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1–3 March 2023
Bangkok, Thailand

2024 Technical Program

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084 AI Applications in Reservoir Simulation and Management

Tuesday, 13 February
Room 11
  • 1600-1620 24367
    Predicting Subsurface Reservoir Flow Dynamics At Scale With Hybrid Neural Network Simulator
    M. Maucec, R. Jalali, Saudi Aramco PE&D; H. Hamam, Saudi Aramco, PE&D
  • 1620-1640 24362
    Physics-informed Neural Networks For Modeling Flow In Heterogeneous Porous Media: A Decoupled Pressure-velocity Approach
    A. Alhubail, King Abdullah University of Science and Technology; M. Fahs, F. Lehmann, University of Strasbourg; H. Hoteit, King Abdullah University of Science and Technology
  • 1640-1700 24296
    Integration Between Different Hydraulic Fracturing Techniques And Machine Learning In Optimizing And Evaluating Hydraulic Fracturing Treatment
    M. Ali, M. Bulatnikov, NESR
  • 1700-1720 24310
    AI-enabled Reservoir Pressure Prediction Method Using Production And Injection Data In Middle East Carbonate Reservoirs
    D. Badmaev, ADNOC Upstream; L. Saputelli, Abu Dhabi National Oil Company
  • Alternate 24355
    Machine Learning-enabled Classification System To Screen And Rank Horizontal Wells By Sidetracking Success Criteria
    M. Maucec, Saudi Aramco PE&D; N. Bu-khamseen, Saudi Aramco, PE&D; A. Aneddame, Saudi Aramco PE&D; M. Hisham, Saudi Aramco, PE&D
  • Alternate 24268
    Towards Developing Data Driven Probabilistic Reservoir Models
    S. Alsinan, Saudi Aramco PE&D; H. Alghenaim, Saudi Aramco; I. Hoteit, KAUST University
  • Alternate 24264
    A New Ensemble Machine-learning Framework For Analyzing Production Capacity Of Future Deployed Wells In Tight Gas Reservoir
    J. Ying, Petroleum Exploration and Production Research Institute, SINOPEC; L. Huang, Research Institute of Petroleum Exploration and Development, PetroChina; C. Zhao, SWPU; G. Ren, Research Institute of Exploration and Development, North China Oil and Gas Company, SINOPEC
  • Alternate 24294
    Prediction And Forecasting Of Saturations Using Dense-net Architecture And Graph Convolution Networks (gcns) Based Hybrid Model.
    A. Kumar, R. Kumar, A. Kumar, K. Gnanasambantham, Telesto Energy
  • Alternate 24308
    Long-term, Multi-variate Production Forecasting Using Non-Stationary Transformer
    A. Kumar, Visage Technology

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