Abstract.Investigations of the distribution of regional seismicity and the results of numerical simulations of the seismic process show the increase of inhomogenity in spatiotemporal distribution of the seismicity prior to large earthquakes and formation of inhomogeneous clusters in a wide range of scales. Since that, the multifractal approach is appropriate to investigate the details of such dynamics.Here we analyze the dynamics of the seismicity distribution before a number of strong earthquakes occurred in two seismically active regions of the world: Japan and Southern California. In order to study the evolution of spatial inhomogeneity of the seismicity distribution, we consider variations of two multifractal characteristics: information entropy of multifractal measure generation process and the higher-order generalized fractal dimension of the continuum of the earthquake epicenters. Also we studied the dynamics of the level of spatio-temporal correlations in the seismicity distribution. It is found that two aforementioned multifractal characteristics tend to decrease and the level of spatio-temporal correlations tends to increase before the majority of considered strong earthquakes. Such a tendency can be considered as an earthquake precursory signature.Therefore, the results obtained show the possibility to use multifractal and correlation characteristics of the spatiotemporal distribution of regional seismicity for seismic hazard risk evaluation.

Surface waves can be used to obtain a near-surface shear wave profile. The inverse problem is usually solved for the locally 1-D problem of a set of homogeneous horizontal elastic layers. The output is a set of shear velocity values for each layer in the profile. P-wave velocity profile can be estimated if higher modes and P-guided waves are used in the inversion scheme. Here, we use an exact acoustic solution to invert for the P-velocity profile in an elastic model with a decreasing constant vertical gradient of the squared P-wave slowness, bounded by a free surface on the top and a homogeneous halfspace at the bottom. The exact acoustic solution can be expressed in Airy functions and leads to a dispersion equation. We can invert several modes of the dispersion equation for the single gradient parameter of the squared P-wave slowness from elastic data. As a first test case, we invert for the P-wave velocity profile of synthetic 2-D isotropic elastic data with a small Vs/Vp-ratio, using the first two dispersive P-wave modes. The method does not require any picking and should be able to provide an initial model for full waveform inversion when applied to real data.

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SUMMARYFull waveform inversion suffers from local minima, due to a lack of low frequencies in the data. A reflector below the zone of interest may help in recovering the long-wavelength components of a velocity perturbation, as demonstrated in a paper by Mora. Because smooth models are more popular as initial guesses for FWI, we consider the Born approximation for a perturbation in a reference model with a constant velocity gradient. Analytic expressions are found that describe the spatial wavenumber spectrum of the recorded seismic signal as a function of the spatial spectrum of the inhomogeneity. We study this spectrum in more detail in terms of sensitivities. Since the velocity model is inhomogeneous near the perturbation, we need to specify its depth. We compare these sensitivities and find that low frequencies are extremely useful for the first stages of inversion -a well-known fact. However, also the high-frequency data contain some information about the low spatial wavenumbers in the perturbation, which offers opportunities for inversion in the absence of low frequencies in the data. We observe that the longer wavenumbers are better resolved in the deeper parts of the model if large enough offsets are available.