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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Geothermal Reserve Pits: Considerations for Installation on BLM-Administered Lands

Reserve pits, also known as sumps, are a common aspect of geothermal drilling operations. This paper describes the Bureau of Land Management's regulatory authorities and key environmental considerations associated with geothermal reserve pits. Reserve pit design, the need for environmental compliance measures, and reclamation approaches will vary depending on site-specific conditions. Groundwater and wildlife impacts are the most common environmental considerations related to reserve pits. In some cases, regulations or groundwater or soil conditions necessitate the use of a synthetic liner. However, the chemical composition of most geothermal drilling fluids and muds, completion fluids, and produced fluids that are discharged to reserve pits does not warrant pit liners. The potential for hazardous fluids, high water temperatures, and entrapment are concerns for wildlife. Common wildlife impact avoidance and mitigation measures include fencing, netting, and escape ramps. The need for these measures depends on localized site and environmental conditions. There are requirements to reclaim reserve pits following geothermal drilling operations. Reserve pits often remain in place to accommodate multiple phases of drilling and well testing. They are eventually backfilled and decommissioned.

BLM↗
DOE OSTI2023

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost: Preprint

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This in turn is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in EGS binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost.

ambient temperature↗
DOE OSTI2023

GeoThermalCloud for EGS – An Open-source, User-friendly, Scalable AI Workflow for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting relatively cold water into subsurface fractures, which are in contact with hot dry rock, and brought back to surface through production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. In this short conference paper, we present a reproducible workflow for modeling EGS. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and high-performance computing. This GTC framework is currently being made open-source, user-friendly, and reproducible through python scripts as well as Google Colab/Jupyter Notebooks. This GTC for EGS modeling scripts are made available at https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS and will constantly be updated to cater for geothermal community. Current GTC framework provides scripts to train deep learning (DL) models for techno-economics and data worth analysis. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. This short paper provides details on the scripts to curate, process, and train DL models. The scripts can easily be modified to train on databases generated by other popular open-source simulators such as PFLOTRAN, STOMP, TOUGH, and GEOSX or commercial software such as ResFrac and COMSOL.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Geothermal Uncertainty Representation in reV: the Renewable Energy Potential Model

We present a preliminary methodology for including geothermal resource uncertainty into the Renewable Energy Potential model, which estimates potential capacity and costs on a gridded surface at the national scale. The uncertainty outputs characterize the 10th, 50th and 90th percentile for geothermal resources using two energy capacity estimation equations. We then present a method and results that demonstrate how other geologic data layers, which may be indicative of permeability, can be used to inform the mean and standard deviation of the geothermal capacity. We demonstrate how the mean and standard deviation can be defined or partially informed by using collocated regression estimates and estimate errors, respectively . These regression results are from 36 observed geothermal power plants in the Great Basin region and are also used to benchmark the P10-P90 calculations.

exclusions↗
DOE OSTI2021

Significance and complications of drilling fluid rheology in geothermal drilling: A review

The harsh downhole conditions of high pressure and high temperature (HPHT) encountered in geothermal wells make the drilling operation challenging. Drilling in such environments requires a special drilling mud formulation with high thermal stability and good rheological properties to fulfill the drilling fluid functions. Therefore, great efforts should be put into selecting the suitable drilling fluid, optimize and monitor the drilling fluid properties throughout drilling operations, and predicting its performance under downhole conditions. Rheological properties significantly impact many drilling parameters such as hole cleaning, fluid and wellbore stability, wellbore hydraulics, torque and drag, and other drilling issues. This paper discusses water-based drilling fluids' flow behavior under HPHT conditions and highlights the significance of fluid rheology in geothermal drilling. The common challenges and complications related to fluid rheology encountered in geothermal drilling are addressed in this paper, such as hole cleaning, wellbore hydraulics, and drilling fluid stability. This article also reviews the recent advances in drilling mud systems, rheology enhancement, and rheological properties measurements at surface and subsurface conditions. Furthermore, the rheology models of drilling fluid at elevated temperatures are reviewed to fully understand their flow behavior and establish a method for drilling engineers to optimize fluid formulations for geothermal drilling.

