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21 Machine Learning Enabled Processes

Thursday, 9 March
Technical Session
Session Chairperson(s)
Øystein Arild - University of Stavanger
Deep Joshi - Corva
  • 0900-0900 212502
    While-Drilling Pore Pressure Surveillance Using Machine Learning
    B.J. Spivey, ExxonMobil Technology and Engineering Company; R. Raman, ExxonMobil Services & Technology Pvt Ltd; R.J. Fink, S.L. Karner, M. Sundberg, ExxonMobil Technology and Engineering Company
  • 0930-1000 212479
    Improve Well Integrity Using a Machine Learning Based Cement Log Interpretation Tool
    E. Time, Equinor ASA; S. Mishra, E. Berg, Equinor; B. Singstad, Simula / Equinor
  • 1000-1030 212446
    Apples to Apples: Impartial Assessment of Drilling Technologies Through Big Data and Machine Learning
    D. Khvostichenko, G. Skoff, Y.I. Arevalo, S.M. Makarychev-mikhailov, Schlumberger
  • Alternate 212559
    Machine Learning-Based Drilling System Recommender: Towards Optimal BHA and Fluid Technology Selection
    G. Skoff, C. Chatar, C. Jeong, V. Vesselinov, F. Mahfoudh, S.M. Makarychev-Mikhailov, O. Petryshak, Schlumberger; V. Bondale, M. Devadas, Pluto7
  • Alternate 212481
    Automated Detection of Rig Events From Real-time Surface Data Using Spectral Analysis and Machine Learning
    T.S. Robinson, O.E. Revheim, Exebenus

Host Organisation

Equinor

Platinum Partner
 

Saudi Aramco

Diversity & Inclusion Session Co-Sponsor

 

Chevron

Diversity & Inclusion Session Co-Sponsor

 

 

NOV

Signage Sponsor

 

 

Baker Hughes

Tech Talks Sponsor

 

Oliasoft