Seismicity Rate Change at the Coso Geothermal Field Following the July 2019 Ridgecrest Earthquakes

ABSTRACT Many geothermal and volcanic regions experience remote and regional triggering following large earthquakes. The transient or permanent changes in stresses acting on faults and fractures can lead to changes in seismicity rates following either the passage of teleseismic waves or the permanent change in stresses following regional events. One such region of prevalent triggering is the Coso Geothermal Field (CGF) in eastern California, which is located roughly 30 km to the north of the 2019 Mw 7.1 Ridgecrest epicenter. Previous regional earthquakes have not only seemingly caused increase in seismicity rate surrounding the CGF, but also showed an absence of such rate increases in the CGF itself. To test whether seismicity rates in the CGF were dissimilar to the surrounding area following the Mw 7.1 Ridgecrest earthquake, I carry out seismicity rate change calculations using a catalog of seismicity compiled using a local seismic network and find that the behavior at CGF is identical to the surrounding area. Comparisons of seismicity rate changes calculated using a regional-network-derived catalog, and the local-network-derived catalog show that for a moderate, regional earthquake (2009 Mw 5.2 Olancha, California), the local network catalog reveals a change in seismicity rate whereas the regionally network catalog shows no significant changes. The differences are possibly related to incomplete sampling of seismicity using the regional network due to the existence of a shallow brittle–ductile transition centered on the CGF. The CGF, thus, is prone to triggering from both teleseismic and regional earthquakes.

Geodetic Measurements and Numerical Models of Deformation at Coso Geothermal Field, California, USA, 2004–2016

We measure transient deformation at Coso geothermal field using interferometric synthetic aperture radar (InSAR) data acquired between 2004 and 2016 and relative positions estimated from global positioning system (GPS) to quantify relationships between deformation and pumping. We parameterize the reservoir as a cuboidal sink and solve for best-fitting reservoir dimensions and locations before and after 2010 in accordance with sustainability efforts implemented in late 2009 at the site. Time-series analysis is performed on volume changes estimated from pairs of synthetic aperture radar (SAR) and daily GPS data. We identify decreasing pore-fluid pressure as the dominant mechanism driving the subsidence observed at Coso geothermal field. We also find a significant positive correlation between deformation and production rate.