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1–3 March 2023
Bangkok, Thailand

2024 Technical Program

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010 AI Applications in Drilling and Completions I

Monday, 12 February
Room 10
  • 1400-1420 23904
    A Developed Robust Model And Artificial Intelligence Techniques To Predict Drilling Fluid Density And Equivalent Circulation Density In Real-time For Drilling Efficiency Optimization
    M. Al-Rubaii, Saudi Aramco D&WO
  • 1420-1440 23859
    Prediction Of Stuck Pipe Events Using Artificial Intelligence
    M.A. Al Nuaimi, M. AlNuaimi, A. Mohamed, ADNOC ONSHORE; A. Arnaout, AIQ
  • 1440-1500 23898
    How Complex Lithology Schemes Affect Drilling Rate Prediction: Machine Learning Study
    H. Gamal, Weatherford Saudi Arabia
  • 1500-1520 23895
    A Hybrid Data-driven Approach To Estimate The Least Principal Stresses And Safe Mud Window Using Petrophysical Logging Data
    A. Gowida, S. Elkatatny, King Fahd University of Petroleum & Minerals
  • Alternate 23885
    Cost-effective In-situ Estimation Of Rock Properties Using Drilling Data
    O. Mutrif Siddig, S. Elkatatny, A. Ibrahim, King Fahd University of Petroleum & Minerals
  • Alternate 23896
    A New Automated Carrying Capacity Index Model Optimizes Hole Cleaning Efficiency And Rate Of Penetration By Applying Machine Learning Technique
    M. Al-Rubaii, Saudi Aramco D&WO
  • Alternate 23874
    Application Of Machine Learning To Predict Well Path Deviation For Enhanced Drilling Efficiency
    H. Khalifa, University of Boumerdes; A. Laalam, University of North Dakota
  • Alternate 23882
    Advanced Lwd Technologies Complemented With Deep Learning
    A. Al-Qasim, Saudi Aramco PE&D; A. Alzayani, K. Katterbauer, PE&D Saudi Aramco

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