Search NASA⌕ Search

SEARCH · Search NASA

Results for “geothermal analysis”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Geothermal Prospector: Supporting Geothermal Analysis Through Spatial Data Visualization and Querying Tools

Determining opportunities for geothermal energy can involve a significant investment in data collection and analysis. Analysts within a variety of industry and research domains collect and use these data; however, determining the existence and availability of data needed for a specific analysis activity can be challenging and represents one of the initial barriers to geothermal development [2]. This paper describes the motivating factors involved in designing and building the Geothermal Prospector application, how it can be used to reduce risks and costs related to geothermal exploration, and where it fits within the larger collection of tools that is the National Geothermal Data System (NGDS) [5].

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Washington Play Fairway Analysis Geothermal Heat and Permeability Potential Geodatabases

This file contains file geodatabases of the Mount St. Helens seismic zone (MSHSZ), Wind River valley (WRV) and Mount Baker (MB) geothermal play-fairway sites in the Washington Cascades. The geodatabases include input data (feature classes) and output rasters (generated from modeling and interpolation) from the geothermal play-fairway in Washington State, USA. These data were gathered and modeled to provide an estimate of the heat and permeability potential within the play-fairways based on: mapped volcanic vents, hot springs and fumaroles, geothermometry, intrusive rocks, temperature-gradient wells, slip tendency, dilation tendency, displacement, displacement gradient, max coulomb shear stress, sigma 3, maximum shear strain rate, and dilational strain rate at 200m and 3 km depth. In addition this file contains layer files for each of the output rasters. For details on the areas of interest please see the 'Phase 1 Technical Report' in the download package. This submission also includes a file with the geothermal favorability of the Washington Cascade Range based off of an earlier statewide assessment. Additionally, within this file there are the maximum shear and dilational strain rate rasters for all of Washington State.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Enhanced Geothermal Shot Analysis for the Geothermal Technologies Office

In 2021, the U.S. Department of Energy (DOE) began the Energy Earthshots initiatives to accelerate breakthroughs of reliable clean energy solutions within the next 10 years. In 2022, the National Renewable Energy Laboratory (NREL) was asked by the DOE Geothermal Technologies Office (GTO) to provide analysis for developing Energy Earthshot targets for Enhanced Geothermal Systems (EGS), human-made underground reservoirs that extract thermal energy from the earth for electricity generation and/or heating applications. The Enhanced Geothermal Shot analysis is based on the technology assumptions in the 2019 GTO report GeoVision: Harnessing the Heat Beneath Our Feet. For Earthshot, we updated some of the technology cost and performance assumptions based on recent technology advances and updated the EGS resource potential to include more detailed analysis. We used the updated EGS supply cost curves to forecast the amount of geothermal electricity generation that could be deployed in the US by 2050 using a capacity expansion model. The results were used to develop a cost target for EGS. On September 8th, 2022, the Enhanced Geothermal Shot was announced. Its target - reduce the cost of EGS by 90%, to $45 per megawatt hour by 2035. This paper summarizes the cost and resource assumptions used in the Enhanced Geothermal Shot. It describes the assumptions used in the Regional Energy Deployment System (ReEDS) capacity expansion model to forecast geothermal deployment and discusses the results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Enhanced Geothermal Shot Analysis for the Geothermal Technologies Office: Preprint

In 2021, the U.S. Department of Energy (DOE) began the Energy Earthshots initiatives to accelerate breakthroughs of reliable clean energy solutions within the next 10 years. In 2022, the National Renewable Energy Laboratory (NREL) was asked by the DOE Geothermal Technologies Office (GTO) to provide analysis for developing Energy Earthshot targets for Enhanced Geothermal Systems (EGS), human-made underground reservoirs that extract thermal energy from the earth for electricity generation and/or heating applications. The Enhanced Geothermal Shot analysis is based on the technology assumptions in the 2019 GTO report GeoVision: Harnessing the Heat Beneath Our Feet. For Earthshot, we updated some of the technology cost and performance assumptions based on recent technology advances and updated the EGS resource potential to include more detailed analysis. We used the updated EGS supply cost curves to forecast the amount of geothermal electricity generation that could be deployed in the US by 2050 using a capacity expansion model. The results were used to develop a cost target for EGS. On September 8th, 2022, the Enhanced Geothermal Shot was announced. Its target - reduce the cost of EGS by 90%, to $45 per megawatt hour by 2035. This paper summarizes the cost and resource assumptions used in the Enhanced Geothermal Shot. It describes the assumptions used in the Regional Energy Deployment System (ReEDS) capacity expansion model to forecast geothermal deployment and discusses the results.

