2011 Geothermal Technologies Program Peer Review Presentation summarizing relevance, proposed approach, and logistics of the Glass Buttes Exploration and Drilling.

This archived dataset contains magnetic and gravity imaging data for the Appalachian Basin, compiled using Poisson Wavelet Multiscale Edge Detection, referred to as 'worm' for brevity, and stored in a PostGIS database, along with shapefiles and CSVs of relevant data. The archive also includes regional earthquake data going back to 1973 and relevant world stress map data. These data are used in estimating the seismic hazards (both natural and induced) for candidate direct use geothermal locations in the Appalachian Basin Play Fairway Analysis by Jordan et al. (2015).

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS). This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain item description documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations. Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015. Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted. UPDATE: Newer version of the Thermal Quality Analysis has been added here: https://gdr.openei.org/submissions/879 (Also linked below) Newer version of the Combined Risk Factor Analysis has been added here: https://gdr.openei.org/submissions/880 (Also linked below)

The purpose of compiling the CEUS-SSC Project database was to organize and store those data and resources that had been carefully and thoroughly collected and described for the TI Team’s use in characterizing potential seismic sources in the CEUS. An important goal for the development of this database was to document sources and dates for all information that was initially assessed for the CEUS-SSC Project, specifying exactly what data and resources were considered, and provide for pertinent future data sets to be incorporated as they were generated for the project. Development of the project database began at the inception of the project to provide TI Team members with a common set of data, maps, and figures for characterization of potential seismic sources. The database was continually updated during the course of the project through the addition of new references and data collected by TI Team members and project subcontractors, including information presented in project workshops and provided through PPRP review documentation. This appendix presents the contents of the project database, as well as information on the workflow, development roles, database design considerations, data assessment tasks, and management of the database. Based on the CEUS Project Plan, the project database included, but was not limited to, the following general types of data: Magnetic anomaly Gravity anomaly Crystalline basement geology Tectonic features and tectonic/crustal domains Tectonic stress field Thickness of sediments Crustal thickness VP at top of crystalline basement Seismic reflection data at Charleston, South Carolina Earthquake catalog Quaternary faulting and potential Quaternary features Mesozoic rift basins Paleoliquefaction sites Topography and bathymetry Liquefaction dates from published literature for the Wabash, New Madrid, and Charleston seismic zones Index map showing locations of published crustal scale seismic profiles and geologic cross sections

This layer contains the weakened basement rocks. Isostatic gravity was utilized to identify structural basin areas, characterized by gravity low values reflecting weakened basement rocks. Together interpreted regional fault zones and basin outlines define geothermal "exploration fairways", where the potential exists for deep, superheated fluid flow in the absence of Pliocene or younger volcanic units.

2010 Peer Review of the 'Conducting a 3D Converted Shear Wave' Project to reduce exploration risk at Wister, CA. The presentation includes a timeline, budget, barriers, and partners. The objective of the project is also explained in the presentation.

2011 Peer Review of the 'Conducting a 3D Converted Shear Wave' Project to reduce exploration risk at Wister, CA.

We conducted a comprehensive analysis of the structural controls of geothermal systems within the Great Basin and adjacent regions. Our main objectives were to: 1) Produce a catalogue of favorable structural environments and models for geothermal systems. 2) Improve site-specific targeting of geothermal resources through detailed studies of representative sites, which included innovative techniques of slip tendency analysis of faults and 3D modeling. 3) Compare and contrast the structural controls and models in different tectonic settings. 4) Synthesize data and develop methodologies for enhancement of exploration strategies for conventional and EGS systems, reduction in the risk of drilling non-productive wells, and selecting the best EGS sites. Phase I (Year 1) involved a broad inventory of structural settings of geothermal systems in the Great Basin, Walker Lane, and southern Cascades, with the aim of developing conceptual structural models and a structural catalogue of the most favorable structural environments. This overview permitted selection of 5-6 representative sites for more detailed studies in Years 2 and 3. Sites were selected on the basis of quality of exposure, potential for development, availability of subsurface data, and type of system, so that major types of systems can be evaluated and compared. The detailed investigations included geologic mapping, kinematic analysis, stress determinations, gravity surveys, integration of available geophysical data, slip tendency analysis, and for some areas 3D modeling. In Year 3, the detailed studies were completed and data synthesized to a) compare structural controls in various tectonic settings, b) complete the structural catalogue, and c) apply knowledge to exploration strategies and selection of drilling sites.

