Water-Cut Measurement Techniques in Oil Production and Processing—A Review

Bushra Kamal, Zahra Abbasi () and Hassan Hassanzadeh ()
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Bushra Kamal: Department of Chemical & Petroleum Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada
Zahra Abbasi: Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada
Hassan Hassanzadeh: Department of Chemical & Petroleum Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada

Energies, 2023, vol. 16, issue 17, 1-27

Abstract: Water cut is a vital monitoring and surveillance parameter with great significance in oil production operations and processing. Water-cut measurements are also challenging due to the significant variations and the harsh measurement environment. The objective of this article is to review the current water-cut measurement techniques and suggest future areas that are expanding to overcome existing measurement challenges. Commercially available online methods such as capacitance-based sensors, tomography techniques, gamma densitometry, ultrasonic meters and infrared meters, and the traditional laboratory offline methods, are discussed, along with their principle of operation, detection range, and sensing resolution. Also, the discussed techniques are summarized, highlighting their main advantages and limitations. Furthermore, future trends and research areas, such as Artificial Intelligence (AI), soft computing, Metamaterials, and Nuclear Magnetic Resonance (NMR), which are integrated with water-cut measurements, are briefly mentioned. The current research hotspots are directed toward integrating full-range measurements with multi-parameter detection, high sensitivity, and reliability.

Keywords: water-cut measurement; production surveillance; production monitoring; production operation; upstream oil industry (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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