Historical hydrothermal estimates have largely relied on temperature or heat flow estimates ignoring the need for natural flowing fluids. More accurate hydrothermal estimates require some indication of permeability and fluids that naturally exist in the subsurface. This paper describes a novel approach that includes proxies of permeability and fluids in hydrothermal estimates by leveraging the relatively data-rich Great Basin. Specifically, nameplate capacities (megawatts) of operating geothermal plants, negative (0 megawatt) locations and 48 geophysical and geologic features are used to used in eXtreme Gradient Boosting (XGBoost) regression to make hydrothermal capacity predictions. Additionally, this work inputs the XGBoost-based hydrothermal predictions into the Renewable Energy Potential (reV) model to quantify technical capacity, its uncertainty and technoeconomics. Compared to historical hydrothermal estimates, these predictions adhere to the 37 operating geothermal plants and negative locations. We present a method for subsampling the negative sites to bring the labels into balance that uses the geologic domain knowledge to proportionally represent negatives. Overall, the distributions of the hydrothermal technical capacity and the site levelized cost of energy are respectively much tighter, lower and more accurate than the previous estimates for the Great Basin, as they include geological and geophysical surrogates for permeability and fluids. Percentile (50th and 90th, median and high estimate, respectively) models provide bookends for these metrics.

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favor -ability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. Finally, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future as-sessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

The Searchlight pluton (SLP) and coeval Highland Range volcanic sequence (HRV) have been suggested to represent intruded and erupted counterparts, and the 15 km tilted crustal section in which they are exposed has been presented as an illustration of the anatomy of a large, upper crustal, intermediate to silicic magmatic system. We summarize herein three decades of published and unpublished research on this system, emphasizing new work on its final silicic products that verifies direct connections between SLP and HRV and provides insights about storage, extraction, transport, and eruption processes in the waning stages of the system.Circumstantial evidence strongly suggests that volcanic and plutonic SLP-HRV products were directly linked for one million years (-17-16 Ma). For most of this period the system produced primarily intermediate rocks: dominantly quartz monzonite in the lower and upper SLP and trachyandesite-trachydacite lavas of the HRV (-58-70 wt% SiO2). Over the final-0.2 million years of the evolution of the system, silicic magma (70-78 wt% SiO2) constructed the youngest part of the pluton (middle SLP granite) and the coeval volcanic sequence (silicic HRV: rhyolite lavas and tuffs). Throughout the system's history, subordinate mafic magma accompanied the more silicic magmas.New results reveal that the youngest silicic rocks exposed in both the middle SLP and the silicic HRV are distinctive rhyolite porphyries (RP) that are essentially identical in texture, mineral assemblage, and elemental compositions. This lithology is phenocryst-rich (40-50%), with large quartz, alkali feldspar, plagioclase, as well as biotite, amphibole, titanite, apatite, Fe-Ti oxides, zircon, and chevkinite. RP dikes emanate from the middle SLP and crosscut the upper SLP and the pluton's roof (Proterozoic basement and lower HRV); small plugs intrude the upper part of the silicic HRV, and identical RP lava is part of a composite lava flow that is the last silicic material erupted in the HRV sequence. This terminal lava also includes basaltic trachyandesite and mechanical mixtures of basaltic trachyandesite and RP. In all environments in which it is exposed, RP is extensively mingled with mafic magma. RP is also very similar in composition, mineralogy, and texture (except for its aphanitic groundmass) to the coarse low-silica granite that dominates the middle SLP. The RP connection provides strong evidence for direct connection between SLP and HRV.A second highly plausible connection between SLP and HRV is strengthened by the RP correlation. Phenocryst-poor high-silica rhyolite (HSR) dikes in the upper SLP and roof that are cut by RP dikes are very similar in mineralogy, texture, and composition to HSR lavas and tuffs that dominate the silicic HRV. The HSR dikes emanate from leucogranite that forms the upper part of the middle SLP; though differing in texture, the fine-to medium-grained leucogranite is compositionally almost identical to the HSR dikes and volcanic rocks. Though more variable and less distinctive than RP, the similarities among the HSR rocks (dikes, lavas, tuffs) and the leucogranite also suggest a direct SLP-HRV connection.Rhyolite-MELTS phase-equilibria and amphibole geobarometers indicate that crystal-poor HSR was stored directly above the crystal-rich RP, consistent with RP derivation from lower middle SLP and HSR from upper -middle SLP. Trace-element modeling suggests that the HSR and leucogranite magmas were produced through-10-50% fractional crystallization of low-silica rhyolite/granite melt that fed the middle SLP. Together, these results suggest that the HSR and leucogranite represent the extracted melts derived from middle SLP mush. Texture and composition of RP indicates that it was derived almost en masse from the middle SLP; its ubiquitous association with mafic magma and thermometry within mingled materials indicate that final mobilization of SLP magma was a consequence of mafic recharge.The silicic portion of the SLP-HRV system documents important processes and distinctive products of magmatic systems that are active in the upper crust: (1) production of granitic mushes (cumulates) and extraction of fractionated melt; (2) resultant "filtering:" preferential eruption of the fractionated melt, retention of the cumulate (the HRV silicic section is mostly HSR, the middle SLP mostly low-silica granite [cumulate]); (3) bulk extraction of mush (RP) facilitated by hot mafic recharging; (4) eruption of both crystal-poor, highly -evolved magmas (HSR) and crystal-rich, less evolved magma similar to "monotonous intermediates" (RP).

