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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 379 records · Page 21

Multi-Scale 3D Imaging for Machine Learning Property Upscaling: Mt. Simon Sandstone Case Study

Petrographic properties of principal target reservoirs for carbon sequestration, such as the Mt. Simon Sandstone, are relevant to broad interest groups. The Mt. Simon Sandstone is a deep, saline, regionally extensive Cambrian sandstone, overlain by low permeability sealing formations, making it one of the viable geologic carbon storage reservoirs in the Midwestern US. Its thickness (exceeding 2400 ft in some localities), depth, and lateral extent, combined with high porosity and permeability make it a high-priority target of multiple ongoing geologic carbon sequestration efforts in the United States of America. The National Energy Technology Laboratory in Morgantown, West Virginia, has been engaged in characterization efforts of the Mt. Simon for over a decade, with a strong focus on Computed Tomographic data acquisition. Data generated during this period has been hitherto not accessible to the public. This archival effort focused on preservation of historical CT data and associated metadata, and facilitating their accessibility, culminating with the publication of the entire dataset on NETL’s Energy Data eXchange (EDX) and the associated Gill et. al (2024) paper.

Gill, Magdalena K.↗

Numerical Simulation of Commercial-Scale CO2 Storage in a Saline Formation Evaluating Basin-Scale Pressure Interference and CO2 Plume Commingling

Presentation at NETL Carbon Management Project Review Meeting held in Pittsburgh, Pennsylvania, August 15–19, 2022. The presentation provides quantitative evaluation of subsurface pressure interference and emphasizes the importance of interproject coordination among stakeholders associated with multi-project geologic CO2 storage in a shared sedimentary basin.

Wijaya, Nur↗

Energy Storage Analysis

This study presents a comprehensive techno-economic characterization of energy storage and exible low carbon power generation technologies that can shift energy across days, weeks, or months to balance daily, weekly, and seasonal disparities in supply and demand. Energy storage technologies evaluated here include pumped hydropower storage (PHS), adiabatic and diabatic compressed air energy storage (CAES), vanadium redox flow batteries (VRBs), pumped thermal energy storage (P-TES), and renewably produced hydrogen stored in either geologic formations or underground pipes with re-electrification via combustion turbines in combined cycles, stationary proton exchange membrane (PEM) fuel cells, or the novel use of PEM fuel cells designed for heavy-duty vehicles (HDVs) which are expected to have shorter lives but also lower capital costs. We also evaluate flexible low-carbon power generation systems, including ethanol combustion in gas turbines and natural gas combustion with carbon capture and sequestration (CCS). We estimate current costs with literature data, use learning rates to characterize future costs, and develop capacity factors calibrated to an 85% renewables grid to calculate the levelized cost of energy (LCOE) of each technology. Results illustrate that at the 12-hour storage duration, PHS and CAES have the lowest LCOE with current costs, and VRBs become competitive if future costs are achieved. At the 120-hour storage duration, hydrogen systems with geologic storage and natural gas with CCS achieve the lowest LCOE in both current and future capital cost scenarios. In particular, the new configuration of HDV-PEM fuel cells with hydrogen storage in geologic formations evaluated here could lower the LCOE by 22-27% compared to stationary fuel cell systems typically evaluated and might help enable very high (>80%) renewable energy electric power systems. P-TES and hydrogen stored in underground pipes are the least-cost options at the 120-hour storage duration rating that do not require some form of geologic storage. Sensitivity analysis and Monte Carlo analysis illustrate that the general trends seen in this study are valid for a wide range of capacity factors and future cost scenarios. The study also illustrates that coproducing and selling hydrogen to other markets could reduce the LCOE of hydrogen systems by up to 39%.

carbon capture and sequestration↗

Alteration of Fractured Foamed Cement Exposed to CO2-Saturated Water: Implications for Well Integrity

Geologic CO2 storage (GCS) is a method to mitigate the adverse impact of global climate change. Potential leakage of CO2 from fractured cement at the wellbore poses a risk to the feasibility of GCS. Foamed cement is widely applied in deepwater wells where fragile geologic formations cannot support the weight of conventional cement. Thus, it is critical to know whether fractures in foamed cement self-seal in a similar manner as conventional cement systems. This study is the first to investigate the changes in physical and chemical attributes of foamed cement under dynamic flow conditions using CO2-saturated water. Self-sealing of fractures in the cement was observed at a solution flow rate of 0.1 mL/min and a pressure of 6.9 MPa. The formation of CaCO3 precipitates in pore spaces and fractures led to a decrease in permeability by 1 order of magnitude. The extents of self-sealing in foamed cement samples, specifically the 20 and 30% air volume formulations, were similar to that of conventional cements. We attribute this to the greater alteration depth in the foamed cement, which compensated for the reduced availability of Portlandite and higher initial porosity. The results can be used to evaluate the risk of leakage associated with foamed cement.

