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Conference Aug 2026

Assessing the Capabilities of Bayesian-Optimized Machine Learning Paradigms for Wax Precipitation Prevention

Wax precipitation poses a significant challenge in crude oil production and transportation. This undesirable phenomenon increases operational costs and reduces efficiency, making it imperative to accurately determine the wax appearance temperature (WAT) of crude oils to preclude wax precipitation and enhance operatio...

A. Sulaimon, Joshua Nsiah Turkson, Massoma Nazar et al. · 0 citations
Conference Aug 2026

Risk-Informed Corrosion Prediction for Supercritical CO2 Pipelines Using Nonlinear Machine Learning and Monte Carlo Uncertainty Propagation

The integrity of Supercritical CO2 (SC-CO2) transport pipelines is threatened by the high temperature–pressure operating conditions, the presence of moisture, and aggressive impurities such as acids, alkalines, salts, O2, SO2, H2S, and NO2. For this reason, this environment gives rise to highly nonlinear and synergis...

P. Dadzie, A. Sulaimon, U. Abdulwasiu et al. · 0 citations

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