Tier 3 data for Appalachian Basin sectors of New York, Pennsylvania and West Virginia used in a Geothermal Play Fairway Analysis of opportunities for low-temperature direct-use applications of heat. It accompanies data and materials submitted as Geothermal Data Repository Submission "Natural Reservoir Analysis 2016 GPFA-AB" (linked below). Reservoir information are derived from oil and gas exploration and production data sets, or derived from those data based on further analysis. Data reported here encompass locations (horizontal and depth), geologic formation names, lithology, reservoir volume, porosity and permeability, and derived approximations of the quality of the reservoir. These differ from the linked 2015 data submission in that this file presents data for New York that are comparable to those in the other two states. In contrast, the 2015 data available measured differing attributes across the state boundaries.

Permeability and porosity crossplot data for the Broom Creek, Amsden, and Inyan Kara Formations of the Williston Basin

DICOM files and dual energy Computed Tomography CT rock type data for Blue Lake 18A-4, Blue Lake 18A-15, State Grant 1-9, Thomas 1-34, Lawnichak 9-33, and Chester 8-16.

Whole and sidewall core inventories, analyses, photos, and thin section photos for Lawnichak 9-33 in Dover 33 reef, Chester 8-16 and Chester 6-16 in Chester 16 reef.

Grid of porosity (%) for the Tertiary section in the Eastern Gulf of Mexico. Generated by the Geological Survey of Alabama, with IHS Petra (v. 3.11.1.14) geologic interpretation software, using highly connected features (least squares) and smoothing contours with grid flexing. Data format is long/lat/Z where long/lat is in WGS84 and Z is % This material is based upon work supported by the U.S. Department of Energy National Energy Technology Laboratory (DE-FE0026086). Cost share and research support are provided by the Project Partners and an Advisory Committee.

Files containing information on core lithology, mineralogy, and petrography, as well as photos of samples and relative porosity and permeability data from mercury injection.

Mixed wireline logs including both cased and open hole logs. Data sets are PDS, LAS, and excel files that commonly contain multiple logs. Types of wireline logs include gamma ray, neutron porosity, photoelectric, sonic, mineral volume, ELAN, FMI, cement bond logs, magnetic resonance, and laterolog.

Mixed wireline logs including both cased and open hole logs. Data sets are PDS, LAS, and excel files that commonly contain multiple logs. Types of wireline logs include gamma ray, neutron porosity, photoelectric, sonic, mineral volume, ELAN, FMI, cement bond logs, magnetic resonance, and laterolog.

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

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.

Online web mapping tool for visualization and simple analysis of Earth-energy data files from public and DOE related sources. Geocube allows users to upload and visualize their own datasets but also comes preloaded with individual spatial datasets as well as spatial data collections that align to topical themes.

This dataset conforms to the Tier 3 Content Model for Geologic Reservoirs Version 1.0. It contains the known hydrocarbon reservoirs within the study area of the Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB) as part of Phase 1, Natural Reservoirs Quality Analysis. The final values for Reservoir Productivity Index (RPI) and uncertainty (in terms of coefficient of variation, CV) are included. RPI is in units of liters per MegaPascal-second (L/MPa-s), quantified using permeability, thickness of formation, and depth. A higher RPI is more optimal. Coefficient of Variation (CV) is the ratio of the standard deviation to the mean RPI for each reservoir. A lower CV is more optimal. Details on these metrics can be found in the Reservoirs_Methodology_Memo.pdf uploaded to the Geothermal Data Repository Node of the NGDS in October of 2015.

Dataset is a compilation of datapoints in the US waters of the Gulf of Mexico where BOEM has released data for oil and gas reservoirs. These reservoirs are typically in sand formations so the name of the dataset is often called "Sands" and the year of the latest release of data from BOEM. To be able to view data spatially, the sand dataset was joined to the BOEM Boreholes dataset by matching the API numbers of the discovery wells. Thus the "sands" are an estimated location below the mudline and are not exact.

