Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter

Abdulrahman Basahel,Mohammad Amir Sattari,Ehsan Nazemi,Osman Taylan

doi:10.3390/math9111227

Abdulrahman Basahel, Mohammad Amir Sattari + Show 2 more

Open Access

https://doi.org/10.3390/math9111227

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Abstract

The increasing consumption of fossil fuel resources in the world has placed emphasis on flow measurements in the oil industry. This has generated a growing niche in the flowmeter industry. In this regard, in this study, an artificial neural network (ANN) and various feature extractions have been utilized to enhance the precision of X-ray radiation-based two-phase flowmeters. The detection system proposed in this article comprises an X-ray tube, a NaI detector to record the photons, and a Pyrex-glass pipe, which is placed between detector and source. To model the mentioned geometry, the Monte Carlo MCNP-X code was utilized. Five features in the time domain were derived from the collected data to be used as the neural network input. Multi-Layer Perceptron (MLP) was applied to approximate the function related to the input-output relationship. Finally, the introduced approach was able to correctly recognize the flow pattern and predict the volume fraction of two-phase flow’s components with root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of less than 0.51, 0.4 and 1.16%, respectively. The obtained precision of the proposed system in this study is better than those reported in previous works.

Highlights

Optimization of separation processes is not possible except with enough knowledge of the quantitative measurement of gas and oil components
The emitted photons from the X-ray tube pass through the pipe, in which the two-phase flow components are being examined, and the portion of them that is not attenuated inside the pipe is detected by the detector
As the blue star is close to the red line, the planned network is more precise

Summary

Introduction

Optimization of separation processes is not possible except with enough knowledge of the quantitative measurement of gas and oil components. The type of flow pattern impacts the efficiency of the separation process in such a way that the percentage of each component indicates whether the drilling needs to be stopped or not. In [1], a calculation of volumetric percentages in three-phase flows was performed by using a dual-energy source and three detectors. Abro and Johansen [2] researched the gas volume ratio by measuring two-phase flows. Their method consisted of a single 241 Am source and three detectors

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