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At least 361 records · Page 20

AmeriFlux FLUXNET-1F US-Cop Corral Pocket

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Cop Corral Pocket. This is the FLUXNET version of the carbon flux data for the site US-Cop Corral Pocket produced by applying the standard ONEFlux (1F) software. Site Description - The Corral Pocket site is located in a semi-arid grassland in southeastern Utah, just east of Canyonlands National park. For the greater part of the year, 38-80% of the ground is essentially bare. Vegetation is primarily native perennial C3/C4 grasses with annual ground converge ranging from 8-35%. Leaving the remaining 0-15% coverage to interspersed annual grasses, the remaining 0-15% coverage is occupied by annual grasses. 6-8 weeks during the late fall or winter, Livestock grazing is responsible for the majority of aboveground vegetation loss and subsequent high variability of ground coverage.

Bowling, David↗

AmeriFlux US-UTN UFLUX Nephi

This is the AmeriFlux version of the carbon flux data for the site US-UTN UFLUX Nephi. Site Description - This tower is located in between 3 agricultural pivots in a rural valley of Utah. It is within 100 meters of SCAN station 2137. Crops include soybeans, corn, and wheat. The tower was installed for a temporary project.

Inkenbrandt, Paul↗

Testing and Design of Discriminants for Local Seismic Events Recorded during the Redmond Salt Mine Monitoring Experiment

The Redmond Salt Mine (RSM) Monitoring Experiment in Utah was designed to record seismoacoustic data at distances less than 50 km for algorithm testing and development. During the experiment from October 2017 to July 2019, six broadband seismic stations were operating at a time, with three of them having fixed locations for the duration, whereas the three other stations were moved to different locations every one-and-half to two-and-half months. RSM operations consist of nighttime underground blasting several times per week. The RSM is located in proximity to a belt of active seismicity, allowing direct comparison of natural and anthropogenic sources. Using the recorded data set, we built 1373 events with local magnitude (M L ) of -2.4 and lower to 3.3. For 75 blasts (RMEs) from the Redmond Salt Mine and 206 tectonic earthquakes (EQs), both M L and the coda duration magnitude (MC) are well constrained. We used these events to test and design discriminants that separate the RMEs from the EQs and are effective at local distances. The discriminants consist of M L -M C , low-frequency Sg to high-frequency Sg, Pg/Sg phase-amplitude ratios, and Rg/Sg spectral amplitude ratios, as well as different combinations of two or more of these classifiers. The areas under the receiver operating characteristic curves (AUCs) of 0.92–1.0 for M L -M C , low-frequency Sg to high-frequency Sg, and Rg/Sg indicate that these discriminants are very effective. Conversely, the AUC of only 0.57 for Pg/Sg suggests that this discriminant is only slightly better than a random classifier. Among the effective classifiers, Rg/Sg, shows the lowest likelihood of misclassification (4.3%) for the populations. In conclusion, results of joint discriminant analyses suggest that even the arguably ineffective single classifier, like Pg/Sg in this case, can provide some value when used in combination with others.

58 GEOSCIENCES↗

Wasatch Fault Structure from Machine Learning Arrival Times and High-Precision Earthquake Locations

Abstract On 18 March 2020, a magnitude 5.7 earthquake hit the Salt Lake valley in the state of Utah, United States. Using a dense geophone deployment and machine learning (ML), an additional several thousand events were detected and located. Currently, both the mainshock and the majority of the aftershocks are suspected to have occurred on or near a deeper portion of the Salt Lake segment of the Wasatch fault—part of a large range-bounding fault system thought to be capable of generating an Mw 7.2 earthquake. However, a small subset of aftershocks may have occurred on a portion of the more steeply, eastward dipping, and poorly understood West Valley fault. Unfortunately, the catalog locations and lack of focal mechanisms for this subset of aftershocks provide only a crude constraint on the true fault structure. To better illuminate fault structure, we relocate the ML-generated catalog with a range of magnitudes from −2 to 4.6, using: (1) NonLinLoc, a nonlinear location algorithm, (2) source-specific station terms, and (3) waveform coherence. We further compute first-motion focal mechanisms for 68 events. Results of the relocation suggest a simpler, minimally listric Wasatch fault geometry, contrary to what has been previously proposed. We also find that analysis of the focal mechanisms and waveform similarity indicates minimal event similarity throughout the Magna sequence, suggesting a highly complex and heterogeneous rupture zone, as opposed to rupture on a single plane. These findings suggest an increased seismic hazard due to the overall shallowness of the earthquake sequence and highly varied rupture mechanisms.