The McGee Mountain geothermal area was selected to test early-stage shallow temperature survey techniques and drill two slim holes to test the resource. Geothermal Technical Partners, Inc. was able to complete only a small portion of the project before lack of funding prevented further exploration work. This work included a shallow (2-meter) temperature survey, a Geoprobe survey, a close-spaced gravity survey, and several reports on geologic and transmission viability. The 18-page report includes a description of the geothermal geology of the area, geochemistry and geothermometry of nearby springs and wells, and findings from the shallow temperature survey, Geoprobe survey, close-spaced gravity survey, heat-in-place estimate, transmission viability, and an archeological survey. The report makes the following conclusions: Both the shallow 2-meter and the Geoprobe surveys are cost-effective methods to detect subsurface thermal anomalies in early-stage exploration, prior to more expensive temperature gradient drilling. The major advantages of the 2-meter survey are its extreme portability (no roads needed), cost per site measurement, and low environmental impact. The 2-meter survey's disadvantages are its inability to penetrate hard substrates and the noise effects due to solar heating of the ground. The Geoprobe's advantages are its ability to collect temperature and uncontaminated water samples, greater depth of penetration (to 60m), relatively low cost, and low environmental impact. The Geoprobe's disadvantages are its inability to go off-road or to penetrate hard substrates. Costs to perform both types of surveys are low, together less than the cost of one conventional temperature gradient well. Given the potential increase in data that these surveys can provide, this is extreme value for the exploration dollar.

This is an electronic database detailing different types of, various phases of, best practices for, and cost and time associated with geothermal exploration techniques. The groups of exploration techniques included in the database are Data and Modeling Techniques, Downhole Techniques, Drilling Techniques, Field Technologies, Geochemical Techniques, Geophysical Techniques, Lab Analysis Techniques, and Remote Sensing Techniques.

ArcGIS Map Package with MT Station Locations, 2D Seismic Lines, Well data, Known Regional Hydrothermal Systems, Regional Historic Earthquake Seismicity, Regional Temperature Gradient Data, Regional Heat Flow Data, Regional Radiogenic Heat Production, Local Geology, Land Status, Cultural Data, 2m Temperature Probe Data, and Gravity Data. Also a detailed down-hole lithology notes are provided.

The data is associated to the Fallon FORGE project and includes mudlogs for all wells used to characterize the subsurface, as wells as gravity, magnetotelluric, earthquake seismicity, and temperature data from the Navy GPO and Ormat. Also included are geologic maps from the USGS and Nevada Bureau of Mines and Geology for the Fallon, NV area.

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.

This submission contains raster files associated with several datasets that include earthquake density, Na/K geothermometers, fault density, heat flow, and gravity. Integrated together using spatial modeler tools in ArcGIS, these files can be used for play fairway analysis in regard to geothermal exploration.

Glass Buttes Exploration and Drilling: 2010 Geothermal Technologies Program Peer Review Presentation, Walsh, et al, Ormat

This report covers data acquisition, instrumentation and processing of a gravity survey performed on the Glass Buttes Geothermal Exploration Project, located in Lake County, Oregon for ORMAT Technologies Inc. The survey was conducted during 21 June 2010 to 26 June 2010. The survey area is located in T23S, R21-23E and lies within the Glass Buttes, Hat Butte, and Potato Lake, Oregon 1:24,000 topographic sheets. A total of 180 gravity stations were acquired along five profile lines.

