Research on earthquake prediction from geomagnetic pulsation"

Transcription

1 Vol. 8 No ACTA SEISMOLOGICA SINICA May,1995 Research on earthquake prediction from geomagnetic pulsation" Jun-Cheng ZHOU ( ~ ~[~ ~), Ke=Li HAN ( ~ ~ ~[~), Pei-De WANG Yue LU (~ ~) Institute of Geophysics, State Seismological Bureau, Bei fing , China ( t :t~ ~ ) and Abstract This paper has presented a research on the method of using digitized data of geomagnetic pulsation observation to predict earthquakes and the research results. According to the theory of inductive magnetic effect, the observation of geomagnetic pulsation events can detect the preseismic conductivity and structure anomalies of subsurface media more effectively than the conventional geomagnetic observations, especially the short-impending anomalies before earthquakes. Our research results have also indicated that the geomagnetic pulsation transfer function has obvious short-impending anomalies and typical anomaly forms before earthquakes. Using the proposed method, satisfactory prediction results have been obtained. Key words: geomagnetic pulsation, transfer function, electromagnetic induction, conductivity, short-impending anomaly 1 Introduction Earthquake prediction from geomagnetic variation is one of the important methods for earthquake prediction; and some encouraging progress in this respect has been made in recent years. However, the research on earthquake prediction from geomagnetic variation in China is now still based only upon the observational means, such as nuclear precession magnetometer, magnetic variometer, etc.. These observational means are only capable of reflecting long-period and part of short-period geomagnetic signals, but are incapable of reflecting geomagnetic pulsation signals that are only a few seconds or a few minutes long. When viewed from the theory of inductive magnetic effect, however, it is just the signal of geomagnetic pulsation which can provide the most effective means for observing seismo-magnetic anomalies and can make the short-impending predictions from geomagnetic variation possible. For these reasons, it is doubtless that the research on earthquake prediction from geomagnetic pulsation may eliminate the gap in this respect in China; and this method as a very promising method may make some contribution to enhance the accomplishment of short-impending prediction. "Beijing Observational Network of Digital Geomagnetic Pulsation" was established in 1990 (Zhou et al., 1994); and have conducted formally the observation and research on earthquake prediction from geomagnetic pulsation since then. From August 1990 to the end of 1992, totally six earthquakes of about ML ~ 4. 0 occurred in Beijing and its surrounding areas and obvious anomalies appeared before all of those earthquakes. By summarizing the characteristics of anomalies for the former three earthquakes, short-impending predictions for the latter three were made * Received April 28, 1993; Accepted November 13, Contribution No. 95A0023, Institute of Geophysics, SSB, China.

