Induced seismicity in geothermal reservoirs: A review of forecasting approaches

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

doi:10.1016/j.rser.2015.08.026

Induced seismicity in geothermal reservoirs: A review of forecasting approaches

Journal Article · Thu Aug 27 00:00:00 EDT 2015 · Renewable and Sustainable Energy Reviews

DOI:https://doi.org/10.1016/j.rser.2015.08.026· OSTI ID:1474900

Gaucher, Emmanuel ^[1]; Schoenball, Martin ^[1]; Heidbach, Oliver ^[2]; Zang, Arno ^[2]; Fokker, Peter A. ^[3]; van Wees, Jan-Diederik ^[4]; Kohl, Thomas ^[1]

Karlsruhe Institute of Technology (KIT) (Germany)
Helmholtz-Zentrum Potsdam (GFZ), (Germany)
Netherlands Organisation for Applied Scientific Research (TNO), Utrecht (Netherlands)
Netherlands Organisation for Applied Scientific Research (TNO), Utrecht (Netherlands); Utrecht University (Netherlands)

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. Thus, 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.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: EnBW Energie Baden-Württemberg AG; EnBW Energie Baden-Württemberg AG, Karlsruhe (Germany); European Commission (EC); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Office (EE-4G); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Office

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1474900

Alternate ID(s):: OSTI ID: 1252285

Journal Information:: Renewable and Sustainable Energy Reviews, Journal Name: Renewable and Sustainable Energy Reviews Journal Issue: C Vol. 52; ISSN 1364-0321

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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“Good Practice” Guide for Managing Induced Seismicity in Deep Geothermal Energy Projects in Switzerland Kraft, Toni; Wiemer, Stefan; Roth, Philippe SED, Swiss Seismological Service at ETH Zürich https://doi.org/10.12686/a5	text	January 2017
Two-grid method on unstructured tetrahedra: Applying computational geometry to staggered solution of coupled flow and mechanics problems Dana, Saumik; Zhao, Xiaoxi; Jha, Birendra arXiv https://doi.org/10.48550/arxiv.2102.04455	preprint	January 2021
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