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DOE OSTI2024

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.

Lee, Jonathan E. [Department of Chemical and Envir↗

DOE OSTI2024

Towards revealing intrinsic vortex-core states in Fe-based superconductors through statistical discovery

Abstract In type-II superconductors, electronic states within magnetic vortices hold crucial information about the paring mechanism and can reveal non-trivial topology. While scanning tunneling microscopy/spectroscopy (STM/S) is a powerful tool for imaging superconducting vortices, it is challenging to isolate the intrinsic electronic properties from extrinsic effects like subsurface defects and disorders. Here we combine STM/STS with basic machine learning to develop a method for screening out the vortices pinned by embedded disorder in iron-based superconductors. Through a principal component analysis of large STS data within vortices, we find that the vortex-core states in Ba(Fe 0.96 Ni 0.04 ) 2 As 2 start to split into two categories at certain magnetic field strengths, reflecting vortices with and without pinning by subsurface defects or disorders. Our machine-learning analysis provides an unbiased approach to reveal intrinsic vortex-core states in novel superconductors and shed light on ongoing puzzles in the possible emergence of a Majorana zero mode.

Guo, Yueming↗

DOE OSTI2024

Characterization of the Triassic Newark Basin of New York and New Jersey for Geologic Storage of Carbon Dioxide

The project Characterization of the Triassic Newark Basin of New York and New Jersey for Geologic Storage of Carbon Dioxide is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. Sandia Technologies, LLC, and co-investigator Conrad Geoscience Corporation, examined the potential for large-scale, permanent CO2 storage in sedimentary strata within the Newark Rift Basin. The Newark Rift Basin underlies an industrialized, developed region comprising parts of New York, New Jersey, and Pennsylvania. The project characterized and investigated the suitability of Triassic age sedimentary formations for potential geologic CO2 storage. The project team drilled and cored two test wells to define the sedimentary geologic formations underlying the basin and to document or reach basement rock. With this geologic characterization phase, an integration of seismic, geologic, borehole, and formation core results provided a higher resolution assessment of CO2 storage potential. The Stockton Formation is known to be a potentially favorable geologic storage formation in the basin. In 2011, the 1-NYSTA Tandem Lot stratigraphic test well was drilled to a depth of 6,855 feet in the northern portion of the Newark Basin in southern New York State. Approximately 9 miles south-southeast on the Lamont Doherty Campus, TW-4 was drilled and cored in 2013 to a depth of 1,802 feet and contacted apparent igneous basement at a depth of 1,712 feet. Both wells penetrated the Palisades Sill ranging from 800 feet thick in the eastern well to approximately 1,800 feet in thickness at the 1-NYSTA Tandem Lot deep drill site. A diabase sill can provide an excellent seal and dense confining layer for potential CO2 storage reservoirs and flow layers that are situated beneath it within the Stockton Sandstone. The Stockton Sandstone was encountered beneath the sill in the TW-4 well on the Lamont campus, and data integration suggests that it was likely observed near total depth in the deep 1-NYSTA Tandem Lot well. The test wells confirm and define reservoirs are present beneath the sill and offer CO2 storage potential. The integration of geologic and reservoir characterization of well logs, formation cores, and formation fluids indicated Triassic age lacustrine playa lake and mudbank shales of the Upper Passaic Group can provide an effective seal for the porous and permeable underlying sandstone reservoir layers. This project acquired seismic data, drilled borehole well logs, acquired core samples, and integrated these findings to provide a better understanding of the subsurface geologic formations in the Newark Rift Basin. These findings have contributed to a higher degree of accuracy in predicting potential geologic storage opportunities, while refining geologic storage capacity estimates for the indicated reservoirs and flow units.

