Modeling crude oil pyrolysis process using advanced white-box and black-box machine learning techniques
Fahimeh Hadavimoghaddam,
Alexei Rozhenko,
Mohammad-Reza Mohammadi
et al.
Abstract:Accurate prediction of fuel deposition during crude oil pyrolysis is pivotal for sustaining the combustion front and ensuring the effectiveness of in-situ combustion enhanced oil recovery (ISC EOR). Employing 2071 experimental TGA datasets from 13 diverse crude oil samples extracted from the literature, this study sought to precisely model crude oil pyrolysis. A suite of robust machine learning techniques, encompassing three black-box approaches (Categorical Gradient Boosting—CatBoost, Gaussian Process Regress… Show more
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