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Optimizing BHA and fluid selection with a machine learning-based drilling system recommender

An innovative digital solution prepares an operational database and stores performance results of drill bits, motor power sections, RSS, BHA configurations and drilling fluids. After parameters of a planned drilling run are set, a multidimensional distance-based approach selects similar previous drilling runs for analysis. The process enables rational technology selection recommendations.
New York United States Fatma Mahfoudh Sergey Makarychew Mikhailov Greg Skoff Cheolkyun Jeong

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