These data are from tidal resource characterization measurements collected between April and July 2017 in Western Passage near Eastport, Maine, USA. The dataset contains the following four sub-datasets, each of which is described in more detail in the README.pdf. 1. A bottom-mounted Teledyne RDI Workhorse 600 kHz acoustic Doppler current profiler (ADCP) was deployed at 44.92015 N, 66.98915 W in ~50 m of water from 3 April to 18 July (106 days). Data were recorded in 6-minute increments in the ENU (East, magnetic North, Up) coordinate system with bin-mapping enabled. 2. A bottom-mounted Nortek Signature 500 kHz ADCP was deployed at 44.92192 N, 66.98913 W in ~50 m of water from 4 April to 18 July (105 days). Data were sampled and recorded at 2 Hz and recorded in the ENU (East, magnetic North, Up) coordinate system. 3. Between those stations along a cross-channel transect, a Stable Tidal Turbulence Mooring (STTM) positioned ~10 m above the seabed was deployed for one week during a spring tide. The STTM was outfitted with two Nortek Vector acoustic Doppler velocimeters equipped with inertial motion units (ADVs), a bottom-tracking downward-looking Teledyne RDI Workhorse 600 kHz ADCP to provide motion-corrected flow and turbulence characteristics at high temporal resolution, and an upward-looking Teledyne RDI Sentinel V20 ADCP. The STTM was deployed at 44.92098 N, 66.98922 W from 24-31 May. 4. A vessel-mounted Teledyne RDI Workhorse 300 kHz ADCP collected current data along three transects over two days, 4-5 April. The data processing used DOLfYN version 0.11.2. All hdf5 files (i.e., files ending in `.h5`) contained here can be opened using that version of DOLfYN (e.g., `dat = dolfyn.load('')`). All distances are in meters (e.g., depth, range, MLLW, hab, eta, z_), and all velocities in m/s. See the DOLfYN documentation https://lkilcher.github.io/dolfyn/), and/or the Nortek and Teledyne RDI documentation for additional details. Additional details on the dataset can be found in the README.pdf, including: - Format details of each data file. - How to regenerate the data-processing (using the files in the `wp2017_processing.zip` archive).

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four learning rates, six minibatch sizes, four levels of label noise, and fourteen levels of L1 and L2 regularization each. Multiple repetitions (typically 30, sometimes 10) of each combination of hyperparameters were preformed, and statistics including training and test loss (using a 80% / 20% shuffled train-test split) are recorded at the end of each training epoch. In total, this dataset covers 178 thousand distinct hyperparameter settings ("experiments"), 3.55 million individual training runs (an average of 20 repetitions of each experiments), and a total of 13.3 billion training epochs (three thousand epochs were covered by most runs). Accumulating this dataset consumed 5,448.4 CPU core-years, 17.8 GPU-years, and 111.2 node-years.

This package includes data and footage from two rounds of downhole camera surveys performed at the Sanford Underground Research Facility (SURF) on the 4850 level. The exercise was performed once on 25 May 2018 and once on 21 December 2018. On May 25th, the first round was done during fluid injection at the 164-ft stimulation zone in the injection well (E1-I). On December 21st, the second round was carried out during fluid injection at the 142-ft stimulation zone. Prior to the injections, downhole instrumentation was removed from the production well (E1-P) to allow room for the downhole camera system. The water within E1-P was then lifted out by the application of air pressure and the downhole camera system was conveyed into the production well. Finally, the water was injected into E1-I and the camera was used to scan for jetting points, or fluid entry, in E1-P. There is a survey description in this package that further describes the procedure of the survey and the overall results. Additionally, there is a detailed analysis of the surveys in the form of a PowerPoint, which includes animations/visualizations from the camera footage, presents interpretations in detail, and provides some general conclusions. Three animations, along with the two video segments that show the jetting into E1-P, are also provided. The video footage was collected using a GeoVISION Dual-Scan Micro Video Camera, the specs of which are also included in this package as a resource.

