Digital Solution for Production Optimization and Production Losses Estimation Using Data Analytics on Real Time in the Shushufindi Field

Abstract In an aging field like Shushufindi, where an intensive activity of new wells and interventions take place, commingle production is establishing and a water flooding project is reaching maturity, it is of paramount importance to have high frequency and high accuracy production data to be able to fine-tune models, to evaluate, to estimate optimization impacts and to reduce losses. A digital solution was implemented to allow early identification of events, estimate production losses, and thus classify and prioritize events for optimizations using data analytics. Production monitoring and optimization have been arduous to accomplish due to problems at surface facilities like cross flow at manifold valves, shared production lines, unstable production from commingled wells and low well test repeatability. The last one due to reduced number of operative equipment such as separators and multiphase flow meters. With the application of big data and data analytics, a Virtual Flow Meter has been created, calibrated and run-on real time for several pilot wells. Such VFM uses the ESP's data and the fluid characteristics, integrated with a dashboard from a business intelligence tool that was developed to rank critical wells to intervene for optimizations. The pilot application allows to quantify the volume lost during operative events in the wells and the volume gained with optimizations, integrating a powerful production monitoring and ESP parameters surveillance tool to guarantee the continuity of operations, maximize wells optimization and to increase operation efficiency and productivity. An average of 475 bopd are associated to deferred production. Using a data base platform and the connectivity provided by SCADA's optical fiber, all the variables can be monitored on real time to develop data analytics and make an early identification of events, give a rapid response and to reduce the production losses. This digital implementation has shown remarkable results allowing to reduce 80% of manual process time, optimizing field operator's mobilizations (less transport time, CO2eq emissions/year and lower mobilizations risk involved), response time from days to minutes and ensuring the operative continuity of the production, optimizing cost, maximizing people efficiency, and evolving the monitoring process. This paper shows the pilot wells selection, the Virtual Flow Meter creation using data analytics, calibration and connections to run the digital application on real time with a dashboard from a business intelligence tool. This solution is a clear example of what The Digital Transformation capability brings to any oilfield, showing to the industry that is not only an example to optimize production but also to settle down that EDGE computing, data analytics and data science can be applied at all maturity levels in the oil and gas industry becoming a mind changer for the next generations.