Enhanced Virtual Flow Metering (PhD)

Enhanced Virtual Flow Metering (PhD)

In subsea field developments, multiphase flowrate measurements play an important role in production optimization, rate allocation and reservoir management. Apart from the technical side, it is important for fiscal reasons to know the flowrates from satellite fields feeding into a field center with a different ownership. Usually, flowrates are measured by hardware multiphase flow meters which are expensive, have a limited operational envelope and are exposed to erosion and failures.

Virtual Flow Metering (VFM) is a method for estimating oil, gas and water flowrates produced from wells without measuring them directly. The method uses data from the field, such as pressure and temperature measurements as well as choke position, to estimate the flowrates by implementing hydrodynamic multiphase models and a reconciliation algorithm.

This project is dedicated to improving the understanding of this technology including identification of critical parameters, applicability of the concept and developing an optimal strategy for flow metering in terms of cost and accuracy. This may include a combination of hardware sensors and suitable modelling techniques. So far, the following has been done:

  • A VFM software based on OLGA and MATLAB has been developed
  • Analysis of the influence of sensor degradation on flowrate estimates based on Monte Carlo simulations and the constructed VFM software

The future plans include:

  • Perform a sensitivity study to identify the most critical measurements which influence the accuracy of VFM
  • Identify the dependence of errors caused by sensor degradation on different conditions (e.g. different Gas Oil Ratio values)
  • Identify an optimal strategy for flow metering in terms of cost and accuracy by implementing VFM technology
  • Evaluate the possibility of improving the flowrate predictions by using additional measurements
  • Evaluate the possibility and conditions of applying data-driven methods for VFM.


The results from this project can be used in subsea production planning and optimization, rate allocation and reservoir management.