SEARCH · Engineering Papers

Results for “reservoir potential”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Wettability Alteration with Weak Acid-Assisted Surfactant Flood

Oil-wetness and heterogeneity are two key reasons for low oil recovery by waterflooding in carbonate reservoirs. Surfactants have been effective in altering the oil-wet matrix to a more water-wet condition and initiating spontaneous imbibition. Because it takes time for the surfactant to alter wettability, oil recovery from the tight matrix is slow and sometimes not economically feasible. Acids have the potential of dissolving minerals, which may alter wettability. In this study, the enhanced oil recovery (EOR) performance of an acid-assisted surfactant solution, a novel technique, was evaluated for low-temperature applications. A set of acids and their acetates were tested. Bulk rock-acid reaction, wettability alteration (WA) tests, and spontaneous imbibition measurements were conducted at reservoir temperature (35°C) to identify effective candidates. Coreflood tests were then performed to evaluate the selected acid-surfactant formulations. Before and after a coreflood test, the core was scanned using micro-computed tomography (CT) to investigate pore structure alteration. Bulk reaction measurements showed that weak acids, especially acetic acid (AA), have the desired low reaction rates at 35°C. WA tests showed that AA can remove the crude oil off the rock surface and alter wettability through mineral dissolution. The surfactant can reduce contact angles from 160° to 58°; adding acid into the surfactant can further reduce it to 52°. Spontaneous imbibition experiments showed the synergy between the acid and the surfactant; the AA-surfactant solution had the highest oil recovery (62.6%) among acid-surfactant formulations. The acid improves the WA efficiency by the surfactant through surface mineral dissolution and lower ζ-potential. The imbibition transports the acid-surfactant solutions into the matrix, which minimizes face dissolution. Coreflood tests show that the AA-surfactant flood can increase the oil recovery rate and recover about 8% more oil compared to the surfactant flood. Micro-CT showed that a few mineral particles were transported along the core and partially plugged pore throats, which reduced permeability and diverted flow leading to improved oil recovery. Here, the transport of the acid in reservoirs and the potential plugging issues have to be carefully evaluated in future studies.

58 GEOSCIENCES↗

DOE OSTI2024

Techno-economic feasibility of geothermal energy production using inactive oil and gas wells for district heating and cooling systems in Tuttle, Oklahoma

Oil and gas wells have been drilled in the United States and often encounter hot co-produced water possibly suitable for geothermal direct-use applications. Here this study evaluated geothermal resources, heating and cooling demand, and techno-economic potential of four oil and gas wells repurposed for geothermal energy production to serve two public schools and 250 nearby houses in Tuttle, Oklahoma, USA. Subsurface geology in the study area primarily consists of Permian to Mississippian sandstone and limestone formations approximately from 2 km to 3.5 km depth. With a geothermal gradient of 25.3 °C/km, the temperature of geothermal energy production was estimated as 68.2 °C at 2.1 km. The potential of calcite scaling within boreholes and pipes was minimal. Using the characterized reservoir properties, techno-economic analyses were conducted for evaluating levelized costs of geothermal energy production for direct-use heating and cooling and district heating systems with five different production scenarios. Heating and cooling demand in two schools and 250 houses and additional 0.3 MW and 0.6 MW base heating loads for potential geothermal direct-use applications in the study area were also incorporated in the modeling. Results indicated that the levelized cost of heating of geothermal district heating systems utilizing existing wells were significantly lower than those of conventional geothermal energy systems that include well drillings. The geothermal energy production with doublet and quartet configurations was generally sufficient to supply total annual heating demand in the district, while a peaking boiler was used to supply peak loads. Doublet configurations showed higher production temperature with a lower thermal drawdown than the quartet configurations. The doublet system at 2.1 km production depth with 9.3 kg/s flow rate represented the optimal levelized cost of $71/MWh and 91.2% utilization factor. These results imply that the Tuttle geothermal district heating system is techno-economically feasible and comparable to geothermal district heating systems in the United States and the regional natural gas rate for residentials by recycling inactive oil and gas wells with no drillings.

