Proposing an Intelligent Dual-Energy Radiation-Based System for Metering Scale Layer Thickness in Oil Pipelines Containing an Annular Regime of Three-Phase Flow

Osman Taylan, Mona Abusurrah, Saba Amiri, Ehsan Nazemi, Ehsan Eftekhari-Zadeh and Gholam Hossein Roshani
Additional contact information
Osman Taylan: Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589, Saudi Arabia
Mona Abusurrah: Department of Management Information Systems, College of Business Administration, Taibah University, P.O. Box 344, Al-Madinah 42353, Saudi Arabia
Saba Amiri: Razi University, Kermanshah 6714414971, Iran
Ehsan Nazemi: Imec-Vision Lab, Department of Physics, University of Antwerp, 2610 Antwerp, Belgium
Ehsan Eftekhari-Zadeh: Institute of Optics and Quantum Electronics, Friedrich-Schiller-University Jena, Max-Wien-Platz 1, 07743 Jena, Germany
Gholam Hossein Roshani: Electrical Engineering Department, Kermanshah University of Technology, Kermanshah 6715685420, Iran

Mathematics, 2021, vol. 9, issue 19, 1-14

Abstract: Deposition of scale layers inside pipelines leads to many problems, e.g., reducing the internal diameter of pipelines, damage to drilling equipment because of corrosion, increasing energy consumption because of decreased efficiency of equipment, and shortened life, etc., in the petroleum industry. Gamma attenuation could be implemented as a non-invasive approach suitable for determining the mineral scale layer. In this paper, an intelligent system for metering the scale layer thickness independently of each phase’s volume fraction in an annular three-phase flow is presented. The approach is based on the use of a combination of an RBF neural network and a dual-energy radiation detection system. Photo peaks of 241 Am and 133 Ba registered in the two transmitted detectors, and scale-layer thickness of the pipe were considered as the network’s input and output, respectively. The architecture of the presented network was optimized using a trial-and-error method. The regression diagrams for the testing set were plotted, which demonstrate the precision of the system as well as correction. The MAE and RMSE of the presented system were 0.07 and 0.09, respectively. This novel metering system in three-phase flows could be a promising and practical tool in the oil, chemical, and petrochemical industries.

Keywords: scale-layer thickness; three-phase flow; volume fraction-independent; petroleum pipeline; dual-energy technique; radial basis function; neural network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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