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Ridgecrest aftershocks at Coso suppressed by thermal destressing

Abstract

Geothermal and volcanic areas are prone to earthquake triggering1,2. The Coso geothermal field in California lies just north of the surface ruptures driven by the 2019 Ridgecrest earthquake (moment magnitude Mw = 7.1), in an area where changes in coseismic stress should have triggered aftershocks3,4. However, no aftershocks were observed there4. Here we show that 30 years of geothermal heat production at Coso depleted shear stresses within the geothermal reservoir. Thermal contraction of the reservoir initially induced substantial seismicity, as observed in the Coso geothermal reservoir, but subsequently depleted the stress available to drive the aftershocks during the Ridgecrest sequence. This destressing changed the faulting style of the reservoir and impeded aftershock triggering. Although unlikely to have been the case for the Ridgecrest earthquake, such a destressed zone could, in principle, impede the propagation of a large earthquake.

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Fig. 1: Ridgecrest aftershock and prior seismicity in the Coso area.
Fig. 2: Production, power generation and surface subsidence for our reference simulation.
Fig. 3: Simulation of stress changes due to thermal contraction, pore pressure changes and anelastic failure of the reservoir.

Data availability

The seismic catalogue10 is publicly available from the Southern California Earthquake Data Center (https://scedc.caltech.edu/data/alt-2011-dd-hauksson-yang-shearer.html). The Coso field well location and flow rate data are available from the California Department of Conservation (https://maps.conservation.ca.gov/doggr/wellfinder, https://www.conservation.ca.gov/calgem/geothermal/manual/Pages/production.aspx). Simulation data are available in the Caltech data repository (https://doi.org/10.22002/D1.1455). Source data are provided with this paper.

Code availability

The TOUGH–FLAC coupled simulator and all input files are available in the Caltech data repository (https://doi.org/10.22002/D1.1455).

References

  1. Zang, A. et al. Analysis of induced seismicity in geothermal reservoirs – an overview. Geothermics 52, 6–21 (2014).

    Article  Google Scholar 

  2. Kim, K.-H. et al. Assessing whether the 2017 Mw 5.4 Pohang earthquake in South Korea was an induced event. Science 360, 1007–1009 (2018).

    ADS  CAS  PubMed  Article  Google Scholar 

  3. Ross, Z. E. et al. Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence. Science 366, 346–351 (2019).

    ADS  CAS  PubMed  Article  Google Scholar 

  4. Hardebeck, J. L. A stress-similarity triggering model for aftershocks of the Mw 6.4 and 7.1 Ridgecrest earthquakes. Bull. Seismol. Soc. Am. 110, 1716–1727 (2020).

    Google Scholar 

  5. Chen, K. et al. Cascading and pulse-like ruptures during the 2019 Ridgecrest earthquakes in the Eastern California Shear Zone. Nat. Commun. 11, 22 (2020).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. Hill, D. P. et al. Seismicity remotely triggered by the magnitude 7.3 Landers, California, earthquake. Science 260, 1617–1623 (1993).

    ADS  CAS  PubMed  Article  Google Scholar 

  7. Grigoli, F. et al. The November 2017 Mw 5.5 Pohang earthquake: a possible case of induced seismicity in South Korea. Science 360, 1003–1006 (2018).

    ADS  CAS  PubMed  Article  Google Scholar 

  8. Deichmann, N. & Giardini, D. Earthquakes induced by the stimulation of an enhanced geothermal system below Basel (Switzerland). Seismol. Res. Lett. 80, 784–798 (2009).

    Article  Google Scholar 

  9. Hauksson, E. & Unruh, J. Regional tectonics of the Coso geothermal area along the intracontinental plate boundary in central eastern California: three-dimensional Vp and Vp/Vs models, spatial-temporal seismicity patterns, and seismogenic deformation. J. Geophys. Res. Solid Earth 112, B06309 (2007).

    ADS  Article  Google Scholar 

  10. Hauksson, E., Yang, W. & Shearer, P. M. Waveform relocated earthquake catalog for Southern California (1981 to June 2011). Bull. Seismol. Soc. Am. 102, 2239–2244 (2012).

