Publications Scientifiques

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Author: search.filters.author.Boukredera, Farouk SaidHas files: No

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    Development of an expert-informed rig state classifier using naive bayes algorithm for invisible loss time measurement
    (Springer Nature, 2024) Youcefi, Mohamed Riad; Boukredera, Farouk Said; Ghalem, Khaled; Hadjadj, Ahmed; Ezenkwu, Chinedu Pascal
    The rig state plays a crucial role in recognizing the operations carried out by the drilling crew and quantifying Invisible Lost Time (ILT). This lost time, often challenging to assess and report manually in daily reports, results in delays to the scheduled timeline. In this paper, the Naive Bayes algorithm was used to establish a novel rig state. Training data, consisting of a large set of rules, was generated based on drilling experts’ recommendations. This dataset was then employed to build a Naive Bayes classifier capable of emulating the cognitive processes of skilled drilling engineers and accurately recognizing the actual drilling operation from surface data. The developed model was used to process high-frequency drilling data collected from three wells, aiming to derive the Key Performance Indicators (KPIs) related to each drilling crew’s efficiency and quantify the ILT during the drilling connections. The obtained results revealed that the established rig state excelled in automatically recognizing drilling operations, achieving a high success rate of 99.747%. The findings of this study offer valuable insights for drillers and rig supervisors, enabling real-time visual assessment of efficiency and prompt intervention to reduce ILT.
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    Drill string torsional vibrations modeling with dynamic drill pipe properties measurement and field validation
    (American Society of Mechanical Engineers (ASME), 2022) Boukredera, Farouk Said; Hadjadj, Ahmed; Youcefi, Mohamed Riad
    This paper aims to present the drill string torsional dynamics through a lumped parameter modeling using the basic physical notions with continuous measurement of drill pipe mechanical properties (inertia, damping, and stiffness). The model represents the mechanical properties as a variable for each drilled stand. A rock bit interactions model is employed in the system considering the kinetic friction as variable and depends on surface drilling parameters and the well length. Field data, including surface and downhole recorded velocities, are used to validate the model by comparing both velocities and to confirm the existence of drill string vibrations together with the simulation results (bit velocity)