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A machine vision system for quantifying velocity fields in complex rock models

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In this paper we describe a machine vision system capable of high-resolution measurement of fluid velocity fields in complex 2D models of rock, providing essential data for the validation of the numerical models which are widely applied in the oil and petroleum industries. Digital models, incorporating the properties of real rock, are first generated, then physically replicated as layers of resin or aluminium (200 mm × 200 mm) encapsulated between transparent plates as a flowcell. This configuration enables the geometry to be permeated with fluid and fluid motion visualised using particle image velocimetry. Fluid velocity fields are then computed using well-tested cross-correlation techniques.

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References

  1. Grant, I.: Particle imaging velocimetry: A review. In: Proceedings of the Institution of Mechanical Engineers, vol. 211, no. C, pp. 55–76 (1997)

  2. Jensen, A., Sveen, J.K., Grue, J., Richon, J.-B., Gray, C.: Accelerations in water waves by extended particle image velocimetry. Exp. Fluids 30, 500–510 (2001)

    Article  Google Scholar 

  3. Eisele, K., Zhang, Z., Wildi, J., Müller, K.: The application of a particle tracking velocimetry system with a high speed video camera on racing cars. In: Proceedings of the 7th International Conference on Laser Anemometry, pp. 755–760 (1996)

  4. Santiago, J.G., Wereley, S.T., Meinhart, C.D., Beebe, D.J., Adrian, R.J.: A particle image velocimetry system for microfluidics. Exp. Fluids 25, 316–319 (1998)

    Article  Google Scholar 

  5. Frisch, U., Hasslacher, B., Pomeau, Y.: Lattice-gas automata for the Navier-Stokes equation. Phys. Rev. Lett. 56(14), 1505–1508 (1986)

    Article  PubMed  Google Scholar 

  6. Benzi, R., Succi, S., Vergassola, M.: The Lattice Boltzmann Equation: Theory and Applications. Phys. Rep. (Review section of Physics letters) 222(3), 145–197 (1992)

    Google Scholar 

  7. Bonnet, E., Bour, O., Odling, N.E., Davy, P., Main, I., Cowie, P., Berkowitz, B.: Scaling of fracture systems in geological media. Rev. Geophys. 39(3), 347–383 (2001)

    Article  Google Scholar 

  8. Cassidy, R., McCloskey, J., Morrow, P.J.: Fluid velocity fields in 2D heterogeneous porous media: Empirical measurement and validation of numerical prediction. In: Shaw, R.P. (ed.) Understanding the Micro to Macro Behaviour of Rock-Fluid Systems, vol. 249, pp. 115–130. Geological Society London Special Publications (2005)

  9. Cundall, P.A., Strack, O.D.L.: A discrete numerical model for granular assemblies. Geotechnique 29, 47–65 (1979)

    Article  Google Scholar 

  10. Davy, P.: On the frequency-length distribution of the San Andreas fault system. J. Geophys. Res. 98, 12141–12151 (1993)

    Article  Google Scholar 

  11. Brown, S.R.: Fluid flow through rock joints: The effect of surface roughness. J. Geophys. Res. 92, 1337–1347 (1987)

    Article  Google Scholar 

  12. Power, W.L., Tullis, T.E., Brown, S.R., Boitnott, G.N., Scholz, C.H.: Roughness of natural fault surfaces. Geophys. Res. Lett. 14(1), 29–32 (1987)

    Article  Google Scholar 

  13. Power, W.L., Durham, W.B.: Topography of natural and artificial fractures in granitic rocks: Implications for studies of rock friction and fluid migration. Int. J. Rock Mech. Min. Sci. 34(6), 979–989 (1997)

    Article  Google Scholar 

  14. Bernhard, P., Hofmann, M., Schulthess, A., Steinmann, B.: Taking lithography to the third dimension. Chimia 48, 427–430 (1994)

    Google Scholar 

  15. Turcotte, D.L.: Fractals and Chaos in Geology and Geophysics, Cambridge University Press, Cambridge, pp. 73–94. (1993)

  16. Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in FORTRAN 77: The Art of Scientific Computing, Cambridge University Press, Cambridge, pp. 992. (1992)

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Correspondence to Rachel Cassidy.

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Rachel Cassidy is a Research Associate in Geophysics at the University of Ulster. Dr. Cassidy's research interests include percolation theory and its application to fluid flow in fractured rock, the fractal and multifractal properties of natural phenomena and the development of experimental techniques for investigating fluid flow in porous fractured media with realistic structure and exhibiting scale invariance. She is currently involved in the development of molecular tracer techniques for characterising reservoir heterogeneity.

Philip Morrow is currently a Senior Lecturer in the School of Computing and Information Engineering at the University of Ulster. Dr. Morrow has a BSc in Applied Mathematics and Computer Science, an MSc in Electronics and a PhD in Parallel Image Processing, all from the Queen's University of Belfast. His main research interests lie in image processing, computer vision and parallel/distributed computing. He has published over 65 research papers in these areas.

John McCloskey is Professor of Geophysics and Head of the School of Environmental Sciences at the University of Ulster. Prof. McCloskey's research interests are in the application of ideas of chaos and complexity to a variety of geophysical problems including earthquake dynamics and fluid flow in fractured porous rock. He has published over 100 articles and is a regular contributor to international press on matters connected with earth science.

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Cassidy, R., Morrow, P.J. & McCloskey, J. A machine vision system for quantifying velocity fields in complex rock models. Machine Vision and Applications 16, 343–355 (2006). https://doi.org/10.1007/s00138-005-0005-z

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  • DOI: https://doi.org/10.1007/s00138-005-0005-z

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