.las↗

DOE OSTI2025

Stochastic Ensemble Generation for Improved Characterization of Representing Geologic Variability in a Reservoir: IBDP Case Study for SMART Initiative

This document is a poster covering the findings from activities on training data generation, specifically geologic ensemble generation. The generated geologic realizations captured the range of possible permeability distributions of the subsurface at the Illinois Basin - Decatur Project (IBDP) site, based on available well log variabilities. The percentages of reservoirs and baffles in the injection zone and a truncation of baffle permeability led to more variance in the simulations. This will be used to build forward modeling, history matching, and optimization workflows. The geologic realizations were also ranked according to dynamic measures of hydraulic diffusivity, and simulations confirm a greater contrast between the reservoir and the baffles during injection.

stochastic ensemble generation↗

NASA NTRS1991

Polarimetric radar for assessing subsurface characteristics

The potential of using the NASA airborne polarimetric radar system to assess the subsurface characteristics of the Rogers lake bed and the Atchadafaya Basin study sites is described. Preliminary analysis of acquired data indicated that VV polarization is capable of muddy water penetration and that the radar system could be used to assess underwater sediment distribution. Statistical analysis of the data will provide insight on the depth of muddy water penetration.

Wu, Shih-Tseng↗

NASA NTRS2002

Infrared Spectra of Hydrated Magnesium Salts and their Role in the Search for Possible Life Conditions on Jupiter Moons

Recent observations from the Galileo satellite indicate that three of the Jupiter moons, Europa, Ganymede, and Callisto, may have subsurface oceans. Possible existence of such ocean and the nature of its composition are of great interest to astrobiologists. Data from Galileo's NIMS spectrometer indicate the possibility of hydrated salts on Europa's surface. To aid in the design of future missions, we investigated infrared spectra of MgSO4-nH20, n=1-3 using ab initio calculations. Geometry, energetics, dipole moments, vibrational frequencies and infrared intensities of pure and hydrated MgSO4 salts were determined. Significant differences are found between vibrational spectra of water molecules in complexes with MgSO4 and pure water. Some of the O-H stretching frequencies in the complexes are shifted to the red by up to 1,500 - 2,000 per cm. In addition, the SO2 stretching vibrations are found at lower frequency regions than the water vibrations. The calculated bands of water and SO2 fragments can serve as markers for the existence of the salt-water complexes on the surface of Jupiter's moon.

Chaban, Galina↗

NASA NTRS2005

Martian Impact Craters as Revealed by MGS and Odyssey

A variety of ejecta and interior morphologies were revealed for martian impact craters by Viking imagery. Numerous studies have classified these ejecta and interior morphologies and looked at how these morphologies correlate with crater diameter, latitude, terrain, and elevation [1, 2, 3, 4]. Many of these features, particularly the layered (fluidized) ejecta morphologies and central pits, have been proposed to result when the crater formed in target material containing high concentrations of volatiles. The Catalog of Large Martian Impact Craters was originally derived from the Viking 1:2,000,000 photomosaics and contains information on 42,283 impact craters 5-km diameter distributed across the entire martian surface. The information in this Catalog has been used to study the distributions of craters displaying specific ejecta and interior morphologies in an attempt to understand the environmental conditions which give rise to these features and to estimate the areal and vertical extents of subsurface volatile reservoirs [4, 5]. The Catalog is currently undergoing revision utilizing Mars Global Surveyor (MGS) and Mars Odyssey data [6]. The higher resolution multispectral imagery is resulting in numerous revisions to the original classifications and the addition of new elemental, thermophysical, and topographic data is allowing new insights into the environmental conditions under which these features form. A few of the new results from analysis of data in the revised Catalog are discussed below.

Barlow, N. G.↗

DOE OSTI2024

Utah FORGE: Geochemical Data for Cold Groundwaters and Produced Geothermal Fluids

Geochemical data for cold groundwaters and produced geothermal fluids around the Utah FORGE site. The data is compiled into four tables in the attached Excel File. Table 1 is a compilation of compositions (anions, cations, weak acids, oxygen, hydrogen, and carbon isotopes) for cold groundwaters and produced geothermal waters in the Milford valley, Utah. Table 2 is a compilation of noble gas (He, Ne, Ar) and He and Ne isotopic compositions for cold groundwaters and produced geothermal waters in the Milford valley, Utah. Table 3 provides values for calculated advective and diffusive fluxes of helium. Table 4 provides values of calculated subsurface stored heat between the Opal Mound fault and the Utah FORGE site, which are related to volumes of recently solidified magmatic heat sources.

