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16 Drilling Mechanics IV - Next Steps Towards Practical, Effective and Sustainable Solutions

Wednesday, 8 March
Technical Session
The industry continues to make giant positive strides in Drilling Optimisation, focusing on fundamental drilling concepts, physics-based discussions and a deeper understanding of all related disciplines – including Drilling Mechanics. This session, in addition to building onto what has already been achieved, challenges some of the industry’s currently held positions. Drilling dysfunctions are demystified based on innovative real-time and memory-based processes. Additionally, MSE shortfalls and limitations are identified and discussed, leading to new and appropriate recommendations for field deployment. Machine learning contributions to digital log generation, fluid circulation effects on Torque and Drag and process-based identification and avoidance of current drill-off-tests limitations will be discussed. In its totality, this must-see drilling mechanics session identifies drilling optimization challenges holistically. Most importantly, the discussions classify the next steps that must be tackled to achieve accelerated gains in drilling performance and project cost reductions.
Session Chairperson(s)
Mohammadreza Kamyab - Corva
Khaydar Valiullin - WellsX
  • 1600-1630 212515
    Deployment of a Combination Machine Learning and Physics Based Drilling Advisory at the Rig Site: Challenges and Solutions
    M. Behounek, Apache Corp.; K. McKenna, Colorado School of Mines; M. Yi, D. Ramos, P. Ashok, Intellicess, Inc.; T.S. Thetford, T. Peroyea, Apache Corp.
  • 1630-1700 212520
    Applying A Downhole Drilling Mechanics Tool To Improve Operational Procedures And Rig Operating Systems In Horizontal Wells
    I.S. Fonseca, Nabors Drilling USA; C. Dubois, ExxonMobil; M.R. Isbell, Hess Corp.; A.C. Groover, Nabors Industries; J. Clark, Exxonmobil
  • 1700-1730 212568
    Field Test Results For Real-time ROP Optimization Using Machine Learning And Downhole Vibration Monitoring - A Case Study
    R. Robertson, A. Deans, Tourmaline Oil; K. Singh, D. Braga, M. Kamyab, C. Cheatham, T. Borges, Corva
  • Alternate 212456
    Real-time Drill String Failure Prediction Methodology Using Data Analytics
    B. Thakur, University of Houston; R. Samuel, Halliburton Company

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