IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i24p6574-d461551.html
   My bibliography  Save this article

Chemical Impacts of Potential CO 2 and Brine Leakage on Groundwater Quality with Quantitative Risk Assessment: A Case Study of the Farnsworth Unit

Author

Listed:
  • Ting Xiao

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

  • Brian McPherson

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

  • Richard Esser

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

  • Wei Jia

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

  • Zhenxue Dai

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

  • Shaoping Chu

    (Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA)

  • Feng Pan

    (Utah Division of Water Resources, Salt Lake City, UT 84116, USA)

  • Hari Viswanathan

    (Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA)

Abstract

Potential leakage of reservoir fluids is considered a key risk factor for geologic CO 2 sequestration (GCS), with concerns of their chemical impacts on the quality of overlying underground sources of drinking water (USDWs). Effective risk assessment provides useful information to guide GCS activities for protecting USDWs. In this study, we present a quantified risk assessment case study of an active commercial-scale CO 2 -enhanced oil recovery (CO 2 -EOR) and sequestration field, the Farnsworth Unit (FWU). Specific objectives of this study include: (1) to quantify potential risks of CO 2 and brine leakage to the overlying USDW quality with response surface methodology (RSM); and (2) to identify water chemistry indicators for early detection criteria. Results suggest that trace metals (e.g., arsenic and selenium) are less likely to become a risk due to their adsorption onto clay minerals; no-impact thresholds based on site monitoring data could be a preferable reference for early groundwater quality evaluation; and pH is suggested as an indicator for early detection of a leakage. This study may provide quantitative insight for monitoring strategies on GCS sites to enhance the safety of long-term CO 2 sequestration.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6574-:d:461551
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/24/6574/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/24/6574/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ampomah, W. & Balch, R.S. & Cather, M. & Will, R. & Gunda, D. & Dai, Z. & Soltanian, M.R., 2017. "Optimum design of CO2 storage and oil recovery under geological uncertainty," Applied Energy, Elsevier, vol. 195(C), pages 80-92.
    2. Liu, Wen & Ramirez, Andrea, 2017. "State of the art review of the environmental assessment and risks of underground geo-energy resources exploitation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 628-644.
    3. Liange Zheng & Nicolas Spycher, 2018. "Modeling the potential impacts of CO2 sequestration on shallow groundwater: The fate of trace metals and organic compounds before and after leakage stops," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 8(1), pages 161-184, February.
    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. 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.
    2. 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.
    3. Xiao, Ting & Chen, Ting & Ma, Zhiwei & Tian, Hailong & Meguerdijian, Saro & Chen, Bailian & Pawar, Rajesh & Huang, Lianjie & Xu, Tianfu & Cather, Martha & McPherson, Brian, 2024. "A review of risk and uncertainty assessment for geologic carbon storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    4. 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.
    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.

