NUMERICAL MODELING OF MICROSTRUCTURAL PROCESSES AND FABRIC EVOLUTION: AN ESSENTIAL STEP IN EXPLORING CRUSTAL SEISMIC ANISOTROPY

A rock’s fabric is defined by the arrangement, modal abundances, and spatial and crystallographic orientations of its constituent mineral grains. The seismic anisotropy produced by rock fabric is controlled by the fabric's bulk stiffness properties. The continental crust is composed of a large variety of rocks that contain modally significant proportions of two or more different minerals. Understanding seismic anisotropy that arises from fabrics in these rocks requires an understanding of how the grain-scale interactions of these different minerals affect the bulk elastic properties, and how the bulk stiffness tensor will change with changing fabric parameters such as arrangement, modal abundances, and spatial and crystallographic orientations of mineral grains. We have developed numerical methods for investigating the elastic properties of representative crustal volumes containing hundreds of individual grains, each with their own stiffness tensor. Snapshots of different stages in evolving numerical fabrics show how the bulk elastic characteristics change with microstructure evolution, and allow us to examine the relationships among fabric evolution parameters and bulk elastic properties. Questions include, for example, whether there is a modal percentage of mica above which the other minerals in the rock have a negligible effect on the anisotropy signal, and what are the primary fabric characteristics that lead to the P45 effect (Okaya and Christensen, 2002). An important long-term goal is to link microstructural evolution and geodynamic model evolution so that the bulk stiffness properties can be calculated at any point in space and time within an evolving model domain. The amount of seismic anisotropy produced by these fabrics can be quantified by mapping the fabrics into larger scale earth volumes that can then be used for anisotropic wave propagation simulations. These synthetic seismic signals can then be compared with observed crustal seismic anisotropy in selected settings. This approach has many challenges but at its foundation is the ability to simulate the 3D evolution of microstructures and fabrics in polymineralic rocks.