15 citations · 25 across the 4 of their papers we have counts for
4 papers
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…
Multi-task neural networks by learned contextual inputs
Anders T. Sandnes, Bjarne Grimstad, Odd Kolbjørnsen
This paper explores learned-context neural networks. It is a multi-task learning architecture based on a fully shared neural network and an augmented input vector containing traina…
Multi-task learning for virtual flow metering
Anders T. Sandnes, Bjarne Grimstad, Odd Kolbjørnsen
Virtual flow metering (VFM) is a cost-effective and non-intrusive technology for inferring multiphase flow rates in petroleum assets. Inferences about flow rates are fundamental to…
Bayesian Neural Networks for Virtual Flow Metering: An Empirical Study
Bjarne Grimstad, Mathilde Hotvedt, Anders T. Sandnes +2
Recent works have presented promising results from the application of machine learning (ML) to the modeling of flow rates in oil and gas wells. Encouraging results and advantageous…