Using Estimated Risk to Develop Stimulation Strategies for Enhanced Geothermal Systems

Abstract

Enhanced geothermal systems (EGS) are an attractive source of low-carbon electricity and heating. Consequently, a number of tests of this technology have been made during the past couple of decades, and various projects are being planned or under development. EGS work by the injection of fluid into deep boreholes to increase permeability and hence allow the circulation and heating of fluid through a geothermal reservoir. Permeability is irreversibly increased by the generation of microseismicity through the shearing of pre-existing fractures or fault segments. One aspect of this technology that can cause public concern and consequently could limit the widespread adoption of EGS within populated areas is the risk of generating earthquakes that are sufficiently large to be felt (or even to cause building damage). Therefore, there is a need to balance stimulation and exploitation of the geothermal reservoir through fluid injection against the pressing requirement to keep the earthquake risk below an acceptable level. Current strategies to balance these potentially conflicting requirements rely on a traffic light system based on the observed magnitudes of the triggered earthquakes and the measured peak ground velocities from these events. In this article we propose an alternative system that uses the actual risk of generating felt (or damaging) earthquake ground motions at a site of interest (e.g. a nearby town) to control the injection rate. This risk is computed by combining characteristics of the observed seismicity of the previous 6 h with a (potentially site-specific) ground motion prediction equation to obtain a real-time seismic hazard curve; this is then convolved with the derivative of a (potentially site-specific) fragility curve. Based on the relation between computed risk and pre-defined acceptable risk thresholds, the injection is increased if the risk is below the amber level, decreased if the risk is between the amber and red levels, or stopped completely if the risk is above the red level. Based on simulations using a recently developed model of induced seismicity in geothermal systems, which is checked here using observations from the Basel EGS, in this article it is shown that the proposed procedure could lead to both acceptable levels of risk and increased permeability.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Notes

  1. 1.

    Another way of reducing the risk would be to reduce the exposure by developing EGS away from populated areas. However, because of the dual use of these systems to produce heat for buildings (in addition to electricity), it is often preferable, from an energy efficiency point of view, for them to be developed close to a town that can use the generated heat.

References

  1. Aochi, H. and Ide, S. (2009), Complexity in earthquake sequences controlled by multi-scale heterogeneity in fault fracture energy, Journal of Geophysical Research, 114, B03305, doi:10.1029/2008JB006034.

  2. Aochi, H., Poisson, B., Toussaint, R., Rachez, X. and Schmittbul, J. (2014), Self-induced seismicity due to fluid circulation along faults, Geophysical Journal International, in press, doi:10.1093/gji/ggt356.

  3. Bachmann, C. E., Wiemer, S., Woessner, J. and Hainzl, S. (2011), Statistical analysis of the induced Basel 2006 earthquake sequence: Introducing a probability-based monitoring approach for Enhanced Geothermal Systems, Geophysical Journal International, 186, 793–807, doi:10.1111/j.1365-246X.2011.05068.x.

  4. Baisch, S., Weidler, R., Vörös, R., Wyborn, D. and de Graaf, L. (2006), Induced seismicity during the stimulation of a geothermal HFR reservoir in the Cooper Basin, Australia, Bulletin of the Seismological Society of America, 96(6), 2242–2256.

    Google Scholar 

  5. Bommer, J. J., Oates, S., Cepeda, J. M., Lindholm, C., Bird, J., Torres, R., Marroquin, G. and Rivas, J. (2006), Control of hazard due to seismicity induced by a hot fractured rock geothermal project, Engineering Geology, 83, 287–306. doi:10.1016/j.enggeo.2005.11.002.

    Google Scholar 

  6. Bruel, D. (2007), Using the migration of the induced seismicity as a constraint for fractured Hot Dry Rock reservoir modelling, International Journal of Rock Mechanics and Mining Sciences, 44(8), 1106–1117.

    Google Scholar 

  7. Charlety, J., Cuenot, N., Dorbath, L., Dorbath, C., Haessler, H. and Frogneux, M. (2007), Large earthquakes during hydraulic stimulations at the geothermal site of Soultz-sous-Forets, International Journal of Rock Mechanics and Mining Science, 44(8), 1091–1105, doi:10.1016/j.ijrmms.2007.06.003.

  8. Convertito, V., Maercklin, N., Sharma, N. and Zollo, A. (2012), From induced seismicity to direct time-dependent seismic hazard, Bulletin of the Seismological Society of America, 102(6), 2563–2573, doi:10.1785/0120120036.

  9. Cua, G., Wald, D. J., Allen, T. I., Garcia, D., Worden, C. B., Gerstenberger, M., Lin, K. and Marano, K. (2010), “Best practices” for using macroseismic intensity and ground motion intensity conversion equations for hazard and loss models in GEM1, GEM Technical Report 2010–4. GEM Foundation, Pavia, Italy.

  10. Douglas, J., Edwards, B., Convertito, V., Sharma, N., Tramelli, A., Kraaijpoel, D., Mena Cabrera, B., Maercklin, N. and Troise, C. (2013a), Predicting ground motion from induced earthquakes in geothermal areas, Bulletin of the Seismological Society of America, 103(3), 1875–1897, doi:10.1785/0120120197.

