Machine Learning Augmented Two-Fluid Model for Segregated Flow

Abstract

Segregated flow, including stratified and annular flows, is commonly encountered in several practical applications such as chemical, nuclear, refrigeration, and oil and gas industries. Accurate prediction of liquid holdup and the pressure gradient is of great importance in terms of system design and optimization. The current most widely accepted model for segregated flow is a physics-based two-fluid model that treats gas and liquid phases separately by incorporating mass and momentum conservation equations. It requires empirically derived closure relationships that have the limitation of being applicable only under a narrow range of input parameters under which they were developed. In this paper, we proposed a more generalized machine learning augmented two-fluid model, using a database that spans the range of various flowing conditions and fluid properties. Machine learning algorithms such as random forest, neural networks, and gradient boosting were tested for the best performing data-driven predictive model. The new model proposed in this work successfully captures the complex, dynamic, and non-linear relationships between the friction factor and flowing conditions. A comprehensive model evaluation against nineteen existing correlations shows the best results from the proposed model.

Improved Two-Fluid Model for Segregated Flow and Integrated Multiphase Flow Modeling for Downhole Pressure Predictions

“…This provides flexibility but, in the meantime, increases the complexity because of the f I correlation selection and the fact that dozens of interfacial friction factor correlations are available in the literature. Each was developed for different flowing conditions or using different databases [8]. Hence, one of the advantages of the proposed integrated model is that it eliminates the need for changing f I correlations when the flowing condition varies, which reduces the complexities associated with closure relationship selection and alteration.…”

“…Most existing models propose to use the single-phase friction factor to determine the liquid and gas wall friction factors in the two-fluid model with hydraulic diameters [5][6][7]. On the other side, numerous correlations can be found for the interfacial friction factor [8]. Once the liquid holdup is determined from the CME, the pressure gradient can be solved from either Equation (1) or (2).…”