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Author

K. Raslan

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2 papers indexed here

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Conference Oct 2026

Data-Driven Prediction of Electrical Submersible Pump Run Life Using Leakage-Resistant Machine-Learning Validation

Electrical submersible pumps (ESPs) are widely deployed to sustain production in mature and high-water-cut wells. Routine surveillance data capture equipment degradation and changing operating conditions and can therefore support remaining-useful-life (RUL) estimation and proactive maintenance planning. However, pred...

M. Sobhy, H. Elnaggar, K. Raslan et al. · 0 citations
Sep 2026

Electrical Submersible Pump Failure Classification Using Machine Learning Models with Advanced Data Splitting Techniques for Field Application

Electrical Submersible Pumps (ESPs) drive approximately 60% of global artificial lift production; however, their continuous exposure to harsh downhole environments can cause mechanical and electrical degradation. This unpredictability in run-life directly causes unplanned well downtime, deferred production, and high-...

M. Sobhy, K. Raslan, H. Elnaggar et al. · 0 citations

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