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

United Nations Educational, Scientific and Cultural Organization and

International Atomic Energy Agency

THE ABDUS SALAM INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS

SPECTRAL CHARACTERISTICS OF NATURAL AND ARTIFICIAL

EARTHQUAKES IN THE LOP NOR TEST SITE, CHINA

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

and

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

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

MIRAMARE – TRIESTE

December 2007

___________________ *Junior Associate of ICTP.

1

Abstract

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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Introduction

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.

Data

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. τπττ 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 the spectral seismogram digital data processing is performed

using the following steps (Farnbach, 1975):

1) Compute the complex FFT spectrum Sk, 0 < k < N

2) Multiply the spectrum by 2 0 / 2 1 0, / 2 0 / 2

for k Nfor k k Nfor N k N

< <⎧⎪ = =⎨⎪ < <⎩

3) Take the inverse FFT to obtain the analytic signal z(t), z(t) to be written in polar coordinates

as:

z(t) = a(t)e iΦ(t) (3)

where

a(t) = z (t) = 2 2( ) [ ( )]t s ts H+ (4)

Φ(t) = arctan [ ( )]( )

H s ts t

⎧ ⎫⎨ ⎬

⎭⎩ (5)

The parameter a(t) is named instantaneous amplitude or envelope and Φ(t) is referred to the

instantaneous phase. The envelope and instantaneous phase are used in seismology for analyzing

the dispersion of surface waves and detection of secondary phases. The display of the variation of

frequency content with the time of the signal can be considered as a good indicator of rupture

process, complexity of the source, discrimination between different tectonic regime earthquakes

and/or natural and artificial events.

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In our attempt to analyze the time-frequency distribution of the selected broadband records,

we follow the procedures of Levshin et al. (1972) in the dispersion analysis by applying the nfilter

algorithm (Saul, 1995). Different time windows of the selected records were analyzed (P-wave

window (60 sec), S-wave window (60) and nearly 400 sec after P-wave onset) to inspect the

variation of the ground motion intensity and their temporal frequency content with travel times.

The spectrograms of the three tested events at the vertical component of the ABKT station

illustrate some essential differences between the natural earthquakes (Fig. 2, A, B) and the nuclear

explosion (Fig. 2, C). First, the P-wave energy decays rapidly for the nuclear explosion whereas, in

the earthquakes, the energy takes more time (i.e. slow rate) to vanish (either for the P-waves or for

the whole trace). Second, the P-wave energy of the explosion is much higher than any other later

phases that are usually not notable due to the great difference in their energy level relative to P-

wave group. This usually occurs due to the isotropic character of the nuclear explosion sources,

which generate mainly compressional P-wave with S-waves completely vanishing or being very

weak. On the other hand, earthquakes show clearly both P- and S-waves groups. Generally, the S-

wave energy is much higher than P-waves energy. A third difference appears in the frequency

content of P and S-wave groups observed for the earthquakes and the explosion. In the case of the

explosion, the P-wave frequency band ranges from 0.3 – 4.0 Hz, while in the earthquakes it ranges

from 0.07 up to 3.0 Hz. The lower frequency content of the earthquakes may be related to the

characteristics of its sources. The S-wave group in the earthquakes is clear and has a frequencies

band range from 0.05-1Hz while it is not clear for the explosion which is limited within 0.2-0.7Hz.

Moreover, the P-waves are rich in higher frequencies than S-waves due to stronger shear

attenuation relative to the bulk attenuation of the earth (Borman, 2002).

Spectral magnitudes

The spectral magnitudes (magnitude spectra) are a quasi-continuous estimate of the velocity density

spectrum of P- (or S-) waves expressed in magnitude units (Kaiser and Duda, 1988). Unlike the

conventional body wave magnitudes, the magnitude spectrum represents the complete P- (or S-)

wave energy radiated from the source. Broadband records of seismic waves enable one to extend

the magnitude definition to bandpass seismograms and to determine a set of magnitudes

corresponding to the respective set of seismograms. These magnitudes are called spectral

magnitudes (Nortmann and Duda, 1982b; Duda and Yanovkaya, 1994). The period corresponding

to the maximum spectral magnitude varies between seismic events depending on the source

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characteristics. The maximum spectral magnitude together with its period is considered as

diagnostic quantities for seismic events.

