MR21A-01 INVITED
3-D Flow pattern detection in magmas by image analysis
Detecting a magmatic flow pattern in an igneous rock is not easy. Mineral grains usually only display a weak mineral shape anisotropy, and late growth and boundary migration tend to erase the original magma fabric. A consistent preferred orientation pattern is therefore often impossible to detect by eye. However, image analysis of the same rocks, using only preferred orientation of grain boundaries can yield patterns that are very consistent over 10s of kilometres. Rapid analysis of boundary and of grain shapes on three or more sections can thus be used to build fabric ellipsoids and to constrain three-dimensional flow patterns. It is applied to various examples using SEM, microscope in a lab and camera in the field. http://www.sciences.univ-nantes.fr/geol/UMR6112/SPO
MR21A-02 INVITED
Kinematic and Petrologic Significance of Magma Mixing Structures in Igneous Rocks: Application of Fractal Geometry and Chaos Theory
The last few years have seen an extraordinary growth of interest in complex systems. In most scientific fields a new vocabulary is emerging to describe discoveries about wide-ranging and fundamental phenomena. Many of the terms have already become familiar: complexity, chaos, criticality, fractals, non-linear dynamics, self-similarity, and many more. All together they point to the emergence of new paradigms, cutting across traditional disciplines, for dealing with complex systems. These new concepts have also reached the field of igneous petrology. Magma interaction structures in igneous rocks are analyzed by applying methods of chaos theory and fractal geometry. It is shown that the development of magma mixing processes is closely associated to the onset of chaotic dynamics, the latter being responsible for the generation of fractal compositional patterns. In particular, in both two dimensional sections and 3D reconstructed rock samples, two types of dynamic regions are recognized to coexist at several length scales (from few microns to several meters). The first, defined Active Mixing Regions, are characterized by filaments of magmas showing strong deformation and intimate dispersion. The second, defined Coherent Regions, are characterized by the occurrence of globular portions of magmas showing little deformation and remaining as discrete entities. Microanalysis has been utilized to study the compositional variability within these two types of regions. Within Active Mixing Regions interfacial area between magmas increases exponentially generating strong chemical gradients and producing high degrees of hybridization in short times. On the contrary, Coherent Regions can preserve their composition for a long time due to the low and constant interfacial area between magmas. This feature allows Coherent Regions to survive complete hybridization. Starting from natural observations, magma interaction processes have been simulated by using chaotic dynamical systems in two and three dimensions. These systems reproduce with very good approximation structures and chemical patterns observed in natural samples and allow us to follow in time the development of chaotic dynamics and the generation of fractal compositional patterns in magma mixing systems. Results from this study have been utilized to offer a new hypothesis for the occurrence of magmatic enclaves in igneous rocks. They are interpreted as regions of magma trapped within Coherent Regions that survived the complete homogenization with the host magma. Host rocks, on the contrary, are interpreted as Active Mixing Regions where efficient chaotic mixing dynamics generated volumes of magmas with high degrees of hybridization. In conclusion, it is shown that magma mixing processes exhibit all typical features of chaotic systems and that their evolution occurs as a non-linear cascade of events that, starting from the micro-scale, is non-linearly amplified determining the behavior of magmatic systems at the macro-scale. It is emphasized that chaotic dynamics and fractal geometry are suitable techniques to study the complexity inherent to petrological phenomena, and they represent useful methods that, combined with conventional analysis, can aid in understanding better petrological processes.
MR21A-03
Anisotropy in Experimentally Compressed Kaolinite-Illite-Quartz Aggregates: Microstructure, Preferred Orientation and Acoustic Velocities
Shales and mudstones composed of clay minerals and quartz are important sedimentary rocks that frequently display anisotropy of physical properties. This study investigates anisotropy in experimentally compressed kaolinite-illite-quartz aggregates by determining preferred orientation (texture) of component phases and comparing results with acoustic anisotropy. Sample were prepared compressing clay (81% kaolinite, 14% illite and 4% K-feldspar)-silt (~99% quartz) mixtures (0 to 100% clay) at 5 and 50 MPa vertical effective stress to explore the role of clay content and compaction stress on the elastic properties. Optical and scanning electron microscopy have been used to characterize microstructures. Texture patterns are quantified based on synchrotron X-ray diffraction patterns analyzed with the Rietveld method. Preferred orientation of quartz is more or less random. Clay minerals are strongly oriented. Pole figures display axisymmetric (001) maxima parallel to the compression direction, ranging in strength from 1.6 to 8 multiples of a random distribution. Texture strength strongly increases with compaction pressure and clay content. Both microstructure and preferred orientation are essential contributions to aggregate elastic properties that have been calculated by averaging single crystal properties over the orientation distributions. Calculated P-wave velocity anisotropies range from 0% (100% quartz) to 44% (100% clay, 50 MPa). Anisotropy roughly doubles by increasing the vertical effective stress from 5 to 50 MPa. In experiments only P- and S-wave velocities parallel to the compression direction were measured and values (2-3 km/s) are much lower than those predicted by single crystal averaging (5-7 km/s) which we attribute mainly to the influence of porosity that was not considered in the model. With these experimental compaction data we are currently refining a model to determine macroscopic properties of mudstones and shales based on detailed information of the microscopic structure.
