The AQUASTAT portal enables users to access the core database of country statistics, focused on water resources, water uses and agricultural water management. Along with it, other water information in the form of complementary databases, such as the irrigated crop calendars and the sub-national irrigation areas databases, the detailed database on dams and reservoirs and the water-and agriculture-related institutions database are available. The glossary is also an important component of AQUASTAT, offering multilingual definitions of 500+ water-related terms and key indicators, including detailed reference sources and links to related terms.
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).
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.
The EGS Collab SIGMA-V project is a multi-lab and university collaborative research project that is being undertaken at the Sanford Underground Research Facility (SURF) in South Dakota. The project consists of studying stimulation, fluid-flow, and heat transfer processes at a scale of 10-20 m, which is readily amenable to detailed characterization and monitoring. One objective of the project is to establish circulation from injector to producer by hydraulically fracturing the injector. Data generated during these experiments is to be compared with predictions from coupled thermal, hydrological, mechanical, and chemical simulators. One such a simulator, TOUGH2-CSM, has been enhanced in order to simulate EGS Collab SIGMA-V project experiments. These modifications include adding tracers, the capability to model tracer sorption, and an embedded fracture formulation. A set of example problems validate our conservative tracer transport and sorption formulations. We then simulated tracer transport and thermal breakthrough for the first EGS Collab SIGMA-V experiment. This dataset includes the TOUGH2-CSM input and output files associated with the thermal and tracer simulations. A conference paper is included for additional context.
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.
The Mountain Home area is characterized by high heat flow and temperature gradient. Temperature data are available from 18 boreholes with depths equal to or greater than 200 m, 5 of which have depths ranging from ~1340 m to ~3390 m (MH-1, MH-2, Bostic1, Lawrence D No.1, and Anschutz No. 1). Although there are large variations, the average temperature gradient exceeds 80 deg C/km. Recently, high-resolution gravity, ground magnetic, magnetotelluric (MT), and seismic reflection surveys have been carried out in the area in order to define key structural features responsible for promoting permeability and fluid flow. Of particular relevance is the MT survey performed in the Mountain Home area. The included reports and papers present preliminary and final 3-D numerical models of the natural-state (i.e. pre-production state) of the Mountain Home geothermal area conditioned using the available temperature profiles from the five deep wells in addition to interpretations of MT data.
The AGS Utilities Tool offers schema validation, data validation and conversion of geotechnical AGS files. The API is publicly available for use in stakeholders’ own analysis, processing or software.
This service provides an application programming interface (API) for data scientists, software developers and software applications to query and download a selection of BGS OpenGeoscience data which is available under Open Government Licence in machine-readable JSON format using the OGCAPI standards. This data can also be accessed directly via ESRI Arc Pro or QGIS. The OGC maintains a complete list of OGCAPI-features clients
This service provides an application programming interface (API) for data scientists, software developers and software applications to query and download BGS-hosted sensor data in machine-readable JSON format. The API is powered by FROST Server and conforms to the OGC SensorThingsAPI specification.
Natural fracture data from wells 33-7, 33A-7,52A-7, 52B-7 and 83-11 at West Flank. Fracture orientations were determined from image logs of these wells (see accompanying submissions). Data files contain depth, apparent (in wellbore reference frame) and true (in geographic reference frame) azimuth and dip, respectively.
This data set estimates large-scale wetland distributions and important wetland complexes, including areas of marsh, fen, peatland, and water.