1-26, September.
    5. William Ampomah & Brian McPherson & Robert Balch & Reid Grigg & Martha Cather, 2022. "Forecasting CO 2 Sequestration with Enhanced Oil Recovery," Energies, MDPI, vol. 15(16), pages 1-7, August.
    6. Aaditya Khanal & Md Fahim Shahriar, 2022. "Physics-Based Proxy Modeling of CO 2 Sequestration in Deep Saline Aquifers," Energies, MDPI, vol. 15(12), pages 1-23, June.
    7. Samuel Appiah Acheampong & William Ampomah & Don Lee & Angus Eastwood-Anaba, 2023. "Coupled Hydromechanical Modeling and Assessment of Induced Seismicity at FWU: Utilizing Time-Lapse VSP and Microseismic Data," Energies, MDPI, vol. 16(10), pages 1-24, May.

    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:14:y:2021:i:6:p:1608-:d:516675. 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.