MR21A-04 INVITED
Mapping of Rock-Fabric Inhomogeneity (Map-Counting) and Mapping of Rock-Fabric Anisotropy (MORFA) – the Piquiri Syenite Massif, Southern Brazil
During the last decade, studies on magmatic fabrics on different scale have been made for analyzing kinematics of melt emplacement and deformation as well as cooling histories of magmatic bodies and their host rocks (Brown 2001). The problem arises for comparing data from structural analysis in thin-sections and fabrics in outcrop scale. Magmatic fabrics in the outcrop scale are often very diffusely developed or show very complex mineral distribution patterns which are mostly not quantifiable with classical field methods. On the other hand the fabrics are too large for thin section investigation. Therefore, methods have to be developed for analyzing microscale rock fabrics like crystal shape preferred orientations on larger image templates, like from outcrop photographs. For analyzing such complex fabrics on different scale, methods of fractal geometry are powerful (Mandelbrot, 1982). Especially methods like map-counting (Kruhl et al., 2004), based on the classical box-counting method, or the modified Cantor-dust method (Volland & Kruhl, 2004) may be used for analyzing meter sized magmatic mineral distribution patterns in granitic rocks and the anisotropic behavior of micro- to macro scale fracture patterns in breccias. Nevertheless, these methods are performed manually and, therefore, not applicable to larger datasets. This study shows the next step towards automated recognition and subsequent quantification of magmatic patterns from micro- to macro-scale. Microstructure shape- and crystallographic preferred orientation measurements on K-feldspar crystals from the Piquiri Syenite Body, Southern Brazil are done manually based on thin-section series parallel to the syenite magmatic foliation. In addition U-stage measurements of K-feldspar indicatrix axis and (010) have been done. Additionally, a slightly changed modified Cantor-dust method was applied on centimeter- to several meter-sized K-feldspar phase distribution patterns, gained by automated image processing of samples and field photographs of the same syenite. The results show that all three methods result in the same shape- and/or crystallographic preferred orientations for K-feldspar, indicating a magmatic lineation, which is not determinable by field observation or in the thin- sections. In addition, the modified and automated Cantor-dust method applied on K-feldspar phase images of a syenite proves the advantage of such type of modified fractal-geometry methods for quantification of magmatic fabrics on various scales. Such automated quantification is fast and precise, and it is suitable for accurate analysis of magmatic fabrics on different scales and for large datasets. References: Kruhl,J.H., Andries,F., Peternell,M. & Volland,S. (2004): Fractal geometry analyses of rock fabric anisotropies and inhomogeneities. In: D.Kolymbas (ed.), Fractals in Geotechnical Engineering. Advances in Geotechnical Engineering and Tunnelling 9. Logos, Berlin, 115-135. Mandelbrot, B.B., (1982): The Fractal Geometry of Nature. Freeman, San Francisco. Volland, S. & Kruhl, J.H. (2004): Anisotropy quantification: the application of fractal geometry methods on tectonic fracture patterns of a Hercynian fault zone in NW-Sardinia.- J. Struct. Geol. 26, 1489-1500. Brown,M. (2001): Crustal melting and granite magmatism; key issues.- Physics and Chemistry of the Earth. Part A: Solid Earth and Geodesy 26/4-5, 201-212.
