3 papers
stat.ML2024
A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes
Bjarne Grimstad, Kristian Løvland, Lars S. Imsland +1
In many industrial processes, an apparent lack of data limits the development of data-driven soft sensors. There are, however, often opportunities to learn stronger models by being…
eess.SP2024
Flow Fusion, Exploiting Measurement Redundancy for Smarter Allocation
Christine Foss Sjulstad, Danielle Monteiro, Bjarne Grimstad
In petroleum production systems, continuous multiphase flow rates are essential for efficient operation. They provide situational awareness, enable production optimization, improve…
cs.LG2023
Sequential Monte Carlo applied to virtual flow meter calibration
Anders T. Sandnes, Bjarne Grimstad, Odd Kolbjørnsen
Soft-sensors are gaining popularity due to their ability to provide estimates of key process variables with little intervention required on the asset and at a low cost. In oil and…