Geologcial Carbon Storage, Well Integrity in CO2 S↗

Advanced Inversion Algorithms for Scientific Data Analysis [Slides]

Accurate subsurface characterization is crucial for all subsurface energy exploration. Accurate characterization of uncertain subsurface properties is also critical for monitoring storage of CO 2 , estimating pathways of subsurface contaminant transport, and monitoring potential nuclear explosions for treaty verification. This research will advance our world-leading subsurface sensing capabilities that are crucial for LANL missions in energy security (geothermal energy, oil/gas resource exploration, geologic carbon storage) and nuclear security (facility monitoring, detonation detection).

47 OTHER INSTRUMENTATION↗

NRAP-Open-IAM Multisegmented Wellbore Reduced-Order Model

Geologic carbon storage is one of the promising strategies to mitigate climate change by reducing the emission of carbon dioxide to the atmosphere. As part of the National Risk Assessment Partnership (NRAP), a systems-level stochastic analysis tool called the open source integrated assessment model, NRAP-Open-IAM, has been developed to estimate and manage the risk of containment loss at a geological carbon sequestration site. NRAP-Open-IAM contains several wellbore leakage model components that estimate the fluid leak rate that may occur through compromised legacy wells due to the increase in pressure resulting from CO 2 injection activities. Coupled to a reservoir component model, these components estimate the leakage of CO 2 and/or brine from a storage reservoir to overlying aquifer layers and the atmosphere through legacy wells. This report presents the theoretical framework and quality testing of the multisegmented wellbore reduced-order model. The model allows for segmenting of the legacy wells passing through the overlying stratigraphy into several intervals to simulate a site’s specific stratigraphic and hydrogeologic properties. For quality assurance, the analytical model is validated against numerical reservoir flow simulations for single and multiple aquifer(s) models. The results indicate that the model accurately predicts the transport of two-phase fluids (brine and injected CO 2 ) through the well over time. A detailed description of the model helps users to understand the model and provides a basis for future improvements.

58 GEOSCIENCES↗

Transitioning CO2-EOR Field to Dedicated CO2 Storage: Risk Considerations and Quantifications

Presentation slides on “Transitioning CO2-EOR Field to Dedicated CO2 Storage: Risk Considerations and Quantifications” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. CO2 injection wells for enhanced oil recovery (EOR) are currently regulated as Class II wells under the U.S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) program, while dedicated geological CO2 storage (GCS) wells are considered Class VI wells. The UIC classification of wells for a transitioning CO2-EOR facility has the potential to substantially impact the feasibility of operations. This paper reports a case study of risk assessment of this transition, including areas review, plume stability and pressure transient and its impacts in dedicated CO2 storage.

carbon storage↗

Data for "Land-based Resources for Engineered Carbon Dioxide Removal in the United States Exceed the Expected Needs"

Gigatonne-scale atmospheric carbon dioxide removal (CDR), alongside deep emission cuts, is critical to stabilizing the climate. However, some of the most scalable CDR technologies are also the most land intensive. Here, we examine whether adequate land resources exist in the contiguous United States to meet CDR targets when prioritizing grid emissions reduction, food production, and the protection of sensitive ecosystems. We focus on biomass carbon removal and storage (BiCRS) and direct air capture and storage (DACS) and show that suitable lands exceed the expected needs: 37.6 million hectares of land are available for BiCRS, resulting in 0.26 GtCO2 of CDR/year, and 34 million hectares are suitable for wind- and solar-powered DACS, resulting in 4.8 GtCO2 of CDR/year if facilities are co-located with geologic CO2 storage. We identify biomass and energy supply hotspots to meet CDR targets while ensuring land protection and minimizing land competition.

carbon↗

Evaluation of Containment and Geomechanical Risks at Integrated Mid-Content Stacked Carbon Storage Hub Sites

