Abstract
Micro-Fabric Analyzer (MFA) is a new GIS-based tool for the quantitative extrapolation of rock microstructural features that takes advantage both of the characteristics of the X-ray images and the optical image features. Most of the previously developed edge mineral grain detectors are uniquely based on the physical properties of the X-ray-, electron-, or optical-derived images; not permitting the exploitation of the specific physical properties of each image type at the same time. More advanced techniques, such as 3D microtomography, permit the reconstruction of tridimensional models of mineral fabric arrays, even though adjacent mineral grain boundaries with the same atomic density are often not detectable. Only electron backscatter diffraction (EBSD) allows providing high-performing grain boundary detection that is crystallographically differentiated per mineral phase, even though it is relatively expensive and can be executed only in duly equipped microanalytical laboratories by suitably trained users. Instead, the MFA toolbox allows quantifying fabric parameters subdivided per mineral type starting from a crossed-polarizers high-resolution RGB image, which is useful for identifying the edges of the individual grains characterizing rock fabrics. Then, this image is integrated with a set of micro-X-ray maps, which are useful for the quantitative extrapolation of elemental distribution maps. In addition, all this is achieved by means of low-cost and easy-to-use equipment. We applied the tool on amphibolite, mylonitic-paragneiss, and -tonalite samples to extrapolate the particle fabric on different metamorphic rock types, as well as on the same sandstone sample used for another edge detector, which is useful for comparing the obtained results.
Highlights
Petrogenetic processes are mostly controlled by chemical–physical counterbalancing factors such as deposition mechanisms vs. diagenesis for sedimentary rocks, emplacement or flow dynamics vs. crystal solidification velocity for plutonic and volcanic rocks, respectively, and deformation vs. recovery processes for metamorphic rocks
We provide for the first time a new Geographic Information Systems (GIS)-based toolbox (Micro-Fabric Analyzer—MFA)
After several tests with different samples acquired at different resolutions, we found that a resolution of ≈5 μm of pixel size corresponding to a scan resolution of 4800 dpi (Table 1) is an optimal trade-off for image quality, hard drive storage of the inputs/outputs obtained by the Micro-Fabric Analyzer (MFA), and processing time
Summary
Petrogenetic processes are mostly controlled by chemical–physical counterbalancing factors such as deposition mechanisms vs. diagenesis for sedimentary rocks, emplacement or flow dynamics vs. crystal solidification velocity for plutonic and volcanic rocks, respectively, and deformation vs. recovery processes for metamorphic rocks. In this view, the quantitative restitution of mineralogical composition and fabric arrangement of rock constituents are crucial parameters to be determined in unravelling most of the geological processes. Many efforts have been focused on the development of quantitative extrapolation techniques that are useful for obtaining more increasingly performing rock microstructural features. All these methods can be summarized in three different groups, which are subdivided in function of the image acquisition physical properties. These methods are based on three crucial points: (a) the image-acquiring methods; (b) the prefiltering process; and (c) the algorithm used for edge detection extraction [1,2,3,4,5,6,7]
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