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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantification of the Impact of Acidified Brine on Fracture-Matrix Transport in a Naturally Fractured Shale Using in Situ Imaging and Modeling

Understanding flow, transport, chemical reactions, and hydromechanical processes in fractured geologic materials is key for optimizing a range of subsurface processes including carbon dioxide and hydrogen storage, unconventional energy resource extraction, and geothermal energy recovery. Flow and transport processes in naturally fractured shale rocks have been challenging to characterize due to experimental complexity and the multiscale nature of quantifying continuum scale descriptions of mass exchange between micrometer-scale fractures and nanometer-scale pores. In this study, we use positron emission tomography (PET) to image the transport of a conservative tracer in a naturally fractured Wolfcamp shale core before and after the core was exposed to low pH brine conditions. Image-based experimental observations are interpreted by fitting an analytical transport model to fracture-containing voxels in the core. Results of this analysis indicate subtle increases in matrix diffusivity and a slightly more uniform fracture velocity distribution following exposure to low pH conditions. These observations are compared with a multicomponent one-dimensional reactive transport model that indicates the capacity for a 10% increase in porosity at the fracture-matrix interface as a result of the low pH brine exposure. This porosity change is the result of the dissolution of carbonate minerals in the shale matrix to low pH conditions. Further, this image-based workflow represents a new approach for quantifying spatially resolved fracture-matrix transport processes and provides a foundation for future work to better understand the role of coupled transport, reaction, and mechanical processes in naturally fractured rocks.

58 GEOSCIENCES↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
DOE OSTI2022

Thermal storage system with coupled tanks

Methods and apparatus are disclosed for high-efficiency thermal storage with a fluid-filled “battery” tank positioned within a fluid-filled “reservoir” tank. Fluid loops couple the tanks to a heat pump and a building. The heat pump can charge the battery tank or deliver thermal energy (cold or heat) to a building, using the reservoir tank or ambient air as a thermal energy source. The battery tank can discharge energy to the building jointly with the heat pump or, at periods of peak electricity usage, with the heat pump switched off. Operating modes allow significant savings in electricity usage and mitigate the “duck curve.” Low duty cycle usage of the reservoir enables efficient underground thermal storage with less digging than conventional geothermal technologies. Additional efficiency is achieved with phase change materials installed inside a tank or in a tank wall, providing temperature regulation. Control methods are disclosed.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Advancing Geothermal Research: Fiscal Year 2024 Accomplishments Report

Geothermal resources have delivered renewable electricity for more than 100 years, and renewable heat for far longer, but recent research and advancements have shown that geothermal is more than a 24/7 clean energy source. With the ability to also provide cooling and storage - plus the potential to access critical minerals, capture and sequester carbon, produce green hydrogen, and more - geothermal technologies and resources are emerging as key solutions to the climate crisis. In fiscal year 2024 (FY24), the National Renewable Energy Laboratory (NREL) broadened its research, development, demonstration, and deployment (RDD&D) portfolio and partnerships with exciting innovations such as next-generation geothermal technologies for power, geothermal energy networks for heating and cooling, subsurface thermal energy storage, well repurposing, and more. In support of the U.S. Department of Energy (DOE) Geothermal Technologies Office's (GTO) mission to increase geothermal energy deployment through research, development, and demonstration of innovative technologies that enhance exploration and production, NREL led impactful research in geothermal technologies and resources, market acceleration, and grid integration while also demonstrating leadership in the sector and increasing stakeholder engagement and outreach efforts.

annual report↗
DOE OSTI2020

Annual Technology Baseline: The 2020 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage. EIA data for coal, natural gas, nuclear, and conventional biopower are included for reference. This webinar presentation introduces the 2020 update to the ATB Electricity data and documentation.

capacity factor↗
DOE OSTI2026

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

accessibility↗
DOE OSTI2025

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE's) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and helping users access data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data. This paper provides an update on recent improvements made to the GDR's data lakes and automated data pipelines, including: (1) streamlining the data lake intake process, (2) better educating users on the process and requirements through a new data lakes page, (3) adding data lake direct access links to GDR data lake submission pages, (4) implementing a DAS data pipeline to convert DAS data uploaded in SEG-Y format to a standardized hierarchical data format v5 (HDF5), (5) extending this pipeline to encompass data in the GDR data lake, (6) adding metadata requirements for geospatial data, (7) making user interface/user experience (UX) enhancements to the data pipelines' documentation pages, and (8) improving the GDR's data standards and pipelines pages to better guide users in ensuring that their data is standardized by the GDR's automated data pipelines. 2024 Geothermal Resources Council. All rights reserved.

