Physics-integrated neural networks for improved mineral volumes and porosity estimation from geophysical well logs

Accurate estimation of mineralogy from geophysical well logs is crucial for characterizing geological formations, particularly in hydrocarbon exploration, CO2 sequestration, and geothermal energy development. Current techniques, such as multimineral petrophysical analysis, offer details into mineral...

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Bibliographic Details

Published in:	Energy Geoscience
Main Authors:	Prasad Pothana, Kegang Ling
Format:	Article
Language:	English
Published:	KeAi Communications Co., Ltd. 2025-06-01
Subjects:	Physics integrated neural networks Petrophysics Well logs Oil and gas Reservoir characterization Mineralogy
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666759225000319