This paper presents the application of real time monitoring techniques on production allocation in a complex scenario, focusing on definition of dedicated KPIs to identify possible issues in flowmeters installed at well level. The analysis includes a comparison with a dedicated Virtual Meter system.
Real time production allocation is monitored by means of a dedicated KPI dashboard, detecting any possible drift in Multiphase Flowmeter (MPFM) measurement processes. The ratio between reference measurements and MPFM readings is calculated for assessing allocation quality. Furthermore, an independent virtual flowmeter (VM) technique was developed to estimate well production rates and compare them with the MPFM flow rates. The VM relies on analytical models (Vertical Lift Performance) to correlate real time pressure losses in the tubing with flow rates. KPIs monitoring and VM are developed in a digital environment available to the engineers operating the field to provide a quick problem detection and a promptly response.
During the initial production phase, a good match between subsea and topside total MPFM readings and daily production figures resulted in a robust production back allocation. This trend was confirmed by the dashboard of allocation KPIs being within the acceptable thresholds. The Virtual Metering system was calibrated against MPFM rates during this initial production phase. After one year of production, KPIs showed a drift between the total subsea and topside MPFM readings, while a good match was achieved by virtual metering, topside MPFM and daily fiscal production. A well by well comparison between VM and MPFM installed at wellhead allowed to identify reliable MFPM and pinpoint the ones requiring retuning. In the meantime, during the troubleshooting process and actions implementation to restore the MPFM functionalities, the virtual metering estimations were used in the production back allocation process.
A combined application of the Virtual Meter and the KPIs monitoring enabled us to improve the quality of back allocation relying on the best type of well production estimation available at each phase of production. The methodology described in this paper entered the daily routines followed by engineers operating the field.
This paper shows the benefits of the digital platform for asset monitoring, as well as the technology that allowed to set up a cooperative environment. Sharing real-time data and model based estimation for a multi-disciplinary team, from Reservoir to Operations, facilitated working together to achieve faster trouble shooting and optimize production performance.