    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. Xiao, Ting & Chen, Ting & Ma, Zhiwei & Tian, Hailong & Meguerdijian, Saro & Chen, Bailian & Pawar, Rajesh & Huang, Lianjie & Xu, Tianfu & Cather, Martha & McPherson, Brian, 2024. "A review of risk and uncertainty assessment for geologic carbon storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    2. Sun, Alexander Y., 2020. "Optimal carbon storage reservoir management through deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
    3. 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).
    4. Xiaolong, Chen & Yiqiang, Li & Xiang, Tang & Huan, Qi & Xuebing, Sun & Jianghao, Luo, 2021. "Effect of gravity segregation on CO2 flooding under various pressure conditions: Application to CO2 sequestration and oil production," Energy, Elsevier, vol. 226(C).
    5. Wang, Sijia & Jiang, Lanlan & Cheng, Zucheng & Liu, Yu & Zhao, Jiafei & Song, Yongchen, 2021. "Experimental study on the CO2-decane displacement front behavior in high permeability sand evaluated by magnetic resonance imaging," Energy, Elsevier, vol. 217(C).
    6. Samin Raziperchikolaee & Ashwin Pasumarti & Srikanta Mishra, 2020. "The effect of natural fractures on CO2 storage performance and oil recovery from CO2 and WAG injection in an Appalachian basin reservoir," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(5), pages 1098-1114, October.
    7. Turgay Ertekin & Qian Sun, 2019. "Artificial Intelligence Applications in Reservoir Engineering: A Status Check," Energies, MDPI, vol. 12(15), pages 1-22, July.
    8. Jin, Lu & Hawthorne, Steven & Sorensen, James & Pekot, Lawrence & Kurz, Bethany & Smith, Steven & Heebink, Loreal & Herdegen, Volker & Bosshart, Nicholas & Torres, José & Dalkhaa, Chantsalmaa & Peters, 2017. "Advancing CO2 enhanced oil recovery and storage in unconventional oil play—Experimental studies on Bakken shales," Applied Energy, Elsevier, vol. 208(C), pages 171-183.
    9. Chengkai Fan & Qi Li & Jianli Ma & Duoxing Yang, 2019. "Fiber Bragg grating‐based experimental and numerical investigations of CO2 migration front in saturated sandstone under subcritical and supercritical conditions," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 9(1), pages 106-124, February.
    10. Zhou, Xiang & Yuan, Qingwang & Rui, Zhenhua & Wang, Hanyi & Feng, Jianwei & Zhang, Liehui & Zeng, Fanhua, 2019. "Feasibility study of CO2 huff 'n' puff process to enhance heavy oil recovery via long core experiments," Applied Energy, Elsevier, vol. 236(C), pages 526-539.
    11. Hanamertani, Alvinda Sri & Ahmed, Shehzad, 2021. "Probing the role of associative polymer on scCO2-Foam strength and rheology enhancement in bulk and porous media for improving oil displacement efficiency," Energy, Elsevier, vol. 228(C).
    12. Vonsée, Bram & Crijns-Graus, Wina & Liu, Wen, 2019. "Energy technology dependence - A value chain analysis of geothermal power in the EU," Energy, Elsevier, vol. 178(C), pages 419-435.
    13. Touati, Khaled & Rahaman, Md. Saifur, 2020. "Viability of pressure-retarded osmosis for harvesting energy from salinity gradients," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    14. Dai, Zhenxue & Zhang, Ye & Bielicki, Jeffrey & Amooie, Mohammad Amin & Zhang, Mingkan & Yang, Changbing & Zou, Youqin & Ampomah, William & Xiao, Ting & Jia, Wei & Middleton, Richard & Zhang, Wen & Sun, 2018. "Heterogeneity-assisted carbon dioxide storage in marine sediments," Applied Energy, Elsevier, vol. 225(C), pages 876-883.
    15. Scanziani, Alessio & Singh, Kamaljit & Menke, Hannah & Bijeljic, Branko & Blunt, Martin J., 2020. "Dynamics of enhanced gas trapping applied to CO2 storage in the presence of oil using synchrotron X-ray micro tomography," Applied Energy, Elsevier, vol. 259(C).
    16. Chen, Bailian & Pawar, Rajesh J., 2019. "Characterization of CO2 storage and enhanced oil recovery in residual oil zones," Energy, Elsevier, vol. 183(C), pages 291-304.
    17. 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).
    18. Lechón, Yolanda & Lago, Carmen & Herrera, Israel & Gamarra, Ana Rosa & Pérula, Alberto, 2023. "Carbon benefits of different energy storage alternative end uses. Application to the Spanish case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    19. Anna Samnioti & Vassilis Gaganis, 2023. "Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part II," Energies, MDPI, vol. 16(18), pages 1-53, September.
    20. Mohamad Reza Soltanian & Mohammad Amin Amooie & David Cole & David Graham & Susan Pfiffner & Tommy Phelps & Joachim Moortgat, 2018. "Transport of perfluorocarbon tracers in the Cranfield Geological Carbon Sequestration Project," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 8(4), pages 650-671, August.

    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:13:y:2020:i:24:p:6574-:d:461551. 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.