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USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2026

Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system

Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.

Colorado↗
USGS2025

Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA

The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty. For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.

California, Idaho, Nevada, Oregon, Utah↗
USGS1985

Low flows and flow duration of Tennessee streams through 1981

Estimates of low-flow characteristics and flow duration for the period of record at continuous-record streamflow gages are essential in hydrologic studies and water-resources management. This report provides estimates of low flow for 1, 3, 7, 14, 30, 60, and 90 consecutive days for recurrence intervals of 2, 5, 10, and 20 years for continuous-record streamflow gages. These estimates were used in correlation methods to estimate low flow at partial-record streamflow sites for 1, 3, and 7 consecutive days for a recurrence interval of 10 years; and 3 consecutive days for a recurrence interval of 20 years.

Tennessee↗
USGS2026

Neutron scattering reveals fractionation of natural gas mixtures in unconventional petroleum reservoir pores: Perspectives on energy resource recovery and storage

In unconventional petroleum reservoirs hydrocarbon fluids are hosted by both mineral and organic matter pores. These pores can have diameters that range from microns to less than a single nanometer and, for unconventional reservoirs, there is evidence that small pores ( <20 nm diameter) may constitute a large proportion of the available space. Understanding subsurface volumes and how fluids behave in them can be helpful for predicting hydrocarbon production and storage in the subsurface. One area with knowledge gaps regarding hydrocarbon behavior in small pores is the possibility for mixtures to fractionate (i.e., unmix) based on pore size or pore type. Mixture fractionation as a function of pore size could impact recovery of hydrocarbons, drive compositional shifts during production, and limit fluid storage within candidate reservoirs. To investigate natural gas fractionation in small geologic pores, we applied total neutron scattering to probe methane-ethane mixtures at reservoir pressures (up to ≈30 MPa) and temperature (60°C) within a sample from the Upper Cretaceous Niobrara Formation. Neutron scattering data reveal only minor fractionation occurs between methane and ethane in 20-nm diameter sample mesopores. Increased fractionation is observed for sample micropores, with up to 72% (±1% at 1-sigma) methane found in 2 nm diameter pores following injection of a 50%-50% methane-ethane mixture. These data provide rarely available direct experimental observations of hydrocarbon mixture behavior under nanoconfinement in a sample from an important unconventional petroleum reservoir. Our results are discussed in the context of evaluating hydrocarbon resources in unconventional reservoir meso- and micropores, reconciling observed gas composition changes during production, and more broadly, understanding subsurface pore volumes within an energy storage framework.

Fuel↗
USGS2025

Review: The hydrogeology of critical mineral resources relevant to the energy transition

Attaining the goals of the international treaty on climate change (the Paris Agreement) will greatly increase the demand for the critical minerals required to implement clean-energy technologies. This poses both challenges and opportunities to the hydrogeologic community from several perspectives. Here, important insights that the hydrogeological sciences have to offer for mineral exploration, mineral production, and addressing environmental issues related to mining and mine decommissioning are summarized. This study focuses on copper, cobalt, lithium, and rare earths to represent the broad spectrum of critical minerals and illustrate their relevance by referring to projected demands and production rates. The current understanding of the hydrogeologic processes that form major deposits of these minerals are then summarized. Ore is defined as the naturally occurring material from which minerals of economic value can be extracted, where most ore deposits are the products of complex hydrogeologic couplings between fluid flow, heat transport, solute transport, chemical reactions, and mechanical deformation. Exploration models for the discovery of deeper, hidden deposits are potentially informed by hydrogeologic theory and hydrogeochemical processes. Hydrogeologic understanding and methods are also essential to production and recovery. Longstanding challenges are mine dewatering and (conversely) mine water supply, as well as mineral-extraction practices such as spoil heap leaching and in situ mining. New challenges arise from element extraction from subsurface brines. Finally, the quantity of water use and potential environmental impacts of mining on water quality are at the core of ‘social license’: the approval and acceptance of society to mining activities.

Hydrogeology Journal↗
USGS1999

Reconfigured-Channel Monitoring and Assessment Program

A U.S. Geological Survey program to monitor and assess channel reconfiguration activity is described. A data base available on the world wide web will enable land-management agencies and other interested parties to evaluate the long-term success of various channel reconfiguration projects. A demonstration project on the Lake Fork of the Gunnison River, Colorado, illustrates the program objectives and approach.

