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At least 109 records · Page 6

Stakeholder Analysis Technical Report for CarbonSAFE Illinois -- Macon County (Task 3)

Stakeholder engagement is considered a critical component for successful deployment of Carbon Capture Utilization and Storage (CCUS). Engagement builds awareness and understanding of the implications, both local and global, that deploying this technology entails. The CarbonSAFE Illinois – Macon County project presents unique challenges for engaging stakeholders as they have various and diverse options and perspectives that vary in influence and personal importance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Report of Geology from the T.R. McMillen #2 Well Drilled for CarbonSAFE Illinois - Macon County (Task 6)

This extensive report describes the sedimentology and sequence stratigraphy of the Mt Simon Sandstone, seismic reflection, Precambrian basement geochronology, petrophysical analyses, reservoir properties and petrographic characterization based on data collected during drilling and 2D seismic surveys conducted as part of CarbonSAFE Illinois - Macon County.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Storage Complex Modeling for CarbonSAFE Illinois - Macon County (Task 8)

This report presents the workflow, processes and data input used in developing geostatic models and conducting dynamic simulations for the geological setting in the CarbonSAFE Illinois - Macon County project. A range of simulation scenarios are described to assess injection characteristics and behavior of injected CO 2 and overall storage performance of the site.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Well-Log Derived Geomechanical Analysis of Microseismicity in the Mt. Simon Saline Aquifers (Illinois Basin - Decatur Project)

The Illinois Basin Decatur Project (IBDP) successfully demonstrated the safe geologic storage of carbon dioxide at a commercial scale. Within the IBDP project three deep wells (injection (CCS1), monitoring (VW1), geophysical (GM1)) were competed and geophysical logs were recorded. During injection and post-injection periods microseismic monitoring was conducted to create a miscoseismic catalog. The correlations between microseimic attributes and geomechanical well logs define major geomechanical drivers of microseismic expression to understand a reservoir response to CO2 injection in geological context. Utilizing standard sonic and density well logs, the dynamic elastic moduli were calculated and employed to correlate with microseismic pseudo-logs. A multi-dimensional Mu-rho and Lambda-rho (MRLR) hyperdimensional plots display of meaningful data and uncovered subtle relationships between elastic properties of sandstones and the seismological attributes of recorded microseismicity.

Myshakin, Evgeniy↗

SMART Task 6: Evaluation of the Costs of Geologic CO2 Storage for the Illinois Basin Decatur Project Site Using the NRAP/SMART Technoeconomic and Liability Evaluation for Storage (TALES) Model

This is a presentation featuring an analysis related to SMART Task 6 in which CO2 storage costs are presented. The National Energy Technology Laboratory has developed the NRAP/SMART Technoeconomic and Liability Evaluation for Storage (TALES) model to provide quantitative cost-based insights to support developers planning CO2 injection and storage projects. TALES calculates the revenues, costs, and financial performance of candidate CO2 saline storage project based on site-specific activity costs and financial parameters. TALES is being integrated as a module pertaining to storage cost as part of the broader SMART Visualization and Decision Support Platform (SVDSP). In this study, the TALES model was applied using real activity cost data associated with the development and operations at the Illinois Basin Decatur Project (IBDP) CO2 storage project site. Scenario analysis was implemented in which crucial operational and cost attributes were varied and the associated cost implications observed. Key results data and project cost summary metrics like first-year breakeven price of CO2 ($/tonne) and net present value (NPV) are presented in similar fashion to how they will appear in the SVDSP.

Vikara, Derek↗

Illinois Basin Carbon Ore, Rare Earth, and Critical Minerals (IB-CORE-CM) Initiative (Final Report (Redacted)(Public))

Final Report; Illinois Basin - Carbon Ore, Rare Earth and Critical Mineral (IB-CORE-CM) project team has conducted a comprehensive basin-wide assessment of CORE-CM presence in coal, coal-based, and waste stream resources, as well as a thorough examination of mining practices, separation technologies, and the local infrastructure necessary for producing and providing the needed CORE-CM resources for U.S. industry. This final report details the research, methods, and results of the project.

