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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.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

3D Play Fairway Analysis for Examining of Superhot Drilling Production Scenarios: Preprint

The DEEPEN (DE-risking Exploration for geothermal Plays in magmatic ENvironments) project was a multi-laboratory, international effort to reduce uncertainty and improve resource characterization in superhot geothermal systems. Building on this foundation, this work advances open-source tools designed to lower the exploration risk and cost of superhot geothermal projects while promoting transparency, reproducibility, and efficiency in exploration workflows. These tools are being tested at two key sites: (1) the Nesjavellir Geothermal Area in Iceland, where the Icelandic Deep Drilling Project (IDDP) will drill its third well, and (2) Newberry Volcano in Oregon, USA, where Mazama Energy will pilot the first superhot enhanced geothermal system (EGS). A major outcome is the creation of a modular, open-source Python framework for play fairway analysis (PFA) in 2D and 3D, called geoPFA. The PFA workflow has been expanded to produce pseudo conceptual models, and will soon be refined to assess reservoir components through integration with the thermo-hydraulic-mechanical-chemical (THMC) simulator TReactMech, to enable iterative coupling between PFA and THMC models, improving characterization of superhot systems. All three of the Icelandic Deep Drilling Project's production scenarios were analyzed via this framework: (1) a superhot deep injection well paired with conventional production wells at Nesjavellir, (2) a superhot deep production well at Nesjavellir, and (3) superhot enhanced geothermal system at Newberry Volcano. This analysis provides useful insights around conceptual modeling of these production scenarios, helping to inform decisions around which scenario is best suited for which types of environments.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Geothermal play fairway analysis, part 1: Example from the Snake River Plain, Idaho

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry. The study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the SRP: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for heat source were heat flow, distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Reservoir and recharge permeability was inferred from the analysis of stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetics and gravity data. Data for cap or seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment maps for heat, permeability, and seal, which were combined to create a Composite Common Risk Segment map for all southern Idaho that reflects the risk associated with geothermal resource exploration and identifies favorable resource tracks. Our regional assessment indicated that undiscovered geothermal resources may be located in several areas of the SRP. Two of these areas, the western SRP and Camas Prairie, were selected for more detailed assessment, during which heat, permeability, and seal were evaluated using newly collected field data and smaller grid parameters to refine the location of potential resources. These higher resolution assessments illustrate the flexibility of our approach over a range of scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Play-fairway analysis for geothermal resources and exploration risk in the Modoc Plateau region

The region surrounding the Modoc Plateau, encompassing parts of northeastern California, southern Oregon, and northwestern Nevada, lies at an intersection between two tectonic provinces; the Basin and Range province and the Cascade volcanic arc. Both of these provinces have substantial geothermal resource base and resource potential. Geothermal systems with evidence of magmatic heat, associated with Cascade arc magmatism, typify the western side of the region. Systems on the eastern side of the region appear to be fault controlled with heat derived from high crustal heat flow, both of which are typical of the Basin and Range. As it has the potential to host Cascade arc-type geothermal resources, Basin and Range-type geothermal resources, and/or resources with characteristics of both provinces, and because there is relatively little current development, the Modoc Plateau region represents an intriguing potential for undiscovered geothermal resources. It remains unclear however, what specific set(s) of characteristics are diagnostic of Modoc-type geothermal systems and how or if those characteristics are distinct from Basin and Range-type or Cascade arc-type geothermal systems. In order to evaluate the potential for undiscovered geothermal resources in the Modoc area, we integrate a wide variety of existing data in order to evaluate geothermal resource potential and exploration risk utilizing ‘play-fairway’ analysis. Here, we consider that the requisite parameters for hydrothermal circulation are: 1) heat that is sufficient to drive circulation, and 2) permeability that is sufficient to allow for fluid circulation in the subsurface. We synthesize data that indicate the extent and distribution of these parameters throughout the Modoc region. ‘Fuzzy logic’ is used to incorporate expert opinion into the utility of each dataset as an indicator of either heat or permeability, and thus geothermal favorability. The results identify several geothermal prospects, areas that are highly favorable for the occurrence of both heat and permeability. These are also areas where there is sufficient data coverage, quality, and consistency that the exploration risk is relatively low. These unknown, undeveloped, and under-developed prospects are well-suited for continued exploration efforts. The results also indicate to what degree the two ‘play-types,’ i.e. Cascade arc-type or Basin and Range-type, apply to each of the geothermal prospects, a useful guide in exploration efforts.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Assessment of high enthalpy geothermal resources and promising areas of Chile

