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  • Available at: http://publications.ictp.it IC/2007/126

    United Nations Educational, Scientific and Cultural Organization and

    International Atomic Energy Agency




    I.M. Korrat Geology Department, Faculty of Science, Mansoura University, Egypt,

    A.A. Gharib, K.A. Abou Elenean, H.M. Hussein National Research Institute of Astronomy and Geophysics, NRIAG, Helwan, Egypt


    M.N. ElGabry* National Research Institute of Astronomy and Geophysics, NRIAG, Helwan, Egypt

    and The Abdus Salam International Centre for Theoretical Physics, Trieste, Italy.


    December 2007

    ___________________ *Junior Associate of ICTP.

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    A seismic discriminants based on the spectral seismogram and spectral magnitude

    techniques has been tested to discriminate between three events; a nuclear explosion which took

    place in Lop Nor, China with mb 6.1 and two earthquakes from the closest area with mb 5.5 and 5.3,

    respectively. The spectral seismogram of the three events shows that the frequency content of the

    nuclear explosion differs from that of the earthquakes where the P-wave is rich with high frequency

    content in the nuclear explosion than the corresponding earthquakes. It is also observed that the

    energy decays very rapidly for the nuclear explosion than that for the earthquakes. Furthermore, the

    spectral magnitudes reveal significant differences in the spectra between the nuclear explosion and

    the two earthquakes. These observed differences appear to be quite enough to provide a reliable

    discriminant. The estimated stress drop from the magnitude spectra indicates a higher stress drop of

    the nuclear explosion relative to the earthquakes of the same tectonic region.

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    Discrimination between earthquakes and underground nuclear explosions is a difficult task which

    has gained considerable attention in the seismological community. Seismic methods provide the

    principal means for a verification of a nuclear test ban (Basham and Dahlman, 1988). The

    discrepancies in signals from earthquakes and explosions arise from differences in source

    mechanisms, source dimensions and duration. An underground nuclear explosion has a small point

    source compared to an earthquake. It sends out compressional waves of equal strength in all

    directions. An earthquake occurs along a rupture as a result of sliding rupture sides. Due to this

    frictional sliding an earthquake emits more shear waves and surface waves than a nuclear explosion.

    As the source dimensions of earthquakes tend to be larger than those of nuclear explosions,

    wavelengths of the radiated seismic waves emitted are longer. Thus, earthquakes usually produce

    signals with lower frequencies than explosions.

    Classical Discriminates such as mb:MS, the ratio of body wave magnitude and surface wave

    magnitude; M0:ML, the ratio of seismic moment and local magnitude and various spectral ratios

    showed promising results in many instances. Denny et al. (1987) and Taylor et al. (1989) show that

    mb:MS works well down to mb = 4. Generally, the explosion generates lower-amplitude surface

    waves than an earthquake of equal size. However, in some cases these methods failed to

    discriminate between natural earthquakes and nuclear explosions. For example, intermediate and

    deep earthquakes can cause problems with mb:MS because they can result in relatively high mb:MS

    differentials and sampling of Rayleigh waves near radiation nodes can bias the MS estimates

    (Dreger and Woods 2002). Additionally, all nuclear explosions produce some nonisotropic radiation

    (Wallace, 1991) and the mode of the nonisotropic radiation (strike-slip vs. dip-slip) can have quite

    different effects on Rayleigh wave amplitudes and, hence, MS (Patton, 1991). Surface waves also

    have source area dependent behavior (Stevens, 1986). As shown by Patton (1991), the degree of

    such bias is a strong function of the F-factor, F= (α2M0/2β2MI), where α and β are the compressional

    and shear wave velocities at the source, and M0 and MI are the nonisotropic and isotropic scalar

    seismic moments, respectively. The ratio of mb:M0 and ML:M0 discriminants are based on the same

    principle as the mb:MS method with the exception that M0 is determined by waveform modeling to

    account for source depth and radiation pattern influences (Woods et al., 1993).

    The seismic waves observed in earthquake records manifest clearly non-stationary

    characteristics, as well as wide frequency content. Those characteristics are twofold (Huerta-López,

    et al., 2003). The first characteristic involves variations of the intensity of ground motion with the

    time. The second characteristic involves variation with the time of the frequency content, with a

    tendency to shift to lower frequencies as the time increases. This phenomenon is well known as the

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    frequency dependent dispersive effect which is very complex and involves the arrival of different

    seismic phases (P, S and surface waves), the intensity of ground motion, the magnitude of

    earthquake, source and path effects, and the local soil conditions. Spectral characteristics of

    different seismic waves have been used before for the discrimination analysis and source parameter

    evaluations of different tectonic origins earthquakes (Hussein et al., 1998, Lyskova et al., 1998 and

    Abou Elenean et al., 2000). Moreover, Chernobay and Gabsatarove (1999) applied the spectrogram

    method for routine discrimination between regional earthquakes and chemical explosions of

    comparable magnitudes in northern Caucasus. Recently, the spectrogram was implemented in the

    routine analysis used by Comprehensive Nuclear-Test- Ban Treaty Organization (CTBTO).

    The need for a suitable tool for measuring strength of any seismic event, as well as for

    discrimination between natural and artificial ones, is very important issue. Our study has been

    forward to apply both the spectral seismogram (spectrogram) and spectral magnitudes tools for the

    verification of a nuclear explosion at the Lop Nor test site, China and the two natural earthquakes

    which occurred closer to the test site. These tools can help in resolving possible biases in the

    identification of an explosion.


    In this study, we used three events; a known nuclear explosion and two natural earthquakes which

    are both located in the China Lop Nor area. The selection is based upon event size (magnitude),

    focal depth and location proximity. We search for the available natural earthquakes with relatively

    comparable magnitudes to that of the explosion and very close to the test site. This ensures that

    dissimilarities observed between both events would originate from the type of the source rather than

    from different propagation paths and origin areas. Table 1 shows the parameters of the three tested

    events. The broadband records of IRIS data base were utilized. We try to use the same stations with

    the same time window during our analysis. Six seismic stations equipped with 3 components

    Streckeisen STS-1 broadband seismometers (Fig. 1) which have good signal to noise ratio were

    used. The available selected stations have epicentral distances ranging from 20°- 60°.

    Spectral seismogram

    The Fourier transform decomposes a signal into its constituent frequency components. Looking at

    the Fourier spectrum we can identify these frequencies; however, we cannot identify their temporal

    localization. Time-frequency distribution map converts a one-dimensional signal into a colored two-

    dimensional function of time and frequency, and describes how the spectral content of the signal

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    changes with time. The basic idea of the method of analyzing the time-varying nature of the

    spectral content is to compute the Fourier transform of the signal using a short sliding time window.

    The absolute values of this function yield the spectrogram (Fasthoff and Lucan, 1996). The basis for

    this approach has been developed by Gabor (1946). He defined the complex (analytic signal) from a

    real one s(t):

    z(t) = s(t)+iH[s(t)] (1)

    where, H is the Hilbert transform which is defined as:

    H[s(t)] = p.v. τ πτ τ dts )( −∫


    ∞− (2)

    (p.v. stands for principal value of the integral). Moreover, Gabor (1946) demonstrated that the

    analytic signal can be calculated as well in the frequency domain by Fourier transforming the signal

    s(t), then doubling the amplitude of the positive frequencies and suppressing the amplitude of the

    negative frequencies. For obtaining th

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