Regional Seismic Event Discrimination

Blandford, R. R.

doi:10.1007/978-94-011-0419-7_37

Cited by 29 publications

(30 citation statements)

References 95 publications

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“…In the early days of forensic seismology finding a robust method of distinguishing between earthquakes and explosions-that is finding what are variously called discriminants, discrimination criteria and identification criteria-using these recordings proved difficult. However, Blandford (1996) concludes that work from 1980 onwards demonstrates that the ratio of S to P amplitudes at high frequencies (> 2 Hz) is a promising discriminant, with the ratio being, as expected, larger for earthquakes than explosions. Several small arrays have been installed to provide data for such studies (see for example Mykkeltveit and Bungum 1984;Kvaerna 2000).…”

Section: Introductionmentioning

confidence: 61%

“…However, such high-frequency amplitudes are strongly dependent on the attenuation and structure on the source-to-station path. Due to this Blandford (1996) argues that discriminants based on the high-frequency amplitudes have to be regionalised: they are not transportable, and so criteria that apply in one region cannot be used in other regions without modification. Further, within each region it is necessary to correct for path and station effects.…”

Section: Introductionmentioning

confidence: 99%

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Forensic seismology revisited

Douglas

2007

Surv Geophys

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The first technical discussions, held in 1958, on methods of verifying compliance with a treaty banning nuclear explosions, concluded that a monitoring system could be set up to detect and identify such explosions anywhere except underground: the difficulty with underground explosions was that there would be some earthquakes that could not be distinguished from an explosion. The development of adequate ways of discriminating between earthquakes and underground explosions proved to be difficult so that only in 1996 was a Comprehensive Nuclear Test Ban Treaty (CTBT) finally negotiated. Some of the important improvements in the detection and identification of underground teststhat is in forensic seismology-have been made by the UK through a research group at the Atomic Weapons Establishment (AWE). The paper describes some of the advances made in identification since 1958, particularly by the AWE Group, and the main features of the International Monitoring System (IMS), being set up to verify the Test Ban.Once the Treaty enters into force, then should a suspicious disturbance be detected the State under suspicion of testing will have to demonstrate that the disturbance was not a test. If this cannot be done satisfactorily the Treaty has provisions for on-site inspections (OSIs): for a suspicious seismic disturbance for example, an international team of inspectors will search the area around the estimated epicentre of the disturbance for evidence that a nuclear test really took place.Early observations made at epicentral distances out to 2,000 km from the Nevada Test Site showed that there is little to distinguish explosion seismograms from those of nearby earthquakes: for both source types the short-period (SP: *1 Hz) seismograms are complex showing multiple arrivals. At long range, say 3,000-10,000 km, loosely called teleseismic distances, the AWE Group noted that SP P waves-the most widely and well-recorded waves from underground explosions-were in contrast simple, comprising one or two cycles of large amplitude followed by a low-amplitude coda. Earthquake signals on the other hand were often complex with numerous arrivals of similar amplitude spread over 35 s or more. It therefore appeared that earthquakes could be recognised on complexity.Later however, complex explosion signals were observed which reduced the apparent effectiveness of complexity as a criterion for identifying earthquakes. Nevertheless, the AWE Group concluded that for many paths to teleseismic distances, Earth is transparent for P signals and this provides a window through which source differences will be most clearly seen. Much of the research by the Group has focused on understanding the influence of source type on P seismograms recorded at teleseismic distances. Consequently the paper concentrates on teleseismic methods of distinguishing between explosions and earthquakes.One of the most robust criteria for discriminating between earthquakes and explosions is the m b : M s criterion which compares the amplitudes of the SP P waves as measured ...