All datasets and products specific to the Carson Sink Basin. Includes a packed ArcMap (.mpk), individually zipped shapefiles, and a file geodatabase for the Carson Sink area; a GeoSoft Oasis montaj project containing GM-SYS 2D gravity profiles along the trace of our seismic reflection lines; a 3D model in EarthVision; spreadsheet of links to published maps; and spreadsheets of well data.

Gravity model for the state of Hawaii. Data is from the following source: Flinders, A.F., Ito, G., Garcia, M.O., Sinton, J.M., Kauahikaua, J.P., and Taylor, B., 2013, Intrusive dike complexes, cumulate cores, and the extrusive growth of Hawaiian volcanoes: Geophysical Research Letters, v. 40, p. 3367-3373, doi:10.1002/grl.50633.

To prepare for its third phase, the Hawaii Play Fairway project conducted groundwater sampling and analyses in ten locations in the Hawaiian islands, magnetotelluric (MT) and gravity surveys, as well as calculations of 3D subsurface stress due to the weight of the rock underlying the topography of the volcano. The subsurface stresses were used to evaluate the potential for fracture-induced permeability. Inversions of the MT and gravity data produce 3D models of resistivity and density, respectively, on Lanai, across Haleakala's SW rift (Maui), and surrounding Mauna Kea (Hawaii Island). The project developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The project then incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. These results were used to identify target sites for exploratory drilling. Spreadsheet information: Each sheet contains data for a particular depth in kilometers. Positive depths are above sea level, and negative below. For more information, go to the Hawaii Groundwater and Geothermal Resources Center website linked in the resources.

The Snake River volcanic province (SRP) overlies a thermal anomaly that extends deep into the mantle; it represents one of the highest heat flow provinces in North America. The primary goal of this project is to evaluate geothermal potential in three distinct settings: (1) Kimama site: inferred high sub-aquifer geothermal gradient associated with the intrusion of mafic magmas, (2) Kimberly site: a valley-margin setting where surface heat flow may be driven by the up-flow of hot fluids along buried caldera ring-fault complexes, and (3) Mountain Home site: a more traditional fault-bounded basin with thick sedimentary cover. In-depth studies continue at all three sites, complemented by high-resolution gravity, magnetic, and seismic surveys, and by downhole geophysical logging.

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

Initial 3D gravity results from Zonge Int'l recorded for the 4D EGS Monitoring project at Newberry, during stimulation of Well 55-29 by AltaRock Energy

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources: CO2 Saturation Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models-part-3); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); Vp Velocity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models-part-3); Vs Velocity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models-part-3); and Density Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models-part-3). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models); [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data); [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models); and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

Using LiDAR to identify structural and volcanic evolution of a Miocene-Pleistocene age bimodal volcanic complex and implications for geothermal potential. The file includes an updated geologic map, methods, and preliminary results.

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.

Multiple data sets converge on a geologic structural model for Glass Buttes, Oregon geothermal prospect, Patrick Walsh, Brigette Martini, Chet Lide, Darrick Boschmann, John DIlles, Andrew Meigs, 2010 Ormat Nevada, Zonge Geophysical, Oregon State University American Geophysical Union, Poster Session

This project focused on defining geothermal play fairways and development of a detailed geothermal potential map of a large transect across the Great Basin region (96,000 km2), with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. systems with no surface hot springs or fumaroles) and thereby accelerating geothermal development in this promising region. Data included in this submission consists of: structural settings (target areas, recency of faulting, slip and dilation potential, slip rates, quality), regional-scale strain rates, earthquake density and magnitude, gravity data, temperature at 3 km depth, permeability models, favorability models, degree of exploration and exploration opportunities, data from springs and wells, transmission lines and wilderness areas, and published maps and theses for the Nevada Play Fairway area.

