Infrastructure, such as roads, airports, water and energy transmission and distribution facilities, sewage treatment plants, and many other facilities, is vital to the sustainability and vitality of any populated area. Rehabilitation of existing and development of new infrastructure requires three natural resources: natural aggregate (stone, sand, and gravel), water, and energy http://rockyweb.cr.usgs.gov/frontrange/overview.htm.

The principal goals of the U.S. Geological Survey (USGS) Front Range Infrastructure Resources Project (FRIRP) were to develop information, define tools, and demonstrate ways to: (1) implement a multidisciplinary evaluation of the distribution and quality of a region's infrastructure resources, (2) identify issues that may affect availability of resources, and (3) work with cooperators to provide decision makers with tools to evaluate alternatives to enhance decision-making. Geographic integration of data (geospatial databases) can provide an interactive tool to facilitate decision-making by stakeholders http://rockyweb.cr.usgs.gov/frontrange/overview.htm.

This data release contains spatial data on the location, number, size and extent of energy-related surface disturbances on the Colorado Plateau of Utah, Colorado, and New Mexico as of 2016. The database includes: 1) polygons of oil and gas pads generated from automated and manual classification of aerial imagery, and 2) polylines of roads derived from the U.S. Census Bureau TIGER/Line Shapefile, supplemented with additional oil and gas access roads digitized from aerial imagery. Pad polygons and road segments are attributed with a "spud year" date based on spud information from the nearest well point. Spudding is the process of beginning to drill a well in the oil and gas industry, and the spud year is a close approximation of when the access roads and pads were cleared for development. The spud year information can be used to develop a chronology of oil and gas surface disturbances across the study region. The remote sensing-based pad mapping captures bright soil of disturbed are ...

This release contains geospatial data digitized from the Map Showing Geology, Structure, and Oil and Gas Fields in the Sterling 1x2 Degree Quadrangle, Colorado, Nebraska, and Kansas (Scott, 1978) and was compiled as part of the National Geologic Synthesis project. The geospatial data depicts the geology of this quadrangle, which is dominated by Quaternary alluvial and aeolian deposits overlying Tertiary and Cretaceous sedimentary rock, including the Ogallala formation, the Fox Hills sandstone, and the Pierre shale. The included database includes spatial data depicting the locations of mapped geologic contacts and faults, polygons denoting the mapped surficial extent of geologic formations, and structural contours denoting the depth to the top of the D sandstone of the Dakota Group. The database also contains non-spatial tables, including a list of data sources, a description of map units, a glossary of terms, and a data dictionary.

The top of the Upper Cretaceous Dakota Sandstone is present in the subsurface throughout the Uinta and Piceance basins of UT and CO and is easily recognized in the subsurface from geophysical well logs. This digital data release captures in digital form the results of two previously published contoured subsurface maps that were constructed on the top of Dakota Sandstone datum; one of the studies also included a map constructed on the top of the overlying Mancos Shale. A structure contour map of the top of the Dakota Sandstone was constructed as part of a U.S. Geological Survey Petroleum Systems and Geologic Assessment of Oil and Gas in the Uinta-Piceance Province, Utah and Colorado (Roberts, 2003). This surface, constructed using data from oil and gas wells, from digital geologic maps of Utah and Colorado, and from thicknesses of overlying stratigraphic units, depicts the overall configuration of major structural trends of the present-day Uinta and Piceance basins and was used to define the elevation of the base of a specific source-rock interval as part of the assessment. A second structure contour map of the top of the Dakota Sandstone, along with a contoured map showing the elevation of the top of the overlying Mancos Shale, was constructed from well data as part of a stratigraphic research thesis of the Douglas Creek Arch, a structural high which separates the Uinta and Piceance basins (Kuzniak, 2009). This digital dataset contains spatial datasets corresponding to the structure contour maps of the top of the Dakota Sandstone produced by the U.S. Geological Survey's petroleum assessment (Roberts, 2003) and the topical studies along the Douglas Creek Arch (Kuzniak, 2009). Both structure contour maps of the top of the Dakota Sandstone were digitized and attributed as GIS data sets so that these data could be used in digital form as part of U.S. Geological Survey and other studies of these basins. The contours depicting the elevation of the top of the Dakota Sandstone are contained in line feature classes within a geographic information system geodatabase and are also saved as individual shapefiles. Feature classes have a single attribute, elevation, that represents the contoured value. Contoured values are given in feet, to maintain consistency with the original publication, and in meters. Nonspatial tables define the data sources used, define terms used in the dataset, and describe the geologic units. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables.

