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Big Data and Digital Transformation in Oil and Gas

2022 Technical Program


Big Data and Digital Transformation in Oil and Gas

Monday, 2 May
Technical / Poster Session
Digital transformation in oil and gas leverages automation and the end to end digital thread. This in turn improves asset and personnel performance through insights and predictivity, as well as simplifying the process workflow. The challenges with Big Data today involve the immense volume and speed at which data is collected. These data sets are so big in volume that traditional data processing software are unable to manage them. In this session we will address the digital twin concept which can be used for system optimization, predictive analysis, and enhanced performance. Automation lifecycle management, modeling for multiphase flow simulations, and well design using integrated cloud software will also be discussed.
Khiem Nguyen - Chevron ETC
Madeleine Kopp - Stress Engineering Services Inc
Sponsoring Societies:
  • American Society of Civil Engineers (ASCE)
  • American Society of Mechanical Engineers (ASME)
  • Society of Petroleum Engineers (SPE)
  • The Minerals, Metals, and Materials Society (TMS)
  • 1400-1422 31913
    The Digital Twin: Optimizing The System Design From The First Draft To The Cloud
    M. Kubacki, J. Duarte da Silva, A. Placido Neto, Bosch Rexroth
  • 1422-1444 31863
    Predictive Digital Twin For Performance And Integrity
    D. Kolak, Siemens Digital Industry Software; M. Straw, R. Mistry, Norton Straw; R. Aglave, Siemens Digital Industry Software; S. Lewis, Norton Straw
  • 1444-1506 31972
    Accelerate Digital Transformation In Oil And Gas Industry
    W.M. Ziadat, Weatherford; R. Kirkham, University of Manchester
  • 1506-1528 31938
    Hybrid Modeling For Multiphase Flow Simulations
    J. Henriksson, L. Wollebæk, Z. Yang, Turbulent Flux
  • 1528-1550 31950
    Automation Lifecycle Management - A Key For Sustained Value
    N. Ronquillo, N. Myers, K. Tangstad, NOV
  • 1550-1612 31783
    Subsurface Digital Models For Automated Drilling Risk Prediction In West Kuwait Jurassic Oilfields
    A. Al-shamali, N. Verma, P.K. Mishra, S. Kumar, R.B. Quttainah, Kuwait Oil Company; A. Rodriguez, Schlumberger; N. Al-Hamad, Schlumberger Oilfield Eastern LTD; J.C. Heiland, Schlumberger Oilfield UK Plc; B. Kumar, Schlumberger Oilfield Eastern LTD
  • 1612-1634 31731
    Review Of AI Implementations And Hybrid Data-physics Modeling For EOR Applications
    M.S. Ghamdi, Saudi Aramco D&WO



  • AAPG Logo
  • AIChE Logo

  • AIME
  • ASCE

  • ASME
  • IBP

  • MTS
  • SEG
  • SME

  • SPE
  • TMS