Drilling data analytics 

PhD Candidate Magnus Nystad

Main Supervisor Alexey Pavlov

Sponsor: NTNU

The main objective of this project is the development and testing of data-based methods that automatically navigate the input variables of the drilling process (such as WOB, RPM, flow rate) to their optimal values in real time while adhering to constraints. The methodology is based on model-free automatic optimization methods that gather information about the current drilling situation through small variations in the input parameters and take optimization actions in accordance with the system response. The expected outcome of the project is an algorithm/prototype software to optimize drilling variables while adhering to operational constraints.

Project result: Real-time drilling optimization through continuous micro-testing
Automatic detection of formation properties and real-time optimization of the drilling process