First posted March 9, 2023 For additional information, contact: Contact Information,Geology, Minerals, Energy, & Geophysics Science Center Moffett FieldU.S. Geological Survey350 N. Akron Rd. P.O. Box 158 Moffett Field, CA 94035 This three-dimensional (3D) geologic map displays the subsurface geology in the upper ~4 kilometers of the Earth's crust in the southeastern Gabbs Valley geothermal area of west-central Nevada. The 3D map was constructed by integrating the results from detailed geologic mapping, 3D gravity inversion modeling, and potential-field-geophysical studies. This effort was undertaken as part of the Nevada Play Fairway Project, a regional effort to characterize new geothermal resources in the United States. Local data collection and analysis in southeastern Gabbs Valley, Nevada, including the construction of this 3D map, led to the drilling of six temperature gradient wells and identification of previously unknown hydrothermal fluids at 150 meters depth. The measured temperatures, which are as high as 124.9 degrees Celsius, indicate that the southeastern Gabbs Valley hydrothermal system has temperatures that are comparable to geothermal fields that have been developed for electricity generation in the region. We describe the geologic units and structures displayed by the map and discuss the methods used to integrate the geologic and geophysical information into the 3D geologic interpretation. The accompanying map provides horizontal and vertical section views and oblique perspective views from several angles. The digital data for elements of the map, the individual 3D fault surfaces, and stratigraphic surfaces are available from Siler (2022). The accompanying map sheet and video displaying the 3D map are available at https://doi.org/10.3133/sim3498.

Laramide northeast-flowing streams from the ancestral Mogollon highland beveled gently northeast-dipping Late Proterozoic to Cretaceous strata across the southern Colorado Plateau Transition Zone. Late Eocene renewed uplift rejuvenated northeast-flowing streams incising paleocanyons. Apache paleocanyon was incised into the Mogollon highland, including the north-trending Laramide Apache uplift bounded by major reverse faults/monoclines. The Mogollon Rim sequence aggraded in Apache paleocanyon and on a broad alluvial plain to the east. Middle Cenozoic tectonic subsidence of the Transition Zone, aridification, and volcanism combined to aggrade Apache paleocanyon with sedimentary and volcanic rocks from 37.6 to 18.63 Ma. Emplacement of the Mogollon-Datil caldera complex and Chuska erg on the southeastern Colorado Plateau forced streamflow to northwest-dispersal of fluvio-eolian sediment from 34 to 26 Ma. Following erosion by northwest-flowing streams on the southern Colorado Plateau from ~26 to 16 Ma, lake sediments of the lower Bidahochi Fm were deposited. Southwestward reactivation of Laramide faults was underway by ~25 Ma coeval with extensive 25 to 20 Ma Natanes Plateau basalt flows and extreme crustal thinning southwest of the Transition Zone. As northeastward streamflow gradually diminished, a Superstition field ash flow tuff ended northeastward flow at 18.63 Ma and was followed by a period of sluggish southwest stream flow and ponding until after ~14.84 Ma. Southwestward structural subsidence and possible spillover from ancestral Lake Hopi on the Colorado Plateau southern margin caused incision of the southwest-directed Dagger Canyon paleovalley after 14.84, which followed the path of the earlier Apache paleocanyon and possibly to the Sespe delta on the California coast before opening of Gulf of California. Structural collapse of the Tonto Basin to the west induced deposition of the Dagger Canyon Conglomerate in the Dagger Canyon paleovalley before the modern Salt River incised all previous deposits and became integrated with the Gila River during the Plio-Pleistocene.

