Morten Hansen Jondahl


Fakultet for teknologi, naturvitenskap og maritime fag
Institutt for elektro, IT og kybernetikk
Campus Porsgrunn (O-203)
PhD candidate conducting research on sensor systems and models for estimation of return flow from oil-well drilling. Working in a project called SEMI-KIDD which focuses on early detection of kick and loss incidents. Applying knowledge of hard sensors, and mathematical modelling to develop new, cost-effective sensor systems. Also applying my experience as a field engineer to make the system fit for purpose and future implementation. Main supervisor is Håkon Viumdal.


Jondahl MH, Viumdal H. Estimating Rheological Properties of Non-Newtonian Drilling Fluids using Ultrasonic-Through-Transmission combined with Machine Learning Methods. In: 2018 IEEE International Ultrasonics Symposium (IUS). 2018. p. 1–4.

Chhantyal K, Jondahl MH, Viumdal H, Mylvaganam S. Upstream Ultrasonic Level Based Soft Sensing of Volumetric Flow of Non-Newtonian Fluids in Open Venturi Channels. IEEE Sensors Journal. 2018 Jun;18(12):5002–13.

Jondahl MH, Viumdal H, Mozie KN, Mylvaganam S. Rheological characterization of non-Newtonian drilling fluids with non-invasive ultrasonic interrogation. In: 2017 IEEE International Ultrasonics Symposium (IUS). 2017. p. 1–4.