Geochemistry & Geophysics↗

Along-Trajectory Acoustic Signal Variations Observed During the Hypersonic Re-Entry of the OSIRIS-REx Sample Return Capsule

The re-entry of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) sample return capsule (SRC) on 24 September 2023 presented a rare opportunity to study atmospheric entry dynamics through a dense network of ground-based infrasound sensors. As the first interplanetary capsule to re-enter over the United States since Stardust in 2006, this event allowed for unprecedented observations of infrasound signals generated during hypersonic descent. We deployed 39 single-sensor stations across Nevada and Utah, strategically distributed to capture signals from distinct trajectory points. Infrasound data were analyzed to examine how signal amplitude and period vary with altitude and propagation path for a nonablating hypersonic object with well-defined physical and aerodynamic properties. Raytracing simulations incorporated atmospheric specifications from the ground-2-space model to estimate source altitudes for observed signals. Results confirmed ballistic arrivals at all stations, with source altitudes ranging from 44 to 62 km along the trajectory. Signal period and amplitude exhibited strong dependence on source altitude, with higher altitudes corresponding to lower amplitudes, longer periods, and reduced high-frequency content. Regression analysis demonstrated strong correlations between signal characteristics and both altitude and propagation geometry. Our results suggest, when attenuation is considered, the amplitude is primarily determined by the source, with the propagation path playing a secondary role over the distances examined. These findings emphasize the utility of controlled SRC re-entries for advancing our understanding of natural meteoroid dynamics, refining atmospheric entry models, and improving methodologies for planetary defense. The OSIRIS-REx SRC campaign represents the most comprehensive infrasound study of a hypersonic re-entry to date, showcasing the potential of coordinated geophysical observational networks for high-energy atmospheric phenomena, including space debris re-entries.

58 GEOSCIENCES↗

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗

SMART CarbonSAFE Model

The modeling work for this project built upon previous work done for the CarbonSAFE Rocky Mountain Phase I. A geologic and dynamic model was built in Petrel version 2019.3 for the area of the Colorado Plateau near Price, Utah. It is located at the north end of the San Rafael Swell in a natural gas field called Drunkards Wash. The model is 61.5 km east-west and 53 km north to south with 123x106x21 cells, giving a cell dimension of 50x50 m2. The 21 layers in the Z direction are of varying thickness depending on the formation. The Carmel, the seal layer, has 3 layers and is about 200 meters thick around the injection well. The Navajo Sandstone, the principal reservoir, has 5 layers and is about 100 meters thick. The Kayenta has 5 layers and is roughly 50 meters thick and the Wingate, a secondary reservoir, has 5 layers and is 120 meters thick. The base of the model is the Chinle Formation with 3 layers and about 120 meters of thickness..

Carbon Dioxide↗

Discrete Measurements of the Least Horizontal Principal Stress from Core Data: An Application of Viscoelastic Stress Relaxation

Summary The emerging Paradox Oil Play in southeastern Utah is among the most significant unconventional plays in the western USA. The mean total undiscovered oil resources within just the Pennsylvanian Cane Creek interval of the Paradox Basin are believed to exceed 215 million barrels. However, to date, less than 5% (~9 million barrels) of the total Cane Creek resource has been produced from fewer than 40 wells, and only approximately one-half of those are horizontal wells. More than 95% of production is from the central Cane Creek Unit (CCU). Natural fractures are a key feature of many production wells, but stimulation by induced hydraulic fractures is not consistently successful. We hypothesize that more effective production in this play will rely on better fundamental characterization, especially on better quantification of the state of stress. Approximately 110 ft of core, well logs, and a diagnostic fracture injection test (DFIT) were acquired from the State 16-2 well within the CCU. With these data, we applied two methods to constrain and clarify the state of stress. The first technique, the Simpson’s coefficient method, provides lower bounds on the two horizontal principal stresses and relies on only limited data. Alternatively, the viscoelastic stress relaxation (VSR) method is used to estimate the least horizontal principal stress, building on observations that principal stresses become more isotropic as the viscous behavior of a rock is more pronounced. Results of these two methods support the hypothesis that the state of stress in the CCU of the Paradox Basin is nearly lithostatic and isotropic. Other factors consistent with this hypothesis include high formation pore pressure, which tends to reduce the possible stress states by changing the frictional failure equilibrium; lack of induced fractures in the core, which should be present in the case of stress anisotropy; and interbedded halite layers, which given their high degree of ductility, probably lead to greater VSR for the entire sedimentary package.