15 GEOTHERMAL ENERGY↗

NASA NTRS2005

Construction and Resource Utilization Explorer: Regolith Characterization Using a Modular Instrument Suite and Analysis Tools

The Construction Resource Utilization Explorer (CRUX) is a technology maturation project for the U.S. National Aeronautics and Space Administration to provide enabling technology for lunar and planetary surface operations (LPSO). The CRUX will have 10 instruments, a data handling function (Mapper - with features of data subscription, fusion, interpretation, and publication through geographical information system [GIs] displays), and a decision support system DSS) to provide information needed to plan and conduct LPSO. Six CRUX instruments are associated with an instrumented drill to directly measure regolith properties (thermal, electrical, mechanical, and textural) and to determine the presence of water and other hydrogen sources to a depth of about 2 m (Prospector). CRUX surface and geophysical instruments (Surveyor) are designed to determine the presence of hydrogen, delineate near subsurface properties, stratigraphy, and buried objects over a broad area through the use of neutron and seismic probes, and ground penetrating radar. Techniques to receive data from existing space qualified stereo pair cameras to determine surface topography will also be part of the CRUX. The Mapper will ingest information from CRUX instruments and other lunar and planetary data sources, and provide data handling and display features for DSS output. CRUX operation will be semi-autonomous and near real-time to allow its use for either planning or operations purposes.

Moon↗

NASA NTRS2021

Availability of Subsurface Water-Ice Resources in the Northern Mid-Latitudes of Mars

Multiple nations and private entities are pushing to make landing humans on Mars a reality. The majority of proposed mission architectures envision “living off the land” by leveraging Martian water-ice deposits for fuel production and other purposes. Fortunately for mission designers, water ice exists on Mars in plentiful volumes. The challenge is isolating accessible ice deposits within regions that optimize other preferred landing-site conditions. Here, we present the first results of the Mars Subsurface Water Ice Mapping (SWIM) project, which has the aim of searching for buried ice resources across the mid-latitudes. Through the integration of orbital datasets in concert with new data-processing techniques, the SWIM project assesses the likelihood of ice by quantifying the consistency of multiple, independent data sources with the presence of ice. Concentrating our efforts across a significant portion of the northern Hemisphere, our composite ice consistency maps indicate that the broad plains of Arcadia and the extensive glacial networks across Deuteronilus Mensae match the greatest number of remote sensing criteria for accessible ice-rich, subsurface material situated equatorward of the contemporary ice-stability zone.

G A Morgan↗

NASA NTRSDate not supplied

The Lunar Explorer Instrument for Space Biology Applications (LEIA) Pre-Flight Tests: Mechanical Considerations

The BioSensor payload on the upcoming LEIA platform aboard the CLPS (CP-22) lander will carry yeast to the Moon's south pole to study the effects of lunar radiation and gravity. From Earth, BioSensor will transport desiccated yeast within 16 fluidic cards, each containing 16 fluidic wells of 100 microliters volume. At the start of the experiment, these microbes will be autonomously rehydrated on the Moon, and optical absorbance measurements at three wavelengths will be performed across all 256 wells. Absorbance measurements in fluidic wells are susceptible to noise and artifacts due to bubble formation during well rehydration and microbial growth. BioSensor, as a biofluidics system, faces significant data anomalies caused by payload vibrations, particularly from the operation of the co-located PROSPECT’s ProSEED drill, to assess lunar resources by penetrating the subsurface. To evaluate the impact of drill vibrations, fully assembled and filled fluidic cards were subjected to sine sweep signals in the x, y, z planes, ranging from 5 - 2560 Hz at g-loads of 0.25 and 0.5, with on-board accelerometer for localized vibration measurement. Wells with various fill conditions, including partial fills with different bubble sizes and completely filled wells, were tested. Results indicated that small bubbles adhered to well walls at high frequencies but were dislodged at low frequencies, causing data anomalies. Medium and large bubbles exhibited higher interference with optical data due to lower surface tension and variable bubble surface flexion. Overall, it was found that irrespective of the fill type, low-frequency vibrations were most detrimental to optical readings. Understanding the drill schedule and correlating it with BioSensor timestamps will help identify periods when BioSensor data is unreliable, a crucial step for accurately interpreting the microbial response data and ensuring the validity of the BioSensor's scientific measurements on the lunar surface.