EPA no longer updates this information, but it may be useful as a reference or resource. Welcome to the STORET Legacy Data Center, site of the world's largest repository of ambient Water Quality Data. From this site you will be able to access a database that holds over 200 million water sample observations from about 700,000 sampling sites for both surface and ground water.This web site allows both scientists and the general public to access the historical data from the legacy STORET system. First-time users should narrow their search based on the options from the Query page, while experienced users may jump to the no-frills Advanced Query form for requesting data. Legacy STORET contains data of undocumented quality. Further, the data in this system is static, and all new data are being entered into Modernized STORET. Background information about the Office of Water and the history of STORET may be found by following the Purpose link. For more information on the layout of this site, please follow the Site Map link. Internet Archive URL: https://web.archive.org/web/*/https://www3.epa.gov/storet/legacy/gateway.htm

The project provides an updated Energy Return on Investment (EROI) for Enhanced Geothermal Systems (EGS). Results incorporate Argonne National Laboratory's Life Cycle Assessment and base case assumptions consistent with other projects in the Analysis subprogram. EROI is a ratio of the energy delivered to the consumer to the energy consumed to build, operate, and decommission the facility. EROI is important in assessing the viability of energy alternatives. Currently EROI analyses of geothermal energy are either out-of-date, of uncertain methodology, or presented online with little supporting documentation. This data set is a collection of files documenting data used to calculate the Energy Return On Investment (EROI) of Engineered Geothermal Systems (EGS) and erratum to publications prior to the final report. Final report is available below, or from the OSTI web site (http://www.osti.gov/geothermal/). Data in this collections includes the well designs used, input parameters for GETEM, a discussion of the energy needed to haul materials to the drill site, the baseline mud program, and a summary of the energy needed to drill each of the well designs. EROI is the ratio of the energy delivered to the customer to the energy consumed to construct, operate, and decommission the facility. Whereas efficiency is the ratio of the energy delivered to the customer to the energy extracted from the reservoir.

This dataset contains a variety of data about the Fort Bliss geothermal area, part of the southern portion of the Tularosa Basin, New Mexico. The dataset contains schematic models for the McGregor Geothermal System, a shallow temperature survey of the Fort Bliss geothermal area. The dataset also contains Century OH logs, a full temperature profile, and complete logs from well RMI 56-5, including resistivity and porosity data, drill logs with drill rate, depth, lithology, mineralogy, fractures, temperature, pit total, gases, and descriptions among other measurements as well as CDL, CNL, DIL, GR Caliper and Temperature files. A shallow (2 meter depth) temperature survey of the Fort Bliss geothermal area with 63 data points is also included. Two cross sections through the Fort Bliss area, also included, show well position and depth. The surface map included shows faults and well spatial distribution. Inferred and observed fault distributions from gravity surveys around the Fort Bliss geothermal area.

