Attenuation of High-Frequency Seismic Waves

2009 ◽  
pp. 109-148
Author(s):  
Haruo Sato ◽  
Michael C. Fehler
Keyword(s):  
High Frequency ◽  
Seismic Waves ◽  
High Frequency Seismic Waves

High frequency seismic waves and slab structures beneath Italy

2014 ◽  
Vol 391 ◽  
pp. 212-223 ◽  
Author(s):  
Daoyuan Sun ◽  
Meghan S. Miller ◽  
Nicola Piana Agostinetti ◽  
Paul D. Asimow ◽  
Dunzhu Li
Keyword(s):  
High Frequency ◽  
Seismic Waves ◽  
High Frequency Seismic Waves

High‐frequency reflections in granite? Delineation of the weathering front in granodiorite at Piñon Flat, California

Geophysics ◽  
1999 ◽  
Vol 64 (6) ◽  
pp. 1828-1835 ◽  
Author(s):  
Stanley J. Radzevicius ◽  
Gary L. Pavlis
Keyword(s):  
High Frequency ◽  
Seismic Waves ◽  
Lower Layer ◽  
Specular Reflection ◽  
Earth Model ◽  
Remarkable Feature ◽  
Reflection Data ◽  
Weathered Layer ◽  
High Frequency Seismic Waves ◽  
Seismic Lines

We analyze data from two orthogonal seismic lines 336 m in length collected at Piñon Flat, California, over weathered granodiorite bedrock. Each line was made up of 10 reversed segments 84 m in length. We analyzed the first arrivals from these data and found dramatic variations in velocity along the profiles. An upper layer (approximately 2-m thick) known from trenching to be composed of soil and sandy grus had measured velocities ranging from 400 to 700 m/s. Velocities inferred from refraction analysis of first arrivals of the reversed lines revealed a heterogeneous lower layer below the soil with measured velocities of 1600–2700 m/s by a depth of 15 m. We interpret these data to be measuring velocities of a deeply weathered unit characterized by granodiorite corestones embedded in a matrix of saprolite. The most remarkable feature of these data emerged from attempting to process the same data as reflection data. Simple bandpass filtering in the 250–400 Hz band revealed a bright, impulsive arrival with three characteristic properties: (1) irregular velocity moveout that is inconsistent with that expected from a layered earth model, (2) the arrival is at a nearly constant time‐depth on all data, and (3) the arrival tends to be followed by a ringing coda whose frequency varies from trace to trace. This arrival ties exactly with a velocity discontinuity measured in a borehole located on one of the profiles that we interpret as the base of the weathered layer. We suggest this arrival is a specular reflection from a weathering front that occurs along horizontal sheeting joints at a fixed depth below the surface. This surface acts as an effective mirror for high‐frequency seismic waves which are then channeled upward through an intact, high-Q path of unaltered blocks of granodiorite to define the observed signals at the surface.

Landslide Characteristics Revealed by High-Frequency Seismic Waves from the 2017 Landslide in Central Japan

2020 ◽  
Vol 91 (5) ◽  
pp. 2719-2729
Author(s):  
Issei Doi ◽  
Takuto Maeda
Keyword(s):  
High Frequency ◽  
Seismic Waves ◽  
Wave Packets ◽  
Impulsive Phase ◽  
Frequency Component ◽  
Source Location ◽  
High Frequency Component ◽  
Central Japan ◽  
Location Determination ◽  
High Frequency Seismic Waves

Abstract The recent development of advanced seismograph networks offers us a chance to remotely detect landslide occurrences with high-frequency (>∼1  Hz) components. This study examined a landslide in central Japan that produced clearly detectable seismic signals at multiple seismic stations in a permanent network. Wave packets propagated with a group velocity of 3  km/s from the landslide area. Using a source location determination method with amplitude information from the high-frequency component, the source location of the wave packets was shown to be in the vicinity of the landslide with an error of 5 km. Moreover, seismograms specific to this landslide also contained a distinct impulsive phase with a source located in the vicinity of the landslide. The study demonstrated that seismic waves with a high-frequency component from landslides can be used to estimate their mechanisms as well as their locations when they are recognized by a routine seismic network.

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