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 International Drilling Conference and Exhibition 2023  SPE/IADC International Drilling Conference and Exhibition
  4-6 March 2025 | Stavanger Forum, Norway


Well Construction Process Automation

Thursday, 7 March
Grand Ballroom B
The drilling industry is moving fast to cope with an increasing number of automated systems designed to improve safety, reliability, or performance of drilling operations. The variety of actors, the intrinsic complexity of drilling processes and the uncertainty in how systems, controls, or states are defined or even designated are major obstacles to their seamless integration at the well site. In this session, we will look at how the drilling community is developing standards and taxonomies to support automated systems interoperability and at actual implementations of automated processes and applications in the field.
Gilles Pelfrene - NORCE Norwegian Research Centre AS
Isabel Poletzky - Weatherford
  • 1240-1305 217754
    Taxonomy Describing Levels of Autonomous Drilling Systems: Incorporating Complexity, Uncertainty, Sparse Data, With Human Interaction
    J. de Wardt, DE WARDT & CO.; E. Cayeux, NORCE; R. Mihai, NORCE Norwegian Research Centre AS; J. Macpherson, Baker Hughes; P. Annaiyappa, Consultant; D. Pirovolou, Weatherford
  • 1305-1330 217748
    Interoperability for Drilling Process Automation
    R. Van Kuilenburg, Noble Drilling (U.S.) Inc.; M. Isbell, Hess Corp.; M. Behounek, Apache Corp.; J. Macpherson, Baker Hughes; S. Schaefer, Exebenus; T. Fox, Helmerich & Payne Intl Drlg Co; D. Pirovolou, Weatherford
  • 1330-1355 217746
    Automated Pump Startup: A Collaborative Approach Towards Drilling Systems Automation
    P. Arevalo, F. Schuberth, R. Aragall, D. Dashevskiy, J. Koeneke, Baker Hughes; M. Lien, S. Hovda, Equinor ASA; K. Evensen, HMH
  • 1355-1420 217751
    The Value of Process and Application Consistency in Drilling Automation
    S. Kern, S. Auld, Z. Whitlow, Helmerich & Payne; F. Hopwood, Helmerich & Payne Intl Drlg Co; M. Willerth, Helmerich & Payne
  • Alternate 217963
    Enhancing Stuck Pipe Risk Detection in Exploration Wells Using Machine Learning Based Tools: A Gulf of Mexico Case Study
    D. Gomes, Exebenus; T. Jaritz, Wintershall DEA; T. Robinson, O.E. Revheim, Exebenus
  • Alternate 217936
    Application Of Advanced Buckling Model Leads To Lighter Well Architecture For Deepwater Development, Saving Cost And CO2 Emissions
    S. Farmer, F. Aichinger, Helmerich & Payne; A. Patel, Tullow Oil