This work aims to assess geothermal power potential in identified high enthalpy geothermal areas in the Chilean Andes, based on reservoir temperature and volume. In addition, we present a set of highly favorable geothermal areas, but without enough data in order to quantify the resource. Information regarding geothermal systems was gathered and ranked to assess Indicated or Inferred resources, depending on the degree of confidence that a resource may exist as indicated by the geoscientific information available to review. Resources were estimated through the USGS Heat in Place method. A Monte Carlo approach is used to quantify variability in boundary conditions. Estimates of total Indicated resource are confined to 3 geothermal systems; Apacheta, El Tatio and Tolhuaca, yielding a total value of 228 ± 154. MWe. The estimates of the total Inferred resources for Chile include 6 geothermal systems and yield a total value of 431 ± 321. MWe. Standard deviation reflects the high variability of reservoir specific parameters for each system. A set of 65 favorable geothermal areas are proposed as the most likely future development targets. Finally, eight of them have initial exploration results that suggest they are highly favorable targets as potential geothermal resources.

58 GEOSCIENCES↗
DOE OSTI2024

EverGREEN 2045: An Energy Mix to Decarbonize Washington State

Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

GOOML: Geothermal Operational Optimization with Machine Learning

Geothermal Operational Optimization with Machine Learning (GOOML) is a project focused on maximizing increased availability and capacity from existing industrial-scale geothermal generation assets. The GOOML project will develop a suite of machine learning-based algorithms that analyze historical production datasets and provide predictive setpoints for geothermal field operations. Historical datasets from New Zealand and the US will provide the input to develop digital geothermal system twins which allow prediction of market conditions, maintenance operations and steamfield optimization. The algorithms will identify key parameters within fields and suggest setpoints for components of the system to maintain optimal generation. Set-points can be instructed to follow mass flow restrictions, generation maximization and optimal field/reservoir balance and give field operators a guide by which generation can be optimized. The datasets that will be used to develop GOOML are sourced from operating geothermal fields in New Zealand and the United States with varying degrees of complexity. This will ensure that most geothermal systems can utilize the GOOML tool to assist in optimizing operations. GOOML aims to achieve a step-change in geothermal operations by developing state-of-the-art machine learning algorithms, comprehensive data analytics, and a first-of-its-kind automated, intelligent geothermal system model.

algorithms↗
DOE OSTI2012

Advanced Horizontal Well Recirculation Systems for Geothermal Energy Recovery in Sedimentary and Crystalline Formations

There is increased recognition that geothermal energy resources are more widespread than previously thought, with potential for providing a significant amount of sustainable clean energy worldwide. Recent advances in drilling, completion, and production technology from the oil and gas industry can now be applied to unlock vast new geothermal resources, with some estimates for potential electricity generation from geothermal energy now on the order of 2 million megawatts. The primary objectives of this DOE research effort are to develop and document optimum design configurations and operating practices to produce geothermal power from hot permeable sedimentary and crystalline formations using advanced horizontal well recirculation systems. During Phase I of this research project Terralog Technologies USA and The University of California, Irvine (UCI), have completed preliminary investigations and documentation of advanced design concepts for paired horizontal well recirculation systems, optimally configured for geothermal energy recovery in permeable sedimentary and crystalline formations of varying structure and material properties. We have also identified significant geologic resources appropriate for application of such technology. The main challenge for such recirculation systems is to optimize both the design configuration and the operating practices for cost-effective geothermal energy recovery. These will be strongly influenced by sedimentary formation properties, including thickness and dip, temperature, thermal conductivity, heat capacity, permeability, and porosity; and by working fluid properties.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Advanced Horizontal Well Recirculation Systems for Geothermal Energy Recovery in Sedimentary Formations

