AI and machine learning techniques offer reliable solutions to transform data into valuable knowledge that can be applied in various stages of the life cycle to improve performance, reduce costs and pollutions.
Publisert:
Endret:
Ongoing research on applied AI and machine learning in the field of petroleum/digital drilling:
- Data issues automated detection and improvements
- Control and optimal algorithms design
- Machine learning on drilling-oriented fault detection and prediction
- AI algorithms tests on laboratorial systems
- Smart agent design via deep learning
- Data platform development
- Evaluation on ML models and algorithms
Staff and researchers
- Staff:
- Professor Dan Sui
- Professor Steinar Evje
- Professor Rune Wiggo Time
- Associate Professor Tomasz Wiktorski
- Researchers:
- Postdoc Ekaterina Wiktorski
- PhD candidate Andrzej Tunkiel
- Drillbotics team (15+ MSc students in IEP, IER, IDE, IMBM and ISØP)
Drillbotics Project (autonomous drilling rig design and test, drilling digital twin development)
Other ongoing relevant projects:
- Drilling Digitalization (AI for drilling)
- Openlab Drilling
- Digiwell (SFI)
Drilling Digitalization (AI for drilling)
Other ongoing relevant projects:
- Drillbotics Project (autonomous drilling rig design and test, drilling digital twin development)
- Openlab Drilling
- Digiwell (SFI)
Openlab Drilling
Other ongoing relevant projects:
- Drillbotics Project (autonomous drilling rig design and test, drilling digital twin development)
- Drilling Digitalization (AI for drilling)
- Digiwell (SFI)