All datasets and products specific to the Steptoe Valley model area. Includes a packed ArcMap project (.mpk), individually zipped shapefiles, and a file geodatabase for the northern Steptoe Valley area; a GeoSoft Oasis montaj project containing GM-SYS 2D gravity profiles along the trace of our seismic reflection lines; a 3D model in EarthVision; spreadsheet of links to published maps; and spreadsheets of well data.

Conceptual model for the Newberry Caldera geothermal area. Model is centered around caldera and evaluates multiple geophysical datasets to derive a conceptual subsurface model. Includes: Conductor layer based on transient electromagnetic data from Fitterman et al., 1988 (figure 10) Base of conductor layer based on MT conductor values found in Waibel et al., 2014 (DOE document, figure 38) Resistor layer based on magnetotellurics from Fitterman et al., 1988 (figure 13). Seismic intrusives layer representing a smoothed version of 5.5 km/s seismic velocity layer defined in Beachly et al., 2012 West flank seismic body representing a fractional change in seismic velocity of 0.1, defined in Beachly et al., 2012 and Heath et al., 2015 West flank gravity body "granite" that represents a gravity anomaly identified in Waibel et al., 2014 (DOE document, figure 35) Magma chamber defined seismically, found in Heath et al., 2015 Ring fracture fault intrusions Various faults and geologic layers

Newberry combined gravity from Zonge Int'l, processed for the EGS stimulation project at well 55-29. Includes data from both Davenport 2006 collection and for OSU/4D EGS monitoring 2012 collection. - Locations are NAD83, UTM Zone 10 North, meters. Elevation is NAVD88. - Gravity in milligals. Free air and observed gravity are included, along with simple Bouguer anomaly and terrain corrected Bouguer anomaly. - SBA230 means simple Bouguer anomaly computed at 2.30 g/cc. - CBA230 means terrain corrected Bouguer anomaly at 2.30 g/cc. - This suite of densities are included (g/cc): 2.00, 2.10, 2.20, 2.30, 2.40, 2.50, 2.67.

Research references to literature about the Newberry geothermal area, Oregon.

These data are Pacific Northwest National Lab inversions of an amalgamation of two surface gravity datasets: Davenport-Newberry gravity collected prior to 2012 stimulations and Zonge International gravity collected for the project "Novel use of 4D Monitoring Techniques to Improve Reservoir Longevity and Productivity in Enhanced Geothermal Systems" in 2012. Inversions of surface gravity recover a 3D distribution of density contrast from which intrusive igneous bodies are identified. The data indicate a body name, body type, point type, UTM X and Y coordinates, Z data is specified as meters below sea level (negative values then indicate elevations above sea level), thickness of the body in meters, suscept, density anomaly in g/cc, background density in g/cc, and density in g/cc. The model was created using a commercial gravity inversion software called ModelVision 12.0 (http://www.tensor-research.com.au/Geophysical-Products/ModelVision). The initial model is based on the seismic tomography interpretation (Beachly et al., 2012). All the gravity data used to constrain this model are on the GDR: https://gdr.openei.org/submissions/760.

Various geophysical exploration data for San Emidio KGRA

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. This collection includes data on seismic events, groundwater, geomechanical models, gravity surveys, magnetics, resistivity, magnetotellurics (MT), rock physics, stress, the geologic setting, and supporting documentation, including several papers. Also included are 3D models (Petrel and Jewelsuite) of the proposed site. Data for wells INEL-1, WO-2, and USGS-142 have been included as links to separate data collections. These data have been 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). Other contributors include the National Renewable Energy Laboratory (NREL), Lawrence Livermore National Laboratory (LLNL), the Center for Advanced Energy Studies (CEAS), the University of Idaho, Idaho State University, Boise State University, University of Wyoming, University of Oklahoma, Energy and Geoscience Institute-University of Utah, US Geothermal, Baker Hughes Campbell Scientific Inc., Chena Power, US Geological Survey (USGS), Idaho Department of Water Resources, Idaho Geological Survey, and Mink GeoHydro.