15 GEOTHERMAL ENERGY↗

NASA NTRS1981

Advanced technology lightweight fuel cell program

The potential of the alkaline electrolyte fuel cell as the power source in a multi hundred kilowatt orbital energy storage system was studied. The total system weight of an electrolysis cell energy storage system was determined. The tests demonstrated: (1) the performance stability of a platinum on carbon anode catalyst configuration after 5000 hours of testing has no loss in performance; (2) capability of the alkaline fuel cell to operate to a cyclical load profile; (3) suitability of a lightweight graphite electrolyte reservoir plate for use in the alkaline fuel cell; (4) long life potential of a hybrid polysulfone cell edge frame construction; and (5) long term stability of a fiber reinforced potassium titanate matrix structure. The power section tested operates with passive water removal eliminating the requirement for a dynamic hydrogen pump water separator thereby allowing a powerplant design with reduced weight, lower parasite power, and a potential for high reliability and extended endurance. It is concluded that two perovskites are unsuitable for use as a catalyst or as a catalyst support at the cathode of an alkaline fuel cell.

Martin, R. E.↗

DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗

DOE OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Modeling Study of Reduced Tubing Size Effects on Flow in Depleted Reservoir Natural Gas Storage Wells

This report explores the effects of tubing size reductions on natural gas flow from representative depleted reservoir underground storage wells and fields using basic models for coupled reservoir and pipe flow. This work was motivated by interest at the U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration, in evaluating the effects of tubing and packer as a potential safety upgrade to implement double-barrier systems to existing underground natural gas storage wells. Reservoir and well flow models were developed from widely accepted industry equations, verified against a commercial process simulator model, and validated against field data. The study utilized U.S. operator survey data to provide context and assure that modeling parameters including aver age deliverability rates for wells and fields, operating pressures, well depths, and storage capacities were all carefully considered to keep the modeling relevant to the known range of U.S. operations. The models generally found that wells and fields with inherently low deliverability were relatively insensitive to reductions in tubing diameter, primarily because the hydraulics in those cases were controlled by reservoir properties. For the high-producing wells and fields, the models found that reducing tubing diameter could produce significant reductions in deliverability, both at the field- and well-level. When put into context with occurrence data regarding average deliverability of fields and wells, it appears that most wells and most fields across the U.S. would experience deliverability reductions on the low end of what was simulated here, generally below 20%. For fields with moderate to high deliverability, reductions were generally larger, and could reach as high as 60% for the highest-producing wells and fields.

03 NATURAL GAS↗

DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

This closeout presentation summarizes a Department of Energy–funded study that evaluated whether large amounts of hydrogen can be safely stored underground in the North Dakota portion of the Williston Basin. The project combined lab testing, computer simulations, and basin‑wide analysis to assess saline formations, depleted oil and gas reservoirs, and salt formations for hydrogen storage capacity, recovery, and risks. Results show that underground hydrogen storage is technically feasible across multiple formation types, with depleted oil and gas reservoirs offering higher recovery and saline formations providing large long‑term storage potential. The study also identifies key challenges—such as wellbore material durability and gas purity management—and recommends pilot projects and further site‑specific studies to support future commercialization.

08 HYDROGEN↗

DOE OSTI2020

Real Time 3D Observations of Portland Cement Carbonation at CO2 Storage Conditions

Depleted oil reservoirs are considered a viable solution to the global challenge of CO 2 storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO 2 . Under reservoir conditions, CO 2 is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging. Here, we present an in situ 3D dynamic X-ray micro computed tomography (μ-CT) study of well cement carbonation at realistic reservoir stress, pore-pressure, and temperature conditions. The high-resolution time-lapse 3D images allow monitoring the progress of reaction fronts in Portland cement, including density changes, sample deformation, and mineral precipitation and dissolution. By switching between flow and nonflow conditions of CO 2 -saturated water through cement, we were able to delineate regimes dominated by calcium carbonate precipitation and dissolution. For the first time, we demonstrate experimentally the impact of the flow history on CO 2 leakage risk for cement plugging. In-situ μ-CT experiments combined with geochemical modeling provide unique insight into the interactions between CO 2 and cement, potentially helping in assessing the risks of CO 2 storage in geological reservoirs.