The U.S. Department of Energy is leading the development of CCS through collaborative projects and programs to not only develop and demonstrate the technology but to also quantify the risks and provide tools that site operators can use to develop a site-specific understanding of their risk to enable successful project operations. This report summarizes results and findings from the application of risk-assessment tools to an industrial-scale Geologic Carbon Storage (GCS) project. Specifically, we applied the National Risk Assessment Partnership’s (NRAP) Open Integrated Assessment Model (NRAP-Open-IAM) and State of Stress Assessment Tool (SOSAT) to two candidate sites being considered for storage by the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project team. These sites, Sleepy Hollow Field in Nebraska and Patterson Field in Kansas, have historical oil and gas production and thus are attractive candidates to store the 50 million metric tons (Mt), which is the CarbonSAFE objective. Because these sites have historical operations, they have a significant number of existing wells that pose a risk for well leakage. Additionally, the storage formations will undergo significant pore pressure perturbation (i.e., increase due to CO 2 injection). Hence, we have selected the two NRAP tools best suited to study the risks associated with well leakage and geomechanical risks. The objective of the study was not only to assess the risk at the site, but to also improve the NRAP tools through application using real site data on an ongoing project.

54 ENVIRONMENTAL SCIENCES↗

Utilizing Ontology Structures To Curate the DOE-NETL Carbon Storage Open Database

The specialized ontology for the Carbon Storage Open Database will enable more rapid assignment of appropriate symbology standards for visualization improvements, optimize topical and spatial tagging within keywords, and improve flexibility for utilization in existing data repositories such as EDX. This effort also aims to establish a foundation for utilization of ontologies for organization of other data related to geologic carbon storage in the future.

Martin, Abigail↗

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗

An experimental investigation on the CO 2 storage capacity of the composite confining system

Assuring secure containment of stored CO 2 is of paramount importance—for climate change mitigation, for permitting, and for reassuring the public. Regional seals, such as those sealing petroleum accumulations, have proven to be effective for securing CO 2 . However, the goal of permanent sequestration can also be satisfied with “composite confining systems” consisting of multiple, possibly discontinuous flow barriers that, in aggregate, create a system with very high permeability anisotropy and effectively retard the vertical migration of CO 2 . This study focuses on investigating the barrier characteristics necessary for effective containment of CO 2 , using both physical flow experiments and modified invasion percolation simulations. The simulations are calibrated to the physical experiments and are used to further extend the analysis. Results show that for a composite confining system, a) even barriers with low capillary entry pressure contrast to the underlying flow unit can divert rising CO 2 ; b) curved or anticlinal barrier topography can enhance CO 2 trapping; c) fining-upward gradations make little difference to barrier effectiveness or CO 2 retention; d) longer barriers retain more CO 2 regardless of barrier topography. Finally, field-scale simulations have demonstrated the importance of barrier length for increasing CO 2 storage capacity. Furthermore, the results presented can be used to inform the development of new screening criteria for characterization and effectiveness of composite confining systems.

58 GEOSCIENCES↗

Novel CCS Monitoring of Approved Class VI Storage in North Dakota

Presentation at Dallas Geophysical Society Meeting, Dallas, Texas, April 24, 2025. This high-level overview of focuses on novel and sustainable monitoring methods at various stages of planning or demonstration to accelerate the deployment at future carbon capture, utilization, and storage (CCUS) sites.

02 PETROLEUM↗

Computational Analysis of Coupled Geoscience Processes in Fractured and Deformable Media

Prediction of flow, transport, and deformation in fractured and porous media is critical to improving our scientific understanding of coupled thermal-hydrological-mechanical processes related to subsurface energy storage and recovery, nonproliferation, and nuclear waste storage. Especially, earth rock response to changes in pressure and stress has remained a critically challenging task. In this work, we advance computational capabilities for coupled processes in fractured and porous media using Sandia Sierra Multiphysics software through verification and validation problems such as poro-elasticity, elasto-plasticity and thermo-poroelasticity. We apply Sierra software for geologic carbon storage, fluid injection/extraction, and enhanced geothermal systems. We also significantly improve machine learning approaches through latent space and self-supervised learning. Additionally, we develop new experimental technique for evaluating dynamics of compacted soils at an intermediate scale. Overall, this project will enable us to systematically measure and control the earth system response to changes in stress and pressure due to subsurface energy activities.

58 GEOSCIENCES↗

Geologic Study in Central North Dakota

Fact sheet explaining the process of drilling a test hole to collect data for the North Dakota CarbonSAFE project. North Dakota CarbonSAFE is an Energy & Environmental Research Center project, conducted in partnership with the U.S. Department of Energy.

20 FOSSIL-FUELED POWER PLANTS↗