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PSAR . Experiments with a Medium Size 3-Component Array Marthijn de Kool Geoscience Australia. For the last 2 years, Geoscience Australia has been operating a new array in North-West Australia: PSAR. Primary purpose (funding): Tsunami Warning, influenced site location. 13 3C elements
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PSAR Experiments with a Medium Size 3-Component Array Marthijn de Kool Geoscience Australia
For the last 2 years, Geoscience Australia has been operating a new array in North-West Australia: PSAR Primary purpose (funding): Tsunami Warning, influenced site location PSAR
13 3C elements • Aperture ~ 20 km • 3-armed log spiral design • Good signal coherence and slowness accuracy • Main problem: noise PSAR
PSAR is unique: no other medium-size full 3C array in operation (AFAIK). • This allows further investigations. • How useful is it to have 3 components? • What are the best algorithms when using this type of data for monitoring? • This talk concentrates on monitoring applications, not detailed off-line analysis • Most obvious candidate to benefit from horizontals: S detection PSAR
Running a real-time correlation detector over 3c array data • Most obvious algorithm: • When exploring slowness plane, rotate traces for each direction implied by the vector slowness of the point under consideration • Run correlation detector on vertical, transverse and radial components separately • Cons: computationally expensive, false P detections on transverse • Alternative used here: “vector semblance” • “length of vector sum divided by sum of vector lengths” • In practice, use PSAR
FSTAT detector on V and T Vector semblance detector PSAR
Array beam properties and 3-component signal attributes PSAR
Coherence properties of seismic signals observed at PSAR Diagram explained: Run detector For each time slice, rotate traces to V,R,T of detected slowness of maximum coherence Compute correlation coefficient between each pair of array elements after applying time corrections for slowness Take bin average in element separation bins All results for 1-3Hz unless noted Time M=5.7, D=12 deg PSAR
Another example, 20km from previous, M=5.4, different mechanism • Sn more coherent on V (better S/N rel P coda?) • Still very poor on T • Difference in P coherence properties surprising • De-coherence not due to structure under array PSAR
Smaller EQ, m=4.2,D=14 • Weak P coherence • No direct P, scattered coda only? • Good Sn signal/noise • Still poor S coherence • T coherence no better than V Insert slideshow title here <insert/header&footer/footer>
Smaller and closer • (M=3.7, D=6 deg) • Relatively poor P coherence • Sn good coherence on V • Sn low coherence on T PSAR
Subduction earthquake • (depth=40km, D=12 deg) • Pn very coherent • Sn coherence poor (even with good S/N) • Again S coherence better on V than on T PSAR
Frequency dependence • Would expect coherence to be frequency dependent • In cases with good S/N, typically getting similar coherence in S and P requires a frequency ratio of about 3-4 • Same subduction EQ as previous slide PSAR
S correlation comparable or worse on transverse than on vertical at all frequencies PSAR
In many cases S never reaches good coherence (M=5.7, D=13) PSAR
For comparison: Similar plot for NK2013 on KSRS PSAR
Preliminary conclusions: • No problems processing 3C arrays and deriving attributes. “Vector semblance” detector seems to work well • Main problem: S phase signal above 1 Hz only coherent up to a few kilometres at best • There would seem to be little point in using 3C arrays larger than this size • No examples found of significantly better S phase coherence on transverse versus vertical • Caveat: this is only one example site PSAR
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