58 GEOSCIENCES↗

DOE OSTI2023

Expansion of smallmouth bass distribution and habitat overlap with juvenile Chinook salmon in the Willamette River, Oregon

Abstract Smallmouth bass populations have expanded far beyond their native range and these predatory fish present a pervasive threat to native aquatic species throughout North America. In the western United States, smallmouth bass are now present in river and reservoir habitats where Pacific salmon are found and are considered a potential threat to salmon recovery in many locations. We conducted a study to determine if smallmouth bass are expanding their range in the mainstem Willamette River, Oregon, and developed a model to assess habitat overlap between smallmouth bass and juvenile Chinook salmon. Sampling during 2011–2022 revealed that the distribution of smallmouth bass had expanded throughout that timeframe to encompass the entire mainstem Willamette River, including important rearing habitats for juvenile Chinook salmon. The model predicted that smallmouth bass and juvenile Chinook salmon habitat overlap was substantial, highlighting the need for additional research to evaluate for potential negative impacts to salmon recovery in the basin. The model was also used to evaluate the efficacy of using flow management to reduce interactions between these two species, but the scenarios we examined suggested that this was not a viable option. These results highlight the need for continued research to assess interactions between smallmouth bass and juvenile salmon, and other native species of concern, in the Willamette River Basin. The development of the model is useful for resource managers to understand interactions between these species to prioritize locations for sampling in the future.

White, James S.↗

DOE OSTI2022

Dissolving Nonionic Surfactants in CO 2 to Improve Oil Recovery in Unconventional Reservoirs via Wettability Alteration

CO 2 injection is a promising method for enhanced oil recovery (EOR) in unconventional shale reservoirs. Here, in this work, we postulate that CO 2 EOR may be improved by the dissolution of surfactants into CO 2 . Although CO 2 is a relatively good solvent for oil, we show that CO 2 and Eagle Ford oil are immiscible at compositions above 70 wt % CO 2 , even at pressures as high as 62 MPa. The presence of a CO 2 –oil interface at reservoir conditions indicates that the addition of a surfactant has the potential to improve oil recovery–via wettability alteration from oil-wet to CO 2 -wet, CO 2 –oil interfacial tension (IFT) reduction, or both. Three nonionic surfactants (branched tridecyl ethoxylate Indorama SURFONIC TDA-9, branched nonylphenol ethoxylate Indorama SURFONIC N-100, and linear dodecyl ethoxylate Indorama SURFONIC L12-6) were evaluated for CO 2 -solubility, shale wettability alteration, effect on CO 2 –oil IFT, ability to generate CO 2 –oil foams, and ability to increase oil extraction from Eagle Ford, Mancos, and Bakken shale cores. Each surfactant dissolved in CO 2 up to 1 wt % at pressures and temperatures commensurate with CO 2 EOR. CO 2 -dissolved surfactants did not significantly affect CO 2 –oil IFT or generate CO2–oil foams, but they did induce a dramatic change in the contact angle of an oil droplet on an oil-aged shale chip in CO 2 from strongly oil-wet (11°) toward intermediate CO 2 –oil wettability (82°) (at 80 °C, 27.6 MPa). The branched tridecyl ethoxylated surfactant, SURFONIC TDA-9, afforded the highest oil recovery in core soaking experiments–75%, compared to 71% by pure CO 2 . Analysis of oil extracts by gas chromatography revealed that heavier oil components were produced when the surfactant was added to CO 2 . These results indicate that CO 2 -dissolved surfactants may increase oil recovery from shale by wettability alteration from oil-wet toward CO 2 -wet.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2026

Prelithiated SiO x /Graphite-NMC811 Cells: Capacity Loss, Impedance Rise and Hidden Degradation Pathways Revealed Using Three-Electrode Diagnostics

Electrodes containing SiO x /graphite (Gr) materials are attractive as anodes for high-energy lithium-ion batteries. However, their mechanical deformation, electrochemical response, and impedance evolution during long-term cycling are strongly coupled, complicating accurate diagnosis of performance fade mechanisms. In this work, the behavior of electrochemically prelithiated SiO x /Gr anodes paired with NMC811 cathodes is systematically investigated using techniques that include in-situ dilatometry, three-electrode electrochemistry, and multiscale post-cycling microscopy. The SiO x /Gr electrode exhibits a maximum expansion of 49% upon lithiation to 10 mV vs Li + /Li, with 84% of the expansion and 91% of the capacity being reversible. In full cells, relatively stable cycling with only 12% capacity fade over 500 cycles is observed. Three-electrode experiments reveal cell-level impedance growth, which is dominated by the NMC811 cathode: the SiO x /Gr anode exhibits minimal net impedance rise and an initial impedance decrease at low potentials. Despite this apparent electrochemical stability, cross-sectional SEM, PFIB tomography, and cryo-STEM reveal irreversible anode thickening caused by the accumulation of an inorganic-rich solid electrolyte interphase (SEI) permeating the anode bulk. Electrode potential-shift analysis further demonstrates that Li + ions released from lithium reservoirs in the prelithiated anode mask true lithium inventory loss during aging. These results demonstrate that low-expansion SiO x /Gr anodes can simultaneously exhibit favorable cycling and impedance metrics while undergoing substantial, hidden degradation, underscoring the importance of electrode-resolved diagnostics for evaluating prelithiated silicon-based anodes.

