WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

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Publication Details

Published
2024-08-05
DOI
https://doi.org/10.2172/2426929
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

WELLBASE - An Interactive Platform for Wellbore Material Assessment

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Reservoir Engineering and Simulation Methods
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WELLBASE - An Interactive Platform for Wellbore Material Assessment

Kelly Rose, Barbara Kutchko, Stellamaris Nakacwa, Michael Sabbatino, Phillip McElroy, Madison Wenzlick, Scott Montross, Zachary Jackson, Daniel Tetteh
article en

Abstract

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

National Energy Technology Laboratory (US)
U.S. Department of Energy, Office of Fossil Energy, National Energy Technology Laboratory, Office of Fossil Energy and Carbon Management
Climate action
Openalex Percentile: Top 84%
Reservoir Engineering and Simulation Methods
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