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Abstract

Nanoseismic monitoring techniques are able to detect extremely low-energy (ML > -4.0) signals generated by active subsurface instabilities within cavities, cliffs, landslides and sinkholes. The data is acquired by portable sparse seismic arrays, which are deployed, within minutes, in varying geometries as close as possible to a presumed zone of instability. Events detection is carried out by semi-automated pattern recognition-supported schemes4, which scan for broad-band energy spikes within continuous data records sampled at 200 to 500 Hz. The authenticity of source signals is verified either by true-scale simulation in the field -when possible- or through a multi-parameter validation process that uses a custom library of reference patterns. This comprehensive waveform characterization process includes full-spectral signal analysis, 3-D source location, waveform cross correlation and source magnitude evaluation. Study cases will be reviewed to show how failure generated within cavities5,6, cliffs7 and sinkholes1 can be located and characterized. Additional analyses include magnitude-time series, source time migration and event coincidence with external parameters as well as a custom calibration of source energy dissipation in unconsolidated material.

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/content/papers/10.3997/2214-4609-pdb.150.A03
2010-01-20
2020-09-25
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.150.A03
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