Thermal conductivity (TC) data taken for different wells at a specified drill depth. This is an abridged version of the complete SMU heat flow database, downloaded from the SMU node of the NGDS at the beginning of INGENIOUS (approximately April 2021), and filtered to the INGENIOUS study area. This National Geothermal Data System (NGDS) project aggregates geothermal data collected and curated by the SMU Geothermal Laboratory and its partner organizations. All columns in this database are the same as the SMU database, except for 2 additions associated with this project. Repeated columns are for data correlation purposes. Column descriptions and data types are the same as previous iterations of the SMU database. The new values that are the addition are two new columns developed as part of the INGENIOUS project: INGENIOUS TC Value | INGENIOUS notes INGENIOUS notes are individual notes that were written for specific data points during the analysis process. There are not always notes associated with each input value. INGENIOUS TC Value includes 4 values: 1. Assumed Measured These are values that are assumed to be measured thermal conductivity values, either within a specific well or within the same study region. Many of these have either a published reference, a reported standard deviation, or a unique thermal conductivity value. 2. Data release - assumed measured These are values in the SMU database that are from proprietary data that were added to the SMU database and are labeled as data release for their reference. These values were searched for in person at the SMU Geothermal Laboratory as well as virtual examination of data available on the NGDS. For many of these, there are reported thermal conductivity values associated with the heat flow data in the database, but no specific table or reference to measurements in the original data release files. 3. Known measured These are values that have a reported measurement, either as an original file in the SMU data files on the NGDS or a reported table in a publication. In the rare circumstances, Maria Richards or David Blackwell confirmed measurement. Confirmation of measurement would be written in the INGENIOUS notes column. 4. Unmeasured Unmeasured values are those that are known to be unmeasured, either estimated from another report or no information given. In the SMU database, there are wells that have a heat flow but no thermal conductivity. These are categorized as unmeasured. There are also heat flow values that are stated to have estimated or generalized average thermal conductivity values for the region and rock type. Because these are known to be unmeasured, they are categorized as such. 5. Blank Blank values are either A quality or X quality. These quality values are stated in the INGENIOUS notes. These values were not going to change associated with the heat flow analysis, so these were not examined.

Comprehensive characterization of carbon capture utilization and storage (CCUS) opportunities throughout the ten-state region. Spanning from the offshore Atlantic Coastal Plain through the Appalachian and Michigan basins, this region hosts a diverse assemblage of reservoir types and provides multiple CCUS targets. A key component of this research is the evaluation of opportunities for enhanced oil recovery (EOR) in legacy oil fields via carbon dioxide (CO2) floods. The latest phase of MRCSP research added several new attributes to an already comprehensive database in order to identify and rank the best opportunities for CO2-EOR throughout the 10-state region. Detailed reservoir parameters are necessary to perform a comprehensive evaluation of any given EOR target, and a ranking of opportunities depends on both availability of data and relative consideration, or weight, assigned to the various attributes. A renewed focus on CO2-EOR also helped to identify information severely lacking in the MRCSP region, such as permeability and oil gravity.

Mixed wireline logs including both cased and open hole logs. Data sets are PDS, LAS, and excel files that commonly contain multiple logs. Types of wireline logs include gamma ray, neutron porosity, resistivity, laterolog, deviation, sonic, mineral volume, and cement bond logs.

Mudlog for the Charlton C3-30A well.

Mudlog/measured depth logs with quantitative data and descriptions of lithology, mineralogy, porosity, hydrocarbon shows, and drilling activities.

New Mexico has a rich legacy of petroleum and mineral exploration and production, most of which has involved subsurface investigations. Hundreds of thousands of holes have been drilled into the subsurface, some to depths of 20,000 feet or more. Considerable data have been collected from these wells in the form of electrical or geophysical logs, cuttings, and rock cores. These materials contain a rich lode of information about the kinds of rocks that lie below the surface, how porous and permeable they are, and even what types of fluids they contain. Part of the Mission of New Mexico Bureau of Geology and Mineral Resources is to serve as a repository for these kinds of data. Data in our collections have been acquired from wells drilled throughout the state over the last 90 years. We currently have more than 15 million pieces of unique subsurface data in our collections, much of it stored in seven steel storage buildings on campus. Core - 20,000+ boxes (oil & gas and mining) from 4,000+ wells Cuttings - 51,0000+ boxes from 16,600+ wells Geophysical Logs (some with mudlogs)- 50,000+ wells Porosity and Permeability Analyses Petroleum Source Rock Analyses Well records - 100,000+ wells Drillers logs - 17,000+ wells Sample descriptions and sample logs - 4,300+ wells Historic petroleum exploration maps with well locations in 26 counties Pool maps with locations of producing oil and gas pools by stratigraphic unit Historic production data - Pre-2002

Processed nuclear magnetic resonance logs with reservoir fluid and rock porosity data.

Dataset containing 646 petrophysical well log interpretations spanning multiple geologic domains (as defined by Subsurface Trend Analysis™) in the Gulf of Mexico. Well logs were manually interpreted by geologic researchers at NETL and were derived from BOEM Sands and IHS data raster logs. This interpretation dataset underpins the Offshore CO2 Saline Storage Calculator.

Field and processed PNC logs.

