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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We have built a novel automated machine vision system to quantify fully fluid velocity fields in 2D complex models of rock (integrating capture, control and image analysis algorithms in a single hardware/software application). The system was developed collaboratively with the University of Ulster's Geophysics research group in response to the lack of detailed empirical data. The research was funded by NERC and is significant in that, for the first time, we can obtain a complete picture of flow in a complex geometry that can be directly applied to test, validate and improve numerical models developed by the wider research community.