Conventional P-P seismic images of geothermal reservoirs are often of poor quality because P-P data tend to have a low signal-to-noise ratio across geothermal prospects. Fracture identification, fluid prediction, and imaging inside subsurface areas influenced by superheated fluids are some of the challenges facing the geothermal industry. We showed that multicomponent seismic technology is effective for addressing all of these challenges across geothermal reservoirs, even when P-P data are of low quality. Although multicomponent seismic technology has advantages in geothermal exploration, there are not many published examples of multicomponent seismic data being used to characterize geothermal reservoirs. We evaluated data examples that illustrate advantages of multicomponent seismic technology for imaging within and below zones having superheated fluids, estimating fracture attributes, analyzing reservoir trapping structures, differentiating lithologies, and predicting spatial distributions of pore fluids. All examples we tested are from the Wister geothermal field in Southern California.