2 310 ACTA SEISMOLOGICA SINICA Vol. 8 with better effect. These have showed a brilliant prospect for short-impending predictions with this new method of "earthquake prediction from geomagnetic pulsation. " 2 Theoretical basis of earthquake prediction from geomagnetic pulsation A popular opinion in the seismological circles is that the process of earthquake preparation is often accompanied by some anomalous conductivity variations of the subsurface media (Chen and Fung, 1993; Barsukov, 1974; Rikitake, 1981~ and Gong and Wu, 1986). The cause resulting in these variations might be that the accumulation of seismogenic stresses can directly influence the porosity of rocks and the interconnection of microcracks. The conductivity of rocks is greatly influenced by the porosity of rocks and interconnection of microcracks. There is generally the following relationship (Zhao and Qian, 1978) : a = aa0q~'( 1 -- V~-~) m (1) where a is constant~ a is conductivity of water-bearing rock~ a0 is conductivity of pore fluid in rock ~ ~ is rock porosity ~ V~ is volume of pores ~ Vg is volume of pore gas in rock ~ and p and m are textural indexes characterizing the interconnection of microcracks. In the late stage of seismogenic stress accumulation, microcracks will occur in rocks in the source region and then propagate to make the original water-bearing cracks in rock interconnected. Therefore, groundwater in surrounding areas will permeate in the source region until saturation so as to raise the conductivity of rocks obviously. Under such a critical condition,the interconnection of rock pores and interstitial water is very sensitive to the variation of stress~ correspondingly, the conductivity of rocks also varies obviously with the variation of stress. This kind of conductivity variations will affect the inductive field component of the varying magnetic field of the earth. Since geomagnetic pulsation varies at a relatively high rate, its inductive effect is most obvious in response to the conductivity variation at a proper depth beneath the ground surface. The so-called proper depth is just where most earthquakes occur. Generaly, harmful earthquakes are all shallow-focus ones~ their focal depths range from a few kilometers to tens of kilometers, mostly ten-odd kilometers (Li, 1981). By computing with a two-dimensional model and assuming earthquakes of different magnitudes, Rikitake (1981) has estimated the period range of geomagnetic signals that can induce the greatest conductivity anomaly. By the numerical method for three-dimensional electromagnetic induction, Qi et al. (1977 ~ 1981) have also made similar computations. Their results all indicate that for observing the conductivity anomalies caused by ML earthquakes with focal depths of a few kilometers to several tens kilometers, geomagnetic pulsation whose period ranges from a few seconds to several minutes can give the best result (Hao, 1986). In other words, the observation of geomagnetic pulsation and corresponding techniques for data processing and analysis have provided a new means. By this method, it would be possible to monitor seismo-magnetic anomalies and predict earthquakes more effectivly. 3 Data procesing and prediction method The data used in this research are the geomagnetic pulsation data observed by "Beijing Observational Network of Digital Geomagnetic Pulsation", while the method for analysis and prediction is mainly the geomagnetic pulsation transfer function method (also called the geomagnetic pulsation conductivity function method). For a specific station, the three components of geomagnetic pulsation, D, Z and H have the

3 No. 2 ZHOU, J. C. et al. ~ RESEARCH ON EARTHQUAKE PREDICTION FORM GEOMAGNETIC 311 following approximate relationship (Parkinson, 1989 ; Gough and Ingham, 1983) : Z = AH + BD (2) where A and B are called the transfer functions, whose magnitudes are closely related with the conductivity of subsurface media in local areas. By monitoring the variations of A and B with time, it would be possible to discover the anomalous conductivity variation caused by earthquake preparation and further to predict the coming earthquake. The magnitudes of A and B are also functions of the periods of geomagnetic pulsation. For different periods of geomagnetic pulsation, the calculated A and B values are also different; they are a reflection of the conductivity values at different depths. Generally, A and B are functions in the complex frequency domain; they are of complex forms as follows: A = A, + ia~ B = B, + ibi (3) (4) The techniques of spectral analysis, such as the fast Fourier transform technique, maximum likelihood method, etc., are generally used to determine the short-period geomagnetic transfer functions A and B. Among them, the fast Fourier transform technique is the most commonly used. Through spectral analysis, the frequency spectra of the three components of various geomagnetic events can be obtained. Substitution of these spectra into equation (2) gives a set of linear equations. Using the least square method to solve for A and B, the following expressions for A and B can be obtained (Gough and Ingham, 1983): A = ~,ZH" ~DD" -- ~,ZD" ~DH" Y, HH" ~DD" -- ~,HD" ~,DH" (5) B = ~_,HH" ~,ZD" -- ~,HD" ~ZH" (6) ~HH" ~,DD* -- ~,HD" ~,DH" where the symbol " * " means conjugate. All of the above-mentioned conventional methods of spectral analysis require a longer time series of data; they cannot provide satisfactory results of spectral analysis and may bring about the pseudo-frequency phenomenon when a short time series of data is used. Many geomagnetic pulsation events are of relatively short duration. In particular, the geomagnetic pulsation data from Baijiatuan station can only be obtained during the period from about 0:00 to 4:30 everyday owing to the disturbance of the subway. Moreover, the data in that period should be further divided into several segments for spectral analysis in order that a group of geomagnetic pulsation transfer functions can be determined within a few days. Besides, the pseudo-frequency component of the conventional spectral analysis method also gives serious effects to the high-frequency end of geomagnetic pulsation. In such a case, the conventional spectral analysis method is obviously not suitable for determining the geomagnetic pulsation transfer function. It is especially so for geomagnetic pulsation signals a few tens seconds in period.