Core photos and analysis collected from Cranfield oilfield in southwest Mississippi as part of SECARB project. Cores are from CFU31F-1, CFU31F-2, and CFU31F-3 wells in the Detailed Area of Study. Data includes permeability and porosity measurements and gamma ray scans. Associated Publications: Kordi, M., 2013, Characterization and prediction of reservoir quality in chlorite-coated sandstones: evidence from the Late Cretaceous Lower Tuscaloosa Formation at Cranfield Field, Mississippi, U.S.A., The University of Texas at Austin, Ph.D. dissertation, 193 p.

Thin sections, sedimentary graphic logs, and XRD results from CFU31-F2 and CFU31-F3 wells. Data collected as part of geologic characterization phase of SECARB project at the Cranfield oilfield in southwest Mississippi. Thin sections for CFU29-12 well also included. Associated Publications: Kordi, M., 2013, Characterization and prediction of reservoir quality in chlorite-coated sandstones: evidence from the Late Cretaceous Lower Tuscaloosa Formation at Cranfield Field, Mississippi, U.S.A., The University of Texas at Austin, Ph.D. dissertation, 193 p.

Total and methyl mercury, moisture content (%), and porosity were measured in Lake Michigan sediment by the U.S. Environmental Protection Agency/Office of Research and Development/National Health and Environmental Effects Research Laboratory/Mid-Continent Ecology Division/Large Lakes Research Station, Grosse Ile, MI. Both core and Ponar grab samples were collected. The samples were collected from 1994 through 1996. These mercury data were used in the LM2-Mercury model. This dataset is associated with the following publication: Zhang, X., K. Rygwelski , M. Rowe, R. Rossmann, and R. Kreis. Global and regional contributions to total mercury concentrations in Lake Michigan water. JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42(1): 62-69, (2016).

This data set includes the daily drilling reports and Pason data for well 78B-32 and Schlumberger logs acquired after drilling completion. This well was drilled between June 27th and July 31st of 2021. Also included is raw and processed data for a variety of well data metrics including temperature, porosity, density, and sonic data. This data was taken at the Utah FORGE site as part of the Utah FORGE project.

Data, logs, and graphics associated with the drilling and testing of Utah FORGE deep test well 58-32 (MU-ESW1) near Roosevelt Hot Springs.

This is a compilation of logs and data from Well 14-2 in the Roosevelt Hot Springs area in Utah. This well is also in the Utah FORGE study area. Data includes: flowmeter survey (1989), geochemistry (1977-1978, 1977-1983), injection test data (1979, 1982), and spinner surveys (1989, 1985-1986). Logs include: borehole compensated sonic and gamma ray (600'-6112'), borehole geometry and gamma ray (50'-4829'), caliper (0'-1720'), compensated neutron formation density (600'-6121'), induction electric (650'-6118'), mud log (79'-6100'), steam injection survey (50'-1175'), subsurface pressure surveys (0'-6087'), and subsurface temperature surveys (0'-6106'). The file is in a compressed .zip format and there is a data inventory table (Excel spreadsheet) in the root folder that is a guide to the data that is accessible in subfolders.

This is a compilation of logs and data from Well 52-21 in the Roosevelt Hot Springs area in Utah. This well is also in the Utah FORGE study area. The file is in a compressed .zip format and there is a data inventory table (Excel spreadsheet) in the root folder that is a guide to the data that is accessible in subfolders.

This is a compilation of logs and data from Well 9-1 in the Roosevelt Hot Springs area in Utah. This well is also in the Utah FORGE study area. The file is in a compressed .zip format and there is a data inventory table (Excel spreadsheet) in the root folder that is a guide to the data that is accessible in subfolders.

This is a compilation of logs and data from Well Acord 1-26 in the Roosevelt Hot Springs area in Utah. This well is also in the Utah FORGE study area. Logs include: mud log (45'-12645'), compensated densilog (1102'-7923', 7900'-12644'), neutron log (1102'-7923'), dual induction focused logs (1100'-7923', 7904'-11447'), BHC acoustilog (7800'-11439'), differential temperature log (380'-11448'), gamma ray neutron logs (7900'-12148', 12000'-12647'), temperature logs (7900'-12144', 7900'-12145', 7800'-12655', 7900'-12655'), and caliper log (7800'-12655'), densilog (7900'-12655'). The file is in a compressed .zip format and there is a data inventory table (Excel spreadsheet) in the root folder that is a guide to the data that is accessible in subfolders.

Well 58-32 (previously labeled MU-ESW1) was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. Well Accord-1 was drilled decades ago for geothermal exploration purposes. While the conditions encountered in the well were not suitable for developing a conventional hydrothermal system, the information obtained suggested the region may be suitable for an enhanced geothermal system. Geophysical well logs were collected in both wells to obtain useful information regarding there nature of the subsurface materials. For the recent testing of 58-32, the Utah FORGE Project contracted with the well services company Schlumberger to collect the well logs.