Document Type: Research Paper
Department of Petroleum Engineering, Federal University of Petroleum Resources, Effurun, Nigeria
An accurate prediction of production rate for wellhead choke is highly vital in petroleum production engineering applications. It is deployed in the control of surface production, prevention of water and gas coning, and optimization of the entire production systems. Although there are several choke correlations in literature to estimate production rate; however, most of the published correlations were derived with datasets outside Niger Delta fields. Thus, this study presents a new empirical-based model, which is a derivative from Choubineh et al. model, to predict the liquid production rate of chokes for Niger Delta oil wells. The new model was developed and optimized using multivariate regression and the Generalized Reduced Gradient (GRG) optimization algorithm. Furthermore, a total of 283 production data points from 21 oil wells in 7 fields in the Niger Delta region, with a randomly generated ratio of 70: 30 of the datasets, was used to develop and validate the developed model. The developed Model 2 predicted the choke production rate with a fitting accuracy of average absolute percentage error (AAPE) of 23.73% and coefficient of determination (R2) of 0.973; in addition, the model predicted validating accuracy of AAPE of 9.33% while the coefficient of determination (R2) stands at 0.982. Consequently, this model can be relied on as a quick and robust tool for estimating the choke production rate of producing oil wells. Moreover, the sensitivity analysis results show that the choke size has the most significant impact on the predicted liquid rate. In contrast, gas gravity has the least impact.