Duda and Yanovskaya (1994) found that it is better for the determination of spectral

magnitudes to use the spectrum instead of amplitudes from bandpass seismograms to avoid the

effect of the band width. The magnitude spectrum Ms(T) is obtained from the formula:

Ms (T) = SI (T) +σ I (∆, h, T) (6)

where I refers to either the vertical Z or radial R component of the ground velocity density SI (T)

and σ I (∆, h, T) is the P-wave calibrating function. Ms(T) is a distribution of magnitude values in

the period range from Tmin = 2∆t (∆t is the sampling interval of the seismogram) to Tmax= 60 sec

(length of the P-wave time window). ∆ is the epicentral distance and h is the focal depth. The

magnitude spectrum is subsequently averaged in period intervals of a width equal to one octave and

centered at the periods 0.25, 0.5, 1, 2, 4, 8, 16 and 32 sec. In this case the spectrum is smoothed and

yields 8 discrete values.

In this analysis, the PASTA algorithm (Roslov, 1994) was used. It estimates the radiation

intensities of P-waves in the whole applicable period range, on the basis of broadband records of

seismic waves. The program incorporates spectral magnitude calibrating functions developed by

Duda and Yanovskaya (1994). In addition, it produces the P-wave magnitude for a given event in

the form of a P-wave magnitude spectrum. The spectral magnitude calibrating functions are

normalized to a record length of 60 seconds. Prior to the analysis, the data were corrected for the

instrumental response and a 10% cosine tapering function was applied at both ends of the

windowed signal.

To yield stable results for the tested events, the same time window (60 sec) was used in our

analysis. Figure 3 (A & B) show the calculated spectral magnitudes for the three studied events at

two different stations (ABKT and ARU). It is certainly clear that, the earthquake spectrum have a

wide band of periods and a slow rate of energy decay, whereas the nuclear explosion spectrum

shows a narrow band of short periods and a rapid rate of energy decay. The average spectral

magnitudes, calculated from four broadband stations of the three events, are shown in Figure 4. The

maximum spectral magnitude for May 2, 1995 and November 23, 2006 earthquakes are 5.8 and 5.4

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at a period of 1.8 and 1.35 sec, respectively. Meanwhile, the maximum spectral magnitude of the

nuclear explosion is 6.7 at a period of 0.8 seconds. Hence, the observed corner period of the

nuclear explosion is smaller than that of the earthquakes because of their source dimensions. The

smoothed average spectral magnitude at eight octaves, specified above for the nuclear explosion

and the two earthquakes at ABKT and ARU stations, are shown in Figure 5. It reflects a significant

deviation of their radiated energy related to their failure condition. Our spectral magnitude plots for

the studied events (Figs. 3, 4 and 5) show good agreement with source spectra plots for natural and

nuclear explosion presented by New Manual of Seismological Observatory Practice (NMSOP).

The differences in the corner periods and in the complexities of the spectra apparently

indicate some profound differences in the source parameters of the studied events. The seismic

moment, Mo, rapture length, L, Dislocation, D, stress drop, ∆σ are derived from the magnitude

spectrum following the equations of Kaiser et al. (1996) assuming far-field omega-square spectral

model:

f

1/ 24m 0.7

2

2= (10 ) r r so c

C CM TR

ρπ

−

ΘΦ

⎛ ⎞⎜ ⎟⎝ ⎠

(7)

where, ρr, Cr are the density and P-wave velocity of the material near the receiver, Cs is the P-wave

velocity near the source, mf and Tc are the maximum observed spectral magnitude and its

corresponding period and RθΦ is the P-wave radiation pattern coefficient (0.44), which is the

average value over the focal sphere (Boore and Boatwright, 1984). The values of ρr, Cr are 2740

kg.m-3 and 6140 m.s-1 while the Cs values are 5080 m.s-1 and 6140 m.s-1 (Bukchin et al., 2001) for

the explosion and earthquake respectively. The fault length L is approximated by the diameter 2ao

of the Burne (1970) circular fault model. Thus

L = 0.74 CsTc (8)

o2o

M=

aoDµπ

(9)

30

7 = 16

oMa

σ∆ (10)

where Do is the average dislocation and ∆σ is the average stress drop.

