The Application of Seismic Double-Difference Attenuation Tomography Method to the Geysers Geothermal Field, California

Session: Advances in Upper Crustal Geophysical Characterization
Type: Oral
Date: 4/29/2020
Time: 04:45 PM
Room: 215 + 220
Description: 

The Geysers geothermal field is the largest geothermal reservoir in the world. Investigating high-resolution subsurface structure at The Geysers is important to understand the reservoir condition, especially the injected water and fracture distribution within the reservoir. We conduct a 3-D attenuation tomography study at The Geysers using ~1000 earthquakes in 2011 and 34 seismic stations with a newly developed seismic double-difference attenuation tomography (DDQ) method. The development of our new DDQ method mainly includes two parts: (1) extracting differential t* data by fitting spectral ratios of pairs of events and (2) inverting differential t* data with a modified seismic triple-difference tomography code. The application of the spectral ratio method to The Geysers dataset shows that the differential t* data can better fit spectral ratio data compared to the absolute t* data, indicating higher accuracy of the differential t* data. By using more accurate differential t* data, we can determine a higher-resolution attenuation model in the source region. Our preliminary DDQ model at The Geysers shows some large-scale structural features that are consistent with previous seismic tomography studies and also shows more detailed structures in earthquake generation zones. Our Qp model shows a spatial variation in attenuation structure, with low Qp in the northwestern part, high Qp in the central part and low Qp in the southeastern part in the depth range of ~ 0-2 km below sea level. The Vp and Vs models from a previous study show a similar pattern, with low Vp and low Vs in the northwest and high Vp and high Vs in the central part. Earthquakes at this depth appear to occur near the boundaries between high and low Q zones. At depths of 2 to 4 km, the central region starts to show more low Qp anomalies that have a strong spatial correlation with earthquake locations.

Presenting Author: Hao Guo

Authors