Version: GOGI_V10_2This data was downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database.Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.Link to SourcePoint of Contact: Jennifer Bauer email:jennifer.bauer@netl.doe.govMichael D Sabbatino email:michael.sabbatino@netl.doe.gov

This resource contains data inputs and a Jupyter Notebook that is used to introduce Hydrologic Analysis using Terrain Analysis Using Digital Elevation Models (TauDEM) and Python. TauDEM is a free and open-source set of Digital Elevation Model (DEM) tools developed at Utah State University for the extraction and analysis of hydrologic information from topography. This resource is part of a HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about

In this activity, the student learns how to (1) derive hydrologically useful information from Digital Elevation Models (DEMs); (2) describe the sequence of steps involved in mapping stream networks, catchments, and watersheds; and (3) compute an approximate water balance for a watershed-based on publicly available data.

Please note that this exercise is designed for the Logan River watershed, which drains to USGS streamflow gauge 10109000 located just east of Logan, Utah. However, this Jupyter Notebook and the analysis can readily be applied to other locations of interest. If running the terrain analysis for other study sites, you need to prepare a DEM TIF file, an outlet shapefile for the area of interest, and the average annual streamflow and precipitation data. - There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects). - If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS. - You also need to obtain average annual streamflow and precipitation data for the watershed of interest to assess the annual water balance and calculate the runoff ratio in this exercise. In the U.S., the streamflow data can be obtained from the USGS NWIS website (https://waterdata.usgs.gov/nwis) and the precipitation from PRISM (https://prism.oregonstate.edu/normals/). Note that using other datasets may require preprocessing steps to make data ready to use for this exercise.

This resource contains data inputs and an iPython Jupyter Notebook used to simulate semi-distributed variable source area runoff generation in a tributary to the Logan River. This resource is part of the HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about.

In this activity, the student learns how to (1) calculate the topographic wetness index using digital elevation models (DEMs) following up on a previous module on DEMs and GIS in Hydrology; (2) apply TOPMODEL concepts and equations to estimate soil moisture deficit and runoff generation across a watershed given necessary watershed and storm characteristics; and (3) critically assess concepts and assumptions to determine if and why TOPMODEL is an appropriate tool given information about a specific watershed.

Please note that this exercise sets up the data needed to estimate runoff in the Spawn Creek watershed using TOPMODEL. Spawn Creek is a tributary of the Logan River, Utah. This exercise uses some of the same data as the Logan River Exercise in Digital Elevation Models and GIS in Hydrology at https://www.hydroshare.org/resource/9c4a6e2090924d97955a197fea67fd72/. If running the TOPMODEL for other study sites, you need to prepare a DEM TIF file and an outlet shapefile for the area of interest. - There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects). - If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS.

The Georgina Basin Geoscience Data Package is a geospatial data compilation for the Georgina Basin, with a focus on the southern part of the basin. The data set includes three components: an ARC-GIS package (that includes geochemistry, biostratigraphy, formation top picks, hydrocarbon shows, XRD data, ICPMS data, SEM-EDX data, geomechanics data, well header information, Geoscience Australia maps, map products and geophysics), a seismic data compilation (incorporating existing publicly-available seismic data from the southern Georgina Basin, and a well folio (summarising in graphic form the key stratigraphic, geochemical, biostratigraphic, hydrocarbon shows, wireline log, porosity, permeability and HyLogger data for 29 wells in the southern Georgina Basin). The data package has been put together to assist explorers in understanding the conventional and unconventional hydrocarbon potential of the Georgina Basin.

This submission contains a technical report describing the development process and visual graphics for the Global Oil and Gas Infrastructure database. Access the GOGI database using the following link: https://edx.netl.doe.gov/dataset/global-oil-gas-features-database There is a web-mapping tool that allows you to visualize and interact with this data also available here: https://edxspatial.arcgis.netl.doe.gov/maps/edxspatial-gogi-index.html Acknowledgement: This work was performed under a CRADA between NETL and EDF, and was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

The NATCARB Viewer allows users to browse and query data under Regional Carbon Sequestration Partnership (RCSP), Atlas V, Worldwide CCS Database, Brine Well Samples, and other tabs. The number of stationary CO2 sources, CO2 emissions, and CO2 storage resource estimates reported in Atlas V is based on information gathered by the National Carbon Sequestration Database and Geographic Information System (NATCARB). NATCARB is a relational database and geographic information system (GIS) that integrates CCS data from the RCSPs and other sources. NATCARB provides a national view of the carbon storage potential; data from NATCARB is uploaded into Energy Data eXchange (EDX).

Database published: February 13, 2020, 6:51 AM (UTC+00:00)This data was downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database.Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.Link to SourcePoint of Contact: Jennifer Bauer email:jennifer.bauer@netl.doe.govMichael D Sabbatino email:michael.sabbatino@netl.doe.gov