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The calculated source parameters (Table 2) show high stress drop and small rupture length

for the nuclear explosion compared to the natural earthquakes, although the latter have a relatively

smaller magnitude. The calculated seismic moment for the earthquake of May 2, 1995 (0.89E17

Nm) is about 3 times smaller than the seismic moment of 2.24E17 Nm published by HRVD while

the seismic moment determined for the October 23, 2006 (5.59E16 Nm) is quite similar to the

seismic moment of 4.95E16 Nm obtained by HRVD. However, the calculated moment of the

explosion (2.29E17 Nm) is larger than the one published by Bukchin et al. (2001), Mo = 0.15E17

Nm, which is based on the surface wave inversion. The source parameters of the Cairo earthquake

of October, 12, 1992 calculated based on magnitude spectra show good agreement with other

techniques as waveform inversion and spectral analysis (Abou Elenean et al., 2000).

Conclusions

The spectral seismograms (spectrograms) exhibit interesting features that may prove useful in

discriminating nuclear explosions from shallow earthquakes. An inspection of the spectrogram

clearly indicates a concentration of the spectral power in the explosion's P-wave relative to S-wave

or any later phases. Meanwhile the S-wave power is usually clear and relatively larger than P-wave

power for the shallow earthquakes. When nuclear explosion fired close to the earth surface, the P-

wave energy decays rapidly whereas in the earthquake the energy takes more time (i.e. slow rate) to

vanish (either for the P-waves or for the whole trace). Besides, the frequency content of the

explosion's P-wave reflects a limited band of higher frequencies compared to the natural

earthquakes with comparable size and epicentral distance. These observed dissimilarities between

nuclear explosion and earthquake spectral content arise from their source mechanism. Nevertheless,

the nuclear explosion has a spectral magnitude of 6.7, that is larger than the values of 5.8 and 5.4

obtained for the two studied earthquakes, its observed corner period is smaller that confirm its small

sources dimension. Additional significance differences between two studied events rests in the

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values of the stress drop and the rupture length estimated from the magnitude spectra. These values

can be used as another criterion for the discrimination studies.

Acknowledgments. This work was done within the framework of the Associateship Scheme of the Abdus Salam International Centre for Theoretical Physics, Trieste, Italy. We thank the ICTP Publications Office for reviewing the manuscript.

References

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Germany, Unpublished paper.

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Table 1: Parameters of the studied events.

Event Date Day Mo. Yr.

Origin Time H. Mn. Sec.

Lat.° (N)

Long.° (E)

H (Km)

mb

Earthquake (1) 02 05 1995 11 48 12 43.490 84.54 18 5.5 Earthquake (2) 23 11 2006 11 04 49 44.230 83.50 28 5.3 Nuclear Explosion 15 05 1995 04 05 57 41.603 88.82 ≈ 0 6.1

Table 2: Source parameters calculated using the magnitude spectrum for the three studied events. Nuclear Explosion Natural Earthquakes 02051995 Natural Earthquakes 23112006

Station Mo

1017

∆σ L Do Station Mo

1016 ∆σ L Do Station Mo

1016

∆σ L Do

ABKT 2.00 15.0 3562 0.75 ABKT 6.63 1.39 5493 0.11 ABKT 5.42 1.01 5708 0.08

ARU 1.35 17.39 3004 0.70 ARU 10.09 1.18 6867 0.11 ARU 2.68 1.11 4390 0.07

KEG 3.53 26.42 3605 1.28 DPC 10.03 2.45 5279 0.17 MALT 5.57 1.10 5622 0.08

OBN 8.67 1.44 5837 0.11

Average 2.29 19.60 3390 0.91 8.90 1.67 5879 0.13 5.59 1.17 5389 0.09

Mo is the seismic moment in Nm, ∆σ is the stress drop in Mpa, L is the fault length in m, Do is the dislocation in m.

13

Fig.1. Broadband stations used for discrimination between the nuclear explosion and the two studied natural

earthquakes.

14

Fig.2. The spectral seismogram (spectrogram) of the two natural earthquakes (A, B) and the nuclear explosion (C) at

ABKT station. The velocity trace (my/sec) is shown above the spectrogram. The color scale reflects the envelope

amplitude normalized to the maximum at each trace.

15

Fig.3A. Spectral magnitudes from ABKT broadband stations for the two natural earthquakes (upper part) and the

nuclear explosion (lower part).

16

Fig.3B. Spectral magnitudes from ARU broadband stations for the two natural earthquakes (upper part) and the nuclear

explosion (lower part).

17

Fig.4. Average spectral magnitudes calculated from four broad band stations for the two natural earthquakes and the

nuclear explosion.

18

Fig.5. Smoothed average spectral magnitudes at 8 octaves for the two natural earthquakes and the nuclear explosion.