We consider the application of machine learning to the evaluation of geothermal resource potential. A supervised learning problem is defined where maps of 10 geological and geophysical features within the state of Nevada, USA are used to define geothermal potential across a broad region. We have available a relatively small set of positive training sites (known resources or active power plants) and negative training sites (known drill sites with unsuitable geothermal conditions) and use these to constrain and optimize artificial neural networks for this classification task. The main objective is to predict the geothermal resource potential at unknown sites within a large geographic area where the defining features are known. These predictions could be used to target promising areas for further detailed investigations. We describe the evolution of our work from defining a specific neural network architecture to training and optimization trials. Upon analysis we expose the inevitable problems of model variability and resulting prediction uncertainty. Finally, to address these problems we apply the concept of Bayesian neural networks, a heuristic approach to regularization in network training, and make use of the practical interpretation of the formal uncertainty measures they provide.

tasks necessary to demonstrate the viability of the Fallon FORGE Project site were completed and the commitment and capability of the Fallon FORGE team to execute FORGE was demonstrated. As part of Phase 1, the Fallon FORGE Team provided an assessment of available relevant data and integrated these geologic and geophysical data to develop a conceptual 3-D geologic model of the proposed test location. Additionally, the team prepared relevant operational plans for full FORGE implementation, provided relevant site data to the science and engineering community, engaged in outreach and communications with interested stakeholders, and performed a review of the environmental and permitting activities needed to allow FORGE to progress through Phase 3. The results of these activities are provided as Appendices to this report. The Fallon FORGE Team is diverse, with deep roots in geothermal science and engineering. The institutions and key personnel that comprise the Fallon FORGE Team provide a breadth of geoscience and geoengineering capabilities, a strong and productive history in geothermal research and applications, and the capability and experience to manage projects with the complexity anticipated for FORGE. Fallon FORGE Team members include the U.S. Navy, Ormat Nevada Inc., Sandia National Laboratories (SNL), Lawrence Berkeley National Laboratory (LBNL), the United States Geological Survey (USGS), the University of Nevada, Reno (UNR), GeothermEx/Schlumberger (GeothelinEx), and Itasca Consulting Group (Itasca). The site owners (through direct land ownership or via applicable permits)—the U.S. Navy and Ormat Nevada Inc.—are deeply committed to expanding the development of geothermal resources and are fully supportive of FORGE operations taking place on their lands.

First posted March 30, 2021 For additional information, contact: National Cooperative Geologic Mapping ProgramU.S. Geological Survey12201 Sunrise Valley DriveReston, VA 20192Contact Pubs Warehouse This document presents the renewed vision, mission, and goals for the National Cooperative Geologic Mapping Program (NCGMP). The NCGMP, as authorized by the National Cooperative Geologic Mapping Act of 1992 (Public Law 102-285, 106 Stat. 166 and its reauthorizations), is tasked with expediting the production of a geologic database for the Nation based on modern geologic maps and their supporting data. In addition to highlighting the benefits of geologic maps for economic prosperity, national security, and environmental quality, the report describes the NCGMP structure and components. A renewed vision and mission for the NCGMP are stated, and three goals for guiding the program toward that vision for the next ten years are established. The vision of creating an integrated, three-dimensional, digital geologic map of the United States and its territories to address the changing needs of the Nation by 2030 is thereby defined to drive the activities of all NCGMP components for the next ten years. The strategic actions required to realize the NCGMP vision are identified for each of its components.

Threats posed by the climate crisis have created an urgent need for sustainable green energy. Geothermal resources have the potential to provide up to 150 GWe of sustainable energy by 2050. However, the key challenge in successfully locating and drilling geothermal wells is to understand how the heterogeneous structure of the subsurface controls the existence of exploitable fluid reservoirs. In this Review, we discuss how key geological factors contribute to the profitable utilization of intermediate-temperature to high-temperature geothermal resources for power generation. The main driver of geothermal activity is elevated crustal heat flow, which is focused in regions of active magmatism and/or crustal thinning. Permeable structures such as faults exercise a primary control on local fluid flow patterns, with most upflow zones residing in complex fault interaction zones. Major risks in geothermal resource assessment and operation include locating sufficient permeability for fluid extraction, in addition to declining reservoir pressure and the potential of induced seismicity. Advanced computational methods permit effective integration of multiple datasets and, thus, can reduce potential risks. Future innovations involve engineered geothermal systems as well as supercritical and offshore geothermal resources, which could greatly expand the global application of geothermal energy but require detailed knowledge of the respective geological conditions. Successful discovery and operation of geothermal resources requires a thorough understanding of the heterogeneous geological subsurface. This Review discusses the key geological factors that contribute to the effective exploration of intermediate-temperature to high-temperature geothermal resources used for power generation and direct use applications.

