| Title | New Large-Scale Passive Seismic Monitoring at the Geysers Geothermal Reservoir, CA, USA |
|---|---|
| Authors | Roland GRITTO, Steve JARPE, David ALUMBAUGH |
| Year | 2022 |
| Conference | Stanford Geothermal Workshop |
| Keywords | 3D seismic imaging, large-scale and dense seismic networks, The Geysers |
| Abstract | In this paper, we present preliminary results for reservoir-wide passive seismic monitoring at The Geysers geothermal reservoir combining data from two seismic networks. The combined network with 139 stations comprises the permanently installed BG network with 49 stations and the recently installed temporary CEC network with 90 stations. For the first time, the combined network offers the opportunity to monitor the geological structure and reservoir heterogeneity on a large scale and with sufficient resolution. During the current project, seismic imaging will be conducted on an annual basis and potential temporal changes analyzed to study the underlying reservoir processes. The study area comprises the whole reservoir with an approximate extension of 30 km in NW-SE direction and 15 km in SW-NE direction. We present results for a one-year period from more than 30,000 earthquakes that were automatically processed for P- and S-wave phase arrival times. The data were subsequently inverted using a joint inversion approach to image the spatial heterogeneity of the reservoir including the 3D P- and S-wave velocity structure, Vp/Vs-ratio, and earthquake hypocenter locations. While the P- and S-wave velocity estimates reveal the geological structure of the reservoir, the Vp/Vs-ratio can be used to deduce the state of the fluid saturation (water vs. steam) in the reservoir. The seismic data will eventually be combined with reservoir wide magnetotelluric (MT) measurements to conduct joint MT and seismic imaging using workflows and algorithms that enforce structural similarity constraints between the different physical properties. The joint inversion of the multi-physics data can yield reservoir structure with higher spatial certainty than either of the data sets by themselves, which would improve the general utility for quantifying the response of an operating geothermal field to changes in injection and production. |