Filters: Tags: TX (X) > Types: Map Service (X) > partyWithName: U.S. Geological Survey (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Shapefile (2) Types Downloadable (2) OGC WFS Layer (2) OGC WMS Layer (2) Shapefile (2) Contacts Farshid (Contractor) Felfelani Steven M Condon Thaddeus S Dyman U.S. Geological Survey - ScienceBase Central Energy Resources Science Center More... Categories Data (2) Tag Types Place (2) Theme (2) Harvest Set (1) USGS Scientific Topic Keyword (1) Tag Schemes U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST (1) none (2) Central Energy Resources Team Keyword Thesaurus (1) USGS Oil and Gas Assessment Units (NOGA-2000) (1) Augmented FIPS 10-4 and FIPS 6-4, version 1.0 (1) EnergyResourceActivities (1) Gateway to the Earth draft 9 28-Jun-2002 (1) More... View Results as: JSON ATOM CSV

National Assessment of Oil and Gas - Cotton Valley Group and Travis Peak-Hosston Formation Assessment Units, Western Gulf and East Texas Basin and Louisiana-Mississippi Salt Basins Provinces (047, 048 and 049) The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic... Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 47 = Western Gulf, 48 = East Texas Basin, 49 = Louisiana-Mississippi Salt Basins, 504701 = Upper Jurassic-Cretaceous-Tertiary Composite, 50470108 = Cotton Valley Blanket Sandstone Gas, All tags... 50470109 = Cotton Valley Massive Sandstone Gas, 50470110 = Cotton Valley Updip Oil and Gas, 50470111 = Cotton Valley Hypothetical Updip Oil, 50470112 = Travis Peak-Hosston Gas and Oil, 50470113 = Travis Peak-Hosston Updip Oil, 50470114 = Travis Peak-Hosston Hypothetical Updip Oil, AL, AR, Assessment Unit, Condon, S.M., Dyman, T.S., Earth Science, East Texas Basin, Economic geology, Energy Resources, Energy Resources, FL, Geology, Gulf Coast, LA, Louisiana-Mississippi Salt Basins, MS, National Assessment of Oil and Gas, Natural Gas, Natural Resources, Natural gas resources, Oil, Oil sand resources, Oil shale resources, Resource Assessment, TX, U.S. Geological Survey, US01 = Alabama, US05 = Arkansas, US12 = Florida, US22 = Louisiana, US28 = Mississippi, US48 = Texas, USGS, USGS Science Data Catalog (SDC), USGS World Energy Region 5, USGS World Energy Region 5, United States, geoscientificInformation, gulfroom, noga2000, nogacvtp, nogaflorida, nogagulf, oilgas, Fewer tags 1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins This data release component contains shapefiles of river basin polygons and monitoring site locations coincident with the outlets of those basins. A table of basin attributes is also supplied. Attributes, observations, and weather forcing data for these basins were used to train and test the stream temperature prediction models of Rahmani et al. (2021b).<\p> Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AL, AR, AZ, Alabama, Arizona, All tags... Arkansas, CA, CO, CT, California, Colorado, Connecticut, DC, DE, Delaware, District of Columbia, GA, Georgia, IA, ID, IL, IN, Idaho, Illinois, Indiana, Iowa, KS, KY, Kansas, Kentucky, MA, MD, ME, MI, MN, MO, MS, MT, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, NC, ND, NE, NH, NJ, NM, NV, NY, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, OH, OK, OR, Ohio, Oklahoma, Oregon, PA, Pennsylvania, RI, Rhode Island, SC, SD, South Carolina, South Dakota, TN, TX, Tennessee, Texas, US, UT, United States, Utah, VA, Virginia, WA, WI, WV, WY, Washington, West Virginia, Wisconsin, Wyoming, deep learning, environment, inlandWaters, machine learning, modeling, streams, water resources, water temperature, Fewer tags