Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the Geological Society of America Connects 2024 Annual Meeting in Anaheim, California, 22-25 September 2024.

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Published
2024-10-04
DOI
https://doi.org/10.2172/2474804
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

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Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

MacKenzie Mark‐Moser, Jacob Shay, Araceli Lara, Neyda Maymi, Christopher Creason, Julia Mulhern, Kelly Rose
article en

Abstract

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the Geological Society of America Connects 2024 Annual Meeting in Anaheim, California, 22-25 September 2024.

Oak Ridge Associated Universities (US), National Energy Technology Laboratory (US), Oak Ridge Institute for Science and Education
U.S. Department of Energy, National Energy Technology Laboratory
Openalex Percentile: Top 78%
Scientific Computing and Data Management
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