An Empirical Correlation to Predict Liquid Loading Considering Influences of Wellhead Data

Liquid loading is a common issue for gas wells. Obviously better predictions of liquid loading will help operators in reducing costs less shutdowns and improve revenue more production .Several authors have introduced various mathematical equations to calculate the critical flow rate necessary to keep gas wells unloaded. Turner's model is the most popular one in predicting liquid loading in gas wells. However, Field practice proves there is still quite gas condensate wells couldn’t be covered in the correlation of Turner et al. Besides turner and other models need laboratory parameters like surface tension and Z-factor which are not available in field right away so a new model would be necessary to be used in field practically. This paper presents a correlation drawing on field data sources, including the tubing size, wellhead pressure and temperature in addition to specific gravity which is representative of gas properties as major factors of liquid loading and points out that threshold value for liquid loading is a function of those parameters which make the presented model easy to use and the first model including just those simple physical parameters in the calculation of gas critical flow rate. Also well data were employed in the paper for evaluating and validation the new model. Turns out the prediction results from the new correlation are better than those from Turner's model, and even better than Turner’s adjusted model in matching real data. The model concludes new correlation have made significant progress toward calculate the critical flow rate of condensate gas wells with available field data quickly and likely to be more effective and applicable to a real situation.

کلیدواژه ها:

Liquid Loading ، Critical Rate ، AUT Correlation