    Article  Google Scholar 

  11. Kaven, J. O. Seismicity rate change at the Coso geothermal field following the July 2019 Ridgecrest earthquakes. Bull. Seismol. Soc. Am. 110, 1728–1735 (2020).

    Article  Google Scholar 

  12. Blake, K. et al. Updated shallow temperature survey and resource evolution for the Coso geothermal field. In Proc. World Geotherm. Congr. (2020).

  13. Bertani, R. World geothermal power generation in the period 2001–2005. Geothermics 34, 651–690 (2005).

    Article  Google Scholar 

  14. Fialko, Y. & Simons, M. Deformation and seismicity in the Coso geothermal area, Inyo County, California: observations and modeling using satellite radar interferometry. J. Geophys. Res. Solid Earth 105, 21781–21793 (2000).

    Article  Google Scholar 

  15. Reinisch, E. C., Cardiff, M., Kreemer, C., Akerley, J. & Feigl, K. L. Time-series analysis of volume change at Brady Hot Springs, Nevada, USA, using geodetic data from 2003–2018. J. Geophys. Res. Solid Earth 125, B017816 (2020).

    Article  Google Scholar 

  16. Wicks, C. W., Thatcher, W., Monastero, F. C. & Hasting, M. A. Steady state deformation of the Coso Range, east central California, inferred from satellite radar interferometry. J. Geophys. Res. Solid Earth 106, 13769–13780 (2001).

    Article  Google Scholar 

  17. Blankenship, D. A. et al. Frontier Observatory for Research in Geothermal Energy: Phase 1 Topical Report West Flank of Coso, CA. Report No. 1455367, https://doi.org/10.2172/1455367 (US Department of Energy, 2016).

  18. Goebel, T. H. W. & Brodsky, E. E. The spatial footprint of injection wells in a global compilation of induced earthquake sequences. Science 361, 899–904 (2018).

    ADS  MathSciNet  CAS  PubMed  MATH  Article  Google Scholar 

  19. Goebel, T. H. W., Weingarten, M., Chen, X., Haffener, J. & Brodsky, E. E. The 2016 Mw 5.1 Fairview, Oklahoma earthquakes: evidence for long-range poroelastic triggering at >40 km from fluid disposal wells. Earth Planet. Sci. Lett. 472, 50–61 (2017).

    ADS  CAS  Article  Google Scholar 

  20. Sanyal, S., Menzies, A., Granados, E., Sugine, S. & Gentner, R. Long term testing of geothermal wells in the Coso hot springs KGRA. In Proc. 12th Work. Geotherm. Reserv. Eng. 37–44 (1987).

  21. Im, K., Elsworth, D., Guglielmi, Y. & Mattioli, G. S. Geodetic imaging of thermal deformation in geothermal reservoirs - production, depletion and fault reactivation. J. Volcanol. Geotherm. Res. 338, 79–91 (2017).

    ADS  CAS  Article  Google Scholar 

  22. Rutqvist, J., Wu, Y.-S., Tsang, C.-F. & Bodvarsson, G. A modeling approach for analysis of coupled multiphase fluid flow, heat transfer, and deformation in fractured porous rock. Int. J. Rock Mech. Min. Sci. 39, 429–442 (2002).

    Article  Google Scholar 

  23. Segall, P. & Fitzgerald, S. D. A note on induced stress changes in hydrocarbon and geothermal reservoirs. Tectonophysics 289, 117–128 (1998).

    ADS  Article  Google Scholar 

  24. Yang, W., Hauksson, E. & Shearer, P. M. Computing a large refined catalog of focal mechanisms for southern California (1981–2010): temporal stability of the style of faulting. Bull. Seismol. Soc. Am. 102, 1179–1194 (2012).

    Article  Google Scholar 

  25. Taron, J., Elsworth, D. & Min, K.-B. Numerical simulation of thermal-hydrologic-mechanical-chemical processes in deformable, fractured porous media. Int. J. Rock Mech. Min. Sci. 46, 842–854 (2009).

