New approaches in 3D visualization and analysis of rocks

International Geological Congress, Oslo, August 2008

Klaus Gessner, Andrew Squelch, M. Ben Clennell, Eun-jung Holden,
Paul Bourke, Bodey R. Baker, Cameron Walsh, Robert Hough, Jie Liu,
Klaus Regenauer-Lieb, Hagen Deckert, Michael Drews


Recent advances in the use of imaging techniques like digital photogrammetry, synchrotron analysis and X-ray tomography provide exciting opportunities to view, analyse and present high resolution geological and mineralogical data in three dimensions. In this paper we present examples of outcrop scale and micro-scale datasets and outline current and future applications in rock mechanics, petroleum geology, hydro-geology, structural geology and mineralogical microanalysis.

In the first example we present an automatic technique to detect anisotropic features on rock surfaces. Surface roughness is an important rock property, which is measured for structural geology and engineering purposes. The analysis method has been applied to synthetic surfaces, and to digitally mapped point clouds of natural rock surfaces shaped by weathering, fault wear, and mining.

In the second example we present an algorithm to generate discontinuity density maps from 3D surface models generated by digital photogrammetry methods. Our method is an extension of the one-dimensional scan-line approach to quantify discontinuities in rock outcrops and has the advantage to take into account a larger amount of spatial data than conventional manual measurement methods. This methodology has potential for application in rock mass characterization, structural and tectonic studies, the formation of hydrothermal mineral deposits, oil and gas migration, and hydro-geology.

In a third example we show how 3D material distributions within a rock sample can be visualized in datasets acquired by X-ray tomography and synchrotron analysis. We show examples from hydrothermal ore deposits, hydrocarbon reservoirs and seals, and present means of calculating and visualizing object shape orientation.

Our analysis methods represent steps towards developing a tool-kit to automatically detect and interpret spatial rock characteristics, by taking advantage of the large amount of data that can be collected by photogrammetric and micro-analytical methods.