In this paper, a new multiphase flow metering device for real-time measurement of oil, gas, and water flow rates is presented. It is composed of several electrical and acoustic sensors whose signals are digitalized and processed by a multilayer neural network. This latest uses the physical models of multiphase fluids to reduce the complexity of the parameter space while improving its accuracy. Furthermore, to overcome the uncertainties of the electrical sensors in the range of 40%-60% and above 90% water-cut (i.e., ranges where most of the multiphase flow meter fail), two rings of high- and low-frequency ultrasonic sensors are used for low and high gas fractions, respectively. The results of experiments that have been conducted in an in-house laboratory-scale multiphase flow loop show that real-time classification for up to 90% gas fraction can be achieved with less than 10% relative error.
|الصفحات (من إلى)||1507-1519|
|دورية||IEEE Transactions on Instrumentation and Measurement|
|المعرِّفات الرقمية للأشياء|
|حالة النشر||Published - يونيو 2010|
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