[1] The rupture of the Sumatra earthquake (M w = 9.0) is complex and quite difficult to estimate using classical source inversion methods due to the exceptional rupture duration. To fix the problem of geographical extent and rupture duration, we use array processing of hydroacoustic and regional seismic data. The CMAR-seismic array and the Diego Garcia hydroacoustic station (H08S) installed by the International Monitoring System are respectively 15.2°and 25.7°far from the hypocenter. The estimation of azimuth and velocity variations of homogeneous wave fronts across the arrays gives us the opportunity to understand how the rupture propagates. The smooth and regular variations of azimuth fit a rupture extension of 1235 km and a duration of 515 s. This study proves that the combination of array analysis using the different technologies installed for the CTBT is an interesting way of research for a rapid estimation of tsunamigenic earthquakes. Citation: Guilbert, J., J. Vergoz, E. Schisselé, A. Roueff, and Y. Cansi (2005), Use of hydroacoustic and seismic arrays to observe rupture propagation and source extent of the M w = 9.0 Sumatra earthquake, Geophys. Res. Lett., 32, L15310,
The results of a 13-day seismic monitoring experiment are presented. It consists in 2 permanent piezoelectric sources, one cemented in depth and the other attached to a surface concrete pad and 28 sensors, 14 at the surface and 14 cemented below the weathering zone. To enhance the signal-to-noise ratio, continuous averaging of the individual SP records is performed providing an average daily SP. 4D attributes are measured on these daily averages. The best repeatability is obtained when both sources and sensors are buried with time and amplitude variations of 6 μs and 0.5% respectively. This extremely high precision level is far above what can be expected from the most accurate surface acquisition methods currently available.
S U M M A R YAn accurate method is developed to characterize the seismic coda phases recorded by smallaperture arrays. The coda is modelled as a superposition of several interfering wavelets identified by their arrival time, frequency content, backazimuth and apparent velocity of propagation. The wavelets are caused by the diffraction and refraction of the direct wavefield by heterogeneities of the propagation medium. The deterministic modelling is different from the statistical one generally used to retrieve mean parameters of the medium. As the complexity of the medium increases, separation of interfering wavelets needs an accurate timefrequency-wavenumber decomposition method that consists of detection and characterization of the different coherent wavelets propagating through the array. Detection is realized by mean time-frequency decomposition, based on the ridges algorithm. The MUltiple SIgnal Classification (MUSIC) algorithm, allowing a higher separation of simultaneous wavelets in the wavenumber domain, is then used to characterize the propagation parameters of the detected components. An optimal use of the MUSIC algorithm assumes the knowledge of the number of sources that simultaneously propagate through the array. The new iterative technique presented here allows the automatic determination of this number of sources. This methodology is applied to synthetic signals simulated in a heterogeneous medium. Results obtained show that: (i) the diffracted wavefield may be more energetic than the primary direct one and (ii) the relative energy diffracted by each heterogeneity is strongly dependent on the location of the array within the medium. The well-controlled results obtained for the synthetic examples allow interpretations of the observations made during the Annot experiment in the southern French Alps in 1998, where four small-aperture arrays were deployed, with small distances between each array (∼10 km). The time-azimuth-velocity evolutions determined for the earthquakes recorded during this experiment are used to characterize the heterogeneous structures of the medium.
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