Modeling of seismo-electromagnetic phenomena
N. Gershenzon and G. Bambakidis

6. Discussion and Conclusions

A. Major seismo-electromagnetic phenomena can be described by the following model. The final phase of the pre-earthquake process is accompanied by the formation of multiple cracks. Cracks appear not only in the focal area but also in a neighborhood. This occurs because regional geodynamic processes are connected by the global shear stress. The appearance of a crack creates, in its neighborhood, a mechanical disturbance over a broad frequency range. In general, the spectral density of the disturbance consists of two parts: a zero-frequency spike related to a change in the residual strain, and a broad region from zero up to the MHz range, related to an impulse-like process. In a crust saturated with water (the usual case), a crack will also cause a change in the pore water pressure, and the spectral density of this response is much less broad, extending from zero up to the range of kHz. Localized mechanical or pore pressure changes give rise to electromagnetic emission by a variety of mechano-electromagnetic transducer mechanisms. The emission will have a spectral density which spans the same range as its source.

B. The major known mechano-electromagnetic mechanisms which may be applied to the earth's crust, namely piezomagnetic, piezoelectric, electrokinetic and induction, have been considered and are compared in Table 1. From this table one can see that a piezomagnetic source has strength comparable to that of a pure quartz piezoelectric source. In the case of high conductivity in the earth's crust, the strength of an electrokinetic source and a piezomagnetic source are also comparable. The magnitude of the induction effect is usually very small compared to the other three, but it could be comparable to them for a source of size 1 km or more.

C. Since the dimensions of the EM source are, in most real cases, much smaller than the distance from source to detector, all sources are represented by a magnetic or electric dipole. Formulas 21 and 22 and Table 2 express the magnitude of the electric and magnetic dipoles in terms of the parameters of both the earth's crust and the mechanical disturbances. The mechanical parameters important in calculations, namely strain spectral densities e(w, r) and q(w, r), pore water pressure spectral density P (w, r), crack density n, and average shear and volume strain changes e and q, are given in equations 1c, 3a, 4, 5 and 5a. The relation between volume strain and pore water pressure is given by equation A9.

Expressions 18(a-d) can be used for calculating the magnetic and electric fields in the so-called static zone and expressions B1-B32 in the near, intermediate and far zones for s/we>1. When s/we<1, expressions 19(a-d) and 20(a-d) can be used in the near and far zones, respectively. In order to connect the "detected'' (filtered and averaged) EM field to the real field one uses expressions 26, 28 and 27, 29.

Collectively, all the above formulas represent the necessary relationships for estimating the measured EM field, at the detector, for a wide range of frequencies and at various distances from the source. Through them, the physical parameters of both the earth's crust and of a localized disturbance are connected to the measured EM field.

D. The magnitude and morphological features of major SEM phenomena have been interpreted on the basis of the model developed here.

1. Tectonomagnetic anomalies can be described either by the piezomagnetic or electrokinetic effect. In rocks containing titano-magnetite, residual strain as a result of the cumulative action of crack formation in a localized area can produce magnetic field variations of the order of nT. The same order of magnetic variation can be produced in water-saturated rocks of high electrical conductivity (sge10-2/W-m) by changes in pore water pressure. These two mechanisms can be distinguished by the temporal behavior of the magnetic variation (step-function behavior corresponding to the piezomagnetic mechanism and unipolar behavior corresponding to the electrokinetic mechanism).

2. Of the mechanisms considered in this paper, only the electrokinetic mechanism can explain the main features of electrotelluric field anomalies, namely duration, magnitude, and high degree of selectivity.

3. Geomagnetic variation in the ULF range may be explained on the basis of the electrokinetic effect, when the detector is located about a water-saturated layer which has a comparatively high conductivity. While the piezomagnetic effect could also contribute to the variation, the electrokinetic effect is a more likely mechanism. The main reason for this is the difference in the spectral density of the mechanical disturbances associated with each. The energy of a piezomagnetic source is distributed widely from zero up to radio frequencies. The electrokinetic source is usually much narrower, with correspondingly much more energy in the ULF range.

