Optimisation of the Smart Plunger Lift Work System and a New Method for Diagnosing Working Conditions

Abstract

Abstract Liquid loading in natural gas wells is a widespread problem worldwide. The plunger lift is one of the most effective methods for deliquification. The smart plunger, as a novel technology, is equipped with sensors at the plunger bottom to monitor pressure and temperature at each production stage. In recent years, numerous scholars have proposed optimization methods for plunger lift work system. However, most of these methods rely on theoretical calculations and fail to consider actual reservoir conditions, resulting in significant discrepancies between calculated outcomes and real-world observations. Also, the working condition of the plunger lift is monitored by changes in tubing and casing pressure, which cannot diagnose complex situations such as wellbore waxing and blockages. In this study, a judgment diagram referring to working condition is established using real-time data from wellhead tubing and casing pressure, and an optimization method for the smart plunger work system is proposed based on the dynamic prediction of reservoir conditions. This approach combines theoretical calculations with field data and uses real-time measurements, adjusting the theoretical calculations to get more accurate dynamic reservoir predictions than traditional optimization methods for plunger lift. Additionally, the smart plunger can automatically adjust the work system through programming. Moreover, based on the sensor data of the smart plunger, a plunger position versus pressure "Dynamometer card" has been proposed, which can more effectively identify faulty plunger lift conditions. This method can accurately identify previously undetectable conditions such as wellbore waxing and downstroke oscillations. The optimization and condition diagnosis of the plunger lift system requires manual tracking to make timely adjustments work system. However, the current process is time-consuming, labor-intensive, and lacks intelligence. For this condition, the smart plunger can provide real-time adjustment of the work system and condition diagnosis, significantly improving deliquification performance and extending the plunger's service life.