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 ev...

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Autors principals:	Ikponmwosa Iyegbekedo, Ebrahim Fathi, Timothy R. Carr, Fatemeh Belyadi
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-09-01
Col·lecció:	Energies
Matèries:	machine learning CO<sub>2</sub> plume dynamics microseismic data Illinois Basin Decatur Project (IBDP) carbon sequestration
Accés en línia:	https://www.mdpi.com/1996-1073/17/17/4421
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