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Machine Learning for Production Optimization

Tuesday, 4 October
370 D-F
Technical Session
Applications of machine learning in production optimization.
Session Chairperson(s)
Satomi Suzuki - ExxonMobil Technology & Engineering Co
  • 1400-1425 210408
    Intelligent Application Of Computer Vision And Data Analytics To Optimize The Separators Cleaning For Unconventional Reservoirs
    J.R. Parizek, Chevron North America; A.S. Popa, Chevron Corporation; S. Tam, Chevron North America
  • 1425-1450 210277
    An Optimum Well Control Using Reinforcement Learning And Policy Transfer; Application To Production Optimization And Slugging Minimization
    J. Poort, J. van der Waa, T. Mannucci, P. Shoeibi Omrani, TNO
  • 1450-1515 210475
    Leveraging Machine Learning And Interactive Voice Interface For Automated Production Monitoring And Diagnostic
    A.P. Singh, A. Shukla, S. Purwar, Amazon Web Services
  • 1545-1610 210235
    Flowing Bottomhole Pressure Prediction With Machine Learning Algorithms For Horizontal Wells
    S. Baki, S. Dursun, Saudi Aramco
  • 1610-1635 210495
    Bayesian Networks Applied To ESP Performance Monitoring And Forecasting
    S. Dussi, R. Octaviano, P. Shoeibi Omrani, TNO
  • 1635-1700 210061
    Accelerating Pipeline Corrosion Modeling Via Bayesian Active Learning
    S. Zhang, Massachusetts Institute of Technology; L. Lu, H. Yang, K. Tsai, Shell Intl E&P, Inc.; M. Sidahmed, Shell Global Solutions International BV
  • Alternate 210220
    Creating An Auto-encoder Based Predictive Maintenance Tool For Offshore Annulus Wells
    A. Jain, A. Morgenthal, M. Aman, M. Horton, S. Khan, SparkCognition

Prepare for an Unforgettable Opening Session!

Through an insightful discussion, we aim to provide a comprehensive understanding of the past, present, and future of innovation within the Oil & Gas industry, inspiring a new era of energy professionals committed to shaping a resilient and sustainable energy landscape.

Moderator: Elena Melchert | Podcast Host and Consultant | Oil and Gas Global Network