U.S. Geological Survey uranium and thorium research assessment and exploration research program
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The U.S. Geological Survey Uranium and Thorium Resource Assessment and Exploration Research Program began in July 1974 (FY 1975). The first year was spent chiefly in redirecting an on-going effort and in staffing for the nearly fourfold increase in funding. A summary of the Fiscal Year 1976 program, including objectives, program model, and project descriptions, is published as Open-File Report 75-575. The overall objectives and program model remain essentially the same as in FY 1976. It should be noted that the beginning of the fiscal year was changed from July 1 to October 1 during the 1976 calendar year and that a transitional quarter was used to make this change. Some program changes were made during the transitional quarter, but these details are not recorded in the present summary.
After expansion of the USGS (U.S. Geological Survey) uranium-thorium program in FY (fiscal year) 1975, new directions of research could be pursued, particularly in sedimentology or genetic stratigraphy, geochemistry-mineralogy, and geophysics. In a relatively short time, many of the new research projects have developed critical information on uranium habitats and improved methods of exploration. In FY 1979 a budget increase of approximately 20 percent is programmed, for a funding base of $6,600,000. The increase is scheduled for research grants and contracts outside the USGS in order to extend the basic program without additional personnel. This outside research will be designed not only to increase basic information on uranium occurrence but also to aid the USGS in its evaluation of uranium favorability in key resource areas for the NURE (National Uranium Resource Evaluation) program of DOE (U.S. Department of Energy).
In 1980, the U. S. Geological Survey (USGS) initiated a program to acquire high-quality, side-looking, airborne-radar (SLAR) imagery of selected areas of the United States. The program goals were to demonstrate the usefulness of SLAR imagery for geologic exploration and geoscience applications and to make radar data readily available to the public for additional research and economic applications. Considerable SLAR imagery has been acquired already since 1980 under a mandate from the U. S. Congress. The U. S. Geological Survey is actively engaged in demonstrating the usefulness of radar imagery, and since 1980 has started more than 50 studies addressing geologic, cartographic, and hydrologic applications. All of the radar-imagery products acquired by the USGS during 1980 and 1982 have been archived and are available for public sale.
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Research studies based on foreland basins (mainly in eastern Colorado) examined three surface geochemical exploration (SGE) methods as possible hydrocarbon (HC) exploration techniques. The first method, microbial soil surveying, has high potential as an exploration tool, especially hi development and enhanced recovery operations. Integrative adsorption, the second technique, is not effective as a quantitative SGE method because water, carbon dioxide, nitrous oxide, unsaturated hydrocarbons, and organic compounds are collected by the adsorbent (activated charcoal) much more strongly than covalently bonded microseeping Q-Cs thermogenic HCs. Qualitative comparisons (pattern recognition) of C8+ mass spectra cannot gauge HC gas microseepage that involves only the Q-Cs HCs. The third method, soil cakite surveying, also has no potential as an exploration tool. Soil calcite concentrations had patterns with pronounced areal contrasts, but these patterns had no geometric relationship to surface traces of established or potential production, that is, the patterns were random. Microscopic examination of thousands of soils revealed that soil calcite was an uncrystallized caliche coating soil particles. During its precipitation, caliche captures or occludes any gases, elements, or compounds in its immediate vicinity. Thus, increased signal intensity of some SGE methods should depend on increasing soil calcite concentrations. Analyses substantiate this hypothesis. Because soil calcite has no utility as a surface exploration tool, any surface method that depends on soil calcite has a diminished utility as an SGE tool. Isotopic analyses of soil calcites revealed carbonate carbon ??13C values of -4.0 to +2.07co (indicating a strong influence of atmospheric CO2) as opposed to expected values of-45 to -30%c if the carbonate carbon had originated from microbial oxidation of microseeping HC gases. These analyses confirm a surface origin for this soil calcite (caliche), which is not necessarily related to HC gas microseepage. This previously unappreciated pivotal role of caliche is hypothesized to contribute significantly to the poor and inconsistent results of some SGE methods.