  11. Douglas, J., Ulrich, T. and Negulescu, C. (2013b), Risk-targeted seismic design maps for mainland France, Natural Hazards, 65(3), 1999–2013, doi:10.1007/s11069-012-0460-6.

  12. Eads, L., Miranda, E., Krawinkler, H., and Lignos, D. G. (2013), An efficient method for estimating the collapse risk of structures in seismic regions, Earthquake Engineering and Structural Dynamics, 42(1), 25–41, doi:10.1002/eqe.2191.

  13. Edwards, B. and Douglas, J. (2013), Selecting ground-motion models developed for induced seismicity in geothermal areas, Geophysical Journal International, 195(2), 1314–1322, doi:10.1093/gji/ggt310.

    Google Scholar 

  14. Goertz-Allmann, B. P. and S. Wiemer (2013), Geomechanical modeling of induced seismicity source parameters and implications for seismic hazard assessment, Geophysics, 78(1), KS25–KS39.

  15. Hakimhashemi, A. H., Yoon, J. S., Heidbach, O., Zang, A. and Grünthal, G. (2013), FISHA – Forward induced seismic hazard assessment application to synthetic seismicity catalog generated by hydrulic (sic) stimulation modeling, Proceedings of Thirty-Eighth Workshop on Geothermal Reservoir Engineering, Stanford, California, February 11–13, SGP-TR-198.

  16. Häring, M. O., Schanz, U., Ladner, F. and Dyer, B. C. (2008), Characterisation of the Basel 1 enhanced geothermal system, Geothermics, 37, 469–495, doi:10.1016/j.geothermics.2008.06.002.

  17. Ide, S. and Aochi, H. (2005), Earthquakes as multiscale dynamic ruptures with heterogeneous fracture surface energy, Journal of Geophysical Research, 110, B11303, doi:10.1029/2004JB003591.

  18. Kennedy, R. P. (2011), Performance-goal based (risk informed) approach for establishing the SSE site specific response spectrum for future nuclear power plants, Nuclear Engineering and Design, 241, 648–656, doi:10.1016/j.nucengdes.2010.08.001.

  19. Kijko, A. (2004), Estimation of the maximum earthquake magnitude, m max , Pure and Applied Geophysics, 161, 1655–1681, doi:10.1007/s00024-004-2531-4.

  20. Kulkarni, R. B., Youngs, R. R. and Coppersmith, K. J. (1984), Assessment of confidence intervals for results of seismic hazard analysis, Proceedings of Eighth World Conference on Earthquake Engineering, 1, 263–270.

  21. Madariaga, R. (1979), On the relation between seismic moment an stress drop in the presence of stress and strength heterogeneity, Journal of Geophysical Research, 84, 2243–2250.

    Google Scholar 

  22. McGarr, A. (1976), Seismic moments and volume changes, Journal of Geophysical Research, 81(8), 1487–1494, doi:10.1029/JB081i008p01487.

    Google Scholar 

  23. Mena, B., Wiemer, S. and Bachmann, C. (2013), Building robust models to forecast the induced seismicity related to geothermal reservoir enhancement, Bulletin of the Seismological Society of America, 103(1), 383–392, doi:10.1785/0120120102.

  24. Miller, S. A., Collettini, C., Chiaraluce, L., Cocco, M., Barchi, M., and Kaus, B. (2004), Aftershocks driven by a high pressure CO 2 source at depth, Nature, 427, 724–727.

  25. Shapiro, S. A., Krüger, O. S., and Dinske, C. (2013), Probability of inducing given-magnitude earthquakes by perturbing finite volumes of rocks, Journal of Geophysical Research: Solid Earth, 118(7), 3557–3575, doi:10.1002/jgrb.50264.

    Google Scholar 

  26. Shinozuka, M., Feng, Q., Lee, J., and Naganuma, T. (2000), Statistical analysis of fragility curves, Journal of Engineering Mechanics, 126(12), 1224–1231.

    Google Scholar 

  27. Worden, C. B, Gerstenberger, M. C., Rhoades, D. A., and Wald, D. J. (2012), Probabilistic relationships between ground-motion parameters and Modified Mercalli intensity in California, Bulletin of the Seismological Society of America, 102(1), 204–221, doi:10.1785/0120110156.

Download references

Acknowledgments

This study was mainly funded by the Geothermal Engineering Integrating Mitigation of Induced Seismicity in Reservoirs (GEISER) project under contract 241321 of the European Commission Seventh Framework Programme (FP7). We also benefited from internal research funding of BRGM. We thank Anne Lemoine for help at the beginning of this study and Xavier Rachez for his comments on an earlier version of this manuscript. Finally, we thank two anonymous reviewers whose detailed comments led to significant improvements to this study.

Author information

Affiliations

Authors

Corresponding author

Correspondence to John Douglas.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Douglas, J., Aochi, H. Using Estimated Risk to Develop Stimulation Strategies for Enhanced Geothermal Systems. Pure Appl. Geophys. 171, 1847–1858 (2014). https://doi.org/10.1007/s00024-013-0765-8

Download citation

Keywords

  • Seismic risk
  • enhanced geothermal systems
  • felt earthquakes
  • fluid injection
  • probabilistic seismic hazard assessment
  • induced seismicity