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Norhan Sedki

1 paper indexed

crossrefFluids2026-02-27

From Laboratory Measurements to AI-Driven Insights: Predicting Shaped Charge Performance with Advanced Machine Learning

Samuel Nashed, Muhammad Abdullah, Oluchi Ejehu, Badr Mohamed, Norhan Sedki, Rouzbeh Moghanloo

The accurate estimation of the perforation length is very vital to improve fluid flow as well as the management of charges. Traditional methods, including empirical correlations, analytical models, and API 19B surface tests, suffer from significant limitations in their scope, req…

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