Shear-wave splitting in a critical crust: The next step

Arguably, shear-wave splitting displaying azimuthal anisotropy has not lived up to its initial promise of opening a new window for understanding cracks and stress in the crust. This paper reviews two recent related developments which appear to renew these initial hopes and provide new opportunities for monitoring, modelling, and even predicting, the (pre-fracturing) deformation of fluid-saturated microcracked rock. A recently developed model of anisotropic pore-elasticity (APE) for the stress-induced evolution of fluid-saturated microcracked rock matches a wide range of otherwise inexplicable or dissociated phenomena and appears to be a good first-order approximation to the evolution of fluid-saturated microcracked rock. Since the parameters that control small-scale (pre-fracturing) deformation also control shear-wave splitting, it appears that the evolution of fluid-saturated microcracked rock can be directly monitored by shear-wave splitting, and the response to future changes predicted by APE. The success of APE-modelling and observations of shear-wave splitting imply that almost all rock is close to a state of fracture criticality associated with the percolation threshold, when shear-strength is lost and through-going fractures can propagate. This confirms other evidence for the self-organized criticality of in situ rock. The significance of this identification is that the small-scale physics that controls the whole phenomena can now be identified as the stress-induced manipulation of fluids around intergranular microcracks. This has the possibly unique advantage amongst critical systems that details of the pre-fracturing deformation and the approach to the criticality threshold (in this case the proximity to fracturing) can be monitored at each locality by appropriate observations of shear-wave splitting. This paper reviews the these developments and discusses their implications and applications, particularly the implications of self-organized criticality. The next step is to employ these techniques to model, monitor, and predict the effects of changing conditions on the deformation of the rockmass.