An optimization method based on mechanism model constraint for gas-liquid slug flow rate prediction

Abstract

Slug flow is a complex and unstable phenomenon that often occurs in petroleum extraction, chemical industry, etc. Accurate measuring of flow rates can aid in comprehending the initiation and progression mechanism of slug flow, thereby controlling or avoiding of slug flow appearance in industrial operations. Classic slug flow two-fluid models are commonly applied to predict pressure drop or hold-up, relying on known gas-liquid flow rates and empirical correlations. These models require numerous slug characteristic parameters as inputs, which are difficult to obtain with a single sensor. In this paper, in order to predict gas-liquid flow rates, the continuity and momentum equations based on the two-fluid model are firstly established. Then an optimization method based on these mechanistic model constraints is proposed to solve gas-liquid flow rates and the genetic algorithm is selected. In the optimization process, only ultrasonic sensors are utilized to obtain four slug characteristic parameters as inputs, including translational velocity of liquid slug, average height of liquid film, slug unit frequency and liquid slug length. Experiments are carried out in 50 mm diameter pipe with air and water as the media. The superficial gas velocity was in range of 1.0–3.0 m/s and superficial liquid velocity was in range of 0.2–0.4 m/s. Ultrasonic pulse echo method is applied to obtain these four parameters. 16 working conditions are tested. Finally, the mean absolute relative deviations (MARD) of the gas-liquid flow rate prediction results are 4.47 % and 2.50 %, respectively, which verifies the validity and accuracy of the new method.