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1–3 March 2023
Bangkok, Thailand

2024 Technical Program

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143 Embracing ML/AI Petrophysical Interpretation

Wednesday, 14 February
Room 10
  • 1600-1620 23487
    Predicting Mineralogy By Well Logs And Thermal Profile Using Machine Learning In Unconventionals
    B. Gainitdinov, Skoltech
  • 1620-1640 23490
    Prediction Of NMR T2 Macro- And Micro-porosity With Machine Learning Techniques: Considering The Constraints Of ECS Lithology Classification
    Z. Han, Z. Tariq, B. Yan, King Abdullah University of Science and Technology
  • 1640-1700 23572
    Advancing Relative Permeability And Capillary Pressure Estimation In Porous Media Through Physics-informed Machine Learning And Reinforcement Learning Techniques
    R. Kalule, S. Ahmed, H. Abderrahmane, W. AlAmeri, Khalifa University
  • 1700-1720 23588
    Cnn-accelerated Rock Property Estimation From Angle-stack Seismic Data
    H. Di, A. Abubakar, SLB
  • Alternate 23598
    Deep Learning For Predicting Evaporite Salt In The Mediterranean: A Case Study
    F. JIANG, Halliburton; S. Das, Halliburton Landmark; S. Ligeza, K. Osypov, J. Wrobel-Daveau, Halliburton; S. Aikaterini, P. Aristotelis, Hellenic Petroleum
  • Alternate 23580
    Big Data Analysis Using Machine Learning And Anomaly Detection Methods To Predict Porosity In Carbonate Formations
    A. Janjua, A. Abdulraheem, King Fahd University of Petroleum & Minerals; Z. Tariq, King Abdullah University of Science and Technology
  • Alternate 23595
    Advanced Machine Learning Framework For Enhanced Lithology Classification And Identification
    P. Zhang, C. An, Variables Intelligence Corporation; T. Gao, Variables Intelligence LLC; R. Li, M.H. Holtz, Variables Intelligence Corporation
  • Alternate 23561
    Real Time Petrophysics Via Artificial Intelligence In Ultra-brown Field Development
    S. Sansudin, PETRONAS; J. Mohd Shah, A. Zakeria, Petronas Carigali Sdn Bhd; I. Marzuki Gazali, M. B M Fadhil, H. Husni, PETRONAS
  • Alternate 23538
    Automated Machine Learning (automl) For Subsurface Well Log Predictions
    Y.A. Almubarak, Saudi Aramco Exploration; A. Koeshidayatullah, King Fahd University of Petroleum and Minerals
  • Alternate 23581
    Rapid Rock Properties Estimation From Micro-CT Images By Deep Leaning
    K. Alsamadony, A. Alabdrabulrasul, M. Mahmoud, College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals
  • Alternate 23537
    Machine-Learning-Assisted Petrophysical Rock Type Classification And Permeability Estimation With Flow Zone Indicators
    E. Andrew, Aramco Americas; C. Xu, Aramco Research Center; U. Odi, A. Silver, S. Sheludko, Aramco Americas; Y. Alzayer, Saudi Aramco Upstream Technology Co.

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