Oil and Gas Floodplain – Colorado 100-year Effective as of January 28, 2016 as reported by the Colorado Oil & Gas Conservation Commission. Aggregate of FEMA DFIRM (digital vector only) 'Zone A' effective 100-year floodplain extents for Colorado. This data is provided as guidance only and the COGCC cannot guarantee that all floodplain data will be current and/or accurate. For many parts of Colorado, 100-year floodplain zones exist only in a raster map format - these are NOT INCLUDED in this vector shapefile download. Please consult the FEMA Flood Map Service Center and the Colorado Water Conservation Board (CWCB) for more comprehensive listings.

Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. A cell map was not created for the Menefee Coal-Bed Gas (50220381) assessment unit because it was considered a hypothetical assessment unit. The Mesaverde Updip oil had production wells associated with it but resource totals were below the minimum and wasn't quantitatively assessed. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.

This digital data release contains geospatial geologic and paleontological data of the 1° x2 °, 1:250,000 Limon quadrangle covering eastern Colorado and western Kansas. The dataset is a digital reproduction of previously published U.S. Geological Survey field mapping which illustrates the spatial configuration of primarily Quaternary surficial units overlying upper Miocene, Oligocene, Paleocene, and Upper Cretaceous bedrock (Sharps, 1980). This quadrangle contains numerous outcrop of the Ogallala Formation, which is a prolific freshwater aquifer throughout the broader great plains. A structure contour map of the top of the Dakota Sandstone are included, which was constructed using selected oil and gas well logs (Sharps, 1980). The Dakota Sandstone is a productive hydrocarbon reservoir within the Limon quadrangle, and the broader Denver-Julesburg Basin. Point data for Mesozoic invertebrate fossil collection localities are depicted on the map, depicted with either Denver or Washingt ...

This dataset shows estimated depth ranges to stratigraphic horizons near the base of the Mesaverde Total Petroleum System, Uinta-Piceance Province, northwestern Colorado and northeastern Utah. The structural horizons used for depth estimates include the top of the Blackhawk Formation (western Uinta Basin), top of the lower Castlegate Sandstone (central and eastern Uinta Basin), and the top of the Rollins and Trout Creek Sandstone Members of the Iles Formation in the Piceance Basin.

This data set is a result of compiling differing source materials of various vintages.Source material examples used to create and maintain dataset include: BLM 100k Subsurface Maps, Oil and Gas Plats, Coal Plats, Public Land Survey GIS Data (cadnsdi v.2.0), Field Office GIS Data, Compiled 24k USGS Maps, and Land Records.

South America is part of Region 6 (Central and South America) for the World Energy Assessment. South America was divided into 107 geologic provinces as background for prioritization and assessment of undiscovered oil and gas resources. The boundaries of geologic provinces are required for the assessment as oil and gas. Data must be allocated to a geographic entity so that decisions can be made as to which provinces are priority for the assessment. Many sources of geologic information were used to define the province boundaries in South America, and several versions of the map were reviewed. Of the 107 geologic provinces defined in South America, about 40 have had some oil and gas production to date.

The purpose of this note is to briefly describe a detailed (30 m) spatial dataset that estimates the degree of human modification for the lands of Colorado reflecting ~2020 conditions. The degree of human modification is a well-established method to estimate the proximate human activities or processes that have caused, are causing, or may cause impacts on biodiversity and ecosystems. This includes stressors for: urban and built-up, crop and pasture lands, livestock grazing, oil and gas production, mining and quarrying, power generation (renewable and nonrenewable), roads, railways, power lines and towers, logging and wood harvesting, human intrusions, and air pollution.

