Paper: Using Real Time Automated Optimization and Diagnosis to Manage an Artificially Lifted Reservoir- A Case Study

Optimization of production from a reservoir produced by artificial lift can take weeks or months. The process typically involves gathering and amalgamation of operating data, then manual analysis of the data in software packages to find optimization opportunity.
To streamline and enhance this process, each artificially lifted well in the reservoir was equipped with an intelligent data processing device programmed with a real time model of the well. The processors were linked to a central access point where the operation of field could be remotely viewed in real time.
Each well's processor was provided with a target bottom hole flowing pressure or target flow rate to enable the optimum production of the reservoir. The real time system automatically compared the desired target drawdown values with the capability of the pumping system installed in each well, and automatically suggested the optimum operating frequency and well head pressure to achieve the target. Where the lift system was not capable of producing to the target bottom hole pressure, a larger pump was automatically recommended. As production conditions change the system automatically adapted its recommended operating points to compensate and maintain target production.
This paper discusses three case studies where real time optimization and diagnosis lead to improved production from the reservoir.