58 GEOSCIENCES↗
DOE OSTI2021

U.S. lithium resources from geothermal and extraction feasibility

As the demand for electric vehicles (EVs) increases, demand for lithium (Li) is expected to grow over the coming decade. To satisfy the demand for rechargeable batteries, it is imperative to devise solutions for sufficient Li production. Additionally, even though commercial Li currently comes from conventional saline salar brine and spodumene ore extractions, efforts to retrieve Li from geothermal brines are increasing in popularity. In this paper, we evaluate the United States’ potential to supply Li from geothermal brines using Systems Dynamics modeling. The main goals are to assess (1) the viability of US Li supply from geothermal brines and (2) the potential supply chain impact of extracting Li from this source. Results show that Li supply from geothermal brines could (1) reach around 4% to 8% of total US Li supply and (2) be economically viable.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Geo-Responsive Chemomechanics in Aluminum Oxyhydroxide via Alkali-Driven Dehydroxylation for Supercritical Geothermal Systems

Widespread use of enhanced geothermal systems can revolutionize global renewable electrical power access, yet its advancement is hindered by the inherent instability of Portland cement-based chemistries for geothermal well construction under high-temperature corrosive conditions. Here, in this work, we demonstrate the tunable mechanical performance of aluminum oxyhydroxides as cementitious materials through an alkali-controlled dehydroxylation reaction pathway for long-term applications under supercritical geothermal environments. Notably, the synthesized aluminum oxyhydroxides demonstrate remarkable stability, maintaining superior mechanical performance under supercritical conditions for over 30 days. Synchrotron X-ray diffraction, spectroscopy measurements and geochemical thermodynamic modeling uncover that the gibbsite dehydroxylation pathway functions as a key dial for tuning the chemomechanics, rendering the aluminum oxyhydroxide a strong cementitious material. By uncovering the mechanistic role of alkali-driven dehydroxylation, this work proposes a cementitious chemistry distinct from conventional Portland cement and geopolymer-dominated alkali-activated systems, laying the groundwork for developing next-generation cementitious materials for supercritical geothermal energy exploitation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Deep Direct-Use Geothermal Feasibility Study for Hawthorne NV

The Hawthorne Nevada, deep direct-use geothermal study is a two-year effort funded by the U.S. Department of Energy to determine the techno-economic feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the public facilities of the city of Hawthorne and Mineral County. The approach links a production side analysis (PSA) and a demand side analysis (DSA) into a whole-system analysis (WSA) to provide an integrated assessment of the resource and the probability of delivering economically viable direct-use energy to Hawthorne. Hawthorne, Nevada is in the western part of the Basin and Range province and has been the focus of geothermal investigations for over 40 years. Over the last 15 years, several studies completed by the U.S. Navy Geothermal Program Office (GPO) in conjunction with industry professionals quantified the existence of several low temperature geothermal prospects, the most promising of which is called Prospect A. The promise of Prospect A is based on drilling and flow testing that produced ~100 °C water at flow rates of up to 31 l/s (500 gallons per minute). Measured productivity indexes range from 40-85 l/s/MPa, suggesting a warm and productive heat source. Despite the promise of the resource, uncertainties in its spatial extent and long-term sustainability mean that techno-economic analyses must include probabilities of the sustainability of the resource under different operating scenarios. Here, the PSA is conducted by integrating a wide range of disparate data to estimate lognormal P90, P50, and P10 resource capacities. These capacities are used as input to a thermal-hydrologic (T-H) model to estimate thermal drawdown for each capacity estimate for several different DSA scenarios. Using a systems-based approach, the WSA links the dynamic T-H simulations of the PSA/DSA combinations with the techno-economic model GEOPHIRES to account for both the temporal dynamics and uncertainties in the system to produce probabilistic distributions of several performance metrics including the levelized cost of heat (LCOH) and the return on investment (ROI). This report is the final delivery for the project and documents the study's activities and results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

GeoTGo: AI/ML software for development of community geothermal resources

For effective and equitable outcomes in achieving the national goal of net-zero carbon emissions, communities must be not only included, but even lead the implementation of innovative green-energy technologies. Collaborations with communities should happen through informed decision-making, community-centered research and engagement of stakeholders at the local, state, and regional levels. Community-led research and implementation are fundamental to achieving success. These collaborations include rule makers, environmental regulators, clean energy industries, and technology researchers and developers. Unfortunately, many green infrastructure initiatives still adhere to a top-down and expert-driven process of site selection and design without awareness and acknowledgment of public engagement needs. This can lead to costly delays, including lawsuits, and ultimately less than desired or lacking outcomes as well as missed opportunities1. Geothermal, like many new technologies whose social and economic impacts are not fully understood, often cause disproportionately high adverse effects on disadvantaged communities. These effects can be related to human health, environmental, climate, and other cumulative impacts, as well as the accompanying economic challenges of these impacts. We are focusing our work on the needs of the New Mexico Native American Pueblos and Tribes (NMP&T). To address these needs, we are developing a novel web-based interactive software and user friendly interface called GeoTGO (https://geotgo.com) that provides everything that is needed for communities to better understand and develop their geothermal resources. We will bridge the gap between technology advancements and community needs by facilitating the interactions between the geothermal industry, regulators, stakeholders, and end-users. GeoTGO will merge data, software (including data analysis, text mining, artificial intelligence, and modeling tools), knowledge, expertise, and experience to provide fast processing and dissemination of the latest information about cutting-edge geothermal technologies to users and communities. More information about the project is available at https://envitrace.com/projects/geotgo.html.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

