The project aim is to develop an automated MPD system that handles all operating conditions without the need of expert users.


Oil and gas constitute more than 50% of the energy consumption of the world today. To maintain growth and continue development more petroleum production is required. However, most of the easily accessible oil resources are already produced. There are still significant amounts of known oil and gas resources, but they are more challenging to drill down to. In an easy well, there are few challenges and traditional technologies can be used to drill. Now, more often than not, there are more considerations to be taken when a well should be drilled. Traditional methods can still be used, but they might pose an increased risk of accidents and failures, threatening crew safety, the environment, and economics.

In the last 20 years, new methods for tackling the increased difficulty in modern wells have been introduced. One method, that has gained more and more popularity since its introduction in the early 2000s, is managed pressure drilling (MPD). This technology is designed to increase crew safety by faster and more precise control of the drilling operation. Additionally, MPD has great potential to reduce non-productive time (NPT), which can be very expensive due to high rig day rates. There are many MPD systems on the market, but often they require a highly competent crew to operate safely and with high accuracy.

The aim of this Ph.D. thesis is to develop an MPD system that automatically handles a large variety of operating conditions. Such a system would be desirable for cost-effective implementation of the MPD technology on new drilling rigs and it offers the first viable solution for a fully integrated MPD system on drilling rigs. The focus of this thesis from the start until now has been on the development of robust methods for drilling control. With the use of advanced control methods, such as model-based and adaptive control, from the aerospace industry, we have developed a fully functional MPD system that monitors its own performance and automatically configures itself to constantly obtain the highest possible performance. The MPD system is already fielded and has so far been used in more than a dozen drilling operations.

The focus forward will be on the creation of standardized measures for MPD system performance. MPD systems are safety critical and failures can cause catastrophic consequences. Therefore, any MPD system should be verified on a set of relevant test cases before it is implemented in the field. These benchmark measures will be published as a resource for MPD comparison of MPD system performance. The results will be made available to the public.


Project at a glance

  • Title - Adaptive model-based control of downhole pressure during drilling operations
  • University - Norwegian University of Science and Technology (NTNU)
  • PhD candidate - Jon Åge Stakvik
  • Main supervisor - Ole Morten Aamo (NTNU)
  • Co-supervisor - Glenn-Ole Kaasa (Kelda)
  • Co-supervisor - Bernt Lie (HSN)
  • Partly founded by the Research Council of Norway through the industrial PhD program - project nr. 241636