Continuous surveillance of production and injection well flow rates throughout field life is essential for well performance monitoring, reservoir management and to meet operational targets. Ideally, surveillance would be achieved using multiphase flow meters on each well, but frequently this is not economically feasible. As an alternative to providing continuous flow rate surveillance, several real-time rate estimation methods can be implemented using existing surface/subsea & sub-surface measured variables, and obtain Best Real Time Estimations (BRTEs) based on the confidence in each method. BRTEs at well level can be added to provide Aggregated Real Time Estimations (ARTEs) at both field and facility levels. Where physical meters exist, a direct comparison and cross validation can be made with the relevant ARTEs, ensuring accuracy and confidence in ongoing well and field surveillance.

The above BRTEs/ARTEs approach has been deployed on a well performance monitoring system in the Petrofac operated Don Fields Development (North Sea UKCS), centred on real-time surveillance and advanced data processing & visualisation. Estimations were implemented based on first principle equations validated with integrated models of reservoir, well and subsea/surface networks, providing Liquid Rate, Oil Rate/Water Rate, Gas Rate and Gas Lift Rate estimations on the production wells, and Water Injection Rate estimations on injection wells. Deployment included user interfaces to allow BRTEs configuration and updating, as well as Aggregate Tables to compare ARTEs with physical field and facility flow meters.

In summary, BRTEs/ARTEs successfully achieved the concept of virtual flow metering on the Don Development, providing the means for continuous well, field and facility surveillance. This enhanced surveillance experience is enabling unique optimization opportunities, allowing engineers to determine optimum settings for maximizing asset production and associated revenue.

You can access this article if you purchase or spend a download.