analysis↗
DOE OSTI2020

Play Fairway analysis of geothermal resources across the State of Hawai‘i: 4. Updates with new groundwater chemistry, subsurface stress analysis, and focused geophysical surveys

This paper is the fourth in a series on a play fairway analysis of geothermal resources across the State of Hawai‘i. Here we describe recent exploration activities that include groundwater sampling in ten locations statewide, as well as geophysical surveys on Lana‘i, across the SW rift of Haleakala Volcano (Maui), and surrounding Mauna Kea Volcano (Hawai‘i Island). We derive a first-order method for computing topographic stress using Green’s functions, finding that topography can induce appreciable crustal stress. We develop a new method for incorporating depth information about resistivity, density, and topographic stresses into our previously published equations to calculate resource probability and confidence. We incorporate newly collected and modeled data into our calculations to update statewide maps of probability and confidence. Lana‘i Island and southeast Mauna Kea are identified as the top targets for exploratory drilling. The east rift of Haleakala Volcano, the southern-most region of Mauna Loa’s SW rift (Hawai‘i Island), and central Kauai are identified as targets for geophysical surveying.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Utilization Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. The submission includes data pertinent to the methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau Places within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped risk of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. UPDATE: Newer version of the Utilization Analysis has been added here: https://gdr.openei.org/submissions/878

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Appalachian Basin Play Fairway Analysis: Thermal Quality Analysis in Low-Temperature Geothermal Play Fairway Analysis (GPFA-AB)

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS). This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain item description documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations. Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015. Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted. UPDATE: Newer version of the Thermal Quality Analysis has been added here: https://gdr.openei.org/submissions/879 (Also linked below) Newer version of the Combined Risk Factor Analysis has been added here: https://gdr.openei.org/submissions/880 (Also linked below)

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Analysis of Geothermal Reservoir and Well Operational Conditions using Monthly Production Reports from Nevada and California

When conducting techno-economic analysis of geothermal systems, assumptions are typically necessary for reservoir and wellbore parameters such as producer/injector well ratio, production temperature drawdown, and production/injection temperature, pressure and flow rate. To decrease uncertainty of several of these parameters, we analyzed field data reported by operators in monthly production reports. This paper presents results of a statistical analysis conducted on monthly production reports at 19 power plants in California and Nevada covering 196 production wells and 175 injection wells. The average production temperature was 304 degrees F (151 degrees C) for binary plants and 310 degrees F (154 degrees C) for flash plants. The average injection temperature was 169 degrees F (76 degrees C) for binary plants and 173 degrees F (78 degrees C) for flash plants. The average production temperature drawdown was 0.5% per year for binary plants and 0.8% per year for flash plants. The average production well flow rate was 112 L/s for binary plant wells and 62 L/s for flash plant wells. For all 19 plants combined, the median injectivity index value was 3.8 L/s/bar, and the average producer/injector well ratio was 1.6. As an additional example of analysis using data from monthly production reports, a coupled reservoir-wellbore model was developed to derive productivity curves at various pump horsepower settings. The workflow and model were applied to two example production wells.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Retrospective Analysis of Geothermal Mineral Recovery and Domestic Resource Assessment - References

This reference database in RIS format contains all of the references that were collected as part of our retrospective analysis of geothermal mineral recovery (REE and Li) activities and domestic resource assessment. The outputs detail the chemistry and molecular processes used in lithium recovery from geothermal brines. The articles included include information about the study including more information on geothermal brines and the technologies used for recovering lithium from geothermal brines.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Improvements in 2016 to Natural Reservoir Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

*These files add to and replace same-named files found within Submission 559 (hover over file display names to see actual file names in bottom-left corner of screen)* The files included in this submission contain all data pertinent to the methods and results of a cohesive multi-state analysis of all known potential geothermal reservoirs in sedimentary rocks in the Appalachian Basin region, ranked by their potential favorability. Favorability is quantified using three metrics: Reservoir Productivity Index for water; Reservoir Productivity Index; Reservoir Flow Capacity. The metrics are explained in the Reservoirs Methodology Memo (included in zip file). The product represents a minimum spatial extent of potential sedimentary rock geothermal reservoirs. Only natural porosity and permeability were analyzed. Shapefile and images of the spatial distributions of these reservoir quality metrics and of the uncertainty on these metrics are included as well. UPDATE: Accompanying geologic reservoirs data may be found at: https://gdr.openei.org/submissions/881 (linked below).

