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Measurement of Gas-Phase Velocities in Two-Phase Flow Using Distributed Acoustic Sensing

  • Guilherme Heim Weber
  • , Eduardo Nunes dos Santos
  • , Danilo Fernandes Gomes
  • , Ana Luiza Beltrão Santana
  • , Jean Carlos Cardozo da Silva
  • , Cicero Martelli
  • , Daniel Rodrigues Pipa
  • , Rigoberto Morales
  • , Sérgio Taveira de Camargo Júnior
  • , Manoel Feliciano da Silva Junior
  • , Marco Da Silva

Research output: Contribution to journalArticlepeer-review

Abstract

From wells to refining plants and distribution networks, operations in the oil and gas industry involve the transport of multiphase mixtures through long pipelines. One of the most representative patterns is the so-called slug flow, which is characterized by the intermittent passage of gaseous and liquid structures. The monitoring of slug flows allows for proper control and safety in many operations in the oil and gas industry. In recent years, distributed acoustic sensing (DAS) has emerged as a promising technology for industrial use and is applied here for flow monitoring. Namely, this article introduces the use of DAS for the measurement of slug flow. A number of flow configurations under controlled conditions are investigated. Measurements were carried out in a 9-m horizontal pipeline Section in a flow-loop laboratory. Fiber optics were helically wrapped along the outer surface of the pipeline to promote higher sensitivity at a higher spatial resolution space. The velocity of the gas phase given by the elongated bubbles velocity is estimated from DAS data through radial integration in k – f space and distributed cross correlation methods. Using measurements from a commercial conductance-based sensor as a reference, the results showed the root-mean-square deviation in % (RMSD%) of 8.34% and 12.18%. The cross correlation method has the clear advantage of being able to yield (spatial) distributed data.
Original languageEnglish
Pages (from-to)3597 - 3608
Number of pages12
JournalIEEE Sensors Journal
Volume23
Issue number4
DOIs
Publication statusPublished - Jan 2023

Fields of science

  • 202012 Electrical measurement technology
  • 202014 Electromagnetism
  • 202021 Industrial electronics
  • 202024 Laser technology
  • 202036 Sensor systems
  • 211908 Energy research
  • 101014 Numerical mathematics
  • 102003 Image processing
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202015 Electronics
  • 202016 Electrical engineering
  • 202022 Information technology
  • 202027 Mechatronics
  • 202037 Signal processing
  • 202039 Theoretical electrical engineering
  • 203016 Measurement engineering
  • 103021 Optics

JKU Focus areas

  • Digital Transformation

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