IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p15049-d972766.html
   My bibliography  Save this article

Gridding Effects on CO 2 Trapping in Deep Saline Aquifers

Author

Listed:
  • Alessandro Suriano

    (Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Costanzo Peter

    (Italian Institute of Technology, Via Livorno 60, 10144 Torino, Italy)

  • Christoforos Benetatos

    (Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Francesca Verga

    (Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

Abstract

Three-dimensional numerical models of potential underground storage and compositional simulation are a way to study the feasibility of storing carbon dioxide in the existing geological formations. However, the results of the simulations are affected by many numerical parameters, and we proved that the refinement of the model grid is one of them. In this study, the impact of grid discretization on CO 2 trapping when the CO 2 is injected into a deep saline aquifer was investigated. Initially, the well bottom-hole pressure profiles during the CO 2 injection were simulated using four different grids. As expected, the results confirmed that the overpressure reached during injection is strongly affected by gridding, with coarse grids leading to non-representative values unless a suitable ramp-up CO 2 injection strategy is adopted. Then, the same grids were used to simulate the storage behavior after CO 2 injection so as to assess whether space discretization would also affect the simulation of the quantity of CO 2 trapped by the different mechanisms. A comparison of the obtained results showed that there is also a significant impact of the model gridding on the simulated amount of CO 2 permanently trapped in the aquifer by residual and solubility trapping, especially during the few hundred years following injection. Conversely, stratigraphic/hydrodynamic trapping, initially confining the CO 2 underground due to an impermeable caprock, does not depend on gridding, whereas significant mineral trapping would typically occur over a geological timescale. The conclusions are that a fine discretization, which is acknowledged to be needed for a reliable description of the pressure evolution during injection, is also highly recommended to obtain representative results when simulating CO 2 trapping in the subsurface. However, the expedients on CO 2 injection allow one to perform reliable simulations even when coarse grids are adopted. Permanently trapped CO 2 would not be correctly quantified with coarse grids, but a reliable assessment can be performed on a small, fine-grid model, with the results then extended to the large, coarse-grid model. The issue is particularly relevant because storage safety is strictly connected to CO 2 permanent trapping over time.

Suggested Citation

  • Alessandro Suriano & Costanzo Peter & Christoforos Benetatos & Francesca Verga, 2022. "Gridding Effects on CO 2 Trapping in Deep Saline Aquifers," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15049-:d:972766
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/15049/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/22/15049/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vo Thanh, Hung & Lee, Kang-Kun, 2022. "Application of machine learning to predict CO2 trapping performance in deep saline aquifers," Energy, Elsevier, vol. 239(PE).
    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. Muhammad Hammad Rasool & Maqsood Ahmad & Muhammad Ayoub, 2023. "Selecting Geological Formations for CO 2 Storage: A Comparative Rating System," Sustainability, MDPI, vol. 15(8), pages 1-39, April.
    2. Xinyu Luo & Lingying Pan & Jie Yang, 2022. "Mineral Resource Constraints for China’s Clean Energy Development under Carbon Peaking and Carbon Neutrality Targets: Quantitative Evaluation and Scenario Analysis," Energies, MDPI, vol. 15(19), pages 1-21, September.
    3. Abdulwahab Alqahtani & Xupeng He & Bicheng Yan & Hussein Hoteit, 2023. "Uncertainty Analysis of CO 2 Storage in Deep Saline Aquifers Using Machine Learning and Bayesian Optimization," Energies, MDPI, vol. 16(4), pages 1-16, February.
    4. 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.
    5. Wang, Yanwei & Dai, Zhenxue & Chen, Li & Shen, Xudong & Chen, Fangxuan & Soltanian, Mohamad Reza, 2023. "An integrated multi-scale model for CO2 transport and storage in shale reservoirs," Applied Energy, Elsevier, vol. 331(C).
    6. Mazahir Hussain & Shuang Liu & Umar Ashraf & Muhammad Ali & Wakeel Hussain & Nafees Ali & Aqsa Anees, 2022. "Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type," Energies, MDPI, vol. 15(12), pages 1-15, June.

    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:jsusta:v:14:y:2022:i:22:p:15049-:d:972766. 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.