The geocellular model of the Mt. Simon Sandstone was constructed for the University of Illinois at Urbana-Champaign DDU feasibility study. Starting with the initial area of review (18.0 km by 18.1 km [11.2 miles by 11.3 miles]) the boundaries of the model were trimmed down to 9.7 km by 9.7 km (6 miles by 6 miles) to ensure that the model enclosed a large enough volume so that the cones of depression of both the production and injection wells would not interact with each other, while at the same time minimizing the number of cells to model to reduce computational time. The grid-cell size was set to 61.0 m by 61.0 m (200 feet by 200 feet) for 160 nodes in the X and Y directions. Within the model, 67 layers are represented that are parameterized with their sediment/rock properties and petrophysical data. The top surface of the Mt. Simon Sandstone was provided by geologists working on the project, and the average thickness of the formation was taken from the geologic prospectus they provided. An average thickness of 762 m (2500 feet) was used for the Mt. Simon Sandstone, resulting in 60 layers for the model. Petrophysical data was taken from available rotary sidewall core data (Morrow et al., 2017). As geothermal properties (thermal conductivity, specific heat capacity) are closely related to mineralogy, specifically the percentage of quartz, available mineralogical data was assembled and used with published data of geothermal values to determine these properties (Waples and Waples, 2004; Robertson, 1988). The Mt. Simon Sandstone was divided into three separate units (lower, middle, upper) according to similar geothermal and petrophysical properties, and distributed according to available geophysical log data and prevailing interpretations of the depositional/diagenetic history (Freiburg et al. 2016). Petrophysical and geothermal properties were distributed through geostatistical means according to the associated distributions for each lithofacies. The formation temperature was calculated, based on data from continuous temperature geophysical log from a deep well drilled into the Precambrian basement at the nearby Illinois Basin Decatur Project (IBDP) where CO2 is currently being sequestered (Schlumberger, 2012). Salinity values used in the model were taken from regional studies of brine chemistry in the Mt. Simon Sandstone, including for the IBDP (e.g., Panno et al. 2018). After being reviewed by the project's geologists, the model was then passed onto the geological engineers to begin simulations of the geothermal reservoir and wellbores.

The geocellular model of the St. Peter Sandstone was constructed for the University of Illinois at Urbana-Champaign DDU feasibility study. Starting with the initial area of review (18.0 km by 18.1 km [11.2 miles by 11.3 miles]) the boundaries of the model were trimmed down to 9.7 km by 9.7 km (6 miles by 6 miles) to ensure that the model enclosed a large enough volume so that the cones of depression of both the production and injection wells would not interact with each other, while at the same time minimizing the number of cells to model to reduce computational time. The grid-cell size was set to 61.0 m by 61.0 m (200 feet by 200 feet) for 160 nodes in the X and Y directions. The top surface of the St. Peter Sandstone was provided by geologists working on the project, and the average thickness of the formation was taken from the geologic prospectus they provided. An average thickness of 68.6 m (225 feet) was used for the St. Peter Sandstone, resulting in 45 layers for the model. Petrophysical data was taken from available rotary sidewall core data (Morrow et al., 2017). As geothermal properties (thermal conductivity, specific heat capacity) are closely related to mineralogy, specifically the percentage of quartz, available mineralogical data was assembled and used with published data of geothermal values to determine these properties (Waples and Waples, 2004; Robertson, 1988). The St. Peter Sandstone was divided into facies according to similar geothermal and petrophysical properties, and distributed according to available geophysical log data and prevailing interpretations of the depositional/diagenetic history (Will et al. 2014). Petrophysical and geothermal properties were distributed through geostatistical means according to the associated distributions for each lithofacies. The formation temperature was calculated, based on data from continuous temperature geophysical log from a deep well drilled into the Precambrian basement at the nearby Illinois Basin Decatur Project (IBDP) where CO2 is currently being sequestered (Schlumberger, 2012). Salinity values used in the model were taken from regional studies of brine chemistry in the St. Peter Sandstone, including for the IBDP (e.g., Panno et al. 2018). After being reviewed by the project's geologists, the model was then passed onto the geological engineers to begin simulations of the geothermal reservoir and wellbores.

Metadata for active distributed temperature survey (DTS) experiments at Guelph, Ontario Canada. This data that this metadata refers to was taken as part of the PoroTomo project. The metadata includes information about status, location, elevation, units, and other metadata.

Aqueous chemistry and well metadata from the USGS for Geothermal Wells in Hawaii

This GIS layer contains bathymetric elevation bands (derived from bathymetric contours) of selected freshwater lakes in Washington State. The majority of the bathymetric contours were digitized from maps contained in a series of seven documents: Reconnaissance Data on Lakes in Washington, Water-Supply Bulletin 43, Volume 1 through 7 by the United States Geological Survey in cooperation with the Washington State Department of Ecology. The exceptions are 1) Lake Chelan which was digitized in 2016 from the publication Morphometry of Lake Chelan (published in January 1987); 2) Lake Sammamish whose digital data was acquired from King County in 2013 and is derived from data collected during the publication of Development of a Three-Dimensional Hydrographic Model of Lake Sammamish (published in November 2008); and 3) Lake Crescent, whose digital bathymetric soundings were taken by a private party during 2013/2014 and provided to the Department of Ecology and were converted to contour lines in 2016.