Colorado↗
USGS1976

Corwin Springs Known Geothermal Resources Area, Park County, Montana

The Corwin Springs Known Geothermal Resources Area (KGRA) is contiguous to Yellowstone National Park along a part of the northern boundary of the park near Gardiner, Park County, Mont. The area contains two known sites of hot-spring activity--LaDuke Spring, 2.8 km southeast of the small resort community of Corwin Springs, and Bear Creek Spring, 2.6 km east of Gardiner. LaDuke Spring issues from brecciated quartzite and has a flow rate of 380 1/min, a surface water temperature of 65°C, a silica-geothermometer temperature of 68.7°C, and a Na-K-Ca geothermometer temperature of 76.8°C. Bear Creek Spring issues from limestone and has a flow rate of 4 1/min, a surface water temperature of 32°C, a silica temperature of 46.7°C, and a Na-K-Ca temperature of 87.2°C. The springs, which are actively depositing travertine, are on or near the trace of the Gardiner fault-a high-angle reverse fault which forms the southwestern boundary of the Beartooth uplift. Features that make the Corwin Springs KGRA potentially significant include: (1) Proximity of the Corwin Springs area to significant Pliocene and Pleistocene volcanism in Yellowstone National Park and related geothermal activity, (2) existence of a large potential geothermal reservoir in the northern extension of the Sepulcher Mountain graben, (3) localization of thermal activity along the Gardiner fault in the Corwin Springs area, (4) occurrence of negative gravity anomaly centered over the northern end of the Sepulcher Mountain graben, (5) existence of negative magnetic anomaly in the Corwin Springs area, (6) location of the area within the Intermountain seismic belt, (7) evidence of recent tectonism in the area, as demonstrated by Pleistocene and Holocene faulting, and (8) observed surface temperatures and estimated geochemical temperatures of the two known hot springs (features which do not indicate high subsurface temperatures).

Montana↗
USGS2025

Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.

The Early Cretaceous (Berriasian–Hauterivian) Hosston Formation in Louisiana and eastward is time correlative to the Travis Peak Formation of Texas and southern Arkansas. The formation is a first-order clastic sequence with a regional carbonate transgressive surface as an upper contact. The Hosston and Travis Peak formations contain conventional natural gas and oil accumulations that have been produced for nearly a century. These mature reservoirs contain terrigenous fluvial-deltaic, shore-zone, and paralic deposits across the productive trend; organic-lean mudstone and siltstone lithologies are found outboard of the Lower Cretaceous shelf margin. Producing reservoirs exhibit normal pressure gradients from 0.43 to 0.55 psi/ft (9.7 to 12.4 kpa/m), depths from 4000 to over 20,000 ft (1220 to 6100 m), and temperatures from 150 to 385°F (65 to 196°C). Wells are primarily vertical completions. The number of new field wildcats has been declining since the late 1990s. This paper presents comprehensive geologic models, which include lithofacies maps, structure and isopach maps, burial history models, regional seismic interpretations, and events charts that underpin the recently completed U.S. Geological Survey assessment of undiscovered, technically recoverable hydrocarbons within the Hosston and Travis Peak formations. This study also provides geographic and stratigraphic distributions of Hosston–Travis Peak reservoir properties, including geopressure, reservoir temperature, porosity, permeability, API gravity, and gas-oil ratios. Results indicate estimated undiscovered, technically recoverable mean resources of 28 million barrels of oil and 35.8 trillion cubic ft of gas in conventional and continuous accumulations within the Lower Cretaceous Hosston and Travis Peak formations of the onshore U.S. Gulf Coast region. Quantitative assessment results are detailed in U.S. Geological Survey Fact Sheet 2025–3021 and associated Data Release.

GCAGS Journal↗
USGS2024

Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources

As part of U.S. Geological Survey's (USGS) efforts to identify and assess geothermal energy resources of the US, a three-dimensional (3D) geologic and thermal model has been constructed for the Williston Basin, USA. The geologic model consists of all sedimentary units above the Proterozoic and Archean crystalline rock (called basement herein), with a total sedimentary thickness of up to 5 km near the basin center. Twenty-nine geologic units were mapped from interpreted formation tops from 16,465 wells. A 3D temperature model was constructed to a depth of 7 km by constructing a 3D heat flow model for the sedimentary units, followed by estimating underlying temperature using a one-dimensional (1D) analytic solution for heat flow within the underlying crystalline basement. Using the sedimentary basin model, heat flow was simulated in 3D and was calibrated using three temperature datasets: 1) 24 high-confidence static temperature logs (equilibrium thermal profiles), 2) more than15,000 drill stem test (DST) measurements from >7,000 wells, and 3) more than 45,000 bottomhole temperature (BHT) measurements from >14,000 wells. The DST and BHT datasets provide broad spatial coverage, but are lower confidence, primarily because measurements were made prior to attaining thermal equilibrium. DST and BHT measurements were binned regionally to develop representative thermal profiles that generally agree with these lower quality data (hereafter called pseudowell temperature profiles). Layer properties (primarily thermal conductivity and compaction curves) were set to best estimate values, then the heat flow model was calibrated to fit pseudowell and static temperature logs primarily by adjusting basal heat flow to approximate the overall temperature profile. Minor adjustments to thermal conductivity allowed adjusting changes in slope at lithologic contacts. Resulting maps include 3D temperature and basal (bottom of sedimentary units) heat flow estimates, which are used as input for the temperature model of the basement. The crystalline basement temperature model uses an analytic 1D solution to the heat flow equation that requires estimates of heat flow and temperature at the upper boundary (i.e., the sediment/basement contact), radiogenic heat production within the crystalline basement, and reference thermal conductivity (i.e., uncorrected for temperature). Two regions of high heat flow are identified: 1) in western North Dakota along the North American Central Plains Conductivity Anomaly and 2) in eastern Montana near the Poplar dome. Within the sedimentary column in the center of the basin of the basin, an area of approximately 100,000 km2 is predicted to have moderate- to high-temperature geothermal resources (>90 °C) under the thickest sequences of sediments. Where thick insulation and high heat flow coincide, electric-grade resources can be less than 4 km deep. Assuming a maximum feasible drilling depth of 7 km, temperatures are predicted to be as high as 175 °C. The geologic model may be used to identify strata at sufficient temperatures that may have natural permeability or that may have conditions that favor development of enhanced/engineered geothermal systems resources.

