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ABSTRACT
Optimizing production becomes a critical concern when it comes to comprehending the dynamics of two-phase flow and its impact on pressure fluctuations within wells. Numerous models, encompassing both empirical and mechanistic approaches, have been introduced to assess pressure drops in wells where a combination of oil and gas is produced (referred to as two-phase flow). Although numerous correlations and models are accessible for projecting pressure losses, these models were formulated with certain assumptions and are tailored to specific data ranges, making them less adaptable when applied to dissimilar datasets. Consequently, to fulfill our objective of evaluating how these correlations forecast pressure drops, we employed experimental data as our primary information source. This dataset encompassed liquid velocity, gas velocity, gas and liquid properties, film fraction, and pipe geometric characteristics, as derived from three distinct correlations: Beggs and Brill, Modified Hagedorn and Brown, and Duns and Ros. Most of the correlations and models intended for pressure drop calculations were initially established upon precise and dependable flow parameters. Hence, based on our comprehensive analysis, the Modified Hagedorn and Brown correlation exhibited superior prediction accuracy and required fewer variables, even when extrapolating beyond the original dataset's boundaries.