New USGS research reveals that the discharge of metal-rich brine that formed sedex deposits on ancient seafloors had profound effects on global ocean chemistry and biologic evolution. For example, brine expulsion caused short-duration positive excursions (“spikes”) in the global marine Sr isotope record. While these spikes are unexplained by conventional oceanic models, our chronostratigraphic correlations of major sedex events, combined with mass balance evidence and oceanographic modeling, confirm that the flux of radiogenic Sr from sedex brines during ore formation was sufficient to cause these once enigmatic 87Sr/86Sr spikes. Recognition that the timing of peak 87 Sr/ 86 Sr spikes correlates exactly with global δ 13 C (and δ 18 O) spikes, climate change, deposition of metal-rich black shales and ironstones, metal-induced malformation (teratology) of marine organisms, and mass extinctions, establishes a causal relationship between sedex deposits and these dramatic events in earth history. The relationships among these features are not fully understood. However, our new model demonstrates that the flux of key biolimiting nutrients and metals contained in sedex brines exceeds that of the total modern riverine flux to the ocean. Undoubtably, these immense nutrient fluxes spurred ocean eutrophication, which, ultimately, through a series of positive feedback mechanisms, may be a previously unrecognized trigger of global ocean anoxic events (OAEs) that produced these chemical and biological perturbations. A derivative result from this integrative research is the recognition that OAEs resulted in the formation of “bathtub rim” deposits at redox boundaries along continental margins that concentrated various redox sensitive critical minerals. For example, we have identified midcontinent phosphorite deposits that contains heavy REE grades and tonnages that rival any REE deposit in the world. The recognition that sedex-forming fluid expulsion events are recorded in the global marine isotopic, geologic, and biological records, defines a new approach to the study of and exploration for sedex deposits. Traditional ore genesis research, coupled with chronostratigraphic correlation and high-resolution 87 Sr/ 86 Sr isotope chemostratigraphy can be used to answer long-standing questions about geologic processes responsible for formation of these extraordinary deposits. This approach allows us to constrain, for the first time, the age, duration, and fluxes of fluids and metals vented into the ocean by these giant hydrothermal systems. Accordingly, the fact that large mineralizing events are recorded in the marine sedimentary record opens the tantalizing prospect that we have the ability to conduct effective resource assessments and define prospective basins anywhere in the world. This innovative approach allows for identification of favorable stratigraphic ages and basins and remote evaluation of the size (and, thus, the mineral potential) of undiscovered mineral deposits. This methodology could be applied on regional basin-wide assessments, to evaluate sedimentary basin prospectivity, resource favorability of specific horizons therein, and to the evaluation of the potential of early-stage prospects.
Metamorphic belts are complex regions where accretion or collision has added to, or thickened, continental crust. Gold-rich deposits can be formed at all stages of orogen evolution, so that evolving metamorphic belts contain diverse gold deposit types that may be juxtaposed or overprint each other. This partly explains the high level of controversy on the origin of some deposit types, particularly those formed or overprinted/remobilized during the major compressional orogeny that shaped the final geometry of the hosting metamorphic belts. These include gold-dominated orogenic and intrusion-related deposits, but also particularly controversial gold deposits with atypical metal associations. There are a number of outstanding problems for all types of gold deposits in metamorphc belts. These include the following: (1) definitive classifications, (2) unequivocal recognition of fluid and metal sources, (3) understanding of fluid migration and focusing at all scales, (4) resolution of the precise role of granitoid magmatism, (5) precise gold-depositional mechanisms, particularly those producing high gold grades, and (6) understanding of the release of CO2-rich fluids from subducting slabs and subcreted oceanic crust and granitoid magmas at different crustal levels. Research needs to be better coordinated and more integrated, such that detailed fluid-inclusion, trace-element, and isotopic studies of both gold deposits and potential source rocks, using cutting-edge technology, are embedded in a firm geological framework at terrane to deposit scales. Ultimately, four-dimensional models need to be developed, involving high-quality, three-dimensional geological data combined with integrated chemical and fluid-flow modeling, to understand the total history of the hydrothermal systems involved. Such research, particularly that which can predict superior targets visible in data sets available to exploration companies before discovery, has obvious spin-offs for global- to deposit-scale targeting of deposits with superior size and grade in the covered terranes that will be the exploration focus of the twenty-first century.
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The US Geological Survey (USGS) instituted a program in 1980 to acquire side-looking airbore radar (SLAR) data and make these data readily available to the public in a mosaic format comparable to the USGS 1:250,000-scale topographic map series. The SLAR data are also available as strip images at an acquisition scale of 1:250,000 or 1:400,000 (depending on the acquisition system), as a variety of print products and indexes, and in a limited amount in digital form on computer compatible tapes. Three different commercial X-band (3-cm) systems were used to acquire the imagery for producing the mosaics.
