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  1. Dataset documenting rock core evaluation from Brady’s Hot Springs well BCH-03

    Nineteen short sections of core were taken from the BCH-03 borehole at Brady’s Hot Springs, Churchill County, Nevada, between 2,945 ft and the total depth of 4,885 ft. This well is in a geothermal field. Data collected includes thin section photomicrographs, Medical CT tiff stacks, microCT tiff stacks, XRD, porosity (from thin sections, He porosimeter, microCT segmentation) and P/S wave velocities.
  2. Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs: Preprint

    Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-termmore » memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.« less
  3. Time–series Analysis of Volume Change at Brady Hot Springs, Nevada, USA using Geodetic Data from 2003 – 2018

    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 1656 cubic voxels in a parameterized elastic dislocation model to identify areasmore » 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. Here, 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.« less
  4. Comparisons Between Array Derived Dynamic Strain Rate (ADDS) and Fiber‐Optic Distributed Acoustic Sensing (DAS) Strain Rate

    Abstract Distributed acoustic sensing (DAS) strain rate and particle velocity can be compared through approximate scaling with medium velocity. We instead performed a direct comparison between array derived dynamic strain (ADDS) rate and DAS strain rate for six frequency bands. The PoroTomo project at Brady's Hot Springs, Nevada, deployed a 240‐geophone 3C array co‐located with fiber‐optic DAS system and 8.7 km of buried cable. We selected subsets of the geophone array to create four smaller arrays and computed ADDS. The horizontal components of the ADDS were rotated into the direction of the fiber‐optic cable and then compared with the observed DASmore » strain rates. From three example regional earthquakes of local magnitudes 2.9, 4.1, and 4.3, the ADDS are found to be coherent with DAS for frequencies ≤1 Hz. For frequencies >1‐Hz, this correlation decays quickly. Small differences between linear and areal dynamic strains at 1‐Hz suggest poor signal‐to‐noise or localized strain that is perturbed by shallow heterogeneities compare to the average strain propagating across the geophone array. The implication is that around 1‐Hz, straight fiber DAS is measuring axial strain along the fiber and can provide good approximations to translational particle motions. However, above 1‐Hz, DAS becomes more sensitive to shallow velocity gradients that can be beneficial for geophysical imaging yet becomes a limitation for traditional seismic analysis methods depending on absolute amplitude and phase from translational particle motions.« less
  5. Characterizing volumetric strain at Brady Hot Springs, Nevada, USA using geodetic data, numerical models and prior information

    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 withmore » ‘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.« less
  6. Modeling Subsurface Performance of a Geothermal Reservoir Using Machine Learning

    Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells—increasing or decreasing the fluid flow rates across the wells—and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for themore » active wells into reservoir-wide estimates of produced energy, and second, to find optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an “open-source” reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 h, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 s. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.« less
  7. Time-series analysis of surface deformation at Brady Hot Springs geothermal field (Nevada) using interferometric synthetic aperture radar

    We analyze interferometric synthetic aperture radar (InSAR) data acquired between 2004 and 2014, by the ERS-2, Envisat, ALOS and TerraSAR-X/TanDEM-X satellite missions to measure and characterize time-dependent deformation at the Brady Hot Springs geothermal field in western Nevada due to extraction of fluids. The long axis of the ~4 km by ~1.5 km elliptical subsiding area coincides with the strike of the dominant normal fault system at Brady. Within this bowl of subsidence, the interference pattern shows several smaller features with length scales of the order of ~1 km. This signature occurs consistently in all of the well-correlated interferometric pairsmore » spanning several months. Results from inverse modeling suggest that the deformation is a result of volumetric contraction in shallow units, no deeper than 600 m, likely associated with damaged regions where fault segments mechanically interact. Such damaged zones are expected to extend downward along steeply dipping fault planes, providing a high permeability conduit to the production wells. Using time series analysis, we test the hypothesis that geothermal production drives the observed deformation. We find a good correlation between the observed deformation rate and the rate of production in the shallow wells. We also explore mechanisms that could potentially cause the observed deformation, including thermal contraction of rock, decline in pore pressure and dissolution of minerals over time.« less
  8. Time-series analysis of surface deformation at Brady Hot Springs geothermal field (Nevada) using interferometric synthetic aperture radar

    For this work, we analyze interferometric synthetic aperture radar (InSAR) data acquired between 2004 and 2014, by the ERS-2, Envisat, ALOS and TerraSAR-X/TanDEM-X satellite missions to measure and characterize time-dependent deformation at the Brady Hot Springs geothermal field in western Nevada due to extraction of fluids. The long axis of the ~4 km by ~1.5 km elliptical subsiding area coincides with the strike of the dominant normal fault system at Brady. Within this bowl of subsidence, the interference pattern shows several smaller features with length scales of the order of ~1 km. This signature occurs consistently in all of themore » well-correlated interferometric pairs spanning several months. Results from inverse modeling suggest that the deformation is a result of volumetric contraction in shallow units, no deeper than 600 m, likely associated with damaged regions where fault segments mechanically interact. Such damaged zones are expected to extend downward along steeply dipping fault planes, providing a high permeability conduit to the production wells. Using time series analysis, we test the hypothesis that geothermal production drives the observed deformation. We find a good correlation between the observed deformation rate and the rate of production in the shallow wells. We also explore mechanisms that could potentially cause the observed deformation, including thermal contraction of rock, decline in pore pressure and dissolution of minerals over time.« less
  9. Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project

    The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the material properties are registered on a three-dimensional grid with a spacing of 25 meters between nodes. The material properties are listed an Excel file. Figures show planar slices in three sets: horizontal slices in a planes normal to the vertical Z axis (Z normal), vertical slices in planes perpendicular to the dominant strike of the fault system (X normal), and vertical slices in planes parallel to the dominant strike of the fault system (Y normal).more » The results agree on the following points. The material is unconsolidated and/or fractured, especially in the shallow layers. The structural trends follow the fault system in strike and dip. The geodetic measurements favor the hypothesis of thermal contraction. Temporal changes in pressure, subsidence rate, and seismic amplitude are associated with changes in pumping rates during the four stages of the deployment in 2016. The modeled hydraulic conductivity is high in fault damage zones. All the observations are consistent with the conceptual model: highly permeable conduits along faults channel fluids from shallow aquifers to the deep geothermal reservoir tapped by the production wells.« less
  10. 3D Imaging of Geothermal Faults from a Vertical DAS Fiber at Brady Hot Spring, NV USA

    In March 2016, arguably the most ambitious 4D (3D space + over time) active-source seismic survey for geothermal exploration in the U.S. was acquired at Brady Natural Laboratory, outside Fernley, Nevada. The four-week experiment included 191 vibroseis source locations, and approximately 130 m of distributed acoustic sensing (DAS) in a vertical well, located at the southern end of the survey area. The imaging of the geothermal faults is done with reverse time migration of the DAS data for both P-P and P-S events in order to generate 3D models of reflectivity, which can identify subsurface fault locations. Three scenarios ofmore » receiver data are explored to investigate the reliability of the reflectivity models obtained: (1) Migration of synthetic P-P and P-S DAS data, (2) migration of the observed field DAS data and (3) migration of pure random noise to better assess the validity of our results. The comparisons of the 3D reflectivity models from these three scenarios confirm that sections of three known faults at Brady produce reflected energy observed by the DAS. Two faults that are imaged are ~1 km away from the DAS well; one of these faults (middle west-dipping) is well-constructed for over 400 m along the fault’s strike, and 300 m in depth. These results confirm that the DAS data, together with an imaging engine such as reverse time migration, can be used to position important geothermal features such as faults.« less
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