The EDX4CCS Carbon Storage Technical Viability Database Version 0.1 is a geodatabase of geologic, geophysical, structural, hydrologic, energy extraction, transportation infrastructure, local political boundaries, community and environmental data, among other categories, that is designed to help users find resources to determine the technical viability of geologic carbon storage in the conterminous United States. This database includes previously obtained data that are publicly available, including resources from entities such as the United States Geological Survey, various state geological surveys, and data available on the National Energy Technology Laboratory’s Energy Data eXchange (EDX). The database is divided into two primary categories: Socioeconomic and Subsurface/Physiography.

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.

This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Using Passive Seismic Emission Tomography". This data set includes descriptions of the instrumentation, data acquisition and processing procedures, as well as the final processed data and digital archive formats. A total of 81 MT locations were surveyed (52 profile sites, and 29 MT sites). Data were processed and inspected for quality assurance on site, and reviewed daily by the geophysicist in charge of the project.

The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic data collections were completed at San Emidio in late 2016 by Microseismic Inc as part of a DOE project. The PSET results are being analyzed as part of the WHOLESCALE project. This submission includes P-wave velocity model data, and the passive seismic data with more information on each bellow.

In December 2016, 1301 vertical-component seismic instruments were deployed at the San Emidio Geothermal field in Nevada. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in one-minute increments in SEGD and MSEED formats. See the metadata in GDR submission (linked below as "Seismic Survey 2016 Metadata at San Emidio Nevada") for details about the seismic station locations, seismic data logger specifications, instrumentation specifications, descriptions of data, a fracture finding summary, and the final report for the 2016 seismic survey done in San Emidio, Nevada.

1301 Vertical Component seismic instruments were deployed at San Emidio Geothermal field in Nevada in December 2016. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in one-minute increments. Data includes seismic station locations, seismic data logger specifications, instrumentation specifications, descriptions of data, a fracture finding summary and the final report for the 2016 WHOLESCALE seismic survey done in San Emidio, Nevada.

This is Reclamation’s new hydrologic database access portal. These new tools are designed to replace the Data Retrieval apps below, as they begin to reach the end of their functional lifespans. We encourage everyone to take a look at our new and improved access portal and begin plans to transition to this improved data delivery source.

(Link to Metadata) WaterHydro_WBD8VT includes Subbasins within Vermont (HUC8 level hydrologic unit boundaries). The boundaries are consistent with Vermont's Hydrography Dataset (VHD).

(Link to Metadata) WaterHydro_WBD12VT was developed by NRCS. The boundaries on consistent with Vermont's Hydrography Dataset (VHD). This data set is a digital hydrologic unit boundary layer at the Subwatershed (12-digit) 6th level for the State of Vermont. The original data set was developed by delineating the boundary lines on base USGS 1:24000 scale topographic quadrangle, and digitizing the delineated lines. Digital Raster Graphics (DRG) images were used to update and correct the data set to meet the new FGDC Federal Standards for Delineating Hydrologic Unit Boundaries. This data set consists of geo-referenced digital map data and associated attributes created in accordance with the FGDC Proposal, Version 1.0 Federal Standards for Delineation of Hydrologic Unit Boundaries 3/01/02 (https://www.nrcs.usda.gov/). The map data are in a statewide coverage format and include complete coverage of the entire state of Vermont, and small parts of surrounding states and Quebec Province. The hydrologic unit ID code attached to each delineated polygon is linked to the attribute data.

(Link to Metadata) This datalayer is comprised of lakes extracted from the USGS DLGs DLG Surface Waters coverage. Digital line graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management RF 100,000 are used. (1)Public Land Survey System; (2) boundaries (3) transportation; (4) hydrography; and (5) hypsography. All DLG data distributed by the USGS are DLG - Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks. VCGI currently offers VGIS users the following DLG datalayers; WaterHydro_DLGLAKES - extracted from WaterHydro_DLGSW (4). UtilityTransmit_DLGMTT - DLG miscellaineous Transmisson Lines (1). TransRoad_DLGRD - Roads (3). TransRail_DLGRR - Railroads (3). WaterHydro_DLGSW - DLG surface waters (4). BoundaryTile_DLGTILES - Quadrangle map boundaries (1).

(Link to Metadata) The WaterHydro_DLGSW layer represents surface waters (hydrography) at a scale of RF 100000. WaterHydro_DLGSW was derived from RF100000 USGS Digital Line Graph (DLG). DLG's of map features are converted to digital form from maps and related sources. Refer to the USGS web site from more information on DLGs (https://www.usgs.gov)

(Link to Metadata) The WaterHydro_DLGSW layer represents surface waters (hydrography) at a scale of RF 100000. WaterHydro_DLGSW was derived from RF100000 USGS Digital Line Graph (DLG). DLG's of map features are converted to digital form from maps and related sources. Refer to the USGS web site from more information on DLGs (https://www.usgs.gov)

Interactive GIS map of Virginia's hydrologic features.

This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in the laboratory at UW-Madison, and an excel catalog of rock samples with information on sample name, rock type, coordinates of sample location, structural measurements, field notes, observations for plug preparation (e.g., weathering, ability to be cut and cored), and rock descriptions. It should be noted that not every sample was photographed in the field. Names and descriptions of rock formation units are taken from Rhodes et al. (2011). The README.txt file is a description of this submission.