Energy & Fuels↗

Seaborgite, LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), the First Uranyl Mineral Containing Lithium

Abstract Seaborgite (IMA2019-087), LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), is a new mineral species from the Blue Lizard mine, Red Canyon, San Juan County, Utah, U.S.A. It is a secondary phase found on gypsum in association with copiapite, ferrinatrite, ivsite, metavoltine, and römerite. Seaborgite occurs in sprays of light-yellow, long flattened prisms or blades, up to about 0.2 mm in length. Crystals are elongated on [100], flattened on {010}, and exhibit the forms {100}, {010}, {001}, and {101}. The mineral is transparent with vitreous luster and very pale-yellow streak. It exhibits bright lime-green fluorescence under a 405 nm laser. The Mohs hardness is ~2½. The mineral has brittle tenacity, curved or conchoidal fracture, and one good cleavage on {100}. The measured density is 2.97(2) g/cm3. The mineral is immediately soluble in H2O at room temperature. The mineral is optically biaxial (–), α = 1.505(2), β = 1.522(2), γ = 1.536(2) (white light); 2Vmeas = 85(1)°; moderate r < ν dispersion; orientation X ^ a ≈ 10°; pleochroic X colorless, Y and Z light green-yellow; X < Y ≈ Z. EPMA and LA-ICP-MS analyses of seaborgite undermeasured its Li, K, and Na. The empirical formula using Li, Na, and K based on the structure refinement is Li1.00Na5.81K2.19(UO2)(SO4)5(SO3OH)(H2O). Seaborgite is triclinic, P1, a = 5.4511(4), b = 14.4870(12), c = 15.8735(15) Å, α = 76.295(5), β = 81.439(6), γ = 85.511(6)°, V = 1203.07(18) Å3, and Z = 2. The structure (R1 = 0.0377 for 1935 I = 2σI) contains [(UO2)2(SO4)8]4– uranyl-sulfate clusters that are linked into a band by bridging LiO4 tetrahedra. The bands are linked through peripheral SO4 tetrahedra forming a thick heteropolyhedral layer. Channels within the layers contain a K site, while an additional K site, six Na sites, and an SO3OH group occupy the space between the heteropolyhedral layers.

Geochemistry & Geophysics↗

Finchite, Sr(UO 2 ) 2 (V 2 O 8 )·5H 2 O, a new uranyl sorovanadate with the francevillite anion topology

Finchite (IMA2017-052), Sr(UO 2 ) 2 (V 2 O 8 )·5H 2 O, is the first uranium mineral known to contain essential Sr. The new mineral occurs as yellow-green blades up to ~10 µm in length in surface outcrops of the calcrete-type uranium deposit at Sulfur Springs Draw, Martin County, Texas, U.S.A. Crystals of finchite were subsequently discovered underground in the Pandora mine, La Sal, San Juan County, Utah, U.S.A., as diamond-shaped golden-yellow crystals reaching up to 1 mm. In this work, the crystal structure of finchite from both localities was determined using single-crystal X-ray diffraction and is orthorhombic, Pcan, with a = 10.363(6) Å, b = 8.498(5) Å, c = 16.250(9) Å, V = 1431.0(13) Å 3 , Z = 4 (R 1 = 0.0555) from Sulfur Springs Draw; and a = 10.3898(16), b = 8.5326(14), c = 16.3765(3) Å, V = 1451.8(4) Å 3 , Z = 4 (R 1 = 0.0600) from the Pandora mine. Electron-probe microanalysis provided the empirical formula (Sr 0.88 K 0.17 Ca 0.10 Mg 0.07 Al 0.03 Fe 0.02 ) Σ1.20 (UO 2 ) 2 (V 2.08 O 8 )·5H 2 O for crystals from Sulfur Springs Draw, and (Sr 0.50 Ca 0.28 Ba 0.22 K 0.05 ) Σ0.94 (U 0.99 O 2 ) 2 (V 2.01 O 8 )·5H 2 O for crystals from the Pandora mine, based on 17 O atoms per formula unit. The structure of finchite contains uranyl vanadate sheets based upon the francevillite topology. Finchite is a possible immobilization species for both uranium and the dangerous radionuclide 90 Sr because of the relative insolubility of uranyl vanadate minerals in water.