Launched in August 2017, Deep Sea Exploration to Advance Research on Coral/Canyon/Cold seep Habitats (DEEP SEARCH) is a multiyear, multi-agency study to characterize the deep-sea ecosystems of the US Mid- and South Atlantic (Figure 1). The study is funded through an interagency partnership between NOAA, the Bureau of Ocean Energy Management (BOEM), and the US Geological Survey, and it is sponsored by the National Oceanographic Partnership Program. DEEP SEARCH will spend four and a half years (from 2017 to 2021) researching the habitats of the US Atlantic to better understand the distribution of sensitive seafloor communities to inform potential offshore energy development and other deep-sea management needs.
Despite historical linkages, the fields of geology and soil science have developed along largely divergent paths in the United States during much of the mid- to late- twentieth century. The shift in recent decades within both disciplines to greater emphasis on environmental quality issues and a systems approach has created new opportunities for collaboration and cross-training. Because of the importance of the soil as a dynamic interface between the hydrosphere, biosphere, atmosphere, and lithosphere, introductory and advanced soil science classes are now being taught in a number of earth and environmental science departments. The National Research Council's recent report, Basic Research Opportunities in Earth Science, highlights the soil zone as part of the land surface-to-groundwater "critical zone" requiring additional investigation. To better prepare geology undergraduates to deal with complex environmental problems, their training should include a fundamental understanding of the nature and properties of soils. Those undergraduate geology students with an interest in this area should be encouraged to view soil science as a viable earth science specialty area for graduate study. Summer internships such as those offered by the National Science Foundation-funded Integrative Graduate Education, Research, and Training (IGERT) programs offer geology undergraduates the opportunity to explore research and career opportunities in soil science.
Windows to the Deep 2018: Exploration of the Southeast US Continental Margin was a 36-day expedition aboard NOAA Ship Okeanos Explorer to acquire data on priority exploration areas identified by the ocean management and scientific communities. This expedition involved high-resolution multibeam sonar mapping and ROV dives, ranging from 340 m to 3,400 m depth, across the southeast US continental margin. Operations primarily targeted areas with potential to host deep-sea coral and sponge communities, including mounds, ridges, and terraced features on the continental slope. Dive sites also included maritime heritage sites, a submarine landslide feature, and several submarine canyon slopes, some of which exhibited evidence of active cold seeps. High biological abundance was noted at six of 17 dive sites, three of which also had high biological diversity. Additionally, deep-sea corals or sponges were observed on every dive except one, which was dedicated to gas seep exploration.
Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.
The U.S. Geological Survey (USGS) assesses potential for undiscovered, technically recoverable oil and gas resources in priority geologic provinces and quantifies resource volume estimates within subdivisions called assessment units (AUs). AU boundaries are defined by USGS geologists using quantitative and qualitative geologic information. Variables contained in IHS Markit’s well and production databases can quantify and/or function as proxies for many of the qualitative, boundary-defining variables. This research explores a new approach to determine AU boundaries and the potential to automate their definition, using data analytics and machine learning algorithms on key, qualitative variables within the IHS Markit databases. Well and production data from the U.S. onshore Gulf Coast region for the Upper Cretaceous Eagle Ford Group and Austin Chalk are used in this analysis because each is relatively geologically uniform in Texas and both have recently been assessed by the USGS. The Eagle Ford is an example of an in situ continuous oil and gas accumulation, and the overlying Austin Chalk is an example of a combined conventional and continuous resource, sourced from the underlying Eagle Ford. Wellspecific values were extracted or calculated from data in IHS Markit’s well and production databases for depth to top and base of the formations, formation thickness, bottom-hole temperature, temperature gradient, temperature at base of formation, cumulative oil and gas production values, barrels of oil equivalent, oil and gas gravities, mud weights from initial well test, depth pressure ratio, and excess pressure. A raster for each variable was interpolated using the natural neighbor technique from the spatial analyst toolbox in ArcGIS. Rasters were then transformed using minimum-maximum scaling, which rescales the distribution to the range of 0–1. Clustering was completed using the iso cluster unsupervised classification tool on the normalized rasters. Raster cell groupings from two to ten were explored, with initial results demonstrating that four to six classes return the most differentiable groups, with depth to formation, oil gravity, pressure, and temperature variables containing the greatest between-group differences. Modeled clusters have spatial similarities to the geologically defined AUs, with indication that temperature and pressure are the most fundamental to AU definition. Input from geologists will remain crucial for further dividing clusters and defining final AUs, since AUs are defined by both qualitative and quantitative information; however, this research documents promising cluster modeling results for the automation of initial AU definitions.