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Human-Centric Technology

Tuesday, 4 March
Room 4
Technical Session
Recent user-driven drilling enhancements highlight increased usage of digital twins, AI-driven operations, and simulation-based learning. Leading experts will present real-world insights on how human factors, simulation-based learning, and AI tools are transforming drilling performance, safety, and wellbore stability. Join us to gain perspectives on optimizing operations through design, field validation, and cross-collaboration, as we showcase the future of drilling innovation.
Chairperson
Serafima Schaefer - Exebenus
Sarah Kern - Helmerich & Payne
  • 0345-0410 223691
    Integration Of Three Digital Twins: A New Perspective On Wellbore Stability And Drilling Optimization
    T. Kristiansen, Aker BP ASA; J. Nabavi, S. Ødegård, eDrilling; S. Hovda, Norwegian University of Science & Technology; M. Hallaråker, NTNU; D. Speirs, Rockfield Global; A. Bere, Rockfield Global Technologies; D. Roberts, Rockfield Global
  • 0410-0435 223668
    Impact Of Change Implementation In The Driller`s Control Cabin: A Human Factors Assessment With Design Implications
    E. Arndt, Equinor ASA; I. Hoffart, EGGS design; S. Gabrielsen, Equinor ASA
  • 0435-0500 223683
    Validating Rig Control Services for Commissioning: Comprehensive Field Validation to Gain End User Acceptance
    S. Wessling, M. Forshaw, A. Manseth, Baker Hughes; M. Lien, S. Hovda, Equinor ASA; M. Ørevik, NOV Rig Techologies; S. Seldal, Shelf Drilling; E. Leirvik, DNV
  • 0500-0525 223694
    Lessons Learned from Operating a Simulation-based Drilling Smart Twin: a 10-year and over 600 Drilled Wells Journey
    A. Martins, R. Tobisawa, Petrobras; F.R. da Silva, M.V. dos Santos, G.L. Mendes, ESSS; A. Fernandes, Petrobras; I. Spoladore, V. Girardi Silva, ESSS
  • Alternate 223828
    Development of The AI Drilling Agent: AI-Physics Hybrid Model for Accurate, Adaptive and Autonomous Decision-making
    J. Cao, R. Muhammad, E. Gocmen, J. Nabavi, S. Oedegaard, eDrilling
  • Alternate 223825
    Federated Learning for Drilling Data Integration: A Collaborative Framework with Application to LWD Lag Correction
    L. Ye, Xi'an Shiyou University; N. Zhang, C. Rong, University of Stavanger; J. Cao, eDrilling