4 312 ACTA SEISMOLOGICA SINICA Vol. 8 The advanced Sompi spectral analysis method (Asakawa, 1988) is very suitable for determining the geomagnetic pulsaton transfer function. One of its significant merits lies in that it not only is suitable for short time series of data, but also has very high resolution without producing pseudo spectral components; and the transfer function determined with this method is also comparatively stable. Another feasible method for determining the geomagnetic pulsation transfer function is to solve for the purely real transfer function (Gong, 1992). When the three components H, D and Z in equation (2) are replaced by the variation amplitudes AH, AD and AZ of geomagnetic events whose periods are within a small range and when the sampling times of the three components are rigorously the same, equation (2) can be rewritten as AZ = AAH + BAD (7) Based on equation (7), an matrix consisting of many groups of sinusoidal variation amplitudes which satisfy the given values can be obtained as follows. Y=W.X where Y = (AZ 1, ~Zz,...,z3Z.)T; W = (A,B); (8) AH~,'.", AH. X = (AH"AD2,...,AD. ) ADl, Then the least square solution of A and B in the form of matrix is W-= (XT)-IXTy (9) and thereby the value of purely real transfer functions A and B can be determined. The wave forms of geomagnetic pulsation events are mostly sinusoidal or quasi-sinusoidal. Even for the Pi type geomagnetic pulsation event whose wave form is somewhat irregular, the wave form can also become regular after band-pass processing with not very wide frequency range. Furthermore, because the record is digitized and data processing is entirely computerized, the sampling times are exactly the same. Therefore, the purely real transfer function can be determined better. This method is even more suitable for short time series of data. The function values of A and B given in this paper are just this kind of purely real transfer function. We determined a group of the transfer functions A and B at a time interval of 5 days and plotted their variations as a function of time in order to monitor their anomalous variations. According to our experience, geomagnetic pulsation transfer functions within the period range of 40 to 80 seconds have the most remarkable short-impending anomaly phenomenon before earthquakes. For the Baijiatuan station, an A value of 0.1 is taken as the critical value of anomaly. This critical value is generally greater than three times the standard deviation of A; and a value greaterthan the critical value is regarded as being anomalous. The shape and size of anomaly depend on the magnitude of earthquake and the epicentral distance from the station. For earthquakes of ML~-4.0 or slightly greater within a range of 100 km from the station, the transfer function A displays anomalies about 40 days before earthquake ; the anomaly is "double-peak" shaped; the peak value of anomaly is 80% greater than the critical value; and earthquake takes place soon after the appearance of the second peak. For greater earthquakes of ML~6.0 within a range of 200 km from the station, the transfer function A displays anomalies about two months

