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Title: Structural Orientations Adjacent to Some Colorado Geothermal Systems

Structural orientations (fractures, joints, faults, lineaments, bedding orientations, etc.) were collected with a standard Brunton compass during routine field examinations of geothermal phenomena in Colorado. Often multiple orientations were taken from one outcrop. Care was taken to ensure outcrops were "in place". Point data was collected with a hand-held GPS unit. The structural data is presented both as standard quadrant measurements and in format suitable for ESRI symbology
Publication Date:
Report Number(s):
DOE Contract Number:
Product Type:
Research Org(s):
DOE Geothermal Data Repository; Flint Geothermal, LLC
Flint Geothermal, LLC
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
15 Geothermal Energy; geothermal; Colorado; Faults; Structure; ArcGIS; GIS; shapefile; shape file; geospatial
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  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. These line shapefiles trace apparent topographic and air-photo lineaments in various counties in Colorado. It was made in order to identify possible fault and fracture systems that might be conduits for geothermal fluids, as part of a DOE reconnaissance geothermal exploration program. Geothermal fluids commonlymore » utilize fault and fractures in competent rocks as conduits for fluid flow. Geothermal exploration involves finding areas of high near-surface temperature gradients, along with a suitable "plumbing system" that can provide the necessary permeability. Geothermal power plants can sometimes be built where temperature and flow rates are high. This line shapefile is an attempt to use desktop GIS to delineate possible faults and fracture orientations and locations in highly prospective areas prior to an initial site visit. Geochemical sampling and geologic mapping could then be centered around these possible faults and fractures. To do this, georeferenced topographic maps and aerial photographs were utilized in an existing GIS, using ESRI ArcMap 10.0 software. The USA_Topo_Maps and World_Imagery map layers were chosen from the GIS Server at, using a UTM Zone 13 NAD27 projection. This line shapefile was then constructed over that which appeared to be through-going structural lineaments in both the aerial photographs and topographic layers, taking care to avoid manmade features such as roads, fence lines, and utility right-of-ways. Still, it is unknown what actual features these lineaments, if they exist, represent. Although the shapefiles are arranged by county, not all areas within any county have been examined for lineaments. Work was focused on either satellite thermal infrared anomalies, known hot springs or wells, or other evidence of geothermal systems. Finally, lineaments may be displaced somewhat from their actual location, due to such factors as shadow effects with low sun angles in the aerial photographs. Credits: These lineament shapefile was created by Geothermal Development Associates, as part of a geothermal geologic reconnaissance performed by Flint Geothermal, LLC, of Denver Colorado. Use Limitation: These shapefiles were constructed as an aid to geothermal exploration in preparation for a site visit for field checking. We make no claims as to the existence of the lineaments, their location, orientation, and/or nature. « less
  2. This layer contains favorable geochemistry for high-temperature geothermal systems, as interpreted by Richard "Rick" Zehner. The data is compiled from the data obtained from the USGS. The original data set combines 15,622 samples collected in the State of Colorado from several sources including 1) themore » original Geotherm geochemical database, 2) USGS NWIS (National Water Information System), 3) Colorado Geological Survey geothermal sample data, and 4) original samples collected by R. Zehner at various sites during the 2011 field season. These samples are also available in a separate shapefile FlintWaterSamples.shp. Data from all samples were reportedly collected using standard water sampling protocols (filtering through 0.45 micron filter, etc.) Sample information was standardized to ppm (micrograms/liter) in spreadsheet columns. Commonly-used cation and silica geothermometer temperature estimates are included. « less
