A New Method of Assessing Uncertainty of the Cross-convolution Method of Shear Wave Splitting Measurement

Shear wave splitting is a commonly used and powerful method for constraining such phenomena as lithospheric strain history or asthenospheric flow. However, a number of challenges with the statistics of shear wave splitting have been noted. This creates difficulties in assessing whether two separate measurements are statistically similar or are indicating real differences in anisotropic structure, as well as for created proper station averaged sets of parameters for more complex situations such as multiple or dipping layers of anisotropy. We present a new method for calculating the most likely splitting parameters using the Menke and Levin [2003] method of cross-convolution. The Menke and Levin method is used because it can more readily be applied to a wider range of anisotropic scenarios than the commonly used Silver and Chan [1991] technique. In our approach, we derive a formula for the spectral density of a function of the microseismic noise and the impulse response of the correct anisotropic model that holds for the true anisotropic model parameters. This is compared to the spectral density of the observed signal convolved with the impulse response for an estimated set of anisotropic parameters. The most likely parameters are found when the former and latter spectral densities are the same. By using the Whittle likelihood to compare the two spectral densities, a likelihood grid for all possible anisotropic parameter values is generated. Using bootstrapping the uncertainty and covariance between the various anisotropic parameters can be evaluated. We will show this works with a single layer of anisotropy and a vertically incident ray, and discuss the usefulness for a more complex case. The method shows great promise for calculating multiple layer anisotropy parameters with proper assessment of uncertainty.