A Technology Roadmap for Advanced Geothermal Well Construction

Recent analysis has shown that by 2050, geothermal energy can supply up to 90 GW of power to the U.S. electrical grid. Reducing the lifecycle cost of geothermal wells is critical to achieving this level of adoption. While time-related costs of drilling remain an important issue, there is also a need to focus on the costs associated with casing and cementing of geothermal wells. This report provides a roadmap of R&D activities needed to reduce the life cycle cost of casing and cementing while improving life-of-well performance. The purpose of the roadmap is to develop priorities for R&D in the areas of (1) high-performance and cost-effective materials for target geothermal well conditions, (2) well construction methods and techniques to reduce construction costs, and (3) methods and techniques to decrease to decrease long-term operating costs. The roadmap sets targets for the next 10-year period and purposely excludes R&D efforts into improved rock reduction. The roadmap was developed by a joint working group of experts from Oak Ridge National Laboratory, Brookhaven National Laboratory, and Sandia National Laboratories as well as 35 experts from industry and academia. Input from a series of information gathering sessions was used to inform and guide the development of the roadmap.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

FEED Study for Climeworks Direct Air Capture at a California Geothermal Facility with Long-Term Storage (Final Scientific/Technical Report)

The overall objective of the project is to execute and complete a front-end engineering and design (FEED) study of an advanced Direct Air Capture (DAC) and Storage (DAC+S) system that is capable of removing and sequestering a minimum of 5,000 tonne/yr of CO 2 from the air based on cradle-to-gate life cycle assessment (LCA). The project will examine retrofitting and utilizing an existing domestic geothermal resource. The selected DAC system will be technology from Climeworks AG (Climeworks) that consists of an adsorption-desorption process to remove CO 2 from ambient air by using a selective filter. The geothermal host site is operated by Ormat Technologies Inc. (ORMAT). The DAC system will capture CO 2 using thermal energy from the host geothermal resource. This Final Scientific/Technical Report is a collection of the deliverables for the project. The project team was not able to successfully complete all the necessary tasks for this project. Shortly after the start of the project, two (2) project partners removed themselves from the study. The Awardee attempted to find a replacement for the direct air capture technology provider and geothermal energy provider. Due to this the awardee submitted a letter of cancellation for the project, letter is attached in the appendix. No funds were expended during the course of the project.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2021

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A VOI Web Application for Distinct Geothermal Domains: Statistical Evaluation of Different Data Types within the Great Basin

The Great Basin region contains different domains that have different structural and hydrothermal flow patterns. Depending on the characteristics of these patterns, certain data types may be more successful at detecting hidden geothermal resources. In this paper, we quantitatively evaluate if certain data types are more successful in certain domains. Given different aquifer, strain and structural conditions, we explore which data types statistically reveal positively labeled geothermal sites. We utilize value of information (VOI) metrics to help quantify the reliability of data types to discriminate against "positive" and "negative" labeled geothermal sites. We also evaluate how kernel density estimation can help generalize the statistics that inform VOI, which is necessary given the limited data in geothermal exploration. Except for the Carbonate Aquifer, the highest ranking of the Vimperfect is the Local Structural Setting. Next, the slip and dilation tendency is first for Carbonate Aquifer and second for Central Nevada Seismic Belt and Western Great Basin. For the Carbonate Aquifer, heat flow is has the lowest Vimperfect value compared to the other three domains, which is consistent with the understanding of how heat flow measurements are masked by regional groundwater flow.

Bayesian analysis↗
DOE OSTI2024

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada: Preprint

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead-observed temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260degreesF (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2025

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260 degrees F (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2024

Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI

This data includes results on an analysis of existing and projected energy, cost, and carbon for the City of Ann Arbor - District Geothermal Design and Deployment to Equitably Decarbonize Low Income Neighborhoods in Ann Arbor project. The scope of the project includes designing and implementing a geothermal district heating and cooling system that reduces thermal heating and cooling load by 75% and greenhouse gas emissions by 40% in the project area (262 households, 6 commercial buildings). The existing neighborhood was modeled using Design Builder, an EnergyPlus software, to understand the current energy load. The energy model was then flipped to reflect the designed district geothermal heating and cooling system to project the effect on energy, carbon, and cost. This dataset includes the analysis files utilized and created for this study. There are 3 categories of data: 1) existing/benchmarking, 2) energy modeling, and 3) post processed calculations. This follows the methodology and process of the project team, which is fully explained in file 00_Technical Economic Environmental Assessment. All uses of data are referenced throughout this assessment to their respective files included below.

15 GEOTHERMAL ENERGY↗