    Article  Google Scholar 

  26. Feng, Q. & Lees, J. M. Microseismicity, stress, and fracture in the Coso geothermal field, California. Tectonophysics 289, 221–238 (1998).

    ADS  Article  Google Scholar 

  27. Davatzes, N. C. & Hickman, S. H. Stress and Faulting in the Coso Geothermal Field: Update and Recent Results from the East Flank and Coso Wash. In Proc. 31st Work. Geotherm. Reserv. Eng. (2006).

  28. Rose, P. et al. An enhanced geothermal system at Coso, California — recent accomplishments. In Proc. World Geotherm. Congr. (2005).

  29. Cooper, H. W. & Simmons, G. The effect of cracks on the thermal expansion of rocks. Earth Planet. Sci. Lett. 36, 404–412 (1977).

    ADS  CAS  Article  Google Scholar 

  30. Spane, F. Jr. Hydrogeologic Investigation of Coso Hot Springs, Inyo County, California. Report No. 6025, https://www.ekcrcd.org/files/bcdf564af/Hydrogeologic+Investigation+of+Coso+Hot+Springs.pdf (Naval Weapons Center, 1978).

  31. MHA Environmental Consulting. Coso Operating Company Hay Ranch Water Extraction and Delivery System. Conditional Use Permit (CUP 2007-003) Application. Report No. SCH 2007101002, https://www.inyowater.org/wp-content/uploads/legacy/INDEX_DOCS/Coso%20Hay%20Ranch_FEIR_Dec_30_08.pdf (2008).

  32. Zarrouk, S. J. & Moon, H. Efficiency of geothermal power plants: a worldwide review. Geothermics 51, 142–153 (2014).

    Article  Google Scholar 

  33. Ali, S. T. et al. Geodetic measurements and numerical models of deformation: examples from geothermal fields in the western United States. In Proc. 41st Work. Geotherm. Reserv. Eng. (2016).

  34. Wang, K. & Bürgmann, R. Co‐ and early postseismic deformation due to the 2019 Ridgecrest earthquake sequence constrained by Sentinel‐1 and COSMO‐SkyMed SAR data. Seismol. Res. Lett. 91, 1998–2009 (2020).

    Article  Google Scholar 

  35. Reinisch, E. C., Ali, S. T., Cardiff, M., Kaven, J. O. & Feigl, K. L. Geodetic measurements and numerical models of deformation at Coso geothermal field, California, 2004–2016. Remote Sens. 12, 225 (2020).

    ADS  Article  Google Scholar 

  36. Ader, T. J., Lapusta, N., Avouac, J.-P. & Ampuero, J.-P. Response of rate-and-state seismogenic faults to harmonic shear-stress perturbations. Geophys. J. Int. 198, 385–413 (2014).

    ADS  Article  Google Scholar 

  37. Dieterich, J. A constitutive law for rate of earthquake production and its application to earthquake clustering. J. Geophys. Res. Solid Earth 99, 2601–2618 (1994).

    Article  Google Scholar 

  38. Zhang, Q. et al. Absence of remote earthquake triggering within the Coso and Salton Sea geothermal production fields. Geophys. Res. Lett. 44, 726–733 (2017).

    ADS  Article  Google Scholar 

  39. Alfaro-Diaz, R., Velasco, A. A., Pankow, K. L. & Kilb, D. Optimally oriented remote triggering in the Coso geothermal region. J. Geophys. Res. Solid Earth 125, B019131 (2020).

    Article  Google Scholar 

  40. Hauksson, E. & Jones, L. M. Seismicity, stress state, and style of faulting of the Ridgecrest‐Coso region from the 1930s to 2019: seismotectonics of an evolving plate boundary segment. Bull. Seismol. Soc. Am. 110, 1457–1473 (2020).

    Google Scholar 

  41. Kostrov, V. Seismic moment and energy of earthquakes, and seismic flow of rock. Izv. Acad. Sci. USSR Phys. Solid Earth 1, 23–44 (1974).