Snake River Plain Play Fairway Analysis - Phase 1 CRS Raster Files. This dataset contains raster files created in ArcGIS. These raster images depict Common Risk Segment (CRS) maps for HEAT, PERMEABILITY, AND SEAL, as well as selected maps of Evidence Layers. These evidence layers consist of either Bayesian krige functions or kernel density functions, and include: (1) HEAT: Heat flow (Bayesian krige map), Heat flow standard error on the krige function (data confidence), volcanic vent distribution as function of age and size, groundwater temperature (equivalue interval and natural breaks bins), and groundwater T standard error. (2) PERMEABILTY: Fault and lineament maps, both as mapped and as kernel density functions, processed for both dilational tendency (TD) and slip tendency (ST), along with data confidence maps for each data type. Data types include mapped surface faults from USGS and Idaho Geological Survey data bases, as well as unpublished mapping; lineations derived from maximum gradients in magnetic, deep gravity, and intermediate depth gravity anomalies. (3) SEAL: Seal maps based on presence and thickness of lacustrine sediments and base of SRP aquifer. Raster size is 2 km. All files generated in ArcGIS.

This presents the results of Phase 1 of the Snake River Plain Play Fairway Analysis project, along with a proposed work for Phase 2. No new data were collected, but we list data sources for our compilation. The Snake River volcanic province (SRP) overlies a thermal anomaly that extends deep into the mantle; it represents one of the highest heat flow provinces in North America. The Yellowstone hotspot continues to feed a magma system that underlies southern Idaho and has produced basaltic volcanism as young as 2000 years old. It has been estimated to host up to 855 MW of potential geothermal power production, most of which is associated with the Snake River Plain volcanic province. Our goals for this Phase 1 study were to: (1) adapt the methodology of Play Fairway Analysis for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal play fairway model for the SRP and identify the most promising plays, using software tools that are standard in the petroleum industry. Our ultimate goals are to lower the risk and cost of geothermal exploration throughout geothermal industry, and to stimulate the development of new geothermal power resources in Idaho.

This report details all of the work done in Phase 2 of a geothermal exploration project in Tularosa Basin, New Mexico. Data acquired as part of Phase 2 includes field geology (geological reconnaissance and mapping), gravity surveys, shallow temperature surveys, well water sampling and geothermometry, temperature logging, and magnetotelluric (MT) surveys. The new data is incorporated into new PFA models and Phase 2 plays were subsequently developed, ranked, and prioritized. This report also presents an overview of recommendations and costs for the next phase.

This submission contains multiple excel spreadsheets and associated written reports. The datasets area are representative of shallow temperature, geochemistry, and other well logging observations made across WSMR (white sands missile range); located to the west of the Tularosa Basin but still within the study area. Written reports accompany some of the datasets, and they provide ample description of the methodology and results obtained from these studies. Gravity data is also included, as point data in a shapefile, along with a written report describing that particular study.

The 2018 Irrigation and Water Management Survey (formerly called the Farm and Ranch Irrigation Survey) is a follow-on to the 2017 Census of Agriculture by the U.S. Department of Agriculture (USDA). This survey provides the only comprehensive information on irrigation activities and water use across American farms, ranches, and horticultural operations. In responding to the survey, producers provide information on topics such as water sources and amount of water used, acres irrigated by type of system, irrigation and yield by crop, and system investments and energy costs. The full reports for the 2003, 2008, 2017, and 2018 surveys are provided in this submission. By following the link to the USDA Census of Irrigation, a specific year can be selected, in which the tables and figures of each report are provided.

This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geophysics, heat flow, and fault dilation and slip tendencies) that cover a large portion of northern Nevada. The geophysics data include map surfaces related to gravity and magnetic data, and line and point data derived from those surfaces. Heat flow data include an interpolated map of heat flow in mW/m^2, an error surface, and well data used to construct them. The dilation and slip tendency information exist as attributes assigned to each line segment of mapped faults and geophysical lineaments. GDR submission contains link to official USGS data release. Additional metadata available on source DOI page.