Chinmayee Govinda Raj↗

DOE OSTI2025

Integrated GW Farm ABM

This Data Repository includes data used for the integrated groundwater- farm ABM model, raw model output from scenario ensemble, and processed outputs that isolate the groundwater storage depletion outcomes for the 35,000 farm cells. Model Inputs: Farm ABM Inputs: This folder contains the input data used by the integrated groundwater - farm ABM modelling script (Python file) used for the high performance computing (HPC) experiments. The sub-folder "data inputs" contains all of the farm attribute data, while the three files in the folder have the hydrogeological data lookup table (NLDAS Cost Curve Attributes.csv), a lookup table (Theis well function table.csv) for the groundwater cost curve function, and the farm indexes and corresponding NLDAS ids for all of the cells run in this experiment (nldas farms subset final.csv). NLDAS Cost curve hydrogeological data: Hydrogeological data aggregated to 1/8 degree resolution and aligned with the NLDAS grid. Parameters include: water depth below ground surface [meters], subsurface porosity [unitless], aquifer depth from ground surface to aquifer bottom [meters], annual average recharge (USGS: mm, Doll: meters), and three different hydraulic conductivity (K) values (meters/day). The three K values represent the mean value from Gleeson et al. (2018), one standard deviation above the mean from Gleeson et al. (2018), and the de Graaf et al. 2020 modifications to certain lithologies. Additional information about these datasets and their processing are documented in the supplement to Yoon et al. 2025 (in review). Output: Raw outputs: This folder contains a .zip file that has model outputs for the entire scenario ensemble. There is one csv for each farm id, using the format "farm farmid cases.csv". The relationship between the farm id and NLDAS id is defined by the "nldas farms subset final.csv" located in the Farm ABM Inputs folder. Each csv has 625 rows, corresponding to 625 combinations of different scenario parameter values. Each row (scenario) represents the outcome of a 100 year simulation. Columns define scenario settings and summary statistics for each scenario. The first four columns define the scenario settings: "hydro ratio," "econ ratio," "K scenario," and "gamma scenario." The hydro and econ ratios are values passed to the modeling script that influence multipliers for other model parameters, as documented in the supplement to Yoon et al. 2025 (in review). The gamma multiplier is a coefficient multiplier applied to the baseline gamma values (values below 1 represent lower unobserved costs compared to baseline, values above 1 represent higher costs). The K scenario names represent K values of: "low": 0.5 m/d, "int 1": 2.5 m/d, "int 2": 10 m/d, "high": 50 m/d, and "gleeson": mean Gleeson K value. "Perc vol depleted" is the fraction of groundwater depleted at the end of the 100 simulation. Processed Output: Derived depletion outcomes from raw outputs: All of the individual csv files from the Raw outputs were aggregated into a single file that has the scenario settings and fraction depletion "Perc vol depleted" for every farm cell, for every scenario. The other two files define relationships between the farm id, NLDAS id, and local and major aquifer units, used for aquifer-level depletion analysis.

Agent based modeling↗

NASA NTRS1995

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System: Dynamical Considerations - Part 1

The dynamical consequences of constraining a numerical model with sea surface height data have been investigated. The model used for this study is a quasigeostrophic model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. The assimilation of the surface data is thus equivalent to the prescription of a surface pressure boundary condition. The authors analyzed the mechanisms of the model adjustment and the characteristics of the resultant equilibrium state when the surface data are assimilated. Since the surface data are the superposition of a mean component and an eddy component, in order to understand the relative role of these two components in determining the characteristics of the final equilibrium state, two different experiments have been considered: in the first experiment only the climatological mean field is assimilated, while in the second experiment the total surface streamfunction field (mean plus eddies) has been used. It is shown that the model behavior in the presence of the surface data constraint can be conveniently described in terms of baroclinic Fofonoff modes. The prescribed mean component of the surface data acts as a 'surface topography' in this problem. Its presence determines a distortion of the geostrophic contours in the subsurface layers, thus constraining the mean circulation in those layers. The intensity of the mean flow is determined by the inflow/outflow conditions at the open boundaries, as well as by eddy forcing and dissipation.

