... challenge, characterized by nonlinear, dynamic, and uncertain production behavior, making conventional analytical methods less effective ( Khan et al., 2019 ). Gilbert (1954) took a significant step toward the development of empirical correlations for gas lifted wells when he published his correlation...

...; be directly related to the multiple contact miscibility process. MMP computation using empirical correlations can be tedious, slow and prone to errors when handled manually. Hence a computerized process is needed just like the many petroleum engineering softwares including those used in EOR processes...

... correlation empirical correlation bubblepoint pressure api range gas gravity solution gas-oil ratio Vasquez and Beggs (1980) developed correlations using 6000 data points as they claimed, for API greater than 30 and API less than or equal to 30. Standing (1947) developed a correlation...

... experimental data. This experimental data might not be readily available when needed for a quick analysis and even when available, the process of tuning requires great skill and experience of the reservoir engineer. An empirical correlation for the vapourized oil-gas ration is proposed based on a statistical...

... method in order to predict the conditions for hydrates formation without considering water vapour pressure has one of the parameters that hydrates formation depend on. Thus, the existing correlations have some limitations. The proposed empirical correlation was developed using gravity method...

... lowest rank of 0.855 and better performance plot compared to existing empirical correlations. The Artificial Neural Network (ANN) is a biologically inspired computing scheme which is an analog, adaptive, distributive and highly parallel system that has been used in many disciplines and has proven...

..., this measurement is either not available, or very costly to obtain. In such cases, empirically derived correlations are used in the prediction of this property. This work focuses on the use an artificial neural network (ANN) to address the inaccuracy of empirical correlations used for predicting oil formation...