Over the past ten years, the cross-correlation of long-time series of ambient
seismic noise (ASN) has been widely adopted to extract the surface-wave
part of the Green’s Functions (GF). This stochastic procedure relies on the
assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed
to the sea-wave climate. Consequently, marked directional properties may be
observed, which call for accurate investigation about location and temporal
evolution of the ASN-sources before attempting any GF retrieval. Within
this general context, this thesis is aimed at a thorough investigation about
feasibility and robustness of the noise-based methods toward the imaging
of complex geological structures at the local (∼10-50km) scale. The study
focused on the analysis of an extended (11 months) seismological data set
collected at the Larderello-Travale geothermal field (Italy), an area for which
the underground geological structures are well-constrained thanks to decades
of geothermal exploration.
Focusing on the secondary microseism band (SM;f>0.1Hz), I first
investigate the spectral features and the kinematic properties of the noise
wavefield using beamforming analysis, highlighting a marked variability with
time and frequency. For the 0.1-0.3Hz frequency band and during Spring-
Summer-time, the SMs waves propagate with high apparent velocities and
from well-defined directions, likely associated with ocean-storms in the south-
ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back-
azimuths is more scattered, thus indicating that this frequency-band is the
most appropriate for the application of stochastic techniques. For this latter
frequency interval, I tested two correlation-based methods, acting in the time
(NCF) and frequency (modified-SPAC) domains, respectively yielding esti-
mates of the group- and phase-velocity dispersions. Velocity data provided
by the two methods are markedly discordant; comparison with independent
geological and geophysical constraints suggests that NCF results are more
robust and reliable.
Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:6973 |
Date | 30 April 2015 |
Creators | Zupo, Maria <1983> |
Contributors | Saccorotti, Gilberto |
Publisher | Alma Mater Studiorum - Università di Bologna |
Source Sets | Università di Bologna |
Language | English |
Detected Language | English |
Type | Doctoral Thesis, PeerReviewed |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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