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Analysis of Geothermal Resources in Three Texas Counties

This project updates the geothermal resources beneath our oil and gas fields, as part of the research for the Texas GEO project. This report "Analysis of Geothermal Resources in Three Texas Counties" (October 2020) improves on previous mapping of the Texas resources for the counties of Crockett (West Texas), Jackson (central Gulf Coast) and Webb (South Texas). Through additional bottom-hole temperatures (BHT), the number of well sites increased from 532 to 5,410 in total for these counties. The improved methodology to calculate formation temperatures from 3.5 km (11,500 ft) to 10 km (32,800 ft) includes thermal conductivity values more closely related to the actual county geological formations, incorporated radiogenic heat production of formations, and the related mapped depth to basement. The results show deep temperatures as hotter than previously calculated, with temperatures of 150 degrees Celcius possible for Webb County between depths of 2.6 - 5.1 km, Jackson County between depths 3.0 - 5.4 km, and Crockett County between depths of 2.7 - 8.0 km.

10 km↗
DOE OSTI2018

Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

In this study, we have undertaken a robust analysis of the global supply chain and manufacturing costs for components of Organic Rankine Cycle (ORC) Turboexpander and steam turbines used in geothermal power plants. We collected a range of market data influencing manufacturing from various data sources and determined the main international manufacturers in the industry. The data includes the manufacturing cost model to identify requirements for equipment, facilities, raw materials, and labor. We analyzed three different cases; 1) 1 MW geothermal ORC Turboexpander 2) 5 MW ORC Turboexpander 3) 20 MW geothermal Steam Turbine

15 GEOTHERMAL ENERGY↗
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 OSTI2016

Play fairway analysis of geothermal resources across the state of Hawaii: 2. Resource probability mapping

We develop a new geostatistical method to combine evidence provided by diverse geological data sets and produce maps of geothermal resource probability. The application is to the State of Hawaii, and the data sets include the locations and ages of mapped volcanic centers, gravity and magnetotelluric measurements, groundwater temperature and geochemistry, ground surface deformation, seismicity, water table elevation, and groundwater recharge. Using the basic principles of Bayesian statistics, these data and expert knowledge about the effects and importance of the data are used to compute the probabilities of the primary resource qualities of elevated subsurface heat, reservoir permeability, and reservoir fluid content. The product of these marginal probabilities estimates the joint probability of all three qualities and hence the probability of a successful geothermal prospect at each map point. An analogous set of algorithms is used to quantify the confidence in the probability at each point. Not surprisingly, we find that successful geothermal prospects are most probable on the active volcanoes of Hawaii Island, including the area of Hawaii’s single geothermal energy plant. Probability decreases primarily with shield volcano age, being relatively moderate in select locations on Maui and Lanai, relatively low on Oahu, and minimal on Kauai. Future exploration efforts should consider these results as well as the practical, societal, and economic conditions that influence development viability. Here, the difficulties of interisland power transmission mean that even areas with moderate to low probabilities are worth investigating on islands with population centers.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Play fairway analysis of geothermal resources across the State of Hawaii: 1. Geological, geophysical, and geochemical datasets

Phase 1 of a Play Fairway Analysis (PFA) of geothermal resource potential across the State of Hawaii was recently completed. The final products of this work include a statewide geothermal resource probability map, a map of confidence in this probability, an assessment of the viability of development in areas of interest, and a prioritized list of recommended future exploration activities. The intersection of subsurface heat (H), permeability (P), and fluid (F) is necessary for an optimum geothermal play. This study: (1) identified and compiled all legacy and current data relevant to Hawaii’s geothermal resource; (2) ranked these datasets in terms of their relevance to subsurface H, P, F; (3) developed a Bayesian statistical method to incorporate the data and their rankings, and produce a statewide resource probability map; (4) developed a method to assess confidence in the probability values; and (5) assessed what we term ‘development viability’ in resulting areas of interest across the state. This paper details the basic project workflow, and activities (1) and (2). It describes the rationale for including this study’s datasets: surface geologic mapping data (calderas, rift zones, volcanic vents, dikes, faults), groundwater data (temperature, Chloride:Magnesium, SiO 2 ) and geophysical data (gravity, magnetotelluric, seismic, geodetic strain), and justifies their relative rankings in terms of H, P, and F. A second paper describes activities (3) and (4) related to the statistical methodology, and a third paper describes activity (5), the development viability criteria, as well as our suggested roadmap for future exploration activities. Overall, we find that the likelihood of abundant of geothermal resources is highest on the youngest island of Hawaii, but groundwater indicators suggest there may also be resources on the other, older islands. Furthermore, the higher demand for renewable energy on the more populated islands of Maui and Oahu, as well as a high viability of development on Lanai, also motivate further exploration on these islands.

15 GEOTHERMAL ENERGY↗