This GIS layer contains bathymetric elevation bands (derived from bathymetric contours) of selected freshwater lakes in Washington State. The majority of the bathymetric contours were digitized from maps contained in a series of seven documents: Reconnissance Data on Lakes in Washington, Water-Supply Bulletin 43, Volume 1 through 7 by the United States Geological Survey in cooperation with the Washington State Department of Ecology. The exceptions are 1) Lake Chelan which was digitized in 2016 from the publiclication Morphometry of Lake Chelan (published in January 1987); 2) Lake Sammamish whose digital data was acquired from King County in 2013 and is derived from data collected during the publication of Development of a Three-Dimensional Hydrographic Model of Lake Sammamish (published in November 2008); and 3) Lake Crescent, whose digital bathymetric soundings were taken by a private party during 2013/2014 and provided to the Department of Ecology and were converted to contour lines in 2016.

Compilation of data (spreadsheet and shapefiles) for several low-temperature resource types, including isolated springs and wells, delineated area convection systems, sedimentary basins and coastal plains sedimentary systems. For each system, we include estimates of the accessible resource base, mean extractable resource and beneficial heat. Data compiled from USGS and other sources. General locations are provided in the spreadsheet; specific locations are provided in the associated shapefiles. The paper (submitted to GRC 2016) describing the methodology and analysis is also included.

Compilation of data (spreadsheet and shapefiles) for several low-temperature resource types, including isolated springs and wells, delineated area convection systems, sedimentary basins and coastal plains sedimentary systems. For each system, we include estimates of the accessible resource base, mean extractable resource and beneficial heat. Data compiled from USGS and other sources. The paper (submitted to GRC 2016) describing the methodology and analysis is also included. * A newer version of this data exists in a more recent submission. See the resources below for more information.

National Data Buoy Center historical images with salinity/depth/temperature data recorded at station number 923, owned and maintained by Dalhousie University in Halifax, Canada.

This submission contains geospatial (GIS) data on water table gradient and depth, subcrop gravity and magnetic, propsectivity, heat flow, physiographic, boron and BHT for the Southwest New Mexico Geothermal Play Fairway Analysis by LANL Earth & Environmental Sciences. GIS data is in ArcGIS map package format.

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to run for weeks and deliver large volumes of water at moderate well-head pressure. Second, to stimulate multiple zones, AltaRock developed thermo-degradable zonal isolation materials (TZIMs) to seal off fractures in a geothermal well to stimulate secondary and tertiary fracture zones. The TZIMs degrade within weeks, resulting in an optimized injection/ production profile of the entire well. Third, the project followed a project-specific Induced Seismicity Mitigation Plan (ISMP) to evaluate, monitor for, and mitigate felt induced seismicity. An initial stimulation was conducted in 2012 and continued for 7 weeks, with over 41,000 m3 of water injected. Further analysis indicated a shallow casing leak and an unstable formation in the open hole. The well was repaired with a shallow casing tieback and perforated liner in the open hole and re-stimulated in 2014. The second stimulation started September 23rd, 2014 and continued for 3 weeks with over 9,500 m3 of water injected. The well was treated with several batches of newly tested TZIM diverter materials and a newly designed Diverter Injection Vessel Assembly (DIVA), which was the main modification to the original injection system design used in 2012. A second round of stimulation that included two perforation shots and additional batches of TZIM was conducted on November 11th, 2014 for 9 days with an additional 4,000 m3 of water injected. The stimulations resulted in a 3-4 fold increase in injectivity, and PTS data indicates partial blocking and creation of flow zones near the bottom of the well. This submission includes all of the files and reports associated with the stimulation, pressure testing, and monitoring included in the scope of the project.

