This database contains spatial data on the location, number, size and extent of energy-related surface disturbances within the Bureau of Land Management’s (BLM) Carlsbad Field Office (CFO) administrative area. The BLM administers over 2 million acres of surface estate and 3 million acres of mineral estate in the southeastern portion of New Mexico. The BLM requires a thorough and comprehensive reasonable foreseeable development (RFD) scenario which quantifies the current and future potential of oil and gas resources and the necessary water use associated with those activities. The database includes: 1) polygons of oil and gas pads generated from automated and manual classification of aerial imagery, 2) polylines of roads derived from the U.S. Census Bureau (2020) TIGER/Line Shapefile, supplemented with additional oil and gas access roads digitized from aerial imagery, 3) point locations of active and abandoned oil and gas wells in the CFO area accessed from NM Oil Conservation Division (OCD) geodata portal, and 4) a set of relationship classes that link the pad polygons to the well points (and all associated well attributes) based on unique identifiers. 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 locations of wells that have been drilled for oil production, gas or salt resources or for underground storage of hydrocarbons.This data can be used for land use and resource management, emergency management, as well as compliance and enforcement in the petroleum industry. The Data is collected on an on-going basis and maintained in the Ontario Petroleum Data System (OPDS). Additional Documentation Petroleum Well - Data DescriptionPetroleum Well - DocumentationPetroleum Well- User Guide Status
On going: data is being continually updated

Maintenance and Update Frequency

Semi-monthly: data is updated twice a month

Contact Petroleum Operations Section, Ministry of Natural Resources and Forestry, POSrecords@ontario.ca

The extensive development of oil and natural-gas resources in south Texas during the past 10 years has led to questions regarding possible environmental effects of processes associated with oil and natural-gas production, in particular the process of hydraulic fracturing, on water and other natural resources. Part of the lower San Antonio River watershed intersects an area of oil and natural-gas production from the sedimentary rocks that compose the Eagle Ford Group. The rapid expansion of infrastructure associated with oil and natural-gas production increases potential pathways for inorganic and organic contaminants to enter surface-water systems. The U.S. Geological Survey, in cooperation with the San Antonio River Authority, analyzed geospatial data from different years (2008 and 2015) to evaluate changes in land cover associated with oil and natural-gas production activities in the lower San Antonio River watershed. Additionally, during 2015-17 surface-water samples collected from 5 sites and streambed-sediment samples collected from 17 sites in the lower San Antonio River watershed were analyzed for a broad range of constituents that might be associated with oil and natural-gas production.

A cells polygon feature class was created by the U.S. Geological Survey (USGS) to illustrate the degree of exploration, type of production, and distribution of production in the United States. Each cell represents a square mile 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, or the type of production of the wells located within the cell is unknown or dry. The well information was initially retrieved from IHS Inc.'s 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 well data. No proprietary data are displayed or included in the cell maps. The data are current through 10/1/2005.

The purpose of this data release is to provide data in support of the Bureau of Land Management's (BLM) Reasonably Foreseeable Development (RFD) Scenario by estimating water-use associated with oil and gas extraction methods within the BLM Carlsbad Field Office (CFO) planning area, located in Eddy and Lea Counties as well as part of Chaves County, New Mexico. Three comma separated value files and two python scripts are included in this data release. It was determined that all reported oil and gas wells within Chaves County from the FracFocus and New Mexico Oil Conservation Division (NM OCD) databases were outside of the CFO administration area and were excluded from well_records.csv and modeled_estimates.csv. Data from Chaves County are included in the produced_water.csv file to be consistent with the BLM’s water support document. Data were synthesized into comma separated values which include, produced_water.csv (volume) from NM OCD, well_records.csv (including _location and completion) from NM OCD and FracFocus, and modeled_estimates.csv (using FracFocus as well as Ball and others (2020) as input data). The results from modeled_estimates.csv were obtained using a previously published regression model (McShane and McDowell, 2021) to estimate water use associated with unconventional oil and gas activities in the Permian Basin (Valder and others, 2021) for the period of interest (2010-2021). Additionally, python scripts to process, clean, and categorize FracFocus data are provided in this data release.

Land Management Software Market size was valued at USD 1.69 Billion in 2024 and is projected to reach USD 2.62 Billion by 2031, growing at a CAGR of 5.65% from 2024 to 2031.

The growth of land management software is primarily driven by the increasing demand for efficient land use, advancements in geospatial technology, regulatory compliance, and the need for data-driven decision-making. As global populations grow and urbanization accelerates, there is a growing need for efficient land resource management. Land management software offers tools to optimize land use, enhance productivity in agriculture, forestry, and urban planning, and ensure sustainable development practices.

Advancements in geospatial technology, such as Geographic Information Systems (GIS), remote sensing, and satellite imagery, have significantly enhanced the capabilities of land management software, enabling more accurate mapping, monitoring, and analysis of land resources. Regulatory compliance and environmental concerns also drive the adoption of land management software among government agencies, landowners, and businesses.

Data-driven decision-making is another driving factor, as land management software provides powerful analytical tools for processing large volumes of spatial data, generating insights, and supporting data-driven decision-making processes. The growing awareness of climate change risks and the need for resilient land management practices drives the adoption of software solutions that enable climate-smart land management.

