Measuring Simplified Pore-Throat Angularity Using Automated Mathematical Morphology
- Aurelien G. Meyer (Natural History Museum of Denmark)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- February 2019
- Document Type
- Journal Paper
- 243 - 253
- 2019.Society of Petroleum Engineers
- pore throat, Image analysis, geometry, mathematical morphology, angularity
- 5 in the last 30 days
- 93 since 2007
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Fluid flow in sedimentary rocks is controlled mainly by the morphology of pore-connecting throats. Pore throats (PTs) typically exhibit diverse converging/diverging morphologies such as biconic, parabolic, or hyperbolic geometries. These different geometries are defined by variable opening angle, or angularity, between the throat walls from the narrowest point of the throat toward the pore body. Importantly, each of these geometries imposes different constraints on fluid flow. However, current pore-level flow models usually favor simple cylindrical or biconic throat morphologies, in part because of the difficulty to extract the throat angularity from pore-space imagery. An image-analysis technique called mathematical morphology has been used to characterize porosity in laterally continuous pore networks (e.g., in sandstones) from thin-section microphotographs. This method allows the extraction of petrophysical parameters such as pore and throat diameters through successive image alterations—namely, erosion/dilation cycles using an expanding structuring element (SE). This study proposes a novel application of this technique and quantifies PT angularity. Angularity can be measured from the throat toward the pore body so that the true geometry—biconic, parabolic, or hyperbolic—can be recognized. The technique is tested on simple geometries to demonstrate the correctness of the mathematic equations involved. Because all equations assume perfect, nonpixelated geometries while images are composed of square pixels, the accuracy of measurements depends strongly on image resolution. Pixelation causes significant fluctuations of ±2 to 10° around the correct angularity values that decrease in amplitude as image resolution increases. Finally, potential implications of this parameter on fluid-flow modeling are discussed.
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