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1–3 March 2023
Bangkok, Thailand

2024 Technical Program

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025 AI Applications in Drilling and Completions II

Monday, 12 February
Room 10
  • 1600-1620 24135
    Deep Learning Real-time Bit-wear Model Approves To Be Robust And Transferable In Hard Drilling Applications
    G. Zhan, A. Aljohar, Saudi Aramco PE&D; Y. Qahtani, Saudi Aramco D&WO; X. Huang, T. Luu, T. Furlong, Baker Hughes; J. Bomidi, HCC (Baker Hughes)
  • 1620-1640 24108
    Recommendation Engine For Clustering And Identifying Similar Bottom Hole Assemblies
    M. Khan, Baker Hughes Co. Saudi Arabia
  • 1640-1700 24176
    Application Of ANN-PSO Model For Predicting Fluid Density Of Water-Based, Oil-Based, And Synthetic Drilling Fluids Containing Bio-Additives
    Y. Balicaco, J. Arellano, Y. Corpuz, K. Tambiga, Palawan State University
  • 1700-1720 24100
    A Data-driven Approach To Infer The Dynamic Linear Swelling Of Shales Treated With Different Water Based Drilling Fluids
    M. Khan, SLB; Z. Tariq, KAUST; M. Murtaza, KFUPM
  • Alternate 24183
    Early Warning Method To Detect Mud Motor Stallings Incidents In Drilling Operations Using Machine Learning
    B.H. Zomarah, B. Otaibi, M.A. Zahrani, A. Saihati, Saudi Aramco
  • Alternate 24116
    Drilling Anomalies Identification Using Near Bit Vibrations
    N. Bukhanov, Aramco Innovations; A. Iufriakova, ITMO University; P. Golikov, A. Bakulin, Saudi Aramco PE&D
  • Alternate 24114
    Application Of Machine Learning In Predicting Cement Properties
    A. Shamsan, Halliburton Saudi Arabia; W. Cuello Jimenez, S. Jandhyala, Halliburton Energy Services Group
  • Alternate 24207
    AI-based Sand Screen Selection Via Deep Learning Model: Challenges, Lessons Learned, And Case Studies
    S. Ab Rasid, S. Shaffee, Petronas; M. Thant, M. Muhammad, PETRONAS Research Sdn Bhd

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