    MathSciNet  Google Scholar 

  42. Cornet, F. H., Helm, J., Poitrenaud, H. & Etchecopar, A. Seismic and aseismic slips induced by large-scale fluid injections. Pure Appl. Geophys. 150, 563–583 (1997).

    ADS  Article  Google Scholar 

  43. Guglielmi, Y., Cappa, F., Avouac, J.-P., Henry, P. & Elsworth, D. Seismicity triggered by fluid injection-induced aseismic slip. Science 348, 1224–1226 (2015).

    ADS  CAS  PubMed  Article  Google Scholar 

  44. Wei, S. et al. The 2012 Brawley swarm triggered by injection-induced aseismic slip. Earth Planet. Sci. Lett. 422, 115–125 (2015).

    ADS  CAS  Article  Google Scholar 

  45. Cappa, F., Scuderi, M. M., Collettini, C., Guglielmi, Y. & Avouac, J.-P. Stabilization of fault slip by fluid injection in the laboratory and in situ. Sci. Adv. 5, eaau4065 (2019).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  46. Kwiatek, G. et al. Controlling fluid-induced seismicity during a 6.1-km-deep geothermal stimulation in Finland. Sci. Adv. 5, eaav7224 (2019).

    ADS  PubMed  PubMed Central  Article  Google Scholar 

  47. Hillers, G. et al. Noise-based monitoring and imaging of aseismic transient deformation induced by the 2006 Basel reservoir stimulation. Geophysics 80, KS51–KS68 (2015).

    ADS  Article  Google Scholar 

  48. Häring, M. O., Schanz, U., Ladner, F. & Dyer, B. C. Characterisation of the Basel 1 enhanced geothermal system. Geothermics 37, 469–495 (2008).

    Article  Google Scholar 

  49. Gan, Q. & Elsworth, D. Thermal drawdown and late-stage seismic-slip fault reactivation in enhanced geothermal reservoirs. J. Geophys. Res. Solid Earth 119, 8936–8949 (2014).

    ADS  Article  Google Scholar 

  50. Eshelby, J. D. The determination of the elastic field of an ellipsoidal inclusion, and related problems. Proc. R. Soc. Lond. Ser. A. 241, 376–396 (1957)

    ADS  MathSciNet  MATH  Article  Google Scholar 

  51. Peaceman, D. W. Interpretation of well-block pressures in numerical reservoir simulation with nonsquare grid blocks and anisotropic permeability. Soc. Pet. Eng. J. 23, 531–543 (1983).

    Article  Google Scholar 

  52. Cappa, F. & Rutqvist, J. Modeling of coupled deformation and permeability evolution during fault reactivation induced by deep underground injection of CO2. Int. J. Greenh. Gas Control 5, 336–346 (2011).

    Article  Google Scholar 

  53. Frohlich, C. Triangle diagrams: ternary graphs to display similarity and diversity of earthquake focal mechanisms. Phys. Earth Planet. Inter. 75, 193–198 (1992).

    ADS  Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Science Foundation via the IUCR center Geomechanics and Mitigation of Geohazards (award number 1822214) and via the Southern California Earthquake Center (SCEC). The SCEC is funded by NSF Cooperative Agreement EAR-1600087 and USGS Cooperative Agreement G17AC00047.

Author information

Authors and Affiliations

Authors

Contributions

K.I. carried out the data analysis and numerical simulations. E.R.H. computed the coseismic Coulomb stress changes. D.E. provided the simulator TOUGH–FLAC. K.I. and J.-P.A. designed the study and wrote the Article. All authors edited the manuscript.

Corresponding author

Correspondence to Kyungjae Im.

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The authors declare no competing interests.

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Peer review information Nature thanks Roland Burgmann, J. Ole Kaven and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Seismicity before and after the Ridgecrest mainshock (5 July 2019) in and around the Coso area.