accessibility↗
DOE OSTI2023

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗
DOE OSTI2023

Environmental risks and opportunities of orphaned oil and gas wells in the United States

Abstract Hundreds of thousands of documented and undocumented orphaned oil and gas wells exist in the United States (U.S.). These wells have the potential to contaminate water supplies, degrade ecosystems, and emit methane and other air pollutants. Thus, orphaned wells present risks to climate stability and to environmental and human health, which can be reduced by plugging. To quantify environmental risks and opportunities of well plugging at the national level, we analyze data on 81 857 documented orphaned wells across the U.S. We find that > 4.6 million people live within 1 km of a documented orphaned well. 35% of the documented orphaned wells are located within 1 km of a domestic groundwater well, yet only 8% of the wells have groundwater quality data within a 1 km radius. Methane emissions from the documented orphaned wells represent approximately 3%–6% of total U.S. methane emissions from abandoned oil and gas wells, but this estimate is based on measurements at < 0.03% of U.S. abandoned wells. 91% of the documented orphaned wells overlie formations favorable for geologic storage of carbon dioxide and hydrogen, meaning that orphaned well plugging can reduce leakage risks from future storage projects. Finally, we estimate plugging costs for documented orphaned wells to exceed the $4.7 billion federal funding by 30%–80%, emphasizing the importance of prioritizing federal spending on wells with large remediation benefits. Overall, environmental monitoring data are not extensive enough to quantify risks, especially those related to air and water quality and human health. Plugging orphaned wells can provide opportunities for geologic storage of carbon dioxide and hydrogen and geothermal energy development, thereby facilitating efforts to transition to net-zero energy systems. Our analysis on environmental risks and opportunities of orphaned wells provides a framework that can be used to manage the millions of documented and undocumented orphaned wells in the U.S. and abroad.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Numerical Modeling of Anisotropic Elastic-Wave Sensitivity Propagation for Optimal Design of Time-Lapse Seismic Surveys

Reliable subsurface time-lapse seismic monitoring is crucial for many geophysical applications, such as enhanced geothermal system characterization, geologic carbon utilization and storage, and conventional and unconventional oil/gas reservoir characterization, etc. In this work, we develop an elastic-wave sensitivity propagation method for optimal design of cost-effective time-lapse seismic surveys considering the fact that most of subsurface geologic layers and fractured reservoirs are anisotropic instead of isotropic. For anisotropic media, we define monitoring criteria using qP- and qS-wave sensitivity energies after decomposing qP- and qS-wave components from the total elastic-wave sensitivity wavefield using a hybrid time- and frequency-domain approach. Geophones should therefore be placed at locations with significant qP- and qS-wave sensitivity energies for cost-effective time-lapse seismic monitoring in an anisotropic geology setting. Our numerical modeling results for a modified anisotropic Hess model demonstrate that, compared with the isotropic case, subsurface anisotropy changes the spatial distributions of elastic-wave sensitivity energies. Consequently, it is necessary to consider subsurface anisotropies when designing the spatial distribution of geophones for cost-effective time-lapse seismic monitoring. This finding suggests that it is essential to use our new anisotropic elastic-wave sensitivity modeling method for optimal design of time-lapse seismic surveys to reliably monitor the changes in subsurface reservoirs, fracture zones or target monitoring regions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Experimental Evaluation of Thermal Storage Performance of a Dual-Purpose Underground Thermal Battery

