Rachapudi, R. V. (Kuwait Oil Company) | Haider, B. Y. (Kuwait Oil Company) | Al-Mutairi, T. (Kuwait Oil Company) | Al Deyain, K. W. (Kuwait Oil Company) | Al-Yahya, M. (Kuwait Oil Company) | Shakeel, A. (Kuwait oil company) | Qureshey, K. R. (Kuwait Oil Company) | Harith, M. (Schlumberger)
Continuous well performance monitoring plays a key role in making decision related to well workover and production optimization. Well parameters and corresponding rates over a period of time will represent the change in well performance. Live Well models are useful for estimating the continuous well production rates. Well models become live if they get updated with changing fluid and reservoir properties along with proper calibration to latest well conditions.
In general industry practice is to update the model manually; this is a tidious and time consuming process. Umm Gudair Field Development team implemented a real time system using available resources that integrates and runs workflows between corporate data base, well surveillance data base and well models. Workflows were implemented as part of the real time system to calculate the well parameters from sensor readings and update the models to run on daily basis, such that the models become live and production rates will be estimated.
The daily output generated from the workflows is basically updated well models and parameters along with production estimation report that will get emailed to users. The daily report contains the information about well status, potential, reasons for well closure etc. The workflows are intelligent enough to flag the need for model calibration and surface rate measurements. The daily estimated well parameters will be saved back to database for visualization. In conclusion, real time system was implemented to keep the well models live and useful as a tool for optimizing the oil production, improving the ESP's run life and delaying the well intervention requirements.
Haider, Bader Y.A. (Kuwait Oil Company) | Rachapudi, Rama Rao Venkata Subba (Kuwait Oil Company) | Al-Yahya, Mohammad (Kuwait Oil Company) | Al-Mutairi, Talal (Kuwait Oil Company) | Al Deyain, Khaled Waleed (Kuwait Oil Company)
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.