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Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time‐series analysis of each of the 1,656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time‐series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. The rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix. Key Points: GPS and InSAR data show temporal variations in subsidence rateSpatial distribution of deformation is described by "multicube" elastic dislocation model of thermal contractionTemporal variations are related to changes in pumping by the power plant at Brady Hot Springs, Nevada, USA [ABSTRACT FROM AUTHOR]

The geothermal field at Brady Hot Springs, Nevada has subsided over the past decade. Between 2004 and 2014, the rate of downward-vertical displacement was on the order of 10 mm yr−1, as measured by two independent geodetic techniques: interferometric synthetic aperture radar (InSAR) and Global Positioning System. The observed deformation field forms an approximately elliptical bowl that is 4 km long and aligned with the trace of the NNE striking normal fault system. We use modelling to estimate the plausibility of pressure changes or thermal contraction as the cause of the observed subsidence. As a result, Bayesian inference favours with 'very strong evidence' thermal contraction over other hypotheses as the dominant driving mechanism for the observed subsidence. Using InSAR data spanning from 2016 July 22 to 2017 August 22, we estimate the volume change rate in the significantly deforming volume to be (−29 ± 3) thousand m3 yr−1 and the total rate of change in thermal energy between −53 and −79 MW. We infer the total volume of cubes where the estimated volumetric strain rate is significantly different from zero with 95 per cent confidence to be 119 million m3. We find that the main region of significant cooling occurs between the injection and production well locations. This result supports the idea that highly permeable conduits along faults channel fluids from shallow aquifers to the deep reservoir tapped by the production wells. [ABSTRACT FROM AUTHOR]

We measure transient deformation at Coso geothermal field using interferometric synthetic aperture radar (InSAR) data acquired between 2004 and 2016 and relative positions estimated from global positioning system (GPS) to quantify relationships between deformation and pumping. We parameterize the reservoir as a cuboidal sink and solve for best-fitting reservoir dimensions and locations before and after 2010 in accordance with sustainability efforts implemented in late 2009 at the site. Time-series analysis is performed on volume changes estimated from pairs of synthetic aperture radar (SAR) and daily GPS data. We identify decreasing pore-fluid pressure as the dominant mechanism driving the subsidence observed at Coso geothermal field. We also find a significant positive correlation between deformation and production rate. [ABSTRACT FROM AUTHOR]

Although subsidence has been observed at the San Emidio geothermal field in Nevada using interferometric synthetic aperture radar since the early 1990s, the spatial extent and temporal evolution of the subsidence have not heretofore been quantified. Furthermore, the weather conditions and geographic location of San Emidio negatively affect interferometric image quality, causing low correlation amongst pairs. To address this, we introduce a new method for selecting pairs in areas of low correlation and small deformation signal using a minimum spanning tree method with a measure of image quality as the weighting criterion. We validate our pair selection approach by comparing our data products to SqueeSAR TM data products from a previous study at San Emidio. We also develop a deformation model which characterizes the spatial extent of subsidence at San Emidio in terms of volume change of the reservoir. After applying this deformation model to our data set of interferometric pairs, we examine the temporal relationship of the observed deformation with production and injection operations associated with geothermal power production. [ABSTRACT FROM AUTHOR]