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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

gas wells↗
DOE OSTI2023

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

GEOTHERMAL ENERGY↗
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↗
NASA NTRS1978

California's geothermal resource potential

According to a U.S. Geological Survey estimate, recoverable hydrothermal energy in California may amount to 19,000 MW of electric power for a 30-year period. At present, a geothermal installation in the Geysers region of the state provides 502 MWe of capacity; an additional 1500 MWe of electric generating capacity is scheduled to be in operation in geothermal fields by 1985. In addition to hydrothermal energy sources, hot-igneous and conduction-dominated resources are under investigation for possible development. Land-use conflicts, environmental concerns and lack of risk capital may limit this development.

Leibowitz, L. P.↗
DOE OSTI2017

Crossing the Barriers: An Analysis of Land Access Barriers to Geothermal Development and Potential Improvement Scenarios

Developers have identified many non-technical barriers to geothermal power development, including access to land. Activities required for accessing land, such as environmental review and private and public leasing can take a considerable amount of time and can delay or prevent project development. This paper discusses the impacts to available geothermal resources and deployment caused by land access challenges, including tribal and cultural resources, environmentally sensitive areas, biological resources, land ownership, federal and state lease queues, and proximity to military installations. In this analysis, we identified challenges that have the potential to prevent development of identified and undiscovered hydrothermal geothermal resources. We found that an estimated 400 MW of identified geothermal resource potential and 4,000 MW of undiscovered geothermal resource potential were either unallowed for development or contained one or more significant barriers that could prevent development at the site. Potential improvement scenarios that could be employed to overcome these barriers include (1) providing continuous funding to the U.S. Forest Service (USFS) for processing geothermal leases and permit applications and (2) the creation of advanced environmental mitigation measures. The model results forecast that continuous funding to the USFS could result in deployment of an additional 80 MW of geothermal capacity by 2030 and 124 MW of geothermal capacity by 2050 when compared to the business-as-usual scenario. The creation of advanced environmental mitigation measures coupled with continuous funding to the USFS could result in deployment of an additional 97 MW of geothermal capacity by 2030 and 152 MW of geothermal capacity by 2050 when compared to the business-as-usual scenario. The small impact on potential deployment in these improvement scenarios suggests that these 4,400 MW have other barriers to development in addition to land access. In other words, simply making more resources available for development does not increase deployment; however, impacts to deployment could increase when coupled with other improvements (e.g., permitting, market and/or technology improvements).

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

GeoVision: Harnessing the Heat Beneath Our Feet - Analysis Inputs and Results

This submission includes input and results data from analysis done as part of the Geothermal Technology Office's Geothermal Vision Study (GeoVision). The submission includes data for both analysis of the electricity sector and the heating and cooling sector. For the electricity sector, the submission includes geothermal resource potential and development cost inputs for the ReEDS model and ReEDS model results of projected installed capacity and generation of geothermal and other technologies under the GeoVision scenarios. It also includes results from environmental and social impacts analysis. For the cooling sector, the submission includes geothermal resource potential and development cost inputs for the dGeo model and dGeo model results of economic, market, and deployment potential.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Update to Enhanced Geothermal System Resource Potential Estimate: Preprint

The deep EGS electricity generation resource potential estimate maintained by the National Renewable Energy Laboratory was updated using the most recent temperature-at-depth maps available from the Southern Methodist University Geothermal Laboratory. The previous study dates back to 2011 and was developed using the original temperature-at-depth maps showcased in the 2006 MIT Future of Geothermal Energy report. The methodology used to update the deep EGS resource potential is the same as in the previous study and is summarized in the paper. The updated deep EGS resource potential estimate was calculated for depths between 3 and 7 km and is binned in 25 degrees C increments. The updated deep EGS electricity generation resource potential estimate is 4,349 GWe. A comparison of the estimates from the previous and updated studies shows a net increase of 117 GWe in the 3-7 km depth range, due mainly to increases in the underlying temperature-at-depth estimates from the updated maps.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Updates to Enhanced Geothermal System Resource Potential Estimate