Precision agriculture practices are increasingly emphasized in the agricultural sector, with land management software playing a critical role in supporting these practices. The emergence of integrated land management platforms that combine GIS, asset management, and workflow automation capabilities is also driving the adoption of comprehensive software solutions.

In conclusion, the growth of land management software is driven by the need for efficient land use, advancements in technology, regulatory requirements, and the recognition of the importance of sustainable land management practices in addressing global challenges such as food security, environmental degradation, and climate change.

A cells polygon feature class was created by the U.S. Geological Survey (USGS) to illustrate the degree of exploration, type of production, and distribution of production in the United States. 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, or the type of production of the wells located within the cell is unknown or dry. The well information was initially retrieved from IHS Inc.'s 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 well data. No proprietary data are displayed or included in the cell maps. The data are current through 10/1/2005.

The locations of wells that have been drilled for oil production, gas or salt resources or for underground storage of hydrocarbons. This data can be used for land use and resource management, emergency management, as well as compliance and enforcement in the petroleum industry. The Data is collected on an on-going basis and maintained in the Ontario Petroleum Data System (OPDS). *[OPDS]: Ontario Petroleum Data System

The Land Management Software market is experiencing robust growth, driven by increasing demand for efficient resource allocation, improved regulatory compliance, and the need for data-driven decision-making across various sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $7 billion by 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and accessibility, appealing to businesses of all sizes. Furthermore, the increasing integration of GIS (Geographic Information Systems) technology enhances spatial data analysis and visualization, improving operational efficiency. The Oil and Gas sector, a significant user of land management software, is a major contributor to market growth, along with expanding applications in urban planning and lease management. While data security concerns and the need for specialized expertise present some restraints, the overall market outlook remains positive, driven by technological advancements and increasing awareness of the benefits of efficient land management practices. The competitive landscape is marked by a mix of established players and emerging technology providers. Companies like Trimble, Tyler Technologies, and others are leveraging their expertise in GIS and software development to offer comprehensive solutions. Smaller companies are focusing on niche applications or specialized functionalities to gain market share. The market exhibits geographical diversity, with North America and Europe currently holding the largest market shares due to established infrastructure and early adoption. However, rapid growth is expected in the Asia-Pacific region, driven by increasing urbanization and infrastructure development projects. Continued innovation in areas like AI-powered analytics, automated workflows, and improved data integration will further shape the market's trajectory in the coming years, particularly in supporting complex land management challenges across diverse geographies and regulatory environments.

From the site: "A cells polygon feature class was created by the U. S. Geological Survey (USGS) to illustrate the degree of exploration, type of production, and distribution of production in the State of Illinois. 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, or the type of production of the wells located within the cell is unknown or dry. Data were retrieved from the Illinois State Geological Survey (ISGS) oil and gas wells database. Cells were developed as a graphic solution to overcome the problem of displaying proprietary well data. No proprietary data are displayed or included in the cell maps. The data are current as of 2006."

Petroleum and natural gas are the most important mineral resources of Wyoming. Because of their value to the economy of the State, detailed information concerning their occurrence, development and properties particularly useful to State and Federal agencies. A comprehensive report on the oil and gas fields in the State is likewise valuable to oil companies searching for new deposits of oil and gas. Thousands of small investors and land owners also have a "stake" in Wyoming's petroleum industry. This study contains individual reports on 271 oil and gas fields in Wyoming. The location of each field is given; and where available, maps of the fields, are included in the report. Brief comments are made on the geology of the fields, surface formations and elevations. History of the discovery and development of each field is recorded and the amounts of oil and gas produced in each are tabulated by years. The facilities by which the oil and gas are transported from the fields are mentioned.

This dataset comprises a collection of tabular data and graphical images supporting the U.S. Geological Survey's National Oil and Gas Assessment (NOGA) for Appalachian Basin Province (067). The dataset includes detailed information on crude oil and natural gas production, including volumetric and descriptive data such as cumulative production, remaining reserves, and known recoverable volumes. Historical data covering field-discovery dates, well completion dates, exploration objectives, and well depths are also provided. Data sources include commercial databases along with supplemental information from various federal and state agencies. No proprietary data is included in this. The dataset is presented in multiple formats, including .pdf files for graphical images and .tab files for tabular data, encompassing eco-regional, federal land, ownership parcels, and state-wise data distributions.

A cells polygon feature class was created by the U. S. Geological Survey (USGS) to illustrate the degree of exploration, type of production, and distribution of production in the State of Illinois. 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, or the type of production of the wells located within the cell is unknown or dry. Data were retrieved from the Illinois State Geological Survey (ISGS) oil and gas wells database. Cells were developed as a graphic solution to overcome the problem of displaying proprietary well data. No proprietary data are displayed or included in the cell maps. The data are current as of 2006.

