Multiphase Flow Meters Targeting Oil &amp; Gas Industries

Meribout, Mahmoud; Aberqi, Ahmed; Ghendour, Nabil; Kharoua, Nabil; Khezzar, Lyes; AlHosani, Esra

doi:10.1016/j.measurement.2020.108111

Cited by 60 publications

(17 citation statements)

References 53 publications

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“…Performance, efficiency, and sustainability of industrial processes that involve multiphase flows are determined by the way different phases are contacted. Examples can be found in (bio) chemical engineering, , medicine, , food production processes, , mining, , and water and wastewater treatment , among others. , There, very often the gas phase is dispersed into the continuous phase in the form of bubbles. Reducing the bubble size at the same gas flow increases mass transfer.…”

Section: Introductionmentioning

confidence: 99%

A Mechanistic Model for Bubble Formation from Microscale Orifices under Constant Gas Flow Conditions

et al. 2021

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We developed a mechanistic model for calculation of bubble volume from orifices in the range from 0.03 mm to 0.193 mm under the constant gas flow conditions in a quiescent liquid. It is known that for such small orifices, the mechanism of bubble formation is highly dependent on the gas momentum force and the liquid inertia force. Accordingly, the model incorporates these forces to calculate the bubble volume in three consecutive stages. Moreover, the model includes the influence of the bubble base expansion and bubble rising induced liquid velocity on the formation of bubbles. Eventually the model is validated with our own experimental data using air and deionized water. Experimental validation of the model confirms that the maximum deviation of the model is less than 10%.

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Section: Introductionmentioning

confidence: 99%

A Mechanistic Model for Bubble Formation from Microscale Orifices under Constant Gas Flow Conditions

et al. 2021

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“…The measured capacitance

can be used to determine the Liquid Volume Fraction

through linear data fitting. The two time-series signals of capacitance

and

can be used to estimate the total volume flowrate through cross-correlation as follows [ 2 , 3 , 4 ]:

…”

Section: Metering System and Methodsmentioning

confidence: 99%

“…Currently, the commonly used metering method is to separate the multiphase flow into oil, gas and water first and then measure their respective flowrates with single-phase flowmeters [ 3 ]. However, the separators are usually bulky and expensive, and the separation process is time-consuming [ 4 ]. Therefore, real-time online measurements for each individual oil well cannot be realized with this method.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, real-time online measurements for each individual oil well cannot be realized with this method. In addition, with the depletion of onshore oil fields, more attentions have been turned offshore, where the compact and expensive offshore platforms place more stringent requirements for the size of a multiphase metering system [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Multi-Sensor Fusion Algorithm Based on Uncertainty Analysis

Xue

Zhang

et al. 2021

Sensors

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During the research and development of multiphase flowmeters, errors are often used to evaluate the advantages and disadvantages of different devices and algorithms, whilst an in-depth uncertainty analysis is seldom carried out. However, limited information is sometimes revealed from the errors, especially when the test data are scant, and this makes an in-depth comparison of different algorithms impossible. In response to this problem, three combinations of sensing methods are implemented, which are the “capacitance and cross-correlation”, the “cross-correlation and differential pressure” and the “differential pressure and capacitance” respectively. The analytical expressions of the gas/liquid flowrate and the associated standard uncertainty have been derived, and Monte Carlo simulations are carried out to determine the desired probability density function. The results obtained through these two approaches are basically the same. Thereafter, the sources of uncertainty for each combination are traced and their respective variations with flowrates are analyzed. Further, the relationship between errors and uncertainty is studied, which demonstrates that the two uncertainty analysis approaches can be a powerful tool for error prediction. Finally, a novel multi-sensor fusion algorithm based on the uncertainty analysis is proposed. This algorithm can minimize the standard uncertainty over the whole flowrate range and thus reduces the measurement error.

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“…An ultrasonic flowmeter was used in natural gas metrology and process control areas based on the principle of the difference in transit time between upstream and downstream flows [ 8 , 9 ]. An electromagnetic flowmeter and a conductance sensor were introduced to measure the gas–oil or gas–water multiphase flow industries [ 10 , 11 , 12 ]. The accuracy and stability of the above-mentioned flow rate measurement devices were verified.…”

Section: Introductionmentioning

confidence: 99%

Development of a Flowmeter Using Vibration Interaction between Gauge Plate and External Flow Analyzed by LSTM

Jin

Chung

Park

2020

Sensors

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(1) Background: This study is aimed at the development of a precise and inexpensive device for flow information measurement for external flow. This novel flowmeter uses an LSTM (long short-term memory) neural network algorithm to analyze the vibration responses of the gauge plate. (2) Methods: A signal processing method using an LSTM neural network is proposed for the development of mass flow rate estimation by sensing the vibration responses of a gauge plate. An FFT (fast Fourier transform) and an STFT (short-time Fourier transform) were used to analyze the vibration characteristics of the gauge plate depending on the mass flow rate. For precise measurements, the vibration level and roughness were computed and used as input features. The actual mass flow rate measured by using a weight transducer was employed as the output features for the LSTM prediction model. (3) Results: The estimated flow rate matched the actual measured mass flow rate very closely. The deviations in measurements for the total mass flow were less than 6%. (4) Conclusions: The estimation of the mass flow rate for external flow through the proposed flowmeter by use of vibration responses analyzed by the LSTM neural network was proposed and verified.

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Multiphase Flow Meters Targeting Oil & Gas Industries

Cited by 60 publications

References 53 publications

A Mechanistic Model for Bubble Formation from Microscale Orifices under Constant Gas Flow Conditions

A Mechanistic Model for Bubble Formation from Microscale Orifices under Constant Gas Flow Conditions

A Novel Multi-Sensor Fusion Algorithm Based on Uncertainty Analysis

Development of a Flowmeter Using Vibration Interaction between Gauge Plate and External Flow Analyzed by LSTM

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