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Wingo, Patrick

Publications and source records attributed to Wingo, Patrick.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Complementing the CCS Class VI Well Permit Process with DOE-NETL's SMART Initiative Tools and Workflows

This is a presentation on model explorer developed under SMART initiative Task 2. Our team will present the current progress of the model explorer in using machine learning models to accelerate CCS project at GWPC meeting. Model explorer bring new capabilities, (fast, Realtime, and accurate) that can help CCS stakeholders including regulatory agencies, public and site operators make faster decisions and process information and data.

Hosseini, Seyyed↗
DOE OSTI2024

Git and Software Tools for CTS

This presentation will provide an overview of the progress made helping the EDX4CCS, SMART, and NRAP projects virtualize their CO2 Transport and Storage software tools to boost their stakeholder availability through the DisCO2ver platform. This presentation will also cover helpful software development tools with a focus on researchers and developers who have not had formal training or many years of experience in software engineering best practices.

Zaengle, Dakota↗
DOE OSTI2024

Deploying a New AI Software Tool for Rapid Characterization & Quantification of Unconventional Sources of Critical Minerals

Poster for the 2024 NETL Resource Sustainability Meeting. The poster presents a new project award by the Office of Technology Transitions to accelerate application and commercial utilization of an NETL-developed technology to rapidly characterize critical mineral occurrences within secondary and/or unconventional feedstocks, such as coal refuse or waste impoundments.

Creason, Christopher↗
DOE OSTI2024

U.S. Offshore Pipeline and Reported Incident Datasets

The U.S. Offshore Pipeline and Reported Incident Datasets provide a compilation of data from a variety of credible resources, spatially-temporally integrated into multivariate resources. This spatial resource includes more than 80,000 points along existing and abandoned pipelines in the Gulf with matched incidents based on similar lease blocks and temporal timelines (e.g., the incident date occurs within reported pipeline lifespan), structural characteristics, geologic and seafloor data, and meteorological, oceanographic, and biochemical statistics spatially and temporally matched to each point. This is provided as both a feature class in a file geodatabase, as well as a CSV file for ease of use. The pipeline incidents table is a CSV file containing more than 900 reported incidents from 1986 to 2021, including incident date, area (Outer Continental Shelf (OCS) lease block and area code), reported causes, reported incident information, and results (i.e., cost, repairs, inspections), along with quantitative severity metrics. Field dictionaries are included for both the pipeline locations and incidents datasets, which detail field definitions. The pipeline locations field dictionary includes original resource reference information.

Advanced Infrastructure Integrity Model↗
DOE OSTI2023

A Multi-scale, Geo-data Science Method for Assessing Unconventional Critical Mineral Resources

Critical minerals (CM) supply raw materials that constitute many of our essential infrastructure, defense, technology, and electrification needs. Currently, production and refinement of these materials from conventional sources is limited to few regions globally, which makes supply of these resources particularly venerable to disruption. To help overcome these risks and meet growing demand, attention has focused on identifying and developing resource potential of unconventional geologic CM sources, such as rare-earth elements in sedimentary systems. However, the unconventional nature of these types of sources means they are often poorly characterized and/or under-explored with respect to conventional counterparts. We present a regional case study for an Unconventional Rare-earth and Critical minerals (URC) assessment method for predicting and identifying REE resource potential and occurrence in unconventional systems in the Central Appalachian Basin (CAB). The method utilizes a geologic and geospatial data-driven approach, informed and guided by knowledge of REE enrichment processes, to systematically predict and identify areas of higher enrichment. Results from the test case indicate locations with potential for different types of coal-REE deposits, demonstrating its utility for reducing the area of exploration and identifying sites for more detailed investigation. Building upon the regional scale assessment capability, ongoing science-based enhancements to the method will allow for finer-scale (e.g., mine-scale) predictions required to support technical and economic assessments.

Creason, Christopher↗
DOE OSTI2023

EDX4CCS 3D Data Preview Tool

For presentation at the 2023 FECM / NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 30-Septamber 1, 2023.

Wingo, Patrick↗
DOE OSTI2023

Geospatial and Information Substitution and Anonymization Tool (GISA)

The Geospatial and Information Substitution and Anonymization Tool (GISA) incorporates techniques for obfuscating identifiable information from point data or documents, while simultaneously maintaining chosen variables to enable future use and meaningful analysis. This approach promotes collaboration and data sharing while also reducing the risk of exposure to sensitive information. GISA can be used in a number of different ways, including the anonymization of point spatial data, batch replacement/removal of user-specified terms from file names and from within file content, and aid with the selection and redaction of images and terms based on recommendations using natural language processing. Version 1 of the tool, published here, has updated functionality and enhanced capabilities to the beta version published in 2023. Please see User Documentation for further information on capabilities, as well as a guide for how to download and use the tool. If there are any feedback you would like to provide for the tool, please reach out with your feedback to edxsupport@netl.doe.gov. Disclaimer: This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. The Geospatial and Information Substitution and Anonymization Tool (GISA) was developed jointly through the U.S. DOE Office of Fossil Energy and Carbon Management’s EDX4CCS Project, in part, from the Bipartisan Infrastructure Law.

Bipartisan Infrastructure Law↗
DOE OSTI2023

URC Assessment Method

This tool evaluates the potential occurrence of URC resources using a series of validated heuristics as outlined in "Creason, C.G., Justman, D., Rose, K. et al. A Geo-Data Science Method for Assessing Unconventional Rare-Earth Element Resources in Sedimentary Systems. Nat Resour Res (2023). https://doi.org/10.1007/s11053-023-10163-x"

Critical Minerals↗
DOE OSTI2023

Ocean & Geohazard Analysis Tool

The Ocean & Geohazard Analysis (OGA) software tool is designed to summarize insights into key offshore hazards drawing from a diverse set of approaches, including artificial intelligence, machine learning, probabilistic and statistical, and offshore data sources. The offshore hazards that can be analyzed include submarine landslides, extreme wind/wave/current event probabilities, earthquakes, and metocean pathways (CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures - Submissions - EDX (doe.gov)). Currently, the tool is developed for use in the Gulf of Mexico. The data underlying the offshore hazard analyses can be found here: https://edx.netl.doe.gov/dataset/gulf-of-mexico-risk-analysis-database-gomrad This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. Disclaimer This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

AIML↗
DOE OSTI2023

Gulf of Mexico Risk Analysis Database (GoMRAD)

The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.

BOEM,Bathymetry,Gulf Of Mexico,Machine Learning,Me↗