25 ENERGY STORAGE↗

DOE OSTI2023

Supersonically expanded sodium metal-dilute halogen gas interactions. The importance of reaction populated and energy storing reservoir states and population inversion created amplification in Na2

The reactions of Cl, Br, and I with Nan=2,3 produced in a supersonic expansion form Na2* and Na* excited states extending across the visible and ultraviolet regions. Emission in the region extending from 410 to 600 nm indicates selectively formed excited state Na2 emission features. Experimental evidence suggests that this emission is associated with Na3 + X reactions. Broadband (0.5 cm−1) laser measurements demonstrate gain (population inversion) for select features at∼524–528(1%), ∼492(0.3%), and ∼458.7–461(0.8%) nm. Single mode (0.007 cm−1) measurements extending from 528.03 to 527.63 nm demonstrate amplification involving five to six individual rovibronic levels with a maximum gain close to 3% recorded at 527.9 nm. The observed gain is associated with select transitions from levels of the Na2 11Πu state populated, via identified curve crossings, through collision induced transfer from long-lived Na2 21Σg+ and 11Πg reservoir states. Collision induced population buildup in the lowest vibrational levels of these reservoir states and collision induced transfer to the Na2 11Πu state create a population inversion in transitions to the X 1Σg+ state of Na2. The observed amplification is aided by rapid vibrational and rotational relaxation in both the Na2 ground and excited reservoir states producing amplifiers in the visible region like the HF amplifier in the infrared. This study suggests the importance of reaction populated and energy storing long-lived reservoir states in small sodium molecule combustion processes and indicates the potential for providing new short wavelength visible and ultraviolet amplifiers for future laser-based chemical propulsion concepts.

Chemistry↗

NASA NTRS2005

Medium-Frequency Pseudonoise Georadar

Ground-probing radar systems featuring medium-frequency carrier signals phase-modulated by binary pseudonoise codes have been proposed. These systems would be used to locate and detect movements of subterranean surfaces; the primary intended application is in warning of the movement of underground water toward oil-well intake ports in time to shut down those ports to avoid pumping of water. Other potential applications include oil-well logging and monitoring of underground reservoirs. A typical prior georadar system operates at a carrier frequency of at least 50 MHz in order to provide useable range resolution. This frequency is too high for adequate penetration of many underground layers of interest. On the other hand, if the carrier frequency were to be reduced greatly to increase penetration, then bandwidth and thus range resolution would also have to be reduced, thereby rendering the system less useful. The proposed medium-frequency pseudonoise georadar systems would offer the advantage of greater penetration at lower carrier frequencies, but without the loss of resolution that would be incurred by operating typical prior georadar systems at lower frequencies.

Arendt, G. Dickey↗

DOE OSTI2026

Energy-efficient scientific computing using chemical reservoirs

The rapid growth of computing demands driven by scientific computing, data analytics, and artificial intelligence (AI) advancements has exposed the limitations of traditional digital processing systems. These systems are nearing physical energy barriers, making significant gains in energy efficiency increasingly unattainable. As we advance toward post-exascale computing, disruptive approaches are critical to overcoming these limitations. Among emerging analog solutions, biochemical computing offers a transformative path for achieving orders-of-magnitude improvements in energy efficiency. By leveraging the natural optimization capabilities of chemical reaction networks (CRNs), biochemical systems have the potential to meet high-performance computing needs through natural scalability. However, numerous challenges remain, including theoretical limitations in mapping computational problems to CRNs and practical barriers in implementing biochemical computing devices. In this paper, we present a framework for chemical computation using biochemical systems and introduce key components of our approach for energy-efficient scientific computing. We showcase the feasibility of this framework by solving a system of ordinary differential equations by emulating a chemical reservoir device, demonstrating its potential for addressing modern computing challenges. This work lays a foundational step toward harnessing the computational power of chemistry to design energy-efficient, scalable, high-performance next-generation computing systems.

