IDEAS home Printed from https://ideas.repec.org/a/wly/greenh/v5y2015i3p254-267.html
   My bibliography  Save this article

Uncertainty quantification for evaluating the impacts of fracture zone on pressure build‐up and ground surface uplift during geological CO2 sequestration

Author

Listed:
  • Jie Bao
  • Zhangshuan Hou
  • Yilin Fang
  • Huiying Ren
  • Guang Lin

Abstract

A series of numerical test cases reflecting broad and realistic ranges of geological formation and fracture zone properties was developed to systematically evaluate the impacts of fracture zone on pressure build‐up and ground surface uplift during CO2 injection. Numerical test cases were conducted using a coupled hydro‐geomechanical simulator, eSTOMP‐RBSM (extreme‐scale Subsurface Transport over Multiple Phases, rigid‐body‐spring model). For efficient sensitivity analysis and reliable construction of a reduced‐order model, a quasi‐Monte Carlo sampling method was applied to effectively sample a high‐dimensional input parameter space to explore uncertainties associated with hydrologic properties. The uncertainty quantification results show that the impacts on geomechanical response from the fracture zone mainly depend on reservoir and fracture zone permeability. When the fracture zone permeability is two to three orders of magnitude smaller than the reservoir permeability, the fracture zone can be considered as an impermeable block that resists fluid transport in the reservoir, which causes pressure increase near the fracture zone. When the fracture zone permeability is close to the reservoir permeability, or higher than 10−15 m2 in this study, the fracture zone can be considered as a conduit that penetrates the caprock, connecting the fluid flow between the reservoir and the upper rock.© 2014 Society of Chemical Industry and John Wiley & Sons, Ltd

Suggested Citation

  • Jie Bao & Zhangshuan Hou & Yilin Fang & Huiying Ren & Guang Lin, 2015. "Uncertainty quantification for evaluating the impacts of fracture zone on pressure build‐up and ground surface uplift during geological CO2 sequestration," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 5(3), pages 254-267, June.
    • Handle: RePEc:wly:greenh:v:5:y:2015:i:3:p:254-267
    DOI: 10.1002/ghg.1456
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ghg.1456
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ghg.1456?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
    ---><---

    References listed on IDEAS

    as
    1. Jie Bao & Zhangshuan Hou & Yilin Fang & Huiying Ren & Guang Lin, 2013. "Uncertainty quantification for evaluating impacts of caprock and reservoir properties on pressure buildup and ground surface displacement during geological CO 2 sequestration," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 3(5), pages 338-358, October.
    2. Antonio P. Rinaldi & Pierre Jeanne & Jonny Rutqvist & Frédéric Cappa & Yves Guglielmi, 2014. "Effects of fault‐zone architecture on earthquake magnitude and gas leakage related to CO 2 injection in a multi‐layered sedimentary system," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 4(1), pages 99-120, February.
    3. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
    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. Víctor Vilarrasa & Jonny Rutqvist & Antonio Pio Rinaldi, 2015. "Thermal and capillary effects on the caprock mechanical stability at In Salah, Algeria," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 5(4), pages 449-461, August.
    2. Burkey, Mark L. & Obeng, Kofi, 2005. "Crash Risk Reduction at Signalized Intersections Using Longitudinal Data," MPRA Paper 36281, University Library of Munich, Germany.
    3. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    4. Hiau LooiKee & Alessandro Nicita & Marcelo Olarreaga, 2009. "Estimating Trade Restrictiveness Indices," Economic Journal, Royal Economic Society, vol. 119(534), pages 172-199, January.
    5. Dabao Zhang, 2022. "Coefficients of Determination for Mixed-Effects Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 674-689, December.
    6. Wam, Hilde Karine & Pedersen, Hans Chr. & Hjeljord, Olav, 2012. "Balancing hunting regulations and hunter satisfaction: An integrated biosocioeconomic model to aid in sustainable management," Ecological Economics, Elsevier, vol. 79(C), pages 89-96.
    7. Simon Blanchard & Wayne DeSarbo, 2013. "A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification," Psychometrika, Springer;The Psychometric Society, vol. 78(2), pages 322-340, April.
    8. Jaimovich, Dany, 2015. "Missing Links, Missing Markets: Evidence of the Transformation Process in the Economic Networks of Gambian Villages," World Development, Elsevier, vol. 66(C), pages 645-664.
    9. Sanghamitra Bandyopadhyay & Frank A. Cowell & Emmanual Flachaire, 2009. "Goodness-of-Fit: An Economic Approach," Economics Series Working Papers 444, University of Oxford, Department of Economics.
    10. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    11. Salvatore Ingrassia & Antonio Punzo, 2020. "Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 526-547, July.
    12. Scuotto, Veronica & Garcia-Perez, Alexeis & Nespoli, Chiara & Messeni Petruzzelli, Antonio, 2020. "A repositioning organizational knowledge dynamics by functional upgrading and downgrading strategy in global value chain," Journal of International Management, Elsevier, vol. 26(4).
    13. Mo'ath ALSHANNAQ & Rana IMAM, 2020. "Evaluating The Safety Performance Of Roundabouts," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 15(1), pages 141-152, March.
    14. Cheng Cao & Hejuan Liu & Zhengmeng Hou & Faisal Mehmood & Jianxing Liao & Wentao Feng, 2020. "A Review of CO 2 Storage in View of Safety and Cost-Effectiveness," Energies, MDPI, vol. 13(3), pages 1-45, January.
    15. Cynthia Wu & Jessica G Woo & Nanhua Zhang, 2017. "Association between urinary manganese and blood pressure: Results from National Health and Nutrition Examination Survey (NHANES), 2011-2014," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-6, November.
    16. Ozili, Peterson K, 2023. "The acceptable R-square in empirical modelling for social science research," MPRA Paper 115769, University Library of Munich, Germany.
    17. Chang, Byeong-Yun & Li, Xu & Kim, Yun Bae, 2014. "Performance comparison of two diffusion models in a saturated mobile phone market," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 41-48.
    18. Moting Su & Zongyi Zhang & Ye Zhu & Donglan Zha, 2019. "Data-Driven Natural Gas Spot Price Forecasting with Least Squares Regression Boosting Algorithm," Energies, MDPI, vol. 12(6), pages 1-13, March.
    19. Yang Zhang & Bo Guo, 2015. "Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine," Energies, MDPI, vol. 8(11), pages 1-19, November.
    20. Selen CAKMAKYAPAN & Atilla GOKTAS, 2013. "A Comparison Of Binary Logit And Probit Models With A Simulation Study," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(1), pages 1-17, JULY.

    More about this item

    Statistics

    Access and download statistics

    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:wly:greenh:v:5:y:2015:i:3:p:254-267. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)2152-3878 .

    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.