This is a composite raw gravity dataset of the Utah FORGE area taken over time from December 2018 to to June 2021. The data shows differences in local gravity at different location across Utah FORGE. Included with the gravity data is the NAD83 UTM coordinates of each station in meters. More detailed information can be found in the readme included in the data resource.

This is a microgravity dataset from the Utah FORGE site near Milford, Utah. This composite dataset was updated in October, 2021 and contains data from December 17th, 2018 through September 24th, 2021. The data includes the GPS location of the measurement, date of the measurement, name of the station, relative difference in gravity, and coordinates of the station. This data was generated by the Utah Geological Survey.

These resources describe the 3D geophysical inversion modeling of gravity data at the FORGE site near Milford, Utah. FORGE is the Frontier Observatory for Research in Geothermal Energy and the site in Utah has been selected by the U.S. Dept. of Energy for a 5-year R&D program to test technologies for the development of Engineered Geothermal Systems (EGS). 3D modelling of gravity data at the FORGE site is to help characterize the subsurface geologic framework. Specifically, modelling of gravity data in 3D, used in conjunction with rock density measurements and other subsurface geologic information can provide an independent test of an existing 3D geologic model (e.g. Witter et al., 2018). Such an exercise can be useful for reducing uncertainty in 3D geologic models (Witter et al, 2019).

This is the final topical report for the Phase 2B Utah FORGE project, which is located near Roosevelt Hot Springs, Utah. This PDF format report details results associated with the conceptual geologic model, deep well 58-32, rock geomechanics, reservoir temperatures, seismic surveys, seismic monitoring, certainty, and NEPA. The report also provides an overview of all of the deliverables which were used to produce the results and full appendices.

This is a zipped GIS compatible shapefile of gravity data points used in the Milford, Utah FORGE project as of March 21st, 2016. The shapefile is native to ArcGIS, but can be used with many GIS software packages. Additionally, there is a .dbf (dBase) file that contains the dataset which can be read with Microsoft Excel. The Data was downloaded from the PACES (Pan American Center for Earth and Environmental Studies) hosted by University of Texas El Paso. A readme file is included in the archive with abbreviation explanations and units.

New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rocks, to define the heat sources, and to derive baseline 3D resistivity structure for later MT monitoring of temporal changes in resistivity structure following well stimulation in the EGS reservoir. There are three files here related to Utah FORGE magnetotelluric (MT) data acquisition and processing. The FORGE MT EDIs zip file contains the observed MT responses in industry-standard EDI format. For each site, there is an EDI response file that utilized a local independent reference for noise cancellation, and a file that utilized a distant reference cancelling noise associated with the DC transmission line of the Delta IPP passing down the west side of Milford Valley. These two site files could be merged as appropriate. The FORGE Model Cell Center file contains the model volume of the 3D Forge MT inversion for characterizing the resistivity structure in the project area. It was derived using finite element inversion methodology described in Wannamaker et al, in the attached FORGE Phase3 Geophysics paper, from the MT observation EDI files. It is ASCII format (.dat) and entries are defined at top of the file in a simple x-y-z-Rho listing in UTM coordinates. The element layers drape the topography so the Rho value layers are not purely horizontal slices. This greatly simplifies the listing.

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 in part downloaded from PACES, University of Texas at El Paso, http://gis.utep.edu/subpages/GMData.html, 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

This is a link to Pan American Center for Earth and Environmental Studies (PACES) which facilitates the download of gravity and magnetic data. Part of the gravity data used in the Utah FORGE project can be found here.

Report detailing data acquisition, quality, processing, and presentation for the gravity survey conducted on the Newberry Volcano. (Validation of Innovative Exploration Technologies for Newberry Volcano: Gravity Report of Newberry prepared by Zonge GeoSciences 2012)

Validation of Innovative Exploration Technologies for Newberry Volcano: Raw data used to prepare the Gravity Report by Zonge 2012