Johnson, Connah G. M. [Pacific Northwest National ↗

DOE OSTI2025

Inorganic Alterations in Unconventional Shale Reservoirs: Importance of Additive and Base Fluid Chemistry

The effective development of unconventional petroleum systems requires the use of significant water resources. In an effort to reduce the consumption of freshwater resources for hydraulic fracturing, highly saline produced waters are increasingly recycled for use as a base fluid. However, there are significant knowledge gaps regarding potential water–rock interactions resulting from the introduction of produced waters and associated additives into shale reservoirs such as formation and deposition of mineral scale, which can negatively affect hydrocarbon production through wellbore restriction and damage to hydraulically generated fractures. To assess the impacts of field stimulation practices in the subsurface, a series of laboratory experiments were completed using (a) three distinct sedimentary rock formations of the Midland Basin (Texas, USA) and (b) additives with two different base fluids: municipal fresh water and clean brine. The experimental approach used relevant injection sequences and mixing ratios in specialized reactors for 3 weeks. Static pressurized experiments and nonpressurized time-resolved experiments were undertaken. The resulting solids and liquids were analyzed by using a variety of laboratory- and synchrotron-based techniques. The use of an acid spearhead (15% HCl) resulted in texturing of both clay-rich and calcareous shales, which can temporarily enhance porosity but subsequently result in mineral scale deposition. The primary matrix scale was Fe(III)-bearing phases, which occurred in all experiments regardless of base fluid chemistry. Additionally, strontium sulfate (SrSO 4 ) precipitated on shale surfaces when clean brines were used. It was concluded that clean brine was the main source of Sr 2+ species, while persulfate breaker degradation and oxidation of pyrite were the sources of SO 4 2– . Sulfate scaling was more pronounced in clay-rich shales, suggesting that Sr sorption is important for promoting celestite formation. This work demonstrates that mineral scale deposition is a complex phenomenon, whereby the type and proportions of various mineral phases are determined from reservoir alteration processes and coprecipitation of constituents from injection fluids. In conclusion, the experimental results shown here should be considered when evaluating different base fluids and additives in order to mitigate mineral precipitation in unconventional shale reservoirs, which could result in reservoir degradation.

Jew, Adam D. [SLAC National Accelerator Laboratory↗

DOE OSTI2024

Carbon Storage Technical Viability Approach and National Data Assessment

Carbon Storage Technical Viability Approach is a comprehensive evaluation of potential geologic carbon storage sites that includes classic subsurface resource assessment components such as reservoir suitability in addition to hazard, environmental, social, regulatory, and jurisdiction components that may enhance or hinder successful carbon storage. Data for assessments of technically viable carbon storage span many categories, types; are disparate and numerous. Variables and types of data required to support CS assessments were previously not clearly defined and documented. Contextualizing available data indicates their utility, potential uncertainty, and gaps. This presentation details the Carbon Storage Technical Viability Approach, the associated matrix and database, and initial results from a portion of the national data availability assessment that contextualizes the data available to support carbon storage projects. Presented at the American Association of Petroleum Geologists' Carbon Capture Utilization and Storage (SPE-AAPG-SEG CCUS 2024) conference in Houston, TX, March 11-13, 2024.

Mark-Moser, Mackenzie K.↗

DOE OSTI2021

Characterization of Offshore Storage Resource Potential in the Central Planning Area of the Gulf of Mexico

This report contains a brief overview of the several studies that provide the basis for this work and details the reservoir characterization efforts that have been completed to date. Briefly, geological characterization data suggests that the deep-water reservoirs are the result of the interplay between turbidite depositional systems and salt tectonics. Project Partners have estimated the CO 2 storage capacity associated with saline reservoirs and that associated with CO 2 -Enhanced Oil Recovery (EOR) in the state waters of Louisiana. In addition, Project Partners have conducted a detailed analysis of CO 2 storage potential associated with CO 2 -EOR in the central planning area of the GOM. This work estimates that 3,140 million metric tonnes of CO 2 can be stored in optimal reservoirs of the shallow- and deep-water central GOM. A reduced order modeling and machine learning approach is introduced that will be used to evaluate CO 2 storage capacity and plume dynamics for down-selected, reservoir-specific, saline characterization. Last, a brief discussion establishes how the data presented in this report will support future work.

02 PETROLEUM↗

DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