Capotondi, Antonietta↗

NASA NTRS1998

Resource Utilization and Site Selection for a Self-Sufficient Martian Outpost

As a planet with striking similarities to Earth, Mars is an important focus for scientific research aimed at understanding the processes of planetary evolution and the formation of our solar system. Fortunately, Mars is also a planet with abundant natural resources, including assessible materials that can be used to support human life and to sustain a self-sufficient martian outpost. Resources required include water, breathable air, food, shelter, energy, and fuel. Through a mission design based on in situ resource development, we can establish a permanent outpost on Mars beginning with the first manned mission. This paper examines the potential for supporting the first manned mission with the objective of achieving self-sufficiency through well-understood resource development and a program of rigorous scientific research aimed at extending that capability. We examine the potential for initially extracting critical resources from the martian environment, and discuss the scientific investigations required to identify additional resources in the atmosphere, on the surface, and within the subsurface. We also discuss our current state of knowledge of Mars, technical considerations of resource utilization, and using unmanned missions' data for selecting an optimal site. The primary goal of achieving self-sufficiency on Mars would accelerate the development of human colonization beyond Earth, while providing a robust and permanent martian base from which humans can explore and conduct long-term research on planetary evolution, the solar system, and life itself.

Barker, Donald↗

NASA NTRS2003

Experimental Evaluation of Hot Films on Ceramic Substrates for Skin-Friction Measurement

An investigation has been performed on the use of low-thermal conductivity, ceramic substrates for hot films intended to measure skin friction. Hot films were deposited on two types of ceramic substrates. Four hot films used composite-ceramic substrates with subsurface thermocouples (TCs), and two hot films were deposited on thin Macor(R) substrates. All six sensors were tested side by side in the wall of the NASA Glenn Research Center 8-ft by 6-ft Supersonic Wind Tunnel (SWT). Data were obtained from zero flow to Mach 1.98 in air. Control measurements were made with three Preston tubes and two boundary-layer rakes. The tests were repeated at two different hot film power levels. All hot films and subsurface TCs functioned throughout the three days of testing. At zero flow, the films on the high-thermal conductivity Macor(R) substrates required approximately twice the power as those on the composite-ceramic substrates. Skin-friction results were consistent with the control measurements. Estimates of the conduction heat losses were made using the embedded TCs but were hampered by variability in coating thicknesses and TC locations.

Noffz, Gregory K.↗

NASA NTRS2010

The Impact of Ocean Observations in Seasonal Climate Prediction

The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

Rienecker, Michele↗

NASA NTRS2015

Impact of Drilling Operations on Lunar Volatiles Capture: Thermal Vacuum Tests

In Situ Resource Utilization (ISRU) enables future planetary exploration by using local resources to supply mission consumables. This idea of 'living off the land' has the potential to reduce mission cost and risk. On the moon, water has been identified as a potential resource (for life support or propellant) at the lunar poles, where it exists as ice in the subsurface. However, the depth and content of this resource has yet to be confirmed on the ground; only remote detection data exists. The upcoming Resource Prospector mission (RP) will 'ground-truth' the water using a rover, drill, and the RESOLVE science package. As the 2020 planned mission date nears, component level hardware is being tested in relevant lunar conditions (thermal vacuum). In August 2014 a series of drilling tests were performed using the Honeybee Robotics Lunar Prospecting Drill inside a 'dirty' thermal vacuum chamber at the NASA Glenn Research Center. The drill used a unique auger design to capture and retain the lunar regolith simulant. The goal of these tests was to investigate volatiles (water) loss during drilling and sample transfer to a sample crucible in order to validate this regolith sampling method. Twelve soil samples were captured over the course of two tests at pressures of 10(exp-5) Torr and ambient temperatures between -80C to -20C. Each sample was obtained from a depth of 40 cm to 50 cm within a cryogenically frozen bed of NU-LHT-3M lunar regolith simulant doped with 5 wt% water. Upon acquisition, each sample was transferred and hermetically sealed inside a crucible. The samples were later baked out to determine water wt% and in turn volatile loss by following ASTM standard practices. Of the twelve tests, four sealed properly and lost an average of 30% of their available water during drilling and transfer. The variability in the results correlated well with ambient temperature (lower the temperature lower volatiles loss) and the trend agreed with the sublimation rates for the same temperature. Moisture retention also correlated with quantity of sample: a larger amount of material resulted in less water loss. The drilling process took an average of 10 minutes to capture and transfer each sample. The drilling power was approximately 20 Watt with a Weight on Bit of approximately 30 N. The bit temperature indicated little heat input into formation during the drilling process.

drilling↗

DOE OSTI2026

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