Comments on “S-wave splitting: A key to earthquake prediction?” By A. Ryall and W. U. Savage

1974 ◽  
Vol 64 (6) ◽  
pp. 1997-2001 ◽  
Author(s):  
Indra N. Gupta
Author(s):  
Lijuan Lu ◽  
Bin Zhou ◽  
Xiang Wen ◽  
Shuiping Shi ◽  
Chunheng Yan ◽  
...  

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. B183-B195 ◽  
Author(s):  
K. De Meersman ◽  
J.-M. Kendall ◽  
M. van der Baan

We relocate 303 microseismic events recorded in 1998 by sensors in a single borehole in the North Sea Valhall oil field. A semiautomated array analysis method repicks the P- and S-wave arrival times and P-wave polarizations, which are needed to locate these events. The relocated sources are confined predominantly to a [Formula: see text]-thick zone just above the reservoir, and location uncertainties are half those of previous efforts. Multiplet analysis identifies 40 multiplet groups, which include 208 of the 303 events. The largest group contains 24 events, and five groups contain 10 or more events. Within each multiplet group, we further improve arrival-time picking through crosscorrelation, which enhances the relative accuracy of the relocated events and reveals that more than 99% of the seismic activity lies spatially in three distinct clusters. The spatial distribution of events and wave-form similarities reveal two faultlike structures that match well with north-northwest–south-southeast-trending fault planes interpreted from 3D surface seismic data. Most waveform differences between multiplet groups located on these faults can be attributed to S-wave phase content and polarity or P-to-S amplitude ratio. The range in P-to-S amplitude ratios observed on the faults is explained best in terms of varying source mechanisms. We also find a correlation between multiplet groups and temporal variations in seismic anisotropy, as revealed by S-wave splitting analysis. We explain these findings in the context of a cyclic recharge and dissipation of cap-rock stresses in response to production-driven compaction of the underlying oil reservoir. The cyclic nature of this mechanism drives the short-term variations in seismic anisotropy and the reactivation of microseismic source mechanisms over time.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Wojciech Gajek ◽  
Dominik Gräff ◽  
Sebastian Hellmann ◽  
Alan W. Rempel ◽  
Fabian Walter

AbstractFractures contribute to bulk elastic anisotropy of many materials in the Earth. This includes glaciers and ice sheets, whose fracture state controls the routing of water to the base and thus large-scale ice flow. Here we use anisotropy-induced shear wave splitting to characterize ice structure and probe subsurface water drainage beneath a seismometer network on an Alpine glacier. Shear wave splitting observations reveal diurnal variations in S-wave anisotropy up to 3%. Our modelling shows that when elevated by surface melt, subglacial water pressures induce englacial hydrofractures whose volume amounts to 1-2 percent of the probed ice mass. While subglacial water pressures decrease, these fractures close and no fracture-induced anisotropy variations are observed in the absence of meltwater. Consequently, fracture networks, which are known to dominate englacial water drainage, are highly dynamic and change their volumes by 90-180 % over subdaily time scales.


Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. D35-D40 ◽  
Author(s):  
Masatoshi Miyazawa ◽  
Roel Snieder ◽  
Anupama Venkataraman

We extract downward-propagating P- and S-waves from industrial noise generated by human and/or machine activity at the surface propagating down a borehole at Cold Lake, Alberta, Canada, and measure shear-wave splitting from these data. The continuous seismic data are recorded at eight sensors along a downhole well during steam injection into a 420–470-m-deep oil reservoir. We crosscorrelate the waveforms observed at the top sensor and other sensors to extract estimates of the direct P- and S-wave components of the Green’s function that account for wave propagation between sensors. Fast high-frequency and slow low-frequency signals propagating vertically from the surface to the bottom are found for the vertical and horizontal components of the wave motion, which are identified with P- and S-waves, respectively. The fastest S-wave polarized in the east-northeast–west-southwest direction is about 1.9% faster than the slowest S-wave polarized in the northwest-southeast direction. The direction of polarization of the fast S-wave is rotated clockwise by [Formula: see text] from the maximum principal stress axis as estimated from the regional stress field. This study demonstrates the useful application of seismic interferometry to field data to determine structural parameters, which are P- and S-wave velocities and a shear-wave-splitting coefficient, with high accuracy.


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