Virtual Flow

Virtual flow metering (VFM) uses computational models to estimate multiphase fluid flow rates in real-time, primarily in oil and gas production, offering a cost-effective alternative to traditional meters. Current research emphasizes improving VFM accuracy and robustness by addressing model limitations, particularly the challenges posed by non-stationary processes. This involves exploring advanced calibration techniques, such as sequential Monte Carlo methods and passive learning approaches (periodic batch and online learning), to adapt models to changing conditions and maintain prediction accuracy over extended periods. Improved VFM accuracy translates to better production optimization and enhanced resource management in the energy sector.