​​​​​​​​The Geologic Energy Management Division's (CalGEM) online mapping application Well Finder presents California’s oil and gas industry information from the geographic perspective. You can find and locate oil and gas wells and other types of related facilities throughout the state. Search by address, latitude/longitude, unique well number (also known as “API”), Public Land Survey System (PLSS) township/range/section, or by oil and gas field names. Dig deeper into individual well records. Explore where permits have been issued for oil and gas operations. Investigate wells by their type of use, such as oil and gas producers versus injectors.Well Finder is a tool CalGEM provides to improve informational transparency. Readily available data contributes to better health and environmental safeguards--fundamentals of the CalGEM mission. Data can help inform California's efforts to achieve the twin goals of mitigating climate change and a net-zero footprint.Well Finder interfaces with CalGEM’s online Well Statewide Tracking and Reporting System (WellSTAR) database and is updated nightly.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Location of all current Production Licence Applications issued under the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, or Petroleum (Submerged Lands) Act, 1967 for the regulated resource or commodity of petroleum. Production Licences provide exclusive tenure rights to produce for the regulated resource or commodity of petroleum for an unlimited term (usually 21 years). Comment is sought on applications for Production Licence from numerous sources before granting. Production programs are subject to strict environmental and heritage conditions.

Purpose

The dataset was developed to record information necessary for the administration of the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, and Petroleum (Submerged Lands) Act, 1967.

Use:

Used to supply government, industry and the general public with an up-to-date status and extent of petroleum production activities throughout the state.

Use Limitation:

The data should not be used at a scale larger than 1:50 000.

Dataset History

Source Data History: Production Licence Application boundaries were sourced from the official Petroleum Register licence application documents. Licence application boundaries are legally defined to follow lines of latitude and longitude, based on potentially several geodetic datums.

Processing Steps: Coordinates entered by keyboard from licence application documents. Non GDA94 coordinates transformed into GDA94. Linework cleaned to remove duplicate arcs. Data adjusted for accurate state border and coastline. Where appropriate cadastral parcels removed from licence application polygons. Associated attribute data also captured from licence application documents.

Dataset Citation

SA Department of Primary Industries and Resources (2013) SA Petroleum Production License Applications. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/ecf1a9b6-44ca-4403-9648-828537652a54.

description: 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 2001 when the cell maps were created in 2002.; abstract: 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 2001 when the cell maps were created in 2002.

description: 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 2001 when the cell maps were created in 2002.; abstract: 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 2001 when the cell maps were created in 2002.

This dataset comprises a collection of tabular data and graphical images supporting the U.S. Geological Survey's National Oil and Gas Assessment (NOGA) for San Juan Basin Province (022). The dataset includes detailed information on crude oil and natural gas production, including volumetric and descriptive data such as cumulative production, remaining reserves, and known recoverable volumes. Historical data covering field-discovery dates, well completion dates, exploration objectives, and well depths are also provided. Data sources include commercial databases along with supplemental information from various federal and state agencies. No proprietary data is included in this. The dataset is presented in multiple formats, including .pdf files for graphical images and .tab files for tabular data, encompassing eco-regional, federal land, ownership parcels, and state-wise data distributions.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Location of all current Exploration Licence/Permit Applications issued under the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, or Petroleum (Submerged Lands) Act, 1967 for the regulated resource or commodity of petroleum. Exploration Licences/Permits provide exclusive tenure rights to explore for the regulated resource or commodity of petroleum for a minimum of 5 or 6 years. Comment is sought on applications for Exploration Licences/Permits from numerous sources before granting. Exploration programs are subject to strict environmental and heritage conditions. Exploitation of identified resources must be made under separate petroleum production leases.

Purpose

The dataset was developed to record information necessary for the administration of the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, and Petroleum (Submerged Lands) Act, 1967.

Use: Used to supply government, industry and the general public with an up-to-date status and extent of petroleum exploration activities throughout the state.

Dataset History

Source Data History: Exploration Licence/Permit Application boundaries were sourced from the official Petroleum Register licence/permit application documents. Licence/permit application boundaries are legally defined to follow lines of latitude and longitude, based on potentially several geodetic datums.

Processing Steps: Coordinates entered by keyboard from licence/permit application documents. Non GDA94 coordinates transformed into GDA94. Linework cleaned to remove duplicate arcs. Data adjusted for accurate state border and coastline. Where appropriate cadastral parcels removed from licence/permit application polygons. Associated attribute data also captured from licence/permit application documents.

Dataset Citation

SA Department of Primary Industries and Resources (2013) SA Petroleum Exploration Licence/Permit Applications. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/d5667303-96c8-473f-af05-d3f53ac7753c.

This dataset comprises a collection of tabular data and graphical images supporting the U.S. Geological Survey's National Oil and Gas Assessment (NOGA) for Southwestern Wyoming Province (037). The dataset includes detailed information on crude oil and natural gas production, including volumetric and descriptive data such as cumulative production, remaining reserves, and known recoverable volumes. Historical data covering field-discovery dates, well completion dates, exploration objectives, and well depths are also provided. Data sources include commercial databases along with supplemental information from various federal and state agencies. No proprietary data is included in this. The dataset is presented in multiple formats, including .pdf files for graphical images and .tab files for tabular data, encompassing eco-regional, federal land, ownership parcels, and state-wise data distributions.