From 2010 to 2015, box core grabs were collected at permanent stations around the Pacific Marine Energy Center - North Energy Test Site (PMEC-NETS) off Newport, Oregon. At each box core station a conductivity, temperature, depth (CTD) cast was conducted. These data include the CTD from the bottom of the cast, sediment grain size analysis, total organic carbon and nitrogen analysis (for the first 3 years only) and macrofaunal organism abundances as retained on a 1 mm mesh sieve. From 2012 to 2015, additional box core grabs were collected around two of the anchors deployed at PMEC-NETS to assess potential changes to sediment conditions and/or organism abundances. From 2013 to 2015, box core samples also were collected in and around the South Energy Test Site (PMEC-SETS). The CTD, grain size, and organism abundances are included. Additionally from 2010 to 2015 beam trawls were conducted at 9 stations (a subset of the box core stations) around PMEC-NETS and CTD casts were conducted before the start of each trawl. Again the CTD data from the bottom of the cast are included. Organism data are fish densities based on the estimated number of meters covered by the trawl. No trawls were conducted at PMEC-SETS.

This file contains a compilation of BHT data from oil wells in southwestern New Mexico. Surface temperature is calculated using the collar elevation. An estimate of geothermal gradient is calculated using the estimated surface temperature and the uncorrected BHT data.

Rock formation top picks from oil wells from southwestern New Mexico from scout cards and other sources. There are differing formation tops interpretations for some wells, so for those wells duplicate formation top data are presented in this file.

Well data for the INEL-1 well located in eastern Snake River Plain, Idaho. This data collection includes caliper logs, lithology reports, borehole logs, temperature at depth data, neutron density and gamma data, full color logs, fracture analysis, photos, and rock strength parameters for the INEL-1 well. This collection of data has been assembled as part of the site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. They were assembled by the Snake River Geothermal Consortium (SRGC), a team of collaborators that includes members from national laboratories, universities, industry, and federal agencies, lead by the Idaho National Laboratory (INL).

Well data for the WO-2 well located in eastern Snake River Plain, Idaho. This data collection includes lithology reports, borehole logs, temperature at depth data, neutron density and gamma data, and rock strength parameters for the WO-2 well. This collection of data has been assembled as part of the site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. They were assembled by the Snake River Geothermal Consortium (SRGC), a team of collaborators that includes members from national laboratories, universities, industry, and federal agencies, lead by the Idaho National Laboratory (INL).

Static Pressure and Temperature Log for Brady monitor well SP-2. This data was taken from Well SP-2 which is part of the Brady Hot Springs Geothermal Site. The data contains pressure and temperature vs depth data for RIH (run in hole) Static conditions and POOH (pull out of hole) Static conditions. The data was recorded on 2/18/2015 and measurements reach a depth of 4392 feet.

This catalog describes the seismicity associated with the 2019 stimulation at Utah FORGE. Containing both matched-filter detections (Dzubay et al., 2022) and Schlumberger-recorded events (detected with a 12-level geophone string), the final combined catalog contains a total of 534 microseismic events spanning -2.0 Mw to -0.1 Mw. Users may differentiate between SLB and MF events using the fact that SLB event magnitudes are recorded to a higher level of precision (MF mags determined using relative amplitude ratios). Users should be wary of locations and depths (measured from sea level) for MF events, as all detections were assigned the same locations as their template events.

This submission contains a shapefile of heat flow contour lines around the FORGE site located in Milford, Utah. The model was interpolated from data points in the Milford_wells shapefile. This heat flow model was interpolated from 66 data points using the kriging method in Geostatistical Analyst tool of ArcGIS. The resulting model was smoothed 100%. The well dataset contains 59 wells from various sources, with lat/long coordinates, temperature, quality, basement depth, and heat flow. This data was used to make models of the specific characteristics.