A Dual-Parameter Measurement Method for Oil–Water Flow Based on a Venturi Embedded With Microwave Transmission Line Sensor

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Huimin Ma;Ying Xu;Chao Yuan;Yiguang Yang;Rongji Zuo;Linfei Cao;Tao Li
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引用次数: 1

Abstract

Accurate and real-time measurement of water cut (WC) and flowrate of oil–water flow is a critical factor in achieving intelligent digital oil field. In this article, a dual-parameter (WC and water flowrate) measurement method for oil–water flow is proposed based on a Venturi embedded with microwave transmission line sensor (V&MS). Dynamic experiments of horizontal fine dispersed oil–water flow are conducted. A two-dimensional finite element simulation model for V&MS under the fine dispersed flow is developed to simulate microwave phase outputs at 0%–100% WC. The simulation results agree with the experiments, providing a low-cost alternative to expensive oil–water dispersed flow tests. Furthermore, it is found that the flow patterns for 0%–10% WC and 40%–100% WC are water-in-oil and oil-in-water flows, respectively, but the flow patterns for 10%–40% WC are dispersions of water-in-oil and oil-in-water flow, and 20% WC is the transition point of the dominant continuous phase. When the water phase is continuous, V&MS has a higher sensitivity to phase signals. Finally, a WC prediction model (40%–100%) is developed by combining a modified Bruggeman model with microwave transmission line theory. Then, a discharge coefficient model is developed and the water flowrate is obtained by combining the pressure drop and the predicted WC. The absolute average relative deviation (AARD) of the predicted WC and water flowrate is 1.49% and 1.54%, respectively. The results suggest that appropriate sensing technology integration can offer a powerful solution for accurate and real-time determination of dual-parameter in oil–water flow systems.
基于文丘里嵌入微波传输线传感器的油水流量双参数测量方法
准确、实时地测量含水和油水流量是实现油田智能化数字化的关键因素。本文提出了一种基于文丘里嵌入微波传输线传感器(V&MS)的油水流量双参数(WC和流量)测量方法。进行了水平细分散油水流动动态试验。建立了细分散流下V&MS的二维有限元仿真模型,用于模拟0% ~ 100% WC时的微波相位输出。模拟结果与实验结果一致,为昂贵的油水分散流动试验提供了一种低成本的替代方法。0% ~ 10% WC和40% ~ 100% WC的流动形态分别为油包水和油包水,10% ~ 40% WC的流动形态为油包水和油包水的分散流动形态,20% WC为优势连续相的过渡点。当水相连续时,V&MS对相位信号的灵敏度更高。最后,将改进的Bruggeman模型与微波传输线理论相结合,建立了WC预测模型(40% ~ 100%)。在此基础上,建立了流量系数模型,并将压降与预测用水量相结合,得到了水流量。预测用水量和水量的绝对平均相对偏差(AARD)分别为1.49%和1.54%。结果表明,适当的传感技术集成可以为油水流动系统双参数的准确实时测定提供有力的解决方案。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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