5 No. 2 ZHOU, J. C. et o2. = RESEARCH ON EARTHQUAKE PREDICTION FORM GEOMAGNETIC 313 before earthquake;the peak value of anomaly is about 50% greater than the critical value; the smaller peak value may be attributed to the greater epicentral distance but the area enveloped by the peak is larger, and the peak is roughly round-hill shaped. By use of these features, it would be possible to predict earthquakes. 4 Effect of earthquake monitoring and prediction --earthquake cases Within a range of 100 km from the Baijiatuan station, a total of three earthquakes of about ML4. 0 occurred in the period from August 1990 to the end of They occurred at Shahe (ML4. 5) on September 22, 1990; at Mafang (ML4.0) on September 28, 1991 and at western Xiangshan (ML3. 5) on November 30, 1991, respectively. Within a range of 200 km from the Baijiatuan station, three earthquakes of about ML5. 0 to ML6. 0 occurred in the same period. They occurred at Datong (ML6.4) on March 26, 1991; at Douhe (ML5.2 and ML5. 6) on May 29 and 30, 1991 and at Ninghe (ML4.7) on July 22, 1992 respectively. There were obvious short-impending anomalies before all of these earthquakes. Based on the summarization of the features of anomalies for the Shahe, Datong and Douhe earthquakes, we have made comparatively satisfactory short-impending predictions for the Mafang, western Xiangshan and Ninghe earthquakes The Shahe earthquake An earthquake of ML4. 5 occurred around Shahe on September 22, The epicenter-to-station distance is about 17 kin. Forty days before the earthquake, the geomagnetic pulsation transfer function A began to show anomalies which were significantly higher than the critical value (0. 1). About ten days later, the first peak which was about 60% higher than the critical value appeared. After having experienced a valley which lasted a certain period 0,211 r 0. t5 -~ 0, ~1~ = ~ _ ~ Ilq IO Figure 1 Anomalies of geomagnetic pulsation transfer function associated with the Shahe earthquake of time, the second peak which was about 80 % higher than the critical value appeared seven days before the earthquake. Later on, the anomaly value began to decrease and the "double-peak" shaped anomaly ended. There was a time separation of about one month between the two peaks and the earthquake occurred when the second peak had decreased to below the critical value (see Figure 1). The A value always fluctuated below the critical value within three months after the earthquake and no noticeable earthquakes took place in that period The Datong earthquake A strong earthquake of ML6. 4 occurred around Datong of Shanxi Province on March 26, The epicenter-to-station distance is about 200 km. The A value began to show anomalies about two months before the earthquake and continued to form a round-hill shaped peak. That peak existed for thirty-odd days and the maximum value was 60 % greater than the critical value. Subsequent to the peak, a valley appeared and lasted about twenty-five days. The earthquake occurred about ten days after the A value had showed a tendency to increase (see Figure 2). As compared with that of the Shahe earthquake, the peak of anomaly for the Datong earthquake has a longer duration, envelops a larger area and is smoother in shape. These might be a reflection of the anomaly features for earthquakes of higher magnitude and longer epieentral dis-

6 314 ACTA SEISMOLOGICA SINICA Vol. 8 tance. However, the maximum value of the peak is smaller than that of the Shahe ~/I I,-I U. 15 earthquake, probably due to the longer epicentral distance too. " The Douhe earthquake t) 05 The Douhe earthquake discussed here O(IoL. PItH 12 Pm2 tll 112 o) actually consists of two earthquakes of ML5. 2 and ML5.6 that occurred in succes- Figure 2 Anomalies of geomagnetic pulsation sion on May 29 and 30, 1991, respectivetransfer function associated with the ly, The epicenter-to-station distance is Datong earthquake about 183 kin. This earthquake occurred roughly two months after the Datong earthquake. Its pre-seismic anomaly did not show the typical features in shape; this may probably be attributed to the influence of the Datong earthquake. Nevertheless, the value of the transfer function A always remained above the critical value within two months before earthquake and was 50% to 90% higher than it. After the earthquake, it decreased to below the critical value (see Figure 3). 4.4 The Mafang earthquake This earthquake refers to the two earthquakes of ML4. 0 that occurred at Mafang on September 28, The epicenter-to-station distance is about 70 km. The A value began to show anomalies forty days before the earthquake. The entire pro- H 2H '~/ "2 ;I. ~!, II II) l) I)'~ Figure 3 I}5 I ~ "" I1< I ~ igq] 114 II'~ 116 1)7 Anomalies of geomagnetic pulsation transfer function associated with the Douhe earthquake cess of anomaly also manifested the double peak feature, with the two peak values more than 100% higher than the critical value. The earthquake took place when the second peak had decreased to around the critical value (see Figure 4). Iqtl[ ) 1)~ IIX I)9 Ill Figure 4 Anomalies of geomagnetic pulsation transfer function associated with the Mafang earthquake The anomaly of this earthquake is very similar to that of the Shahe earthquake in shape and the two curves shown in Figures 1 and 4 are very similar. This right reflects the features of anomalies associated with near and small earthquakes. In view of the one-by-one correspondence of the former three earthquakes (the Shahe, Datong and Douhe earthquakes ) with the phenomena of geomagnetic pulsation anomalies and the close similarity of the anomaly shape of this earthquake with that of the Shahe earthquake, we believed that the anomaly should imply the impending of a near earthquake of about ML4.0. Therefore, we made short-impending predictions whose result was in agreement with the actual earthquake The Western Xiangshan earthquake An earthquake of ML3.5 occurred at Western Xiangshan on November 30, The epi-