There is increased recognition that geothermal energy resources are more widespread than previously thought, with potential for providing a significant amount of sustainable clean energy worldwide. Recent advances in drilling, completion, and production technology from the oil and gas industry can now be applied to unlock vast new geothermal resources, with some estimates for potential electricity generation from geothermal energy now on the order of 2 million megawatts. Terralog USA, in collaboration with the University of California, Irvine (UCI), are currently investigating advanced design concepts for paired horizontal well recirculation systems, optimally configured for geothermal energy recovery in permeable sedimentary and crystalline formations of varying structure and material properties. This two-year research project, funded by the US Department of Energy, includes combined efforts for: 1) Resource characterization; 2) Small and large scale laboratory investigations; 3) Numerical simulation at both the laboratory and field scale; and 4) Engineering feasibility studies and economic evaluations. The research project is currently in its early stages. This paper summarizes our technical approach and preliminary findings related to potential resources, small-scale laboratory simulation, and supporting numerical simulation efforts.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

High Temperature Perforating System for Geothermal Applications

The objective of this project is to develop a perforating system consisting of all the explosive components and hardware, capable of reliable performance in high temperatures geothermal wells (>200 ºC). In this light we will focused on engineering development of these components, characterization of the explosive raw powder and developing the internal infrastructure to increase the production of the explosive from laboratory scale to industrial scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Simulations of carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley—Sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis

Characterizing the faults and fractures that provide flow pathways for efficient geothermal energy production is critical for design of sustainable geothermal energy production. Both natural faults and stimulated fractures in enhanced geothermal systems (EGS) are difficult to image and map by seismic methods because hot brine filling the fractures and faults does not create a strong seismic property contrast relative to surrounding rock. We investigate here the technical feasibility of using supercritical CO 2 (scCO 2 ) injection into faults in a single-well push-pull scenario to characterize the hydraulic properties of the fault zone by emplacing scCO 2 that can serve as a contrast fluid for seismic monitoring. We develop a conceptual and numerical reservoir model of two intersecting faults based on the Dixie Valley geothermal system in Nevada, USA.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Recent Thermal and Hydraulic Stimulation Results at Raft River, ID EGS Site

The Raft River geothermal system, located 160 km northwest of Salt Lake City, Utah is the site of a Department of Energy Enhanced Geothermal System (EGS) stimulation demonstration project. The target well RRG-9 ST-1, is roughly 1.6 km (1 mile) south of the power plant. This well has undergone a series of thermal and hydraulic stimulation treatments. Furthermore, the well passes through approximately 1,524 m MD (5,000 ft. MD) of laterally discontinuous Quaternary and Tertiary volcanoclastic and volcanic rocks that unconformably overlie the Precambrian basement. The Elba Quartzite formation located in the Precambrian basement is the target zone for the stimulation program. Fluid injected into the well exits through a fracture zone in the Elba Quartzite at 1,567 m TVD (5,140 ft. TVD). In June 2013 low-rate stimulation began at RRG-9 ST-1 using injection water from the geothermal plant. The average injection rate, temperature, and well head pressure of the low-rate stimulation was 163 Lpm (43 gpm), 34°C, and 1,931kPa (280 psig), respectively. This injection continued through late August of 2013 when wellhead pressures were intentionally increased to approximately 5,516 kPa (800 psig) at approximately 984 Lpm (260 gpm). From September 12 to September 24, 2013 cold well water was injected. The average surface injection temperature was approximately 12°C. On September 25, 2013 injection of the warmer plant water was resumed. This was continued through the rest of 2013 and into 2014. Between April 1, 2014 and April 4, 2014, a higher rate hydraulic stimulation was conducted. Colder water (~10°C) was injected at rates of 20 bpm to 30 bpm (3,178 Lpm to 4,770 Lpm) at wellhead pressures of 5,861 kPa (850 psig) over approximately 24 hours. Microseismic activity was recorded near the Tertiary-Precambrian contact. Subsequently, injection of water from the plant was resumed. As of mid-January, 2015, over 666 million liters (176 million gallons) have been injected into the well. The fate of this water is the subject of ongoing numerical analyses and continuous site monitoring. Various analyses have been implemented to monitor and assess the ongoing stimulation program. Modified Hall plot analysis shows increasing conductivity and/or a decreasing skin factor around the wellbore. Since April, 2014, the injectivity index has increased significantly from 0.28 Lpm/kPa (0.5 gpm/psig) to 0.93 Lpm/kPa (1.7 gpm/psig).

enhanced geothermal system↗
DOE OSTI2015

Characterizing Structural Controls of EGS-Candidate and Conventional Geothermal Reservoirs in the Great Basin: Developing Successful Exploration Strategies in Extended Terranes

