Using Real Time Automated Optimisation & Diagnosis to Manage an Artificially Lifted Reservoir - A Case Study

Abstract

Abstract The time taken to safely optimise a reservoir produced by artificial lift can be measured in weeks or months. Typically the well by well process is as follows: Well testingAmalgamation of the well test data with down hole gauge and ESP controller dataAnalysis of the data to find the existing operation conditionsAnalysis of the ESP pump curve operating point and optimisation limitationsSensitivity studies in software to assess the optimum frequency and WHPNotification for the field operations to action the changesFurther well tests to verify the new production data.Analysis of the data to ensure the ESP and well are running optimally and safely at the new set points New technology enables this process to be performed in real time across the entire reservoir or field, significantly shortening the time to increased production and enabling real time reservoir management. 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 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 adapted its recommended operating points to compensate and maintain target production. This paper discusses three case studies where real time optimisation and diagnosis lead to improved production from the reservoir.