7 No. 2 ZHOU,J. C. et al.. RESEARCH ON EARTHQUAKE PREDICTION FORM GEOMAGNETIC 315 center-to-station distance is only 10 km. Again the geomagnetic pulsation transfer function began to show the "double-peak" shaped anomaly about forty days before the earthquake (see Figure 5) and the anomaly shape was extremely similar two those of the Shahe and Mafang earthquakes. This implied that another near earthquake of about ML4. 0 was coming. We made short-impending predictions and the result was consistent with the actuality. ItlL) 1 tit) I~ ]l '" Figure 5 Anomalies of geomagnetic pulsation transfer function associated with the Western Xiangshan earthquake Although the western Xiangshan earthquake was of lower magnitude, the anomaly was still so large that the peak value was about 150 % higher than the critical value because the epicentral distance was very short. Besides, there were also obvious pre-seismic anomalies before the Ninghe ML4. 7 earthquake on July 22, 1992, and predictions were made to a certain extent. 5 Conclusions In summary, the above-mentioned facts have indicated that obvious short-impending anomalies of geomagnetic pulsation did occur before earthquake and they showed typical features of anomaly shape. Besides, the anomalies had very close one-by-one correspondence with earthquakes and no evident non-seismic anomalies occurred. The controlling range of geomagnetic pulsation in monitoring and predicting earthquake is within 70 km for earthquakes of ML~4. 0, within 100 km for earthquakes of ML~5. 0 and more, and within 200 km for earthquakes of ML ~6.0. The above facts seem to suggest that earthquake prediction from geomagnetic pulsation is a very promising method for short-impending predictions of earthquakes indeed. Within the Beijing Observational Network of Digital Geomagnetic: Pulsation, the anomalous phenomena at the Baijiatuan station are the most obvious. However, they are not so obvious at the Madaoyu and Xibozi stations than the Baijiatuan station. On the one hand, this may be the result of the highnoise transducers that the two stations were obliged to use in the early stage of station establishment due to insufficient funds. Such transducers are less capable in detecting weak signals and have already been replaced by low-noise ones now. On the other hand, the electric structures of underground media of those two stations may have some influence too. In order to select the site for stations more properly and to enhance the research on earthquake prediction, the mechanism of pre-seismic anomalies of the geomagnetic pulsation transfer function should be studied. References Asakawa, E., Utada, H. and Yukutake, T., Application of Sompi spectral analysis to the estimation of the geomagnetic transfer function. J. Geomagn. Geoelec., 40, Barsukov, O. M., Variations in the electrical resistivity of rocks and earthquakes. In: Earthquake precursors, 216pp. Acad. Sci. U. S. S. R., Moscow, Chen, P. F. and Fung, P. C. W., Time changes in geomagnetic transfer functions at Lunping before and after the 1986 Hualian earthquake. J. Geomagn. Geoelec., 45,

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