Dr. Roman Shor is the principal investigator of the integrated Drilling Research Laboratory (iDRL) at the University of Calgary. The focus of iDRL is drilling system optimization, mechanization and automation, but also includes work in the application of machine learning, artificial intelligence and computer vision to the fields of drilling and completions.
Current Projects
- Geothermal Energy. Multiple projects investigating drilling for hot and deep geothermal reservoirs, systems designs for shallow geo-exchange systems, thermal conductivity and thermal flows in reservoirs, and community engagement.
- Drillstring modeling. By modeling the drillstring using the wave equation, adding the proper form of distributed friction and investigating the proper couplings between vibration modes, it is possible to develop real time physics based models which may be used for control.
- Drilling parameter optimization and vibration reduction through machine learning techniques. By training classifiers using historic datasets which include downhole data, it is possible to identify drilling parameter regions which result in lower drillstring vibration and increased drilling performance.
- Developing advanced closed loop control for drilling operations. To handle latency and delay in drilling systems, realtime models may be used for feedforward and model predictive control to improve drilling performance.
- Machine Learning. Applications of machine learning techniques to tool life estimation and fracture optimization. Work ranges from downhole tool life prediction to well cost analysis.