Montana, North Dakota, South Dakota↗
USGS2024

Development of a hydrogeologic visualization model for western Sarpy County, Nebraska

Population in western Sarpy County, Nebraska, has steadily increased over the last several decades and has led to increased groundwater use for domestic purposes. To meet the increase in demand, the Papio-Missouri River Natural Resources District is seeking to use all available sources of groundwater in western Sarpy County. Additionally, elevated groundwater nitrate plus nitrite as nitrogen concentrations were detected, indicating the need to better understand the groundwater quality of the area. Although the general geology of the area is understood, the area does not have detailed information on the extent of the various aquifers, particularly the Dakota aquifer. To characterize these aquifers, the Papio-Missouri River Natural Resources District invested in airborne electromagnetic surveys of the area to better understand the subsurface geology. Although these surveys improved understanding of the groundwater systems in the area, the Papio-Missouri River Natural Resources District wanted to integrate the subsurface information with available water-quality and groundwater-level data. In response, the U.S. Geological Survey, in cooperation with the Papio-Missouri River Natural Resources District, the Nebraska Natural Resources Commission, and the Nebraska Department of Natural Resources, assembled geologic, hydrogeologic and nitrate plus nitrite as nitrogen information for the selected area into a three-dimensional visualization computer software package called GeoScene3D. The completed GeoScene3D project was assembled to provide a visualization of the groundwater systems and associated water-quality results in Sarpy County and to provide the Papio-Missouri River Natural Resources District managers with information that can be used to make more informed groundwater resource-planning decisions in the future. This report details the development of a three-dimensional model created within GeoScene3D to visualize the subsurface, particularly the Dakota Sandstone in western Sarpy County.

Nebraska↗
USGS2024

Participatory engagement to reduce communication gaps

Underserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underserved coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. Here we outline our participatory engagement framework and process, along with two specific resources developed with the information collected from this effort. These resources are available in English and Spanish and consist of user-friendly, non-technical information products. Among them are: (1) a website where users can learn about USGS research on landslides, hurricanes, earthquakes, water resources, coastal hazards, tsunamis, and ecosystem hazards and environmental contaminants, and (2) a geonarrative highlighting shoreline changes in Puerto Rico with sections on historical shoreline trends, hurricane impacts, and potential solutions that could help protect communities and mitigate coastal hazards. Continuing participatory engagement in future projects could enhance the accessibility and usability of natural hazards resources within the community.

San Juan↗
USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗
USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗
USGS1983

Technique for estimating depth of floods in Tennessee

Estimates of flood depths are needed for design of roadways across flood plains and for other types of construction along streams. Equations for estimating flood depths in Tennessee were derived using data for 150 gaging stations. The equations are based on drainage basin size and can be used to estimate depths of the 10-year and 100-year floods for four hydrologic areas. A method also was developed for estimating depth of floods having recurrence intervals between 10 and 100 years. Standard errors range from 22 to 30 percent for the 10-year depth equations and from 23 to 30 percent for the 100-year depth equations.

Tennessee↗
USGS2000

Method for estimating water use and interbasin transfers of freshwater and wastewater in an urbanized basin

Techniques for management of drainage basins that use water budgets to balance available water resources with actual or anticipated water use require accurate and precise estimates of basin withdrawals, interbasin transfers of freshwater, unaccounted-for use, water use, consumptive use, inflow and infiltration, basin return flow, and interbasin transfers of wastewater. Frequently, interbasin transfers of freshwater and wastewater are not included in basin water budgets because they occur within public water-delivery and wastewater-collection systems. A new 10-step method was developed to improve estimates of inflow and infiltration and interbasin transfers using readily available statewide data. The accuracy and precision of water-use estimates determined by this method are improved through careful application of coefficients for small users and the use of metered values for large users. The method was developed and tested with data for the Ten Mile River Basin in southeastern Massachusetts. This report uses examples from the basin to illustrate each step of the method.

Massachusetts↗
USGS2025

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado↗