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Machine Learning-Driven Quantification of CO<sub>2</sub> Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO<sub>2</sub> plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO<sub>2</sub> injection metrics, this work aims to predict the temporal ev...

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Bibliografische Detailangaben
Hauptverfasser: Ikponmwosa Iyegbekedo, Ebrahim Fathi, Timothy R. Carr, Fatemeh Belyadi
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-09-01
Schriftenreihe:Energies
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Online-Zugang:https://www.mdpi.com/1996-1073/17/17/4421
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