2D microwave tomography system for imaging of multiphase flows in metal pipes

Abstract The accurate measurement of multiphase flows is a major challenge in the process industry. In this paper, we present an experimental 8-port microwave tomography system for imaging of multiphase flows in metal pipes, primarily intended for oil–gas–water flows. A special sensor design is proposed which accounts for the requirements of the process industry and allows for broadband measurements in the frequency range from 0.7 GHz to 5.5 GHz. The electromagnetic behaviour of the sensor can be accurately modelled by a 2D model based on the finite element method (FEM) resulting in a moderate computational effort for image reconstruction. The hardware for data acquisition and the algorithm for image reconstruction are reported, focussing on the sensor design and the modelling of sensor's electromagnetic behaviour. The permittivity distributions in case of different static dielectric phantoms modelling oil/water-in-gas and gas/water-in-oil flow distributions were successfully reconstructed at frequencies between 1.25 GHz and 2.5 GHz using the one-step Gauss–Newton method.

[1]  B. T. Hjertaker,et al.  Three-phase flow measurement in the petroleum industry , 2012 .

[2]  Zhipeng Wu,et al.  Developing a microwave tomographic system for multiphase flow imaging: advances and challenges , 2015 .

[3]  Geir Anton Johansen,et al.  Recent developments in three-phase flow measurement , 1997 .

[4]  Thomas Musch,et al.  Ultra-Wideband Microwave Tomography: A Concept for Multiphase Flow Measurement , 2014 .

[5]  W. Chew,et al.  A frequency-hopping approach for microwave imaging of large inhomogeneous bodies , 1995, IEEE Antennas and Propagation Society International Symposium. 1995 Digest.

[6]  Henk A. van der Vorst,et al.  Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems , 1992, SIAM J. Sci. Comput..

[7]  D. Pozar Microwave Engineering , 1990 .

[8]  S. Semenov Microwave tomography: review of the progress towards clinical applications , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[9]  William R B Lionheart,et al.  Uses and abuses of EIDORS: an extensible software base for EIT , 2006, Physiological measurement.

[10]  Zhipeng Wu,et al.  Microwave-tomographic system for oil- and gas-multiphase-flow imaging , 2009 .

[11]  Lluis Jofre,et al.  Three decades of active microwave imaging achievements, difficulties and future challenges , 2010, 2010 IEEE International Conference on Wireless Information Technology and Systems.

[12]  R. Kress,et al.  Inverse Acoustic and Electromagnetic Scattering Theory , 1992 .

[13]  J. LoVetri,et al.  Microwave Biomedical Imaging Using the Multiplicative Regularized Gauss--Newton Inversion , 2009, IEEE Antennas and Wireless Propagation Letters.

[14]  George A. Kyriacou,et al.  MICROWAVE TOMOGRAPHY EMPLOYING AN ADJOINT NETWORK BASED SENSITIVITY MATRIX , 2009 .

[15]  P. M. Berg,et al.  A contrast source inversion method , 1997 .

[16]  Qing-Hua Huang,et al.  An optical coherence tomography (OCT)-based air jet indentation system for measuring the mechanical properties of soft tissues , 2009, Measurement science & technology.

[17]  Ruzairi Abdul Rahim,et al.  Microwave Tomography Application and Approaches – A Review , 2015 .

[18]  George A. Kyriacou,et al.  A Sensitivity Matrix Based Microwave Tomography Exploiting an Adjoint Network Theorem , 2007 .