MR21A-05 INVITED
Quantifying Fabric Anisotropy in Breccias: Insights Into Brecciation in a Mineralizing Environment
Breccias are commonly regarded as having random fabrics, but clast alignment can cause significant fabric anisotropy. Orientation and shape are two complementary aspects of clast anisotropy. Standard circular statistics can be used to characterize orientation anisotropy, such as the direction and length of the mean resultant vector (with standard error and confidence intervals), and the concentration parameter, kappa. The Rayleigh test can be applied to establish statistical significance. Shape anisotropy can be characterized by the aspect ratio. However, none of these quantities fully describe anisotropy. The axial ratio of the finite shape matrix, a concept borrowed from strain analysis, accounts for both anisotropy components. A review of brecciation mechanisms suggests that anisotropy may be imparted by: 1) preferred fracturing directions 2) fabrics in rocks prior to brecciation 3) laminar flow during transport 4) preferred orientation during deposition. Anisotropy may be reduced by turbulent flow during transport. The orientation anisotropy and the final shape matrix are the most sensitive discriminants among breccias from the Proterozoic Mount Isa inlier, where breccias are prominent hosts in several ore deposits. These parameters reveal fabrics that can not be discerned without measurement. Breccias that have considerable clast transport distances have low anisotropies and no preferred orientations, consistent with random fabrics that were formed by fluidization. Such a fluidized breccia hosts the Cu-Au deposit at Ernest Henry mine, and regional examples contain infill sulphides. In situ breccias, on the other hand, have orientation and total anisotropies that are inherited from the fragmentation process, and regional examples are not mineralized. Clast roughness in the Mount Isa breccias varies very little, but particle size distribution, clast/(matrix+infill) ratios, and circularity, are additional useful parameters to characterize breccias and understand their genesis. http://www.jcu.edu.au/ees/staff/academic/JCUDEV_008366.html
MR21A-06
Multiscale Analysis of Patterns Based on Random Pattern Subsets
Natural geological patterns such as the distribution of minerals or fractures within a rock can provide important information e.g. the genesis of the rock or its deformation. In order to develop techniques that allow for the analysis of such patterns, artificial patterns, such as mathematical fractals, serve as input data for testing purposes. While the analyses of artificial patterns can often rely on complete patterns or datasets, most geoscientific applications are limited to one or multiple available subsets of a pattern. The use of natural patterns is further complicated as many ways of obtaining them involve a thresholding process. The parameters of this thresholding process are likely to be reflected in the data point density. Depending on the internal structure of the pattern, both of these limitations can have an influence on the analyses' results. To evaluate the sensitivity of different natural and artificial pattern, we suggest a multiscale approach which uses different sizes of random subsets. The required quantitative measurements are obtained by applying different fractal geometry-based analytical methods. Preliminary results indicate an interdependence between the obtained results and the size of the subsets. Moreover, the parameters of this relationship can be used to characterize and differentiate the patterns.
MR21A-07
Orientation and misorientation analysis on public domain software
One of the great advances in microstructure analysis was the introduction of electron back scatter diffraction (EBSD). Based on the scanning electron microscope it is essentially an imaging tool, capable of analysing the complete crystallographic orientation (three Euler angles) at each point (pixel) of the sample surface. An alternative is optical orientation imaging which can be achieved with computer-integrated polarization microscopy (CIP). This method is capable of analysing the orientation of the optical axis (azimuth and inclination) of uniaxial minerals at each pixel of the thin section. Both methods have their merits: EBSD can derive the complete texture of all minerals, CIP is fast, has a high spatial resolution and is public domain. We have now merged CIP with Image SXM (a public domain software developed from NIH Image, www.liv.ac.uk/~sdb/ImageSXM/). A special version of this program calculates azimuth and inclination of c-axes from a set of optical micrographs (like the CIP method) and stores them in two image planes. From these, different types of orientation and misorientation images are calculated and displayed. Different types of masks can be used to select areas of analysis. Images of orientation gradients, orientation profiles and histograms can be displayed, c-axis polefigures can be calculated, for the entire image or for selected areas only. The standard image analysis tools of Image SXM can be applied in order to derive and analyze the microstructure by grain boundary detection, grain size and grain shape determination, ACF analysis, etc.. Three additional image planes can be used for the Euler angles from EBSD analysis. These can be visualized and analyzed by first converting to CIP type orientation images and then applying the same analysis methods as described above. Alternatively, direct analysis and visualization of the three Euler planes is possible too. In this form the program is a valuable extension of the EBSD imaging and analysis software provided by the producers of EBSD equipment, allowing users to study their results off-line. In this presentation we demonstrate the use of such a combined texture analysis. We will present diffrent types of misorientations measurements and their relevance for the interpretation of deformation mechanisms.
MR21A-08
Mesh Generation and Microstructure Extraction based on Rock Images
With the development of SEM and/or MRI based techniques, it is getting much easier to get the high quality images of the rocks including the mineralogical and textural information etc.. Once the pixel information for one layer is obtained, a point array description for this rock layer is defined, which includes detailed pixel position, material property information at each pixel position. With information assembled with the images at different layers, the digital image the whole rock volume can be obtained and saved in the corresponding format, such as JPEG. To analyze such related data and apply them into the further numerical modeling, a mesh generator is developed. It has the following functions: (1) Reading and converting the image data (e.g. the JPEG file) to the point data with the material property/microstructure information; (2). Extracting the point with the specified material property; (3) Defining the interfacial position of the different materials/microstructure boundaries; (4) Mesh generation and optimization based on the related available point information (such as keeping the specified interfacial point position) including mesh coarsening/refining; (5) Define the material property at each node and extract the interface boundaries once the mesh generated; (6) Quantify the related information from the rock images and output the mesh for the further numerical (e.g. FEM, FDM, FVM) analysis.