A new model for estimating the gas compressibility factor using Group Method of Data Handling algorithm (case study)

Abstract

It is crucial to accurately determine the gas compressibility factor (z factor) in chemical and petroleum engineering calculations. Empirical correlations are one of the most rapid and convenient methods of determining the gas compressibility factor. Most of correlations have been developed based on data from Standing–Katz chart, where for high‐pressure conditions (P > 3,000 Psia), solely the data of pure methane was adopted and finally plotted. Therefore, the performance of these correlations would deteriorate for pressurized gas reservoirs. This study intends to use the adopted data of Iranian gas reservoirs (as the second largest source) to develop an empirical correlation concerning with pressurized gas reservoirs. To this end, the correlation was presented based on corresponding states model through the robust group method of data handling algorithm. In comparison with foregone studies, results suggested improvements in prediction of gas compressibility factor with the proposed correlation by up to 9% of average absolute percentage relative error, yielding the error of 1.46% against real data.

Two-Phase Flow Pressure Drop Modelling in Horizontal Pipes with Different Diameters

“…Several methods exist (e.g., Kendall, Pearson and Spearman) in the literature to perform this analysis (Chok, 2010;Faraji et al, 2022). Pearson's relevancy factor (r) method was used as one of the most popular techniques for sensitivity analysis (Mesbah et al, 2017;Shariaty et al, 2019). The method is based on the relevant importance of each input variable on the output by assigning them a normalized scale between − 1 and 1.…”

Modeling natural gas compressibility factor using a hybrid group method of data handling

“…More information about this modeling approach can be found in our previous work (Hemmati-Sarapardeh & Mohagheghian, 2017). This method was recently used for modeling gas compressibility factor of Iranian gas reservoirs (Shariaty, Khorsand Movaghar, & Vatandoost, 2019).…”