A geothermal heat pump (GHP) system is an energy-efficient building heating and cooling technology with great potential for reducing energy consumption and decarbonization. However, applications of GHP are still limited due to the high cost, of which 30% is related to the cost of installing the conventional vertical bore ground heat exchangers, which are usually installed in boreholes 60 meters deep. A dual-purpose underground thermal battery (DPUTB) has been developed to offer a low-cost ground heat exchanger with a built-in thermal storage capacity. The DPUTB innovatively integrates a shallow-bore ground heat exchanger (the outer tank), which can be installed in a borehole less than 6 m deep, with thermal energy storage (TES) (the inner tank). DPUTB has the potential to reduce the cost of a ground source heat pump system while allowing shifting the electric demand of the building served by the GHP system from peak to off-peak hours of the electric grid by charging and discharging the thermal storage. A lab-scale (1:125 in volume) DPUTB prototype was built. Phase change material (PCM) was added to increase the thermal storage capacity and maintain the supply water temperature from the TES within the desired range for direct cooling operation during the discharge period. As PCMs are critical to the TES performance of the DPUTB, this study compared the influence of different PCMs (including salt hydrate and organic PCMs) on the discharge performance of the DPUTB. The thermal State of Charge (SoC) of the DPUTB was used to compare the performance resulting from using different PCMs. Test results indicate that the organic PCM (Methyl Laurate) outperforms salt-hydrate PCMs due to a lower melting temperature and a narrower melting temperature range during the phase change process. The results of this study provide a guide for PCM selection and the optimal design of DPUTB.

Wang, Lingshi↗
DOE OSTI2026

Seismic Elastic Double-Beam Characterization of Faults and Fractures for CO₂ Storage Site Selection

Site characterization for underground injection and storage of gigatonne-scale CO₂ requires reliable and cost-effective methods to detect and characterize faults and fractures and to assess their stress state and fault activation potential. This is critical, as wastewater injection and disposal have been shown to activate faults and induce earthquakes, and CO₂ leakage remains a key concern for long-term storage. In this project, we developed seismic methods to detect and characterize large-scale sedimentary and crystalline basement faults and associated small-scale fractures below conventional seismic imaging resolution using multicomponent (9C) surface seismic data. Machine learning was used to automatically interpret large-scale faults, providing key information for estimating the maximum magnitude of potential induced earthquakes. High-fidelity imaging was achieved by exploiting redundancy across multiple elastic wave modes, where independent images from different modes and frequencies cross-validate each other. We also used our nonlinear signal comparison (NLSC) method for ground roll removal, improving data quality in complex near-surface conditions. The methods were validated using field data acquired in central Montana. Results show that basement faults extend into the sedimentary section and that small-scale fractures are widespread above the basement. The inferred stress orientation is consistent with regional stress data, and the estimated maximum induced earthquake magnitude is small (Mw ~2.3). The developed workflow provides a practical approach for fault and fracture characterization and for assessing induced seismicity and leakage risk. It is directly applicable to CO₂ storage site selection and to other subsurface systems.

02 PETROLEUM↗
DOE OSTI2021

Hybrid-energy approach enabled by heat storage and oxy-combustion to generate electricity with near-zero or negative CO 2 emissions

We assess a hybrid-energy approach that modifies a steam-turbine power plant to use renewable energy sources (electricity, plus options for geothermal and solar heat), plus fossil fuel (natural gas and coal) and/or waste biomass (e.g., Douglas fir woodchips). Heat storage allows heat to be created during periods of excess energy supply and for that heat to be converted to electricity when demanded. Excess electricity, such as from variable renewable energy (VRE), is used to generate oxygen for oxy-combustion furnaces that create very-hot, high-purity CO 2 that heats granular rock beds in insulated vessels. Cool CO 2 leaving the beds is dried, sent to compressors powered by excess VRE electricity, before being sent by pipeline to geologic CO 2 storage. Very-hot CO 2 transfers high-grade heat from storage to the power plant in a closed loop that returns medium-grade heat back to storage, allowing low- and medium-grade renewable-heat sources to be stacked beneath combustion heat, with all heat sources being converted to electricity at the same (high) thermal efficiency. Reliable, on-demand power may be generated with near-zero CO 2 emissions with fossil fuel and with negative CO 2 emissions with waste biomass. Our analyses show that with fossil fuel, up to 35% of gross power can be derived from renewable sources, while for waste biomass, it can be entirely derived from renewable sources. Because our approach has the potential to ensure that grids have a continuous supply of clean energy and because electricity is only generated once, when demanded, it could serve as an efficient alternative to bulk energy storage.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Chapter 8: Geothermal Energy

Geothermal resources are used at different temperatures for different applications, depending on the resource temperature; applications include power generation, direct heating and cooling, mineral recovery, and energy storage. This chapter focuses on the most prominent applications of geothermal energy today: power generation and direct heating and cooling, specifically, dry steam, flash, and binary technologies. Other topics explored include: direct use of geothermal resources, thermodynamic cycle applications, and the multiple steps and multiple technologies involved in capturing all minerals of interest in a cost-effective way.

cooling↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