01 COAL, LIGNITE, AND PEAT↗

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES)

This report presents the physical and chemical characterization of breaker and sorter reject materials sourced from the Prairie State Generation facility, as part of the Illinois Rare Earth Novel Extraction and Supply (IRENES) project. Key analyses include particle size distribution, density, angle of repose, proximate and ultimate composition, mineralogy, and elemental content. Breaker reject material was found to be coarser and higher in ash content (~80%) with lower calorific value, while sorter reject showed finer distribution, lower ash (~68%), and higher carbon and energy content. XRD and XRF analyses confirmed the presence of REE-bearing minerals and relevant oxides, supporting process design and beneficiation strategy development for critical mineral recovery.

01 COAL, LIGNITE, AND PEAT↗

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗

Bird Species Use of Bioenergy Croplands in Illinois, USA—Can Advanced Switchgrass Cultivars Provide Suitable Habitats for Breeding Grassland Birds?

Grassland birds have sustained significant population declines in the United States through habitat loss, and replacing lost grasslands with bioenergy production areas could benefit these species and the ecological services they provide. Point count surveys and autonomous acoustic monitoring were used at two field sites in Illinois, USA, to determine if an advanced switchgrass cultivar that is being used for bioenergy feedstock production could provide suitable habitats for grassland and other bird species. At the Brighton site, the bird use of switchgrass plots was compared to that of corn plots during the breeding seasons of 2020–2022. At the Urbana site, the bird use of restored prairie, switchgrass, and Miscanthus × giganteus was studied in the 2022 breeding season. At Brighton, Common Yellowthroat, Dickcissel, Grasshopper Sparrow, and Sedge Wren occurred on switchgrass plots more often than on corn; Common Yellowthroat and Dickcissel increased on experimental plots as the perennial switchgrass increased in height and density over the study period; and the other two species declined over the same period. At Urbana, Dickcissel was most frequent in prairie and switchgrass; Common Yellowthroat was most frequent in miscanthus and switchgrass. These findings suggest that advanced switchgrass cultivars could provide suitable habitats for grassland birds, replace lost habitats, and contribute to the recovery of these vulnerable species.

59 BASIC BIOLOGICAL SCIENCES↗

Atlas of electron content values observed at Urbana, Illinois, 1 December 1967 - 30 December 1970

Ionospheric electron content versus local time data deduced from Faraday rotation observations of ATS-III geostationary satellite signals at Urbana, Illinois are reported. The data are presented in two forms. Values of subionospheric latitude (SILAT) and subionospheric longitude (SILON) are in degrees north and degrees west, respectively. These are computed on the basis of 350 km for the mean ionospheric height, which value is also used for the calculation of the geometric-magnetic factor, required for the conversion of the measured Faraday rotation angle to electron content. Entries of zero for the electron content in the tables represent no data for those times.

Flaherty, B. J.↗

The Toulon meteorite - A new chondrite from Illinois

Toulon is an olivine-bronzite chondrite found near Toulon, Illinois in 1962. It contains abundant, well preserved chondrules, as well as glasses that are not well devitrified. Most of the metal has been weathered out. Olivine and pyroxene are well equilibrated. It has been classified as an H5 chondrite.

Olsen, E.↗

Simultaneous partial reflection and meteor radar wind observations at Urbana, Illinois, during the winter of 1974-1975

A program of observation was undertaken during the winter of 1974-1975 utilizing the meteor winds radar and partial reflection system at Urbana, Illinois. The north-south component of the prevailing wind representative of 80-100 km altitude was deduced for four 24-h observational periods during which partial reflection measurements of D-region electron density were made. These observations indicate southward mean motion during periods of higher electron density and northward mean motion during periods of lower electron density. This is consistent with the idea that increases in the transport of nitric oxide from the auroral zone is a cause of winter increases in D-region electron density at midlatitudes.

Geller, M. A.↗

Variations in electron density in the middle latitude D-region above Urbana, Illinois

Electron density measurements made with the partial reflections technique above Urbana, Illinois (44 deg 10 min N, 88 deg 10 min W) were analyzed for day-to-day variations, seasonal variations, magnetic storm aftereffects, and stratosphere-ionosphere coupling effects. As well as showing a winter anomaly, the electron densities near 76 km were significantly lower in fall than in spring. Magnetic storm aftereffects of the type predicted by models of energetic electron precipitation at middle latitudes were observed. No strong correlations were found between stratospheric and D-region time series, or between the occurrence of stratospheric warmings and D-region changes. It is likely that most of the electron density variation was due to variations in the transport of minor neutral constituents. The spring-fall differences were also probably caused by differences in minor constituent concentrations rather than the effect of temperature changes on the recombination coefficient.

Wratt, D. S.↗