No abstract

The usefulness of microtremors as a geophysical exploration tool has been analyzed. This application is possible due to the relationship between the main resonance frequency of a given soil, obtained from the H/V spectral ratios of microtremors, its thickness and average shear velocity. We first measured the ambient noise at 33 sites and determined their main resonance frequency. Detailed geotechnical information was available for 23 of the sites, thereby allowing us to establish a quantitative relationship between the resonance frequency and the thickness of the soil, and indirectly between either of them and the shear velocity of the soil. The practical application of this relationship has revealed its usefulness in determining the surface structure of a valley with excellent accuracy, with an error of only 15% in the depths calculated. These errors are due to the simplification of the problem that this method implies: it requires that the shear velocity vary constantly with depth throughout the study region, which is evidently not always so, and that the input data themselves intrinsically have a certain degree of uncertainty. This method is therefore not valid when there is no mechanical contrast between the study soil and the underlying layer or when the shear velocity varies irregularly with depth in the study area.

The wavelet packet transform gives information in both the time and frequency domains, and it is very useful for describing nonstationary signals like seismograms. Moreover, this structure is dependent on the signal under study; hence we can choose the time-frequency decomposition more appropriate for every signal. In this article, we propose a new method for filtering based on the wavelet packet transform. This approach uses different parameters for filtering, depending on the band of frequencies that we are analyzing. This filtering is employed in order to achieve a high signal-to-noise ratio (SNR) and low distortion. We first apply the method to synthetic signals that we have contaminated with noise. In this way, the shape of the whole output signal and the onset time of the first pulse can be compared to the ideal signal. Finally, we apply it to short-period seismograms recorded at the local seismic network of the University of Alicante in southeastern Spain. The method proposed is compared with conventional passband filters and other methods based on wavelets. The comparison demonstrates that our method achieves a higher SNR without introducing noticeable distortion.

No abstract

No abstract