The goal of this study is to utilize a cost-effective high-density seismic array to obtain high-resolution images of reservoir properties at The Geysers geothermal reservoir in northern California. The study is based on the deployment of a dense seismic network over a 5 x 5 km study area in the central Geysers geothermal reservoir. The network configuration resulted from a design study, which employed 100 sensors and analyzed the resulting resolution in elastic parameters such as P- and S-wave velocity estimates. The design study is based on a one-year period of previously acquired microearthquake locations within the study area, 3D P- and S-wave velocity models, and surface topography. Over 3,000 earthquakes were selected, which are densely distributed and cluster in various locations of the region. Based on the hypocenter locations, the 3D velocity models and the various network designs of seismic stations in the study area, synthetic P- and S-wave travel times were computed using an eikonal solver. The algorithms used to estimate model parameter resolution of our seismic velocity estimates were based on (a) a method for computing singular values of large sparse systems values with an iterative Lanczos scheme to obtain quantitative resolution and (b) by 3D inversion for earthquake hypocenters and velocity structure based on absolute and double difference travel times to obtain qualitative resolution estimates. We present the effects of various network topologies including regular and irregular shaped network geometries with a varying number of sensors and incorporate the influences of surface topography on the resolution of the reservoir parameters. The results of the design study were subsequently used to deploy a high-density network of autonomous seismic sensors at The Geysers. The ultimate goal of the study includes the application of rock physics models and theory to the seismic imaging results to derive mechanical properties that are relevant for reservoir engineers.

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