58 GEOSCIENCES↗

Gas-mediated trace element incorporation into rhyolite-hosted topaz: A synchrotron microbeam XAS study

Magmatic gas exsolving during late-stage cooling of shallow magmas has been considered an important facilitator of low-pressure alteration and metal transport. However, the chemical properties of such gas, particularly its metal transport mechanisms and capacity, remain elusive. Trace elements in minerals produced by gas-mediated surface reaction or precipitation from gas capture details of gas composition and reaction pathways. However, interpretation of mineral trace element contents is dependent on understanding crystallographic controls on gas/mineral partitioning. Here, this work investigates the structural accommodation of As, Mn, Ga, Ge, Fe, and Ti in vapor-deposited topaz of vesicular topaz rhyolite from the Thomas Range, Utah, through single-crystal synchrotron microbeam X-ray techniques on picogram quantities of those trace elements. X-ray absorption near edge structure (XANES) data indicates that these elements are incorporated into topaz as As 5+ , Fe 3+ , Mn 3+ , Ti 4+ , Ga 3+ , and Ge 4+ . Extended X-ray absorption fine structure (EXAFS) analysis for these trace elements, compared to EXAFS of structural Al and Si, reveals that As 5+ and Ge 4+ are incorporated directly into the tetrahedral site of the topaz structure, with the octahedral site accommodating Mn 3+ , Fe 3+ , Ga 3+ , and Ti 4+ . For As 5+ and Fe 3+ , the structural impact of substitution extends to at least second neighbors (other elements were only resolvable to first neighbors). Further interpretation of the EXAFS results suggests that the substitution of Ti 4+ results in increased distortion of the octahedral site, while the other trace elements induce more uniform expansion correlating in magnitude to their ionic radius. Comparison of quantified X-ray fluorescence (XRF) data for two topaz crystals from this rhyolite reveals variable trace element concentrations for As 5+ , Fe 3+ , Ga 3+ , and Ti 4+ , reflective of a source gas undersaturated in these trace elements changing in concentration over the period of topaz deposition. The identical Ge 4+ content of the two topaz crystals suggests that Ge 4+ in the gas was buffered by the growth of another Ge 4+ -bearing phase, such as quartz. The very low Mn 3+ content in the topaz crystals does not reflect the abundance of Mn 3+ in the gas (saturation of Mn is evidenced by coexisting bixbyite). Instead, it suggests a strong Jahn-Teller inhibitory effect to the substitution of Mn 3+ for Al 3+ in the distorted octahedral site of topaz. It is proposed that exsolution of an HF-enriched gas from cooling rhyolitic magma led to local scouring of Al, Si, and trace metals from the magma. Once topaz crystals nucleated, self-catalyzed reactions that recycle HF led to continued growth of topaz.

36 MATERIALS SCIENCE↗

Data-driven modeling of municipal water system responses to hydroclimate extremes

Sustainable western US municipal water system (MWS) management depends on quantifying the impacts of supply and demand dynamics on system infrastructure reliability and vulnerability. Systems modeling can replicate the interactions but extensive parameterization, high complexity, and long development cycles present barriers to widespread adoption. To address these challenges, we develop the Machine Learning Water Systems Model (ML-WSM) – a novel application of data-driven modeling for MWS management. We apply the ML-WSM framework to the Salt Lake City, Utah water system, where we benchmark prediction performance on the seasonal response of reservoir levels, groundwater withdrawal, and imported water requests to climate anomalies at a daily resolution against an existing systems model. The ML-WSM accurately predicts the seasonal dynamics of all components; especially during supply-limiting conditions (KGE > 0.88, PBias < ±3%). Extreme wet conditions challenged model skill but the ML-WSM communicated the appropriate seasonal trends and relationships to component thresholds (e.g., reservoir dead pool). The model correctly classified nearly all instances of vulnerability (83%) and peak severity (100%), encouraging its use as a guidance tool that complements systems models for evaluating the influences of climate on MWS performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Factorial experiment to identify two-way interactions between temperature, harvesting period, hydraulic retention time, and light intensity that influence the biomass productivity and phosphorus removal efficiency of a microalgae–bacteria biofilm

Rotating algae biofilm reactors (RABRs) can reduce energy requirements for wastewater reclamation but require further optimization for implementation at water resource recovery facilities (WRRF). Optimizing RABR operation is challenging because conditions at WRRF change frequently, and disregarding interaction terms related to these changes can produce incorrect conclusions about RABR behavior. This study evaluated the two-way interaction and main effects of four factors on the biomass productivity and phosphorus removal efficiency of a microalgae-bacteria biofilm grown in municipal anaerobic digester centrate, with factor levels and operating conditions selected to mimic a pilot RABR at a WRRF in Utah. Two-way interactions harvesting period*light intensity (LI), harvesting period*temperature, and LI*hydraulic retention time (HRT) had significant effects on biomass productivity: at high temperature and low LI, highest biomass productivity was achieved with a 14-day harvesting period, but at medium temperature and high LI, highest biomass productivity was achieved with a 7-day harvesting period. At high HRT, highest biomass productivity occurred at low LI, but at low HRT, highest biomass productivity occurred at high LI. Phosphorus removal was strongly influenced by LI and occurred most rapidly during the first 2 days HRT, which suggests precipitation contributed significantly to phosphorus removal. These observations provide insight for further RABR optimization.

