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Title: AASG Wells Data for the EGS Test Site Planning and Analysis Task

AASG Wells Data for the EGS Test Site Planning and Analysis Task Temperature measurement data obtained from boreholes for the Association of American State Geologists (AASG) geothermal data project. Typically bottomhole temperatures are recorded from log headers, and this information is provided through a borehole temperature observation service for each state. Service includes header records, well logs, temperature measurements, and other information for each borehole. Information presented in Geothermal Prospector was derived from data aggregated from the borehole temperature observations for all states. For each observation, the given well location was recorded and the best available well identified (name), temperature and depth were chosen. The “Well Name Source,” “Temp. Type” and “Depth Type” attributes indicate the field used from the original service. This data was then cleaned and converted to consistent units. The accuracy of the observation’s location, name, temperature or depth was note assessed beyond that originally provided by the service. - AASG bottom hole temperature datasets were downloaded from between the dates of May 16th and May 24th, 2013. - Datasets were cleaned to remove “null” and non-real entries, and data converted into consistent units across all datasets - Methodology for selecting ”best” temperature and depth attributesmore » from column headers in AASG BHT Data sets: • Temperature: • CorrectedTemperature – best • MeasuredTemperature – next best • Depth: • DepthOfMeasurement – best • TrueVerticalDepth – next best • DrillerTotalDepth – last option • Well Name/Identifier • APINo – best • WellName – next best • ObservationURI - last option. The column headers are as follows: • gid = internal unique ID • src_state = the state from which the well was downloaded (note: the low temperature wells in Idaho are coded as “ID_LowTemp”, while all other wells are simply the two character state abbreviation) • source_url = the url for the source WFS service or Excel file • temp_c = “best” temperature in Celsius • temp_type = indicates whether temp_c comes from the corrected or measured temperature header column in the source document • depth_m = “best” depth in meters • depth_type = indicates whether depth_m comes from the measured, true vertical, or driller total depth header column in the source document • well_name = “best” well name or ID • name_src = indicates whether well_name came from apino, wellname, or observationuri header column in the source document • lat_wgs84 = latitude in wgs84 • lon_wgs84 = longitude in wgs84 • state = state in which the point is located • county = county in which the point is located « less
Publication Date:
Report Number(s):
DOE Contract Number:
FY13 AOP 1.2
Product Type:
Research Org(s):
DOE Geothermal Data Repository; National Renewable Energy Lab. (NREL), Golden, CO (United States)
National Renewable Energy Laboratory
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Office (EE-4G)
15 Geothermal Energy; geothermal; well; temperature; EGS test site; bottomhole; shp
OSTI Identifier:
  1. The Geothermal Data Repository (GDR) is the submission point for all data collected from researchers funded by the U.S. Department of Energy's Geothermal Technologies Office (DOE GTO). The DOE GTO is providing access to its geothermal project information through the GDR. The GDR is powered by OpenEI, an energy information portal sponsored by the U.S. Department of Energy and developed by the National Renewable Energy Laboratory (NREL).
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  1. To help guide its future data collection efforts, The DOE GTO funded a data gap analysis in FY2012 to identify high potential hydrothermal areas where critical data are needed. This analysis was updated in FY2013 and the resulting datasets are represented by this metadata. Themore » original process was published in FY 2012 and is available here: Though there are many types of data that can be used for hydrothermal exploration, five types of exploration data were targeted for this analysis. These data types were selected for their regional reconnaissance potential, and include many of the primary exploration techniques currently used by the geothermal industry. The data types include: 1. well data 2. geologic maps 3. fault maps 4. geochemistry data 5. geophysical data To determine data coverage, metadata for exploration data (including data type, data status, and coverage information) were collected and catalogued from nodes on the National Geothermal Data System (NGDS). It is the intention of this analysis that the data be updated from this source in a semi-automated fashion as new datasets are added to the NGDS nodes. In addition to this upload, an online tool was developed to allow all geothermal data providers to access this assessment and to directly add metadata themselves and view the results of the analysis via maps of data coverage in Geothermal Prospector ( A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the five data types. Using these five data coverage maps and the USGS Resource Potential Map, sites were identified for future data collection efforts. These sites signify both that the USGS has indicated high favorability of occurrence of geothermal resources and that data gaps exist. The uploaded data are contained in two data files for each data category. The first file contains the grid and is in the SHP file format (shape file.) Each populated grid cell represents a 10k area within which data is known to exist. The second file is a CSV (comma separated value) file that contains all of the individual layers that intersected with the grid. This CSV can be joined with the map to retrieve a list of datasets that are available at any given site. The attributes in the CSV include: 1. grid_id : The id of the grid cell that the data intersects with 2. title: This represents the name of the WFS service that intersected with this grid cell 3. abstract: This represents the description of the WFS service that intersected with this grid cell 4. gap_type: This represents the category of data availability that these data fall within. As the current processing is pulling data from NGDS, this category universally represents data that are available in the NGDS and are ready for acquisition for analytic purposes. 5. proprietary_type: Whether the data are considered proprietary 6. service_type: The type of service 7. base_url: The service URL « less
