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16 Drilling Mechanics IV - Applied Data Analysis for Drilling Dynamics

Wednesday, 8 March
Mastrafjorden A
Technical Session
Data analysis, machine learning, and automation are no longer new concepts in the oil and gas industry. This session presents some recently developed and deployed applications and tools that apply advanced data analysis techniques to better understand and optimize drilling dynamics.
Session Chairperson(s)
Khaydar Valiullin - WellsX
Mohammadreza Kamyab - Corva
  • 1545-1615 212515
    Deployment of a Hybrid Machine Learning and Physics Based Drilling Advisory System at the Rig Site for ROP Optimization
    M. Behounek, K. McKenna, T.S. Thetford, T. Peroyea, Apache Corporation; M. Roberts, J.D. Pearce, NOV Inc.; P. Ashok, M. Yi, D. Ramos, Intellicess Inc.
  • 1615-1645 212520
    Applying a Downhole Drilling Mechanics Tool to Improve Operational Procedures and Rig Operating Systems in Horizontal Wells
    I.S. Fonseca, Nabors Drilling Solutions; C. Dubois, ExxonMobil; M.R. Isbell, Hess Corporation; A.C. Groover, Nabors Industries
  • 1645-1715 212568
    Field Test Results for Real-time ROP Optimization Using Machine Learning and Downhole Vibration Monitoring - A Case Study
    R. Robertson, A. Deans, Tourmaline; K. Singh, D. Braga, M. Kamyab, C. Cheatham, Corva AI LLC; T. Borges, Formerly Corva AI LLC
  • Alternate 212456
    Drill String Failure Prediction Methodology Using Data Analytics for Real Time Well Engineering
    B. Thakur, V. Chokshi, K. Patel, University of Houston; R. Samuel, Halliburton