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Brady's Geothermal Field - Analysis of Pressure Data
*This submission provides corrections to GDR Submissions 844 and 845* Poroelastic Tomography (PoroTomo) by Adjoint Inverse Modeling of Data from Hydrology. The 3 *csv files containing pressure data are the corrected versions of the pressure dataset found in Submission 844. The dataset has been corrected in the sense that the atmospheric pressure has been subtracted from the total pressure measured in the well. Also, the transducers used at wells 56A-1 and SP-2 are sensitive to surface temperature fluctuations. These temperature effects have been removed from the corrected datasets. The 4th *csv file contains corrected version of the pumping data found in Submission 845. The data has been corrected in the sense that the data from several wells that were used during the PoroTomo deployment pumping tests that were not included in the original dataset has been added. In addition, several other minor changes have been made to the pumping records due to flow rate instrument calibration issues that were discovered.
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Brady Geothermal Field Borehole Pressure Data
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This submission supersedes pressure data from March 2017 which can be found as a link in the submission resources. This submission contains 3 .csv files with time series pressure data in 3 observation wells at Brady Geothermal Field as part of the PoroTomo project. These pressure files correct a time stamp issue that was in older data which did not correct for daylight savings time which occurred 13 Mar 2016 at 0900 UTC. The data here provides borehole pressures at different temperatures and times. The timeframe each resource was taken in varies between each resource and can be found in the resource descriptions.
Brady Geothermal Field Well Pumping Data During Deployment
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Contains pumping data associated with the wells used in the 2016 Spring Campaign led partially by UW - Madison, LBNL, and LLNL scientists. The well coordinates and the depths to the pressure sensors used in the pumping wells can be found at the link "Coordinates and Sensor Depths" below.
Understanding Constraints on Geothermal Sustainability Through Reservoir Characterization at Brady Geothermal Field, Nevada
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The vast supply of geothermal energy stored throughout the Earth and the exceedingly long time required to dissipate that energy makes the world's geothermal energy supply nearly limitless. As such, this resource holds the potential to provide a large supply of the world's energy demands; however, like all natural resources, it must be utilized in an appropriate manner if it is to be sustainable. Understanding sustainable use of geothermal resources requires thorough characterization efforts aimed at better understanding subsurface properties. The goal of this work is to understand which critical subsurface properties exert the most influence on sustainable geothermal production as a means to provide targeted future resource characterization strategies. Borehole temperature and reservoir pressure data were analyzed to estimate reservoir thermal and hydraulic properties at an active geothermal site. These reservoir properties then served as inputs for an analytical model which simulated net power production over a 30-year period. The analytical model was used to conduct a sensitivity analysis to determine which parameters were most critical in constraining the sustainability of a geothermal reservoir. Modeling results reveal that the number of preferential flow pathways (i.e. fractures) used for heat transport provides the greatest impact on geothermal reservoir sustainability. These results suggest that early and pre-production geothermal reservoir exploration would achieve the greatest benefit from characterization strategies which seek to delineate the number of active flow pathways present in the system.
Raw Pressure Data from Observation Wells at Brady's Hot Springs
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This .csv files contain the raw water pressure data from three observation wells during pumping tests performed in the Spring of 2016. Included is a "read me" file explaining the details of where and how the data were collected.