Regional Seismic-Event Characterization Using a Bayesian Formulation of Simple Kriging

Abstract

An approach is presented to calibrate and use regional P-S amplitude ratios to improve seismic-event characterization capabilities with regard to monitoring the Comprehensive Nuclear-Test-Ban Treaty. Data for presumed earthquakes are used to estimate distance corrections for Pn-Sn and Pn-Lg ratios in the 6-8-Hz passband for tectonic and stable-region types. The regional phase-amplitude ratios are further corrected for path variations using simple kriging. Simple kriging is derived using a Bayesian approach. A correction surface is determined for each type of amplitude ratio at each station as an optimal linear combination of existing amplituderatio data at the station, giving greater weight to calibration data nearer to the correction location. A corresponding uncertainty surface is also estimated in terms of the residual variance of the data and a calibration variance. For well-calibrated locations, the correction converges to the mean of nearby data, and the uncertainty converges to the residual variance. For locations far from calibration data, the correction surface converges to the worldwide average, with larger uncertainty. With these correction and uncertainty surfaces, corrected values of Pn/Smax(6-8 Hz) are obtained and used to define a hypothesis test that fixes the significance level with respect to misclassifying explosions. The criterion is applied to 140 explosions at known nuclear-test sites and to 4173 Reviewed Event Bulletin (REB) events above m b 3.5 (presumed to be mostly earthquakes) with regional recordings between 3Њ and 17Њ, Pn signal-to-noise ratio (SNR) Ͼ2.0, and Sn or Lg SNR Ͼ1.3. At a 0.005 significance level, none of the 140 explosions at any of the known nuclear-test sites are screened out, whereas about 78% of the REB events are screened out. Correcting regional P-S ratios for spatial variations improves the screening performance by about 25% over just correcting for distance. The screening results are fairly insensitive to estimates of parameters (correlation length, calibration variance, and residual variance) that are used, along with data, to compute the correction and uncertainty surfaces at each station.

Regional Seismic Signals from Chemical Explosions, Nuclear Explosions and Earthquakes: Results from the Arizona Source Phenomenology Experiment

“…Walter et al, 1995, Taylor, 1996, Hartse et al 1997, Battone et al 2002. When similar-sized earthquakes and explosions are nearly co-located, we can understand the observed seismic contrasts, such as the relative P-to-S wave excitation, in terms of depth, material property, focal mechanism and source time function differences.…”

Regional Multistation Discriminants: Magnitude, Distance, and Amplitude Corrections, and Sources of Error

“…These station-centric discriminants are known to be robust to instrument response calibration, and this calculation also removes the effect of magnitude. In the literature, station discriminants are then corrected for distance with a regression model built from earthquake calibration data (see Hartse et al, 1997;Bottone et al, 2002). Analogous to the development in the section titled The MDAC Discriminant: Model Inadequacy and Station Noise, define the random variable X ijk to be the regression corrected station discriminant for source type i 0; 1 (earthquake, explosion), event j, and station k (observed station discriminants are denoted x ijk ).…”

“…In the context of this article, we calculate the difference of the observed station amplitudes P g and L g . We then distance correct these station discriminants with Δ and log Δ as regressor variables (see Hartse et al, 1997;Bottone et al, 2002). Applying this regression model to all events gives distance corrected station discriminants X ijk -the residuals.…”

“…The ratio of regional P-and S-wave amplitude measurements at high frequencies can discriminate between earthquakes and explosions (e.g., Walter et al, 1995;Taylor, 1996;Bottone et al, 2002). An issue with using these amplitudes in a practical application is how to remove the effects due to path, site, and magnitude to emphasize the source differences.…”

Testing Event Discrimination over Broad Regions using the Historical Borovoye Observatory Explosion Dataset

“…Walter et al, 1995;Taylor, 1996;Hartse et al, 1997;Kim et al, 1997;Rodgers and Walter, 2002;Taylor et al, 2002;Bottone et al, 2002;Walter et al, 2007). The application of this discriminant to broad regions, however, has been hampered by large variations in the amplitudes of phases due to propagation effects in the crust and upper mantle.…”