In subsea oil and gas production, many important variables are not measured due to lack of reliable qualified sensors. Some of these variables are however essential for process control, monitoring and safety, and may further be used to plan interventions. State and parameter estimation are powerful tools to obtain estimates of un-measured variables and for improving the accuracy of measurements from inaccurate sensors.

In this project, we want to develop models for subsea processes, such as oil-water-gas separation. These models would form the basis for estimation of variables, such as oil concentration in water outlet of the separator. For estimation, we will use state-of-the-art estimation methods, such as moving horizon estimation, Bayesian estimation, extended Kalman filtering etc. Estimation algorithms, if needed, would be tweaked to cater for specific applications, such as online estimation and control.