Production from Artificially lifted (ESP) well depends on the performance of ESP and reservoir inflow. Realtime monitoring of ESP performance and reservoir productivity is essential for production optimization and this in turn will help in improving the ESP run life. Realtime Workflow was developed to track the ESP performance and well productivity using Realtime ESP sensor data. This workflow was automated by using real time data server and results were made available through Desk top application.

Realtime ESP performance information was used in regular well reviews to identify the problems with ESP performance, to investigate the opportunity for increasing the production. Further ESP real time data combined with well model analysis was used in addressing well problems.

This paper describes about the workflow design, automation and real field case implementation of optimization decisions. Ultimately, this workflow helped in extending the ESP run life and created a well performance monitoring system that eliminated the manual maintenance of the data. In Future, this workflow will be part of full field Digital oil field implementation.

Keywords:
artificial lift system, artificial intelligence, production control, optimization problem, frequency, drillstem/well testing, production monitoring, drillstem testing, esp performance, flow rate
Subjects:
Artificial Lift Systems, Well & Reservoir Surveillance and Monitoring, Formation Evaluation & Management, Electric submersible pumps, Drillstem/well testing
Copyright 2012, Society of Petroleum Engineers
You can access this article if you purchase or spend a download.