Image Analysis of Granular Materials
Understanding the Effects of High Temperatures and Pressures
K.A. Snellink (TU Delft - Civil Engineering & Geosciences)
Auke Barnhoorn – Mentor (TU Delft - Applied Geophysics and Petrophysics)
Tobias Schmiedel – Mentor (TU Delft - Resource Engineering)
Dominique J.M. Ngan-Tillard – Graduation committee member (TU Delft - Geo-engineering)
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Abstract
Understanding the behaviour of rocks subjected to high temperatures and pressures is essential for a wide range of subsurface applications. This thesis aims to develop an image analysis methodology to measure the porosities and permeabilities of rock samples. These samples were created as part of the doctoral thesis of K.H.A.A. Wolf by compacting rock rubble in a copper tube and subjecting it to various high temperatures and pressures. Despite earlier image analysis on these samples, there was an opportunity for improvement using higher-resolution imaging and more advanced processing techniques. UsingaDSLRcameraand2typesoflight (normal and UV), 33 samples were photographed and then analysed using Adobe Photoshop and ImageJ. Additionally, three samples were selected to be scanned using a µCT scanner. The image processing included the conversion to greyscale, binarisation and the use of the morphological ”open” operation. Porosity was directly measured, while permeability was estimated using a modified Kozeny-Carman equation. The quality of the impregnation of the sample with UV dye differed, yet for 28 out of the 33 samples, imaging with UV light worked better than with normal light. Using temperature data from when the samples were formed, a clear trend emerged showing that the higher the temperature, the lower the porosity and permeability become. This trend was also visible in the work by Wolf (2006) and the values were generally in agreement, except for the samples with extremely low porosities and permeabilities. While CT and image analysis gave similar porosity values, permeability results differed, highlighting the need for simulation-based permeability estimates from CT data. Further research into impregnation techniques is also recommended to enhance future image analysis workflows.