Optimizing the Gamma Ray-Based Detection System to Measure the Scale Thickness in Three-Phase Flow through Oil and Petrochemical Pipelines in View of Stratified Regime

ORCID
0000-0001-7739-0105
Affiliation
Electrical Engineering Department, King Khalid University, Abha 61411, Saudi Arabia
Mayet, Abdulilah Mohammad;
ORCID
0000-0002-2942-7839
Affiliation
College of Management and Design, Ming Chi University of Technology, New Taipei City 243303, Taiwan
Chen, Tzu-Chia;
ORCID
0000-0003-0951-174X
Affiliation
Petroleum Engineering Department, Australian University, West Mishref 13015, Kuwait
Alizadeh, Seyed Mehdi;
Affiliation
Electrical Engineering Department, King Khalid University, Abha 61411, Saudi Arabia
Al-Qahtani, Ali Awadh;
ORCID
0000-0002-9221-4385
Affiliation
Department of Chemistry, Faculty of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Alanazi, Abdullah K.;
Affiliation
Faculty of Computers and Artificial Intelligence, Cairo University, Giza P.O. Box 12613, Egypt
Ghamry, Nivin A.;
Affiliation
Department of Physics, College of Science, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, City Dammam 31441, Saudi Arabia
Alhashim, Hala H.;
GND
1231322179
ORCID
0000-0003-1480-1450
Affiliation
Institute of Optics and Quantum Electronics, Friedrich Schiller University Jena, Max-Wien-Platz 1, 07743 Jena, Germany
Eftekhari-Zadeh, Ehsan

As the oil and petrochemical products pass through the oil pipeline, the sediment scale settles, which can cause many problems in the oil fields. Timely detection of the scale inside the pipes and taking action to solve it prevents problems such as a decrease in the efficiency of oil equipment, the wastage of energy, and the increase in repair costs. In this research, an accurate detection system of the scale thickness has been introduced, which its performance is based on the attenuation of gamma rays. The detection system consists of a dual-energy gamma source ( 241 Am and 133 Ba radioisotopes) and a sodium iodide detector. This detection system is placed on both sides of a test pipe, which is used to simulate a three-phase flow in the stratified regime. The three-phase flow includes water, gas, and oil, which have been investigated in different volume percentages. An asymmetrical scale inside the pipe, made of barium sulfate, is simulated in different thicknesses. After irradiating the gamma-ray to the test pipe and receiving the intensity of the photons by the detector, time characteristics with the names of sample SSR, sample mean, sample skewness, and sample kurtosis were extracted from the received signal, and they were introduced as the inputs of a GMDH neural network. The neural network was able to predict the scale thickness value with an RMSE of less than 0.2, which is a very low error compared to previous research. In addition, the feature extraction technique made it possible to predict the scale value with high accuracy using only one detector.

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