Wafer Scale Engine Applications for Carbon Capture and Storage
This is a demonstration of WSE/WFA software toward the simulation of CO2 injection into a reservoir.
Kim, Hyoungkeun↗
SEARCH · Engineering Papers
Results for “Carbon storage”
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.
EFRC-MUSE: Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials
Phase interactions and fluid properties in geological and other environments are critical in applications ranging from hydrogen production and geologic storage and recovery, carbon dioxide storage and sequestration, and the sustainable use of water resources. The four goals of EFRC-MUSE: Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials were based on the priority directions articulated in the Basic Research Needs documents, and the scientific needs in nanoscience. 1. Develop a fundamental understanding of confinement and surface interactions in mesoscale media with nanometer-sized pores on the phase behavior, thermodynamic and multiphase flow properties of multicomponent fluid mixtures. 2. Examine the impact of mineralogy and material heterogeneity on mechanical properties to better understand chemo-mechanical interactions in material failure. 3. Determine in-operando cross-scale structural and nanostructural material properties with fluids in confinement and flow under realistic condi
58 GEOSCIENCES↗
Cost and Performance of Bituminous Coal and Natural Gas Plants with Carbon Capture and Storage
Presentation at the Pittsburgh Coal Conference, based on our study report "Cost and Performance Baseline for Fossil Energy Plants, Volume 1: Bituminous Coal and Natural Gas to Electricity, Revision 4"
Kilstofte, Aaron↗
NORTH DAKOTA INTEGRATED CARBON CAPTURE AND STORAGE COMPLEX FEASIBILITY STUDY
Presentation given at Energy Generation Conference, Bismarck, North Dakota on January 24, 2018.
Peck, Wesley↗
Carbon Capture, Utilization, & Storage (CCUS) in Achieving a Net Zero Emissions Future - System Cost of Replacement Energy (SCoRE): A Tool for Assessing Technology Substitution Pathways to Decarbonization
This presentation outlines the SCoRE tool, which can be used to identify the least-cost technology substitution pathway to meeting a decarbonization target within an operating region of the United States. The presentation showcases results from an application of the tool in the ERCOT operating region.
Harker-Steele, Amanda↗
Core Characterization of Patterson #5-25 Well for Carbon Capture and Storage in Western Kansas
Society of Core Analysis Annual Symposium 2022, Austin, TX, September 19-23, 2022
Paronish, Thomas J.↗
An Environmental, Energy, Economic, and Social Justice Database for Carbon Capture and Storage Applications
For presentation at the 2023 American Geophysical Conference, San Francisco, CA, December 11-15, 2023.
Sharma, Maneesh↗
Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage
The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.
Barajas-Olalde, César↗
Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis
Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.
Shih, Chung Yan↗
From carbon to climate action: harnessing basalt for geological carbon dioxide (CO 2 ) storage onshore and offshore
Abating emissions and reducing atmospheric concentrations of carbon dioxide (CO 2 ) are crucial in avoiding catastrophic climate change. Basalt reservoirs offer suitable CO 2 storage sites and are present onshore and offshore. This study compares the geological, economic and social aspects of CO 2 storage in both domains using two basalt formations from the Republic of Ireland: the Limerick Igneous Suite and the Druid Formation. Offshore reservoirs offer larger storage resources but are more expensive to develop. Nevertheless, both offer gigatonne-scale theoretical CO 2 storage. Reviewing public perception studies on wind energy demonstrates that the commonly held belief that offshore projects face less opposition owing to their distance from communities has been dispelled, while similar studies on carbon capture and removal show no preference for onshore or offshore development. Instead, a general scepticism towards carbon removal is observed, with concerns that it hinders broader decarbonization efforts. The desire of all stakeholders to be involved throughout project development is consistently observed. Lessons from offshore natural gas projects highlight the consequences of failing to engage with local communities. The Republic of Ireland has significant potential to deploy geological CO 2 storage in basalt reservoirs, but policy hurdles such as legal limits on storage volumes must be overcome to reconcile climate ambition and legislative capacity.
