Analyzing pressure and temperature data from smart plungers to optimize lift cycles

The problem of liquid loading is common for all gas producing wells and should be identified and solved for efficient gas production. Production engineers and operators need to choose the best solution possible, one that is cost effective and also efficient in doing the job. The plunger lift operation is a cost-effective solution to this liquid loading problem and also is efficient in increasing the gas production. However, the current understanding of plunger lift operation has used field experience and some previous models that have restrictive assumptions which might not be applicable for all plunger lift installations. This research proposes a new plunger lift model that overcomes some of the limiting assumptions of earlier models by using additional data available in the form of pressure and temperature from new technology like smart plunger. The model is based on fundamental principles of mass conservation and pressure balance, and uses the smart plunger data as input. The implementation of the model is carried out in user-friendly and easily accessible software like Excel VBA (Visual Basic Applications). The model predicts the plunger velocity, plunger position and annulus liquid level during an upward travel of the plunger in an onshore gas well in East Texas. The results of model implementation in VBA show the importance of fluid properties for the model, apart from indicating that the model is optimized for the given set of input data. The model developed in this research considers only pressure drop due to gravitational effects, and thus provides a scope for improvement in modeling the plunger lift dynamics by adding frictional and acceleration components. This research also provides recommendations for future work that can be carried out on plunger lift modeling using smart plungers