09 BIOMASS FUELS↗

GATE Center of Excellence in Innovative Drivetrains in Electric Automotive Technology Education (IDEATE) (Final Report)

The IDEATE project recognized that this is a critical point in history where advanced engineering solutions are required to propel the U.S. automotive industry irrevocably to the next level: the electrified drivetrain. The existing workforce is not sufficient to this task. It is imperative that automotive engineers with traditional backgrounds focused on internal-combustion and mechanical-drivetrain technologies be retrained with the most current advanced solutions in battery controls and vehicle power electronics. For the long-term success of the U.S. automakers, it is even more important that a future workforce be developed that has both broad and deep comprehension of the issues involved and the most advanced solutions known to these problems. Two campuses of the University of Colorado system joined forces to establish the GATE Center of Excellence in Innovative Drivetrains in Electric Automotive Technology Education (IDEATE). The University of Colorado Boulder (CU-Boulder) is widely regarded as having one of the top graduate programs in power electronics in the country; the University of Colorado Colorado Springs (UCCS) has unrivaled expertise in algorithms for automotive battery control. By collaborating, IDEATE built on our team’s proven strengths to develop innovative curricula and to initiate courses and programs that have provided (and continue to provide) students with a unique opportunity for holistic and specialty education in electric drivetrain technology (part-way through the project, we invited Utah State University to join the project, adding to our strength in power electronics for battery application).

42 ENGINEERING↗

Cost of saving natural gas through efficiency programs funded by utility customers: 2012–2017

This study estimates the cost of saving a therm of natural gas from energy efficiency programs funded by utility customers during the period 2012 to 2017. Berkeley Lab researchers compiled and analyzed efficiency program data reported by investor-owned utilities and other program administrators in a dozen states representative of the four U.S. Census regions — Arkansas, California, Connecticut, Iowa, Massachusetts, Michigan, Minnesota, New Jersey, New York, Oklahoma, Rhode Island and Utah. Depending on the year, the dataset accounts for about 50 percent to 70 percent of annual national spending on natural gas efficiency programs. The estimated cost of saving natural gas during the study period is $0.40 per therm. The analysis also includes estimates of the program administrator cost of saved energy for three core sectors for natural gas: commercial and industrial, residential, and low-income households. It aggregates these sectors to provide regional and national values. Our metrics include savings-weighted averages, unweighted medians, and interquartile ranges (25th and 75th percentiles) of the levelized program administrator cost of saving gas, in constant 2017 dollars. In addition, the study analyzes cost trends during the study period, finding that average program costs trended downward. The U.S. Department of Energy’s Building Technologies Office supported this work.

03 NATURAL GAS↗

A look back 75 years at Little Boy, the crew, the plane and the Lab’s first mission

Hours before the sun would rise over Tinian island on the morning of August 6, 1945, a B- 29 airplane was positioned above a specially built bomb-loading pit, as crews readied it with cargo unlike anything the world had ever known. Preparations on the tiny Pacific island—nearly 6,600 miles from Los Alamos and about 1,500 miles from its intended target in Japan—had begun months before on April 3. And months before that, pilot Paul Tibbets Jr. and his crew had practiced dropping dummy concrete bombs on targets in Utah. Even years before that, development of this cargo destined for Japan began in secrecy under the direction of a physicist and an Army general in the mountains of Northern New Mexico. It was all leading to one day that would help end years of bloodshed and change the world forever.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

A Multi-Instance learning Framework for Seismic Detectors

In this report, we construct and test a framework for fusing the predictions of a ensemble of seismic wave detectors. The framework is drawn from multi-instance learning and is meant to improve the predictive skill of the ensemble beyond that of the individual detectors. We show how the framework allows the use of multiple features derived from the seismogram to detect seismic wave arrivals, as well as how it allows only the most informative features to be retained in the ensemble. The computational cost of the "ensembling" method is linear in the size of the ensemble, allowing a scalable method for monitoring multiple features/transformations of a seismogram. The framework is tested on teleseismic and regional p-wave arrivals at the IMS (International Monitoring System) station in Warramunga, NT, Australia and the PNSU station in University of Utah's monitoring network.

58 GEOSCIENCES↗

Discovering Blind Geothermal Systems in the Great Basin Region: An Integrated Geologic and Geophysical Approach for Establishing Geothermal Play Fairways: All Phases

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.

15 GEOTHERMAL ENERGY↗