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Section: Introductionmentioning

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Forensic seismology revisited

Douglas

2007

Surv Geophys

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“…The multistation regional discriminant is analogous to the formulation of the m b versus M s discriminant used for decades in seismic event identification (see Blandford, 1982). To see this, we note that the calculation of a corrected amplitude (equation 3) is very similar to the calculation of a station m b or M s .…”

Section: Introductionmentioning

confidence: 92%

“…Prior to the MDAC formulation, discriminants were formed by first calculating a spectral ratio in a common frequency band at each station observing the event (see Blandford, 1982). These station-centric discriminants are known to be robust to instrument response calibration, and this calculation also removes the effect of magnitude.…”

Section: Nts Data Analysis With a Regression Correction Multistation mentioning

confidence: 99%

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

Anderson¹,

Walter²,

Fagan³

et al. 2009

Bulletin of the Seismological Society of America

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Magnitude, distance, and amplitude corrections (MDAC) made to observed regional amplitudes are necessary so that what remains in the corrected amplitude is mostly information about the seismic source type. Corrected amplitudes can be used in ratios to discriminate between earthquakes and explosions. However, source effects remain that cannot easily be determined and applied as amplitude corrections, such as those due to depth, focal mechanism, local material property, and apparent stress variability. We develop a mathematical model to capture these nearsource effects as random (unknown), giving an error partition of three sources: model inadequacy, station noise, and amplitude correlation. This mathematical model is the basis for a general multistation regional discriminant formulation. The standard error of the discriminant includes the variances of model inadequacy and station noise, along with amplitude correlation in its formulation. The developed methods are demonstrated for a collection of Nevada test site (NTS) events observed at regional stations (see Fig. 1). Importantly, the proposed formulation includes all corrected amplitude information through the construction of multistation discriminants. In contrast, previous studies have only computed discriminants from single stations having both P and S amplitudes. The proposed multistation approach has similarities to the wellestablished m b versus M s discriminant and represents a new paradigm for the regional discrimination problem.

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“…The m b versus M S discriminant is mature (see Evernden [1975] and Blandford [1982]) and requires no development for inclusion in the multidiscriminant methods developed in this article. In practice, this discriminant is formed from the difference of station-averaged surface-wave and body-wave magnitudes, m b and M S .…”

Section: The M B Versus M S Discriminantmentioning

confidence: 99%

A Mathematical Statistics Formulation of the Teleseismic Explosion Identification Problem with Multiple Discriminants

Anderson

Fagan

Tinker

et al. 2007

Bulletin of the Seismological Society of America

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Seismic monitoring for underground nuclear explosions answers three questions for all global seismic activity: Where is the seismic event located? What is the event source type (event identification)? If the event is an explosion, what is the yield? The answers to these questions involves processing seismometer waveforms with propagation paths predominately in the mantle. Four discriminants commonly used to identify teleseismic events are depth from travel time, presence of long-period surface energy (m b vs. M S ), depth from reflective phases, and polarity of first motion. The seismic theory for these discriminants is well established in the literature (see, for example, Blandford [1982] and Pomeroy et al. [1982]). However, the physical basis of each has not been formally integrated into probability models to account for statistical error and provide discriminant calculations appropriate, in general, for multidimensional event identification. This article develops a mathematical statistics formulation of these discriminants and offers a novel approach to multidimensional discrimination that is readily extensible to other discriminants. For each discriminant a probability model is formulated under a general null hypothesis of H 0 : Explosion Characteristics. The veracity of the hypothesized model is measured with a p-value calculation (see Freedman et al. [1991] and Stuart et al. [1994]) that can be filtered to be approximately normally distributed and is in the range [0, 1]. A value near zero rejects H 0 and a moderate to large value indicates consistency with H 0 . The hypothesis test formulation ensures that seismic phenomenology is tied to the interpretation of the p-value. These p-values are then embedded into a multidiscriminant algorithm that is developed from regularized discrimination methods proposed by DiPillo (1976), Smidt andMcDonald (1976), andFriedman (1989). Performance of the methods is demonstrated with 102 teleseismic events with magnitudes (m b ) ranging from 5 to 6.5. Example p-value calculations are given for two of these events.

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Regional Seismic Event Discrimination

Cited by 29 publications

References 95 publications

Forensic seismology revisited

Forensic seismology revisited

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

A Mathematical Statistics Formulation of the Teleseismic Explosion Identification Problem with Multiple Discriminants

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