Weatherford unveils enhancement to ForeSite optimisation platform

Weatherford International has introduced an enhancement to the ForeSite production optimisation platform, expanding predictive failure analytics to electric submersible pumping systems (ESPs).

Another key enhancement to the field-wide intelligence software is the addition of complete optimisation capabilities for plunger-lifted wells.

The addition of predictive failure analytics for ESP systems strengthens the platform’s capabilities in reciprocating rod lift.

The ability to predict an ESP failure before it occurs helps reduce failure frequency, as well as total downtime and lost production, by introducing proactive failure management and planning.

The plunger-lift optimisation feature builds on ForeSite’s previous optimisation capabilities in rod lift, gas lift, natural drive and ESP-lifted wells.

ForeSite provides operators with real-time optimisation and surveillance, intelligent alerts, well modelling and plunger-cycle design.

Weatherford Production president Kyle Chapman said: “Since its launch, ForeSite has been deployed around the world with unmatched success, enabling operators to identify and prioritise their production opportunities.

“Simply put, the new ForeSite release gives operators the field-wide intelligence that they need to monetise their data. The new capabilities added to ForeSite combine an unprecedented ability to monitor performance and recognise current and future improvement opportunities across all reservoirs, wells, surface equipment and pipelines.”

ForeSite now supports edge-computing. The company noted that the combination of ForeSite modelling capabilities, advanced IoT-enabled hardware and CygNet SCADA software can help clients realise greater asset profitability, productivity and uptime.

Weatherford added that the release of ForeSite comprises automated well testing and the ability to execute well-work activities in the field through ForeSite Mobile.

Launched in May 2017, the ForeSite platform combines physics-based models with advanced data analytics to provide improved performance across wells, reservoirs and surface facilities on a single platform.