4. The most powerful source of EME in the RF range is the piezoelectric effect due to the presence of quartz grains in the crust. The magnitude of the piezomagnetic effect in the RF range is 2-3 orders of magnitude less.

E. Calculations based on the model presented here show that the source of all types of EM anomalies considered here should be local, i.e. close to the detector but not necessarily in the focal region, in order to be observed. The maximum distance from source to detector depends on the type of anomaly and on the detector, and can range from several hundred meters to several kilometers. One of the best experimental confirmations of this statement is the fact that there are no SEMS during earthquakes (excluding co-seismic signals accompanying seismic waves). An earthquake itself is a huge mechanical disturbance, much bigger than the disturbances we expect during the pre-seismic time. So it should, and probably does, produce large SEMS from all the mechanisms we have discussed. But the magnitude of these signals decreases as an inverse power of the distance and at 10 km or more from the focal region it should be negligible in most cases. That is why "global'' models, which suppose that the source of SEM anomalies is at the earthquake origin, have to introduce some additional (and sometimes unrealistic) suppositions to explain how the signal can still be detected at several hundred kilometers from the focus. Even with these suppositions, the experimental fact is that no SEMS are observed during a quake.

F. Some general recommendations for field experiments can be made based on the model described here. Since all sources should be close to the detector to be observed, the placement of detectors is critical and depends on the frequency range and on whether an electric or magnetic measurement will be made. For example, the nearby presence of rock containing titano-magnetite is required for monitoring tectono-magnetic variation. The existence of a nearby water-saturated layer provides a necessary condition for electrotelluric anomalies as well as geomagnetic variation in the ULF and quasi-static ranges. The best condition for the appearance of anomalies in the RF range is the nearby presence of quartzite or granitic rock and, for their detection, a low crustal conductivity about the detector is also necessary. Because all sources become active only under a mechanical disturbance, the presence of an active geophysical structure such as a fault is necessary.

Since magnetic variation from an electrokinetic source can apear only in the presence of a vertical inhomogeneity, the detector should be placed close to it. For monitoring an electrotelluric anomaly the best setting of the electrodes is across the vertical plane defining the inhomogeneity. The anomaly is enhanced if the water table is close to the surface, provided the electrode separation is not much less than the depth of the table. An electrotelluric anomaly can also be observed without a vertical inhomogeneity if the electrodes are displaced vertically, with one above the water table and the other below it.

Since ULF and RF anomalies are expected to have a pulse-like character, “impulse averaging” is the best technique for monitoring them. This technique avoids the “dead time” between impulses, and requires a small acquisition time. On the other hand, the acquisition time should be large enough to record the entire impulse (or a cluster of multiple impulses). The choice of optimal threshold value is also important for this type of averaging, since it should be low enough to record small impulses but high enough for a good signal-to-noise ratio. Following the above recommendations would involve investigating, at the detector location, both the composition of the crust and the noise level in the frequency range of interest.

G. Since our results indicate that SEMS arise from a local source, the usual triangulation technique cannot be used to locate a distant seismic focus. At the heart of our model, however, earthquakes and SEMS are connected by a global stress field. This connectedness means that the possibility still exists for locating a seismic focus using SES. One way is by statistical analysis of these two types of events (SES and earthquakes) using a detector network [Varotsos et al., 1996a, 1996b]. Such an analysis may allow one to establish a connection between a group of SES measurement points and a group of seismic areas.

H. EM emission is a secondary effect of local changes in the stress field of the crust. The question arises, why not measure the stress changes directly? After all, it is known that the latter can be measured with more accuracy. There is at least a twofold answer to why measurements of EME can be useful and can give additional (and sometimes the only) information about stress changes. First, EME measurements can give information about remote stress field changes, while direct stress field measurement give information only at the immediate vicinity of the detector. Second, the latter type of measurement is usually more expensive than EME detection.


The authors would like to thank their colleagues Paul J. Wolfe, Kostas Eftaxias and Nikos Bogris for several helpful conversations. Special thanks go to Ms. Barbara O'Brien for typing the manuscript. This research was supported in part by NATO Grant CRG970028.

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