We divided the area into different domains. ad, Relocated seismicity10 of all magnitude, before (2010 to the Mw = 7.1 mainshock; grey circles) and after (Mw = 7.1 mainshock to the end of 2019; blue circles) the Ridgecrest earthquake. ah, We compare the spatial distribution (ad) and cumulative magnitude–frequency distribution (eh) of earthquakes before (black) and after (blue) the mainshock for the Coso volcanic area (a, e), Cactus flat (b, f), Coso geothermal field (c, g) and the northwest edge of the Mw = 7.1 event (d, h). Red rectangles in a define the areas for each plot. Black triangles in c indicate the locations of geothermal wells. The density of aftershocks above the detection threshold (Mw > 1) is about two orders of magnitude lower in the Coso geothermal field (c) than in the surrounding areas (b, d). A similar result has been reported previously4.

Extended Data Fig. 2 History of seismicity in the Coso area.

a, Distribution of seismicity (Mw > 1)10. b, Seismicity history over the entire Coso area. cf, Seismicity history of event magnitude (circles; left axis) and annual rate (black line; right axis) for each fault zone (ce, Coso main field; f, east flank area), as indicated in a. The fault zones are selected on the basis of the expression of the seismic cloud.

Extended Data Fig. 3 Change of focal mechanism in the Coso main field area and effective stress changes predicted by the simulation.

a, The rake angle shows that the proportion of normal faulting (−120° to about −60°) increases with time. b, c, Ternary plots53 show that the formal mechanism is more diverse, with increased normal faulting in the later operation period (2001–2019; c) than in the earlier period (1981–2000; b). df, Time-dependent maximum horizontal (red), minimum horizontal (blue) and vertical (black) stress at different depths, calculated as an average along a 1-km baseline at the centre of the reservoir at each depth (d, 1,000 m; e, 1,500 m; f, 1,750 m). The stresses within the reservoir (e, f) decline with time, but the rate of decline in vertical stress is lower than that in maximum horizontal stress. The simulation predicts an increase in the proportion of normal faulting and diversity of focal mechanism, as observed in ac.

Extended Data Fig. 4 Model description.

Blue, dark green and light green blocks represent the reservoir, upper host and lower host elements, respectively. The right-hand side shows the repeating five-spot pattern of injectors (triangles) and producers (circles). Inset, initial horizontal stresses (σ1, maximum; σ3, minimum) calculated from Coso field data (Fig. 1a, inset). Vertical stress (σv) is calculated as gravitational stress for an effective density of 1,400 kg m−3 at every time step. The x axis is chosen to be parallel to the dominant fault orientation in the main field (Fig. 1a, inset), which is parallel to the main fault ruptured in the Mw = 7.1 Ridgecrest earthquake. Roller and shear stress boundaries are applied corresponding to the initial stress, as shown in the inset. The ground surface is stress-free.

Extended Data Fig. 5 Simulation results with lower flow rate.

This simulation result is identical to that shown in Fig. 2, but with a lower flow rate, set to match the injection rate via permeability reduction. Other parameters are identical to our reference simulation (Fig. 2). a, Reported injection and production flow rates from the Coso field (thin lines) and simulation (bold lines). b, Ground deformation recovered from InSAR measurements between May 1996 and June 199814. Image adapted with permission from ref. 14, American Geophysical Union. c, Cumulative line-of-sight (LOS) surface displacement at the end of the simulation (year 30). The white arrow shows the line-of-sight unit vector (0.38, −0.09, 0.92)14. d, Time evolution of maximum line-of-sight displacement (black line) and observations (blue solid lines)14,33,34, along with their extrapolations (blue dashed lines). e, Shear stress at the end of the simulation (year 30) in the orientation parallel to the Mw = 7.1 rupture in the reservoir area (inset).

Extended Data Fig. 6 Well bore and reservoir pressure.

a, Pressure change at well bores (black straight line) and well blocks (the block where the imaginary well bore is embedded; coloured lines). The pressure gap between the well bore and well block is larger at injection than at production, owing to the low temperature and consequent low fluid viscosity. b, Pressure drop distribution at the end of the simulation. The white rectangle indicates the 4 km × 4 km × 3 km reservoir area. The pressure drops by around 5.5 MPa in the reservoir, and the halo of pressure drop extends beyond the reservoir area.