The deep EGS electricity generation resource potential estimate maintained by the National Renewable Energy Laboratory was updated using the most recent temperature-at-depth maps available from the Southern Methodist University Geothermal Laboratory. The previous study dates back to 2011 and was developed using the original temperature-at-depth maps showcased in the 2006 MIT Future of Geothermal Energy report. The methodology used to update the deep EGS resource potential is the same as in the previous study and is summarized in the paper. The updated deep EGS resource potential estimate was calculated for depths between 3 and 7 km and is binned in 25 degrees C increments. The updated deep EGS electricity generation resource potential estimate is 4,349 GWe. A comparison of the estimates from the previous and updated studies shows a net increase of 117 GWe in the 3-7 km depth range, due mainly to increases in the underlying temperature-at-depth estimates from the updated maps.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional Energy Deployment System (ReEDS) model to evaluate geothermal resource potential under different scenarios of resource depth and technology combinations through the year 2050. The study considers geothermal resource potential, natural resource conflicts, and transmission access to categorize areas into near, mid, and far deployment priorities. The dataset includes outputs from the ReEDS model, such as geothermal capacity, generation, system costs, and emissions under various economic and technical scenarios. Favorability site data with geographic coordinates and site-specific attributes (e.g., resource favorability, land type) are also provided. Supporting resources include a technical report detailing methodologies and assumptions, along with a link to the ReEDS model GitHub repository, which requires GAMS and Python software for execution.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Shallow Geothermal Potential of the Snake River Plain

The Snake River Plain (SRP) terrestrial heat flow and subsurface thermal regime are not well understood but are important for assessing the local geothermal resource potential, both for conventional and for Enhanced Geothermal Systems (EGS) development in the region. Resource evaluation for the SRP is complicated by the disparate data density, along with the known lateral advection of heat in the Eastern Snake River Plain Aquifer and vertical heat transport by fluids in the bounding faults, primarily in the southwestern section. Fortunately, recent studies, e.g., the Snake River Plain Play Fairway Analysis, the Idaho FORGE site, and site-specific investigations, which included drilling within the Camas Prairie and on the Mountain Home Air Force Base, near Twin Falls, and in the Eastern Snake River Plain as part of the HOTSPOT Project, add both additional drilling and geophysical data. The SMU Geothermal Laboratory has conducted detailed studies of SRP tectonics and heat flow since the 1970's and used this knowledge as part of the EGS geothermal potential estimation for the conterminous United States in 2006 and again in 2011, calculating geothermal potential from 3.5 km to 10 km depth. Recent temperature modeling refined the calculation methodology to estimate shallow (1 km to 4 km) resource potential using an improved thermal conductivity model and incorporation of shallow groundwater flow. By incorporating the new SRP geology, geophysics, and 206 thermal data sites into the SMU thermal modeling methodology, this project updates the resource estimate for the SRP, and generates new temperature-at-depth maps for the shallow subsurface (1 km to 4 km). The project results highlight the EGS potential resource areas (=150°C) and areas with more exploration risks based on minimal and/or low-quality data. The newest temperature modeling results suggest EGS potential is near five times greater in the SRP than previously estimated.

EGS↗
DOE OSTI2023

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2024

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2023

Renewable Energy Potential Model: Geothermal Supply Curves

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. The included paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results provided here should be considered with care due to the high uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for three scenarios: two hydrothermal (3.5km depth, USGS heat flow & SMU temperatures respectively) and one EGS (4.5km depth, SMU temperatures). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Low-Temperature Geothermal Geospatial Datasets: An Example from Alaska: Preprint

This project is part of a broader effort focused on geothermal heating and cooling with the purpose of demonstrating the multi-faceted value of integrating GHC/GHX into national decarbonization plans and community energy plans. Currently, there is a need to better define and evaluate low-temperature geothermal resource potential to provide the basis for supporting private sector investment. For shallow GHC/GHX fields, there is no formal compilation of subsurface characteristics shared among industry practitioners that can improve system design and operations. Alaska is specifically noted in this work, because heretofore, it has not received a similar focus in geothermal potential evaluations as the contiguous United States. The methodology consists of leveraging relevant data generate a baseline low-temperature resources (< 150 degrees C) geospatial dataset to compare and analyze information accessible to anyone trying to understand the potential of GHC/GHX and small-scale low-temperature geothermal power in Alaska (e.g., energy modelers, communities, planners, and policymakers). Importantly, this project is identifying data related to (1) the evaluation of GHC/GHX in the shallow subsurface, and (2) the evaluation of low-temperature geothermal resource availability. Additionally, data is being compiled to assess repurposing of oil and gas wells to contribute co-produced fluids toward the geothermal direct use and heating and cooling resource potential. The goal of this project is facilitating future deployment of GHC/GHX analysis and community-led programs and update the low-temperature geothermal resources assessment of Alaska. A better understanding of shallow potential for geothermal heat exchange (GHX) will improve design and operations of highly efficient GHC systems. The deployment and impact that can be achieved for low temperature geothermal resources will contribute to decarbonization goals and facilitate widespread electrification by shaving and shifting grid loads.

bottom-hole temperature↗
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↗