54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
Transport Cost for Carbon Removal Projects With Biomass and CO2 Storage
Strategies to remove carbon from the atmosphere are needed to meet global climate goals. Promising strategies include the conversion of waste biomass to hydrogen, methane, liquid fuels, or electricity coupled with CO 2 capture and storage (CCS). A key challenge for these projects is the need to connect geographically dispersed biomass supplies with geologic storage sites by either transporting biomass or CO 2 . We assess the cost of transport for biomass conversion projects with CCS using publicly available cost data for trucking, rail, and CO 2 pipelines in the United States. We find that for large projects (order of 1 Mt/yr CO 2 or greater), CO 2 by pipeline is the lowest cost option. However, for projects that send most of the biomass carbon to storage, such as gasification to hydrogen or electricity production, biomass by rail is a competitive option. For smaller projects and lower fractions of carbon sent to storage, such as for pyrolysis to liquid fuels, CO 2 by rail is the lowest cost option. Assessing three plausible example projects in the United States, we estimate that total transport costs range from $24/t-CO 2 stored for a gasification to hydrogen project traversing 670 km to $\$ 36$/t for a gasification to renewable natural gas project traversing 530 km. In general, if developers have flexibility in choosing transport mode and project type, biomass sources and storage sites can be connected across hundreds of kilometers for transport costs in the range of $20-40/t-CO 2 stored. Truck and rail are often viable modes when pipelines cannot be constructed. Distances of 1,000 km or more can be connected in the same cost range when shared CO 2 pipelines are employed.
09 BIOMASS FUELS↗
Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon
Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.
Data-driven framework↗
Insights into activators on biomass-derived carbon-based composites for electrochemical energy storage
Biomass-derived carbon materials are now an essential source of carbon electrodes for high-performance supercapacitors due to their cost-effectiveness and abundant heteroatom self-doping properties. When preparing porous carbon materials from biomass for supercapacitor use, the use of activators can significantly increase the specific surface area of carbon materials, enhance pore structures, introduce more heteroatoms, promote the generation of various functional groups, and play a crucial role in the capacitance performance of biomass-derived carbon materials. However, the role of activators during the activation process has been overlooked in previous work focused on improving supercapacitor capacitance performance. In addition, there is a lack of comprehensive reviews summarizing the role of activators. Therefore, this work classifies the types of activators, discusses their activation mechanisms, operability, economy, and environmental friendliness, and proposes future development directions for activators. The main mixing methods of activators and carbon materials are also demonstrated, highlighting the advantages and disadvantages of each method. In conclusion, this work could provide valuable insights for the development of activators for high-performance supercapacitors.
25 ENERGY STORAGE↗
Agent-based modeling for multimodal transportation of CO 2 for carbon capture, utilization, and storage: CCUS-agent
Here, to understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO 2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO 2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40 %. The MPFY and SDFY algorithms capture more CO 2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Upcycling Polyethylene Waste Into Advanced Carbon Materials Used for Energy Storage Applications
Upcycling plastic into advanced carbons, such as graphite and graphene, offers attractive options to manage waste streams by converting the plastic into carbon electrode materials for energy storage devices. However, polyethylene (PE) is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into advanced carbons. This work addresses this challenge by oxidatively functionalizing PE between 300-330 C which stabilizes it for higher temperature processing into graphite & graphene. In addition, the graphite & graphene are tested as lithium-ion battery or supercapacitor electrodes where their electrochemical performances outperform commercial materials.
graphene↗
Upcycling Polyethylene Waste Into Advanced Carbon Materials Used for Energy Storage Applications
Upcycling plastic into advanced carbons, such as graphite and graphene, offers attractive options to manage waste streams by converting the plastic into carbon electrode materials for energy storage devices. However, polyethylene (PE) is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into advanced carbons. This work addresses this challenge by oxidatively functionalizing PE between 300-330 C which stabilizes it for higher temperature processing into graphite & graphene. In addition, the graphite & graphene are tested as lithium-ion battery or supercapacitor electrodes where their electrochemical performances outperform commercial materials.
graphene↗
Findings from the NETL Well Integrity Workshop: Insights for multiple subsurface energy operations
Wells are a core aspect of subsurface energy infrastructure. Ensuring the resilience of that infrastructure relies on the integrity of wells as engineered pathways that safely extract, inject, and store fluids in the subsurface. To identify areas where focused research can yield new insights to improve integrity and extend the operational life of wells, the United States (US) Department of Energys (DOE) National Energy Technology Laboratory (NETL) organized and hosted a workshop on well integrity research needs in May and June of 2021. The three-day workshop consisted of six technical sessions and 18 presentations from international well integrity experts on topics of geologic storage of carbon dioxide, natural gas, and hydrogen, as well as hydrocarbon and geothermal energy production. There were over 350 registrants from more than 10 countries, 4 major oil & gas companies, 14 US states, 8 US DOE National Laboratories, US Departments of Interior, Transportation, and Energy, and regulators from eight of ten US Environmental Protection Agency (EPA) regions and US EPA headquarters. Through presentations, moderated discussions, and an attendee survey several important areas for future research were identified. In this presentation, we highlight the findings of the NETL well integrity workshop and discuss future well integrity research needs.
carbon capture utilization and storage (CCUS)↗
DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site
Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering
58 GEOSCIENCES↗