Extended Data Fig. 7 Predicted surface displacements at the end of the reference simulation.

ad, Displacement along the x (a), y (b) and z (c) axes and line-of-sight displacement (d; identical to Fig. 2e). The white arrow denotes the azimuth of the line-of-sight vector (0.38, −0.09, 0.92)14.

Extended Data Fig. 8 Predicted surface deformation due to changes in pore pressure alone.

a, Line-of-sight surface displacement recovered from InSAR measurements between May 1996 and June 1998 (identical to Fig. 2d). Image adapted with permission from ref. 14, American Geophysical Union. b, Predicted line-of-sight surface displacement at the end of the isothermal simulation. All parameters are identical to those for the reference simulation (Fig. 2), which accounts for thermal strain. c, Time evolution of maximum line-of-sight displacement of the isothermal (red) and non-isothermal (black; Fig. 2f) simulations, together with observations (blue solid lines)14,33,34 and their interpolations (blue dashed lines). The ‘no thermal stress case’ represents the subsidence from pressure depletion alone. d, Observed and predicted ground displacements projected along the line of sight (arrow in b) of the InSAR images14,33. The black solid line are from our reference simulation (Fig. 2); the red solid line is from the isothermal simulation (no thermal strain). The curves are normalized by the maximum displacement of about 65 cm and about 35 cm for the reference and no-thermal-stress cases, respectively (c). The case from ref. 14 is measured between September 1993 and May 1996, with a maximum displacement of about 8 cm (west–east) and about 5 cm (south–north); the case from ref. 33 is measured between February 2008 and October 2009, with a maximum displacement of around 2 cm.

Extended Data Fig. 9 Predicted stress changes in a simulation with reduced friction.

The simulation geometry and parameters are identical to those for the reference simulation (Fig. 3), except for a lower internal friction coefficient of 0.3. a, Change in Coulomb stress at the end of the simulation (year 30), calculated for faults parallel to the main rupture (inset). b, Shear stress at the end of the simulation (year 30). Shear stress in the reservoir area (white rectangle) is strongly depleted owing to rock failure. c, Mohr circle representation of stress changes during the simulation. Maximum and minimum effective normal stress are calculated at the centre of the reservoir (stresses averaged along the yellow line in b). The Mohr circle at year 0 is smaller than for the higher friction cases (Fig. 3c) owing to initial failure. The grey dashed line indicates the input failure criteria in this simulation. d, Change in shear stress at the centre of the reservoir (averaged along the yellow line in b).

Extended Data Fig. 10 Comparison between fully elastic and Mohr–Coulomb failure models.

a, As in Fig. 3c. b, As in a, except that the reservoir is fully elastic (no failure). When the reservoir is fully elastic (that is, when failure and the resulting drop in stress are neglected), normal stresses become impossibly large in tension. c, d Evolution of normal and shear stress relative to the orientation of the Ridgecrest fault (Extended Data Fig. 4, inset) at a depth of 1,500 m, for the Mohr–Coulomb failure model (c) the fully elastic model (d). With the failure model (c), the stresses naturally approach zero over time, as a result of shear and tensile failure; in the fully elastic case (d), normal stresses transit through zero and become highly tensile when the shear stress drops, as a result of failure being ignored. The wiggles in the well pattern area of the reservoir are due to the non-uniform distribution of temperature driving differential thermal stresses.

Extended Data Fig. 11 Cumulative shear strain at the conclusion of the reference simulation (after 30 years of production).

The largest change in strain occurs in the well pattern area, where the change in temperature is largest. The maximum shear strain is about 1.1 × 10−3, which is approximately two orders of magnitude larger than the strain released by seismicity, as estimated from the sum of all seismic moments (see text).

Extended Data Table 1 Simulation model parameters

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Im, K., Avouac, JP., Heimisson, E.R. et al. Ridgecrest aftershocks at Coso suppressed by thermal destressing. Nature 595, 70–74 (2021). https://doi.org/10.1038/s41586-021-03601-4

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