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Drilling Fluids - I

08 Mar 2022
Grand Ballroom C
Technical Session

In these sessions we review how new digital tools can bring benefits into the Drilling Fluids domain. 

In the first session we consider how enhanced modelling of the hydraulic system can bring improvements in control of the wellbore pressures and extend the reach of our new wells as well as enabling drilling into formations with a more challenging pressure regime. 

We also look into the use of Model Predictive Control to enhance the management and control of the critical mud properties through out the drilling process. 

In the second session we introduce AI and discuss how Machine Learning and Big Data can be brought into the mud selection, optimisation and management.

Session Chairs
Ashley Johnson - Schlumberger
John Thorogood - Drilling Global Consultant LLP

Site Sort Order

6

Proposal

  • 1345-1415208727Enhanced Annular Pressure Drop Modeling Assists To Drill Extreme Shallow Ultra-ERD Wells
    V. Lopes Pereira, A.J. Porter, D.E. Jamison, Halliburton
  • 1415-1445208730Enabling Foam Application in PMCD Using a Hydraulics Model
    S.S. Rao, ExxonMobil Upstream Research Company; J. Mollica, ExxonMobil Global Business Center; Q. Wu, ExxonMobil Upstream Research Company; G.A. Samdani, ExxonMobil Services & Technology Pvt Ltd; V. Gupta, ExxonMobil Upstream Research Company
  • 1445-1515208769Model Predictive Control for Automated Drilling Fluid Maintenance
    I. Feng, S. Gul, D. Chen, E. van Oort, The University of Texas At Austin

Proposal JSON

[{"proposaltitle":"Enhanced Annular Pressure Drop Modeling Assists To Drill Extreme Shallow Ultra-ERD Wells","TechnicalDiscipline1":"1. Drilling","proposalnumber":208727,"SessionRoleStatus":"Primary","proposaltime":"1345-1415","authorblock":"V. Lopes Pereira, A.J. Porter, D.E. Jamison, Halliburton"},{"proposaltitle":"Enabling Foam Application in PMCD Using a Hydraulics Model","TechnicalDiscipline1":"1. Drilling","proposalnumber":208730,"SessionRoleStatus":"Primary","proposaltime":"1415-1445","authorblock":"S.S. Rao, ExxonMobil Upstream Research Company; J. Mollica, ExxonMobil Global Business Center; Q. Wu, ExxonMobil Upstream Research Company; G.A. Samdani, ExxonMobil Services & Technology Pvt Ltd; V. Gupta, ExxonMobil Upstream Research Company"},{"proposaltitle":"Model Predictive Control for Automated Drilling Fluid Maintenance","TechnicalDiscipline1":"1. Drilling","proposalnumber":208769,"SessionRoleStatus":"Primary","proposaltime":"1445-1515","authorblock":"I. Feng, S. Gul, D. Chen, E. van Oort, The University of Texas At Austin"}]

Host Organisation

Equinor

Diversity and Inclusion Session Co-Sponsor

 

 

NOV