  2. This submission contains raster and vector data for the entire state of Washington, with specific emphasis on the three geothermal play fairway sites: Mount St. Helens seismic zone (MSHSZ), Wind River valley (WRV), and Mount Baker (MB). Data are provided for 3 major geothermal models:more » heat, permeability, and fluid-filled fractures, and an additional infrastructure model. Both of the permeability and fluid-filled-fracture models are produced at 200 m and at 2 km depths; the heat model is only produced at the 200 m depth. Values are provided for both model favorability and model confidence. A combined model at 200m and 2 km depths is provided for favorability, confidence, and exploration risk. Raster data are provided in GeoTiff format and have a statewide coverage. Cell size is 104.355 ft; file type is unsigned 8-bit integer (0-255); 0 represents no favorability or confidence; 255 represents maximum favorability or confidence. The NAD83(HARN)/Washington South (ftUS) projection is used (EPSG:2927). Vector data are provided in shapefile or comma-delimited text file formats. Geographic coordinates, where provided, are in WGS84. A readme file accompanies each folder and provides an overview and description of the enclosed data. The heat model combines 5 intermediate raster layers (which are included in the download package): temperature gradient wells, young volcanic vents, hot springs, young intrusive volcanic rocks, and geothermometry. The permeability model combines 8 intermediate raster layers: density of mapped faults, 2D dilation tendency of mapped faults, 2D slip tendency of mapped faults, seismicity, 3D dilation tendency, 3D slip tendency, 3D maximum coulomb shear stress, and 3D slip gradients. The fluid-filled fracture model combines up to 4 intermediate rasters: resistivity from magneto-telluric 3D inversions, seismicity, Vp/Vs anomalies from passive seismic tomography, and Vs anomalies from ambient-noise tomography. A statewide infrastructure model is also provided that formalizes land-use constraints and restrictions relevant for geothermal prospecting and development. This model combines 10 intermediate rasters: areas off limits to drilling, existing or proposed geothermal leases, DNR-owned land, land-use restrictions along the Columbia River Gorge, areas inundated by water, availability of potential process water, proximity to existing roads, proximity to transmission lines, distance from urban areas, and snow-related elevation restrictions. Supporting vector data for the development of each raster layer is provided. For details on the areas of interest and modeling process please see the 'WA_State_Play_Fairway_Phase_2_Technical_Report' in the download package. « less
  3. This submission includes a gravity data in text format and as a GIS point shapefile and transient electromagnetic (TEM) raw data. Each text file additionally contains location data (UTM Zone 12, NAD83) and elevation (meters) data for that station. The gravity data shapefile was inmore » part downloaded from PACES, University of Texas at El Paso,, and in part collected by the Utah Geological Survey (UGS) as part of the DOE GTO supported Utah FORGE geothermal energy project near Milford, Utah. The PACES data were examined and scrubbed to eliminate any questionable data. A 2.67 g/cm^3 reduction density was used for the Bouguer correction. The attribute table column headers for the gravity data shapefile are explained below. There is also metadata attached to the GIS shapefile. name: the individual gravity station name. HAE: height above ellipsoid [meter] NGVD29: vertical datum for geoid [meter] obs: observed gravity ERRG: gravity measurement error [mGal] IZTC: inner zone terrain correction [mGal] OZTC: outer zone terrain correction [mGal] Gfa: free air gravity gSBGA: Bouguer horizontal slab sCBGA: Complete Bouguer anomaly « less
  4. x,y,z data of the 3D temperature model for the West Flank Coso FORGE site. Model grid spacing is 250m. The temperature model for the Coso geothermal field used over 100 geothermal production sized wells and intermediate-depth temperature holes. At the near surface of this model,more » two boundary temperatures were assumed: (1) areas with surface manifestations, including fumaroles along the northeast striking normal faults and northwest striking dextral faults with the hydrothermal field, a temperature of ~104ËšC was applied to datum at +1066 meters above sea level elevation, and (2) a near-surface temperature at about 10 meters depth, of 20ËšC was applied below the diurnal and annual conductive temperature perturbations. These assumptions were based on heat flow studies conducted at the CVF and for the Mojave Desert. On the edges of the hydrothermal system, a 73ËšC/km (4ËšF/100’) temperature gradient contour was established using conductive gradient data from shallow and intermediate-depth temperature holes. This contour was continued to all elevation datums between the 20ËšC surface and -1520 meters below mean sea level. Because the West Flank is outside of the geothermal field footprint, during Phase 1, the three wells inside the FORGE site were incorporated into the preexisting temperature model. To ensure a complete model was built based on all the available data sets, measured bottom-hole temperature gradients in certain wells were downward extrapolated to the next deepest elevation datum (or a maximum of about 25% of the well depth where conductive gradients are evident in the lower portions of the wells). After assuring that the margins of the geothermal field were going to be adequately modelled, the data was contoured using the Kriging method algorithm. Although the extrapolated temperatures and boundary conditions are not rigorous, the calculated temperatures are anticipated to be within ~6ËšC (20ËšF), or one contour interval, of the observed data within the Coso geothermal field. Based on a lack of temperature data west of 74-2TCH, the edges of this model still seem to have an effect on West Flank modeled temperatures. « less
  5. Unprocessed active distributed temperature sensing (DTS) data from 3 boreholes in the Guelph, ON Canada region. Data from borehole 1 was collected during a fluid injection while data from boreholes 2 and 3 were collected under natural gradient conditions in a lined borehole. The columnmore » labels/headers (in the first row) define the time since start of measurement in seconds and the row labels/headers (in the first column) are the object IDs that are defined in the metadata. Each object ID is a sampling location whose exact location is defined in the metadata file. Data in each cell are temperature in Celsius at time and sampling location as defined above. « less