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Low-flow measurement of oil–water two-phase flow based on the dynamic swirling differential pressure method

物理 两相流 流量(数学) 机械 压差 差速器(机械装置) 相(物质) 流量测量 热力学 量子力学
作者
Huixiong Wu,Ruiquan Liao,H L Qin,Xingkai Zhang,Dong Wang
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:37 (3)
标识
DOI:10.1063/5.0260550
摘要

With the ongoing development of oilfield production, real-time monitoring of wellbore flow rates has become a crucial indicator for evaluating oilfield efficiency. However, under low-flow conditions, the sensitivity of differential pressure is insufficient, and existing differential pressure measurement methods are insufficient for accurate measurement under low-flow conditions. To address this, this study introduces a novel oil–water two-phase flow measurement device based on the dynamic spiral flow differential pressure method. By applying external forces to the swirling pipe section, the irregular upstream flow is forced into a distinct “oil-core water-ring” flow, generating both axial and radial differential pressures. The mechanisms behind these pressures are analyzed, and a theoretical dynamic swirling flow model is developed. Thorough laboratory experiments examine the relationships between the dual differential pressures and flow rate, water cut at various rotational speeds, with experimental data used to validate the model. The results indicate that the dynamic swirling method enhances the sensitivity of radial differential pressure measurements, with both flow rate and water cut positively correlated with the dual differential pressures. When rotational speed exceeds 3000 rpm and oil phase flow rate exceeds 0.7 m3/h, emulsification between the oil and water phases occurs, impacting measurement accuracy. Experimental validation of the established dynamic swirling flow oil–water two-phase measurement model reveals that the relative errors for flow rate and water cut are 4.69% and 7.53%, respectively. The method effectively extends the measurement range of oil–water two-phase flow using the differential pressure method, contributing to the advancement of intelligent oilfields.

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