We conducted a comprehensive analysis of the structural controls of geothermal systems within the Great Basin and adjacent regions. Our main objectives were to: 1) Produce a catalogue of favorable structural environments and models for geothermal systems. 2) Improve site-specific targeting of geothermal resources through detailed studies of representative sites, which included innovative techniques of slip tendency analysis of faults and 3D modeling. 3) Compare and contrast the structural controls and models in different tectonic settings. 4) Synthesize data and develop methodologies for enhancement of exploration strategies for conventional and EGS systems, reduction in the risk of drilling non-productive wells, and selecting the best EGS sites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Innovative computational tools for reducing exploration risk through integration of water-rock interactions and magnetotelluric surveys

Mapping permeability distributions in geothermal reservoirs is essential for reducing the cost of geothermal development. To avoid the cost and sampling bias of measuring permeability directly through drilling, we require remote methods of imaging permeability such as geophysics. Electrical resistivity (or its inverse, conductivity) is one of the most sensitive geophysical properties known to reflect long range fluid interconnection and thus the likelihood of permeability. Perhaps the most widely applied geophysical methods for imaging subsurface resistivity is magnetotellurics (MT) due to its relatively great penetration depths. A primary goal of this project is to confirm through ground truthing at existing geothermal systems that MT resistivity structure interpreted integratively is capable of revealing permeable fluid pathways into geothermal systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Environmental Impact Calculations for Geothermal DDU system on WVU Campus

This dataset contains all the inputs used and output produced from Matlab for the environmental analysis of an improved hybrid geothermal district heating and cooling (GDHC) system with a heat pump, without a heat pump, and for a hot water GDHC. Detailed descriptions of the contents of this repository are provided below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Unsupervised learning from three-component accelerometer data to monitor the spatiotemporal evolution of meso-scale hydraulic fractures

Enhanced geothermal systems can provide a substantial share of the global energy demand. There exist several hurdles in the engineering implementations of such geothermal systems. One such hurdle is the accurate monitoring of the fracture networks created in subsurface through hydraulic stimulation of these systems. Micro seismicity associated with the stimulation is the primary means to locate the event hypocenters for estimating the stimulated rock volume. Existing methods for location the hypocenters are restricted to only the highest amplitude impulsive signals that are simultaneously detected on several sensors. Consequently, a large portion (usually ~99%) of the measurements are left unused. In this paper, an unsupervised manifold-approximation followed by clustering of 3-component accelerometer data is used to analyze the seismicity recorded on a monitoring well. With this method, a larger portion of the measured signal is used for the monitoring of the hydraulic fracture network. We analyze the EGS Collab experiment 1 microseismic data, recorded at the Sanford Underground Research Facility, South Dakota. Using the data from a single three-component accelerometer, the polarization features viz. Azimuth, incidence, rectilinearity, and planarity are used as inputs for the unsupervised manifold approximation followed by clustering. Our study shows that density-based clusters in the projected 3D space correspond to distinct types of hydraulically fractured zones around the injection point. Finally, we show that the temporal evolution of these clusters can be used to track fracture creation and propagation.

58 GEOSCIENCES↗
DOE OSTI2024

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 identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from 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. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (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. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States

This dataset presents the results of techno-economic simulations performed using the Distributed Geothermal Market Demand Model (dGeo) to evaluate the feasibility of Enhanced Geothermal Systems (EGS)-based district heating in the Northeastern United States. Developed by the National Renewable Energy Laboratory (NREL), dGeo is a geospatially resolved, bottom-up modeling framework designed to explore the deployment potential of geothermal distributed energy resources. The dataset, created as part of the Cornell EGS Ground-Truthing Project, provides census tract-level data that includes inputs and outputs such as thermal demand, road length, energy prices, geothermal system sizing, annual energy contributions from geothermal and natural gas peaking boilers, system capital costs (CAPEX), operation and maintenance costs (OPEX), and the levelized cost of heat (LCOH). Key simulation parameters include geothermal gradients, measured well depths, production temperatures, and district heating piping lengths based on S1400 neighborhood road lengths. The simulations assume a target bottom hole temperature of 80C and the development of new district heating networks in each census tract.

15 GEOTHERMAL ENERGY↗