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Schedule of Events 2026

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AI Applications in Well Construction and Economic

Tuesday, 14 April
Room 2
Technical Session
  • 1100-1130 232114
    Enhancing Drilling Performance Using Real-time Machine Learning Models: A Framework For Predicting Formation Transitions During Drilling Operations
    R.M. Elgaddafi, Australian University Kuwait; R. Ahmed, University of Oklahoma
  • 1130-1200 231950
    Machine Learning For Capital Estimation In Oil And Gas Projects
    C. Nugraha, Petronas Carigali Sdn Bhd
  • 1200-1230 232257
    Enhancing Drilling Efficiency And Precision Through Downhole Directional Drilling Automation In 12 ¼” Deviated Section, A Case Study In Offshore Abu Dhabi
    W. Fares, K. Mossallam, Halliburton; M. Cesetti, ADNOC Offshore
  • Alternate 232034
    Machine Learning Application For Reciprocating Compressor Performance Prediction Under Varying Suction Pressures: A Case Study On Gas Pipeline Pump-back Operations
    T. Ismail, UNIVERSITY OF WYOMING; E. Amer, PETROGISTIX
  • Alternate 232241
    Data-driven Autonomous Gas-lift Optimization Leveraging Iot, Edge Computing, And Machine Learning
    K. Heshmat, M. Alkharraz, Weatherford Saudi Arabia
  • Alternate 232116
    Research And Application Of Intelligent Diagnosis And Decision Technology For Cementing: A Case Study Of Deep Coal Rock Gas Gt1h Well In Dagang Oilfield, China
    D. Su, Y. Shi, Southwest Petroleum University; S. Tang, Petroleum Engineering Research Institute,PetroChina Dagang Oilfield Company; J. Sun, S. Huang, Z. Li, Southwest Petroleum University
  • Alternate 232264
    Bridging The Gap Between Seismic And Well-derived Porosity In Stacked Carbonate Reservoirs: Lessons From A Mature Oil Field
    J... Ahmad, S. Alhammadi, J.H. Al Shehhi, ADNOC Offshore
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