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Induced seismicity in geothermal reservoirs: A review of forecasting approaches

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  • Gaucher, Emmanuel
  • Schoenball, Martin
  • Heidbach, Oliver
  • Zang, Arno
  • Fokker, Peter A.
  • van Wees, Jan-Diederik
  • Kohl, Thomas

Abstract

In order to reach Europe׳s 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced seismicity is often perceived as an unsolicited and uncontrollable side effect of geothermal development. In the last decade, significant advances were made in the development of models to forecast induced seismicity, which are either based on catalogues of induced seismicity, on the underlying physical processes, or on a hybrid philosophy. In this paper, we provide a comprehensive overview of the existing approaches applied to geothermal contexts. This overview will outline the advantages and drawbacks of the different approaches, identify the gaps in our understanding, and describe the needs for geothermal observations. Most of the forecasting approaches focus on the stimulation phase of enhanced geothermal systems which are most prone to generate seismic events. Besides the statistical models suited for real-time applications during reservoir stimulation, the physics-based models have the advantage of considering sub-surface characteristics and estimating the impact of fluid circulation on the reservoir. Hence, to mitigate induced seismicity during major hydraulic stimulations, application of hybrid methods in a decision support system seems the best available solution. So far, however, little attention has been paid to geochemical effects on the failure process and to production periods. Quantitative modelling of induced seismicity still is a challenging and complex matter. Appropriate resources remain to be invested for the scientific community to continue its research and development efforts to successfully forecast induced seismicity in geothermal fields. This is a prerequisite for making this renewable energy resource sustainable and accessible worldwide.

Suggested Citation

  • Gaucher, Emmanuel & Schoenball, Martin & Heidbach, Oliver & Zang, Arno & Fokker, Peter A. & van Wees, Jan-Diederik & Kohl, Thomas, 2015. "Induced seismicity in geothermal reservoirs: A review of forecasting approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1473-1490.
    • Handle: RePEc:eee:rensus:v:52:y:2015:i:c:p:1473-1490
    DOI: 10.1016/j.rser.2015.08.026
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    1. Anderson, Austin & Rezaie, Behnaz, 2019. "Geothermal technology: Trends and potential role in a sustainable future," Applied Energy, Elsevier, vol. 248(C), pages 18-34.
    2. Pan, Shu-Yuan & Gao, Mengyao & Shah, Kinjal J. & Zheng, Jianming & Pei, Si-Lu & Chiang, Pen-Chi, 2019. "Establishment of enhanced geothermal energy utilization plans: Barriers and strategies," Renewable Energy, Elsevier, vol. 132(C), pages 19-32.
    3. Soltani, M. & Moradi Kashkooli, Farshad & Souri, Mohammad & Rafiei, Behnam & Jabarifar, Mohammad & Gharali, Kobra & Nathwani, Jatin S., 2021. "Environmental, economic, and social impacts of geothermal energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    4. Lu, Shyi-Min, 2018. "A global review of enhanced geothermal system (EGS)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2902-2921.
    5. Prabhav Borate & Jacques Rivière & Chris Marone & Ankur Mali & Daniel Kifer & Parisa Shokouhi, 2023. "Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Esmaeilpour, Morteza & Gholami Korzani, Maziar & Kohl, Thomas, 2023. "Stochastic performance assessment on long-term behavior of multilateral closed deep geothermal systems," Renewable Energy, Elsevier, vol. 208(C), pages 26-35.
    7. Diego Paltrinieri & Paolo Favali & Francesco Italiano & Patrizio Signanini & Carlo Caso & Fabrizio B. Armani, 2022. "The Marsili Seamount Offshore Geothermal Reservoir: A Big Challenge for an Energy Transition Model," Energies, MDPI, vol. 15(5), pages 1-16, March.
    8. Sandro Andrés & David Santillán & Juan Carlos Mosquera & Luis Cueto-Felgueroso, 2019. "Thermo-Poroelastic Analysis of Induced Seismicity at the Basel Enhanced Geothermal System," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    9. Falcone, Gioia & Liu, Xiaolei & Okech, Roy Radido & Seyidov, Ferid & Teodoriu, Catalin, 2018. "Assessment of deep geothermal energy exploitation methods: The need for novel single-well solutions," Energy, Elsevier, vol. 160(C), pages 54-63.
    10. Elżbieta Węglińska & Andrzej Leśniak, 2021. "Induced Seismicity and Detailed Fracture Mapping as Tools for Evaluating HDR Reservoir Volume," Energies, MDPI, vol. 14(9), pages 1-17, May.
    11. Kang, Fangchao & Jia, Tianrang & Li, Yingchun & Deng, Jianhui & Tang, Chun'an & Huang, Xin, 2021. "Experimental study on the physical and mechanical variations of hot granite under different cooling treatments," Renewable Energy, Elsevier, vol. 179(C), pages 1316-1328.
    12. Miguel Angel Marazuela & Alejandro García-Gil, 2022. "Frontier Research of Engineering: Geothermal Energy Utilization and Groundwater Heat Pump Systems," Sustainability, MDPI, vol. 14(21), pages 1-3, October.
    13. Valeria Longobardi & Sahar Nazeri & Simona Colombelli & Raffaele Rea & Grazia De Landro & Aldo Zollo, 2023. "Time Domain Source Parameter Estimation of Natural and Man-Induced Microearthquakes at the Geysers Geothermal Field," Energies, MDPI, vol. 16(3), pages 1-15, January.
    14. Moraga, J. & Duzgun, H.S. & Cavur, M. & Soydan, H., 2022. "The Geothermal Artificial Intelligence for geothermal exploration," Renewable Energy, Elsevier, vol. 192(C), pages 134-149.

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