科研之友
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摘要
We present a method to construct non-stationary and anisotropic second-order random model realizations that can be used for numerical wave propagation simulations in various geometries. Models are generated directly from a given covariance matrix using its eigenvector decomposition (principal component or Karhunen-Loeve method). Because this decomposition is very expensive computationally in 3-D, we use model symmetries to reduce the size of the covariance matrix to its non-stationary components. Stationary components can then be described through their power spectrum, such that models with axisymmetric or spherically symmetric statistics can be generated from a 1-D covariance matrix. We focus in particular on models with spherically symmetric statistics that are important to study wave propagation in the Earth. We use this method to show the influence of hypothetical small-scale structure in the Earth's mantle on the elastic wavefield. To this end, we extend tomographic models beyond their spatial resolution limit with different distributions of small-scale scatterers that generate a coda and attenuate direct waves (scattering attenuation). We observe that scattering attenuation of fundamental mode Rayleigh waves is small (0.5-2 per cent of the total attenuation), if the elastic mantle structure does not become significantly stronger at smaller scales. At the examined heterogeneity strengths, scattering attenuation scales linearly with the model variance. The long-period fundamental mode Rayleigh wave coda is difficult to measure because it is weak and overlaps with other signals. However, it can be shown that its intensity also scales linearly with model power, and that it depends strongly on the spherical geometry of the Earth. It can therefore be used to distinguish between models with different small-scale power. We show qualitatively that the coda generated by the type of random models we consider can explain observed scattered energy at long periods (100 s).
- 出版日期2015-12