Please see the attached PDF -- Technical note on a map of human modification in Colorado for 2020 -- that provides further details.

This digital dataset was created as part of a U.S. Geological Survey hydrologic resource assessment and development of an integrated numerical hydrologic model of the hydrologic system of the Upper Colorado River Basin, an extensive region covering approximately 412,000 square kilometers in five states: Wyoming, Colorado, Utah, Arizona, and New Mexico. As part of this larger study, the USGS developed this digital dataset of geologic data and a three-dimensional hydrogeologic framework model (3D HFM) that define the elevation, thickness, and extent of seven hydrogeologic units in the Upper Colorado River Basin. The hydrogeologic setting of the Colorado Plateau consists of thick Paleozoic, Mesozoic, and Cenozoic aquifers, predominantly sandstone and limestone, that are separated by regionally extensive confining units of fine-grained siliciclastic rocks, all overlain by generally thin Quaternary sediments. Based in part on the need to maintain consistency with previously published USGS hydrogeologic studies in the region (Craigg, 2001; Freethy and Cordy, 1991; Geldon, 2003; Glover and others, 1998), seven hydrogeologic units (HGUs) were modeled across the Upper Colorado River Basin: (1) TIPCG, Tertiary Intrusions and Precambrian Granite, a confining unit that includes crystalline igneous and metamorphic rocks of all ages; (2) PZAU, Paleozoic aquifer unit, including Mississippian and Pennsylvanian carbonate rocks and Permian sandstones and conglomerate; (3) CMCU, the Chinle-Moenkopi confining unit, including red Triassic fine-grained sandstone, siltstone and shale; (4) MZAU, Mesozoic aquifer unit, including thick, dominantly eolian Triassic and Jurassic sandstones of the Glen Canyon Group and overlying dominantly fluvial and alluvial sandstones and shales of the San Rafael Group; (5) MCU, Mancos confining unit, including thick sections of Cretaceous marine shale; (6) KTAU, Cretaceous-Tertiary aquifer unit, including marginal marine to continental siliciclastic sections with locally thick Cenozoic volcanic rocks; and (7) QAU, Quaternary alluvial unit, consisting predominantly of alluvial sediment along modern washes and drainages. Surface and subsurface data compiled include a digital elevation model, geologic contacts shown on geologic maps, reported formation tops from oil and gas wells, and structure contour and isopach maps. Input surface and subsurface data have been reduced to points that define the elevation of the top of each hydrogeologic units; these point data sets serve as digital input to the 3D framework model. Surfaces representing the elevation of the top of each hydrogeologic unit were created through standard interpolation methods of input data points using two-dimensional horizon gridding software. Data were interpolated using faults as two-dimensional boundaries that acted as a barrier to information flow during interpolation. Resultant HGU elevations were mapped to an x, y array of 1-km polygonal cells in geographic information systems (GIS) software. Each cell within the array was assigned attributes representing the top elevation thickness of each hydrogeologic unit. This polygonal cellular array is essentially a “flattened”, 2.5D (multiple z values stored at each x,y coordinate) representation of the digital 3D HFM, defining the elevation, thickness, and extent of each of the 7 HGUs at every cell centroid. The digital dataset includes a geospatial database that contains the following data elements: (1) a digital hydrogeologic map and map of fault locations for the model domain, (2) compiled digital input data to the 3D HFM for each hydrogeologic unit; (3) the 3D HFM, stored as interpolated elevation and thickness of the seven hydrogeologic as attributes of an XY array of polygonal cells; and (4) elevation surfaces of each HGU interpolated as triangular irregular networks (TINs) and extruded volumes (“multipatch”). The spatial data are accompanied by non-spatial tables that describe the sources of geologic information, a glossary of terms, a description of model units, and a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file. Spatial data from the geodatabase are also saved in shapefile format and nonspatial tables from the geodatabase are also provided in CSV format.