  3. The New River Geothermal Exploration (DOE Award No. EE0002843) is located approximately 25km south of the Salton Sea, near town of Brawley in Imperial County and approximately 150km east of San Diego, California. A total of 182 MT Logger sites were completed covering the twomore » separate Mesquite and New River grids. The data was collected over a frequency range of 320Hz to 0.001Hz with variable site spacing. A number of different inversion algorithms in 1D, 2D and 3D were used to produce resistivity-depth profiles and maps of subsurface resistivity variations over the survey area. For 2D inversions, a total of eighteen lines were constructed in east-west and north-south orientations crossing the entire survey area. For MT 3D inversion, the New River property was divided in two sub-grids, Mesquite and New River areas. The report comprises of two parts. For the first part, inversions and geophysical interpretation results are presented with some recommendations of the potential targets for future follow up on the property. The second part of the report describes logistics of the survey, survey parameters, methodology and the survey results (data) in digital documents. The report reviews a Spartan MT survey carried out by Quantec Geoscience Limited over the New River Project in California, USA on behalf of Ram Power Inc. Data was acquired over a period of 29 days from 2010/06/26 to 2010/07/24. « less
  4. 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
  5. Over the course of the entire project, field visits were made to 117 geothermal systems in the Great Basin region. Major field excursions, incorporating visits to large groups of systems, were conducted in western Nevada, central Nevada, northwestern Nevada, northeastern Nevada, east‐central Nevada, eastern California,more » southern Oregon, and western Utah. For example, field excursions to the following areas included visits of multiple geothermal systems: - Northwestern Nevada: Baltazor Hot Spring, Blue Mountain, Bog Hot Spring, Dyke Hot Springs, Howard Hot Spring, MacFarlane Hot Spring, McGee Mountain, and Pinto Hot Springs in northwest Nevada. - North‐central to northeastern Nevada: Beowawe, Crescent Valley (Hot Springs Point), Dann Ranch (Hand‐me‐Down Hot Springs), Golconda, and Pumpernickel Valley (Tipton Hot Springs) in north‐central to northeast Nevada. - Eastern Nevada: Ash Springs, Chimney Hot Spring, Duckwater, Hiko Hot Spring, Hot Creek Butte, Iverson Spring, Moon River Hot Spring, Moorman Spring, Railroad Valley, and Williams Hot Spring in eastern Nevada. - Southwestern Nevada‐eastern California: Walley’s Hot Spring, Antelope Valley, Fales Hot Springs, Buckeye Hot Springs, Travertine Hot Springs, Teels Marsh, Rhodes Marsh, Columbus Marsh, Alum‐Silver Peak, Fish Lake Valley, Gabbs Valley, Wild Rose, Rawhide‐ Wedell Hot Springs, Alkali Hot Springs, and Baileys/Hicks/Burrell Hot Springs. - Southern Oregon: Alvord Hot Spring, Antelope Hot Spring‐Hart Mountain, Borax Lake, Crump Geyser, and Mickey Hot Spring in southern Oregon. - Western Utah: Newcastle, Veyo Hot Spring, Dixie Hot Spring, Thermo, Roosevelt, Cove Fort, Red Hill Hot Spring, Joseph Hot Spring, Hatton Hot Spring, and Abraham‐Baker Hot Springs. Structural controls of 426 geothermal systems were analyzed with literature research, air photos, google‐Earth imagery, and/or field reviews (Figures 1 and 2). Of the systems analyzed, we were able to determine the structural settings of more than 240 sites. However, we found that many “systems” consisted of little more than a warm or hot well in the central part of a basin. Such “systems” were difficult to evaluate in terms of structural setting in areas lacking in geophysical data. Developed database for structural catalogue in a master spreadsheet. Data components include structural setting, primary fault orientation, presence or absence of Quaternary faulting, reservoir lithology, geothermometry, presence or absence of recent magmatism, and distinguishing blind systems from those that have surface expressions. Reviewed site locations for all 426 geothermal systems– Confirmed and/or relocated spring and geothermal sites based on imagery, maps, and other information for master database. Many systems were mislocated in the original database. In addition, some systems that included several separate springs spread over large areas were divided into two or more distinct systems. Further, all hot wells were assigned names based on their location to facilitate subsequent analyses. We catalogued systems into the following eight major groups, based on the dominant pattern of faulting (Figure 1): - Major normal fault segments (i.e., near displacement maxima). - Fault bends. - Fault terminations or tips. - Step‐overs or relay ramps in normal faults. - Fault intersections. - Accommodation zones (i.e., belts of intermeshing oppositely dipping normal faults), - Displacement transfer zones whereby strike‐slip faults terminate in arrays of normal faults. - Transtensional pull‐aparts. These settings form a hierarchal pattern with respect to fault complexity. - Major normal faults and fault bends are the simplest. - Fault terminations are typically more complex than mid‐segments, as faults commonly break up into multiple strands or horsetail near their ends. - A fault intersection is generally more complex, as it generally contains both multiple fault strands and can include discrete di... « less