Play fairway analysis (PFA) is a statistically based data integration and exploration tool originating in the oil and gas industry that has recently been applied to geothermal exploration. Here, we apply geothermal PFA to a similar to 40,000 km(2) area in the Argentine Puna of the South American Andes (average elevation >4,000 m aMSL) that has geothermal potential but no geothermal resource development to date. We develop a PF workflow customized to the local geological setting and availability of regional geoscience datasets. Evidence layers were grouped to model the spatial distribution of three primary geological attributes of a geothermal system: heat, permeability, and fluid. These layers included hot springs, geothermometry, age and distribution of volcanism, hydrothermal alteration, regional faults along with their kinematics and approximate age of most recent rupture, structural settings, and earthquakes. Spatial statistical methods were used to model and weight the distribution of these evidence layers, including distance buffers, point statistics, and weighted sum functions. Resulting favorability models were created using the veto (product) and voter (sum) methods, and both models indicate highest geothermal potential in Cerro Tuzgle/Aguas Calientes/Tocomar and west Coranzuli. Additional locations in the Puna study area may be prospective but are not resolved given the current data availability. Thus, further data collection to reduce the geological uncertainty is recommended, including acquisition of relatively low-cost datasets such as spring temperatures, fluid chemistry, detailed geological mapping, and structural characterization.

Most geothermal resources in the Great Basin region of the western USA are blind, and thus the discovery of new commercial-grade systems requires synthesis of favorable characteristics for geothermal activity. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity to identify promising areas for new development. This project integrated multiple datasets to apply the play fairway concept and assess geothermal potential in a large region of the Great Basin in Nevada. It is therefore referred to as the Nevada play fairway project. This project was a strong collaborative effort between several organizations, led by the Nevada Bureau of Mines and Geology at the University of Nevada, Reno, but with key support from the U.S. Geological Survey, ATLAS Geosciences, Inc,, Hi-Q Geophysical, Inc., Lawrence Berkeley National Laboratory, Utah Geological Survey, and Innovative Geothermal Ltd. In Budget Period 1 of this project, available data for nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new detailed geothermal potential map of 96,000 km2 from west-central to eastern Nevada. These parameters were grouped into subsets and individually weighted to delineate rankings for local permeability, intermediate permeability, regional permeability, and thermal potential, which collectively defined geothermal play fairways (i.e., most likely locations for significant geothermal fluid flow). This initial work was aimed at reducing the risks in regional exploration and therefore facilitating discovery of new commercial-grade systems in blind settings, as well as in areas with surface expressions of geothermal activity. Budget Period 2 of the project involved detailed analysis of some of the most promising areas identified in Phase 1. Twenty-four highly prospective areas, including both known undeveloped systems and previously undiscovered potential blind systems, were identified for further analysis. After reconnaissance of these areas, five of the most promising sites were selected for detailed studies. Multiple techniques were employed in the detailed studies, including geologic mapping, shallow temperature surveys, gravity surveys, Lidar, geochemical studies, seismic reflection analysis, and 3D modeling. The goal of the detailed studies was to identify specific areas with the highest likelihood for high permeability and thermal fluids, such that drill sites could be targeted. Three main sets of predictive maps were generated for each detailed study area: 1) play fairway maps, 2) play fairway error maps, and 3) direct evidence maps. Local- and intermediate-scale permeability models were revised to reflect results of the detailed geologic, geophysical, and geochemical analyses. Budget Period 3 of the project involved more detailed geophysical analyses and temperature-gradient (TG) drilling in southeastern Gabbs Valley and northern Granite Springs Valley, deemed the two most promising sites, with the goal of providing preliminary validation of the play fairway methodology. In southeastern Gabbs Valley, the collocation of a favorable structural setting (displacement transfer zone and fault intersections), Quaternary faults, intersecting and terminating gravity gradients, magnetic low, shallow (2 m) temperature anomaly, low resistivity anomaly, and promising geothermometry from nearby water wells provided evidence for a blind system. Drilling of six TG holes defines an apparent geothermal system at this locality with temperatures as high as 124°C at 152 m. This system is blind, with no surface hot springs, fumaroles, or paleo-geothermal deposits. For northern Granite Springs Valley, a favorable structural setting (termination of a major Quaternary normal fault), terminating gravity gradient, magnetic gradient, newly discovered sinter deposits, nearby warm water wells, previously drilled TG holes in the vicinity, and promising geothermometry suggest a hidden system. Drilling of six new TG holes yields temperatures of ~96°C at ~250 m, suggesting the presence of a geothermal system. Major lessons learned in the course of this project include: 1) initially identified sites commonly include multiple favorable structural settings at a finer scale; 2) promising sites in Cenozoic basins cannot be recognized without detailed geophysical surveys; and 3) play fairway analysis should be refined as the exploration program vectors into the most promising sites and finer-scale data are acquired. In addition to producing copious amounts of data, this project resulted in 16 published papers, 10 abstracts, more than 40 presentations across the U.S. and abroad (including several keynote addresses), 2 Masters theses, and 7 media reports.