This dataset is part of an effort to highlight the advantages of incorporating low-temperature (< 150 C) geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). For this Denver Basin example, resource favorability maps were created to identify potentially favorable areas for further geothermal exploration and are provided here. Favorability was based on three types of data: (1) geologic, (2) economic, and (3) risk. This raw data is also provided below. Geologic data include bottom-hole temperatures (BHT) from oil and gas wells, water co-production volumes from oil and gas wells, well groundwater levels, hot spring locations, temperatures, and chemistries, faults, and earthquakes. Economic feasibility data include population, thermal energy demand, infrastructure, and roads. Risk data (which includes data on excluded areas) include flood plains, protected lands (e.g. wildlife conservation areas, national parks). The included report describes this project in detail, covering workflows, relevant datasets, Python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The figures in this report include: maps of the original datasets; maps of transformed data and derived parameters (such as the geothermal gradient or thermal conductivity); results of uncertainty analyses; results of data completeness (using the GeoRePORT tool); examples of the data combination and processing (using the geoPFA Python library, which is introduced in the attached report); favorability maps for each criteria; and a final combined favorability map. This project is designed to facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of April 2003 when the cell maps were created in 2003.

Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2002 when the cell maps were created in 2004.

This dataset shows depth contours to the top of the Mesaverde Group within the Southwestern Wyoming Province, southwestern Wyoming, northeastern Utah, and northwestern Colorado

This dataset shows depth contours to the top of the Frontier Formation within the Southwestern Wyoming Province, southwestern Wyoming, northeastern Utah, and northwestern Colorado.

This report contains only Colorado Geological Survey desorption data for Colorado as determined by the US Bureau of Mines direct method. This data was collected during the years 1975 through 1982 in order to determine the extent of the potential methane hazard and/or resource. Most of the samples tested are coal; a few are sandstone, siltstone, shale, or oil shale. The data are arranged by CGS numbers. A Colorado coal region map, a stratigraphic chart, and sample locations maps for each sample coal region are provided to aid in data searches. Table 1 indicates which tests were run on each sample. Gas results are presented in cubic feet per ton, not standard cubic feet per ton. These cubic feet per ton results are approximately 20% higher than standard cubic feet results, due to the elevation of the sample locations and our Denver office. Furthermore, the US Bureau of Mines admits to a - 30% error in their direct method. Therefore, total gas content figures are best considered to be relative numbers indicating high, medium, or low gas contents. Only raw data is presented. This report and our other individual basin reports on the Green River, Raton, San Juan, and Piceance Basins, are designed to give an indication of where high gas contents (based on the desorption data herein and other geological factors) are likely to be found. We cannot quantify the relationship between gas contents and reservoir production potential. We assume that successful production is more likely in an area of high gas content; however, other factors such as water saturation, permeability, and structural position might also be significant. Furthermore, even in areas where gas content and other geologic factors appear favorable, proper production procedures are still in dispute and await further testing. 9 figures, 1 table.

Streams and lakes managed by CPW for sportfish buffered to 300 ft. for use in SB181 oil and gas analyses. Most data pulled from NHD (National Hydrography Dataset) created and maintined by USGS.

These geospatial data characterize the potential for geographic overlap among land-use practices and between land-use and climate change on the Colorado Plateau—a dryland region experiencing rapid changes in land-use and facing aridification. They were used to characterize spatial patterns and temporal trends in aridification, land-use, and recreation at the county and 10-km2 grid scales. Increasing trends and overlapping areas of high intensity for use, including oil and gas development and recreation, and climate drying, suggest areas with high potential to experience detrimental effects to the recreation economy, water availability, vegetation and wildlife habitat, and spiritual and cultural resources. Patterns of overlap in high-intensity land-use and climate drying differ from the past, indicating the potential for novel impacts and suggesting that land managers and planners may require new strategies to adapt to changing conditions. This analytical framework for assessing th ...