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Drilling Automation

Tuesday, 4 March
Room 1
Technical Session
This session will cover various applications within drilling automation. The digital drilling program will be revisited, with discussions around recent developments. One presentation will address the automatic classification of drilling activities and the resulting improvements in operational efficiency. Another paper will focus on the automated correction of drillstring data, aimed at enhancing the reliability of physics-based models used in Drilling Advisory Systems. Additionally, the session will explore time series pattern recognition techniques for detecting drilling and production events.

The e-poster session will feature an early warning system for diesel engine failure, a probabilistic framework for risk-based evaluation of drilling plans, and a cloud-enabled transient wellbore simulation workflow designed for testing operations
Chairperson
Kriti Singh - Corva
Rolv Rommetveit - EDRILLING
  • 0345-0410 223774
    Drilling Automation: Revisiting the Digital Drilling Program
    E. Cayeux, B. Daireaux, G. Pelfrene, R. Mihai, NORCE Norwegian Research Centre AS
  • 0410-0435 223786
    Automated Correction of Drillstring Data for Improved Reliability and Trust in Use of Physics-based Models in Drilling Advisory Systems
    D. Yoon, Intellicess, Inc.; M. Yi, Intellicess; J. Cortez Juarez, M. Behounek, P. Ashok, Intellicess, Inc.
  • 0435-0500 223782
    Automatic Online Classification of Drilling Activities
    E. Cayeux, NORCE Norwegian Research Centre AS; J. Macpherson, Baker Hughes; H. Brackel, Baker Hughes INTEQ GMBH; J.K. Igland, S. Schaefer, Exebenus
  • 0500-0525 223795
    Automated Drilling and Production Event Detection Using Advanced Time-Series Pattern Recognition Techniques
    A.C. Montes, K. Sudyodprasert, The University of Texas at Austin; Y. Wu, University of Texas At Austin; P. Ashok, E. van Oort, The University of Texas At Austin
  • Alternate 223787
    Early Warning System for Diesel Engine Failures in Drilling Operations using Long Short-Term Memory Network
    K. McCarthy, T. Ziehm, A. Mitkus, T. Gee, P. Reynerson, H. Lee, P. Gupta, M. Willerth, Helmerich & Payne
  • Alternate 223781
    A Probabilistic Framework For The Risk-based Evaluation Of Drilling Plans
    B. Daireaux, NORCE Norwegian Research Centre AS; A. Ambrus, S. Moi, E. Cayeux, NORCE