| Abstract |
The primary objective of this study was to develop and test the seismic component of a calibrated exploration method that integrated geological, geophysical, and geochemical data to identify potential drilling targets for Engineered Geothermal Systems (EGS). In exploring for EGS sites, the primary selection criteria identified by the AltaRock Energy, Inc. (AltaRock) Team were, in order of importance, (1) temperature, (2) rock type at the depth of interest; and (3) stress regime. The core exploration methodology we developed was a new seismic technique which used complementary information derived from regional tomographic models of body, shear and surface waves statistically integrated with shear velocity models derived from ambient noise to predict temperature and rock type. Using the new estimated seismic models, we tested the supposition that the uncertainty and the degree of non-uniqueness in predictions of temperature and rock type from the seismic data could be reduced by integration with other geophysical and geochemical data into an EGS conceptual model that will form the basis of an exploration methodology. The new method has been applied in Dixie Valley, NV, (DV) one of the best characterized geothermal areas in Northern America, also known for low seismicity between large events. The conclusion of an initial publicly available information review was that improved P/S seismic velocity model resolution in DV was required. A dense seismic array (21 three-component, broadband sensors, with an overall array aperture of 45km) was installed in two deployments, each of a three-month length. Ambient seismic noise and signal rather than active sources were used to retrieve inter-station and same-station Green\'s Functions (GFs), to be used for subsurface imaging. Another innovative aspect of the seismic work was to determine if estimating the receiver functions beneath the stations using noise auto-correlation could be used to image the substructure. We report results of applying the technique to estimate a P/S velocity model from the GF surface wave and P-components retrieved from ambient noise cross-correlation beams and the GF body-wave reflection component from layer interfaces. Using seismic velocity models to infer temperature is statistically assessed, in combination with other geophysical technique results. |