Seismic Electric Signals Research Articles

Preface Special Issue: Developments in Earthquake Precursors Studies

This Special Issue of Annals of Geophysics is dedicated to present recent developments in the field of earthquake (EQ) precursors. Due to their potentially catastrophic nature, EQs have early attracted the attention of humans. During the last decades, a considerable amount of scientific effort has been devoted to the study of EQ precursors, aiming at EQ forecast. Prediction of large EQs, especially in the short-term, is of outmost importance for our society, since it could prevent, or at least restrict, their disastrous consequences, both in terms of infrastructure / material damages and in terms of casualties. It is clear that EQ preparation processes are complex and multifaceted, which call for a multidisciplinary approach. Many possible precursors have been reported and studied during the last decades, which include (just to mention some): foreshock activity, pre-slip effect, surface deformation, seismic electric signals (SES), ultra-low frequency (ULF) magnetic field anomalies, fracture-induced electromagnetic emissions (FEME) (fracture-induced electromagnetic radiation, FEMR), ULF/ELF (extremely low frequency) atmospheric electromagnetic radiation, atmospheric anomalies (such as SLHF, OLR etc.) and ionospheric (lower and upper regions) anomalies, lithosphere-atmosphere-ionosphere (LAI) coupling, even abnormal animal behavior.

Seismogenic ULF/ELF Wave Phenomena: Recent Advances and Future Perspectives

There has been enormous progress in the field of electromagnetic phenomena associated with earthquakes (EQs) and EQ prediction during the last three decades, and it is recently agreed that electromagnetic effects do appear prior to an EQ. A few phenomena are well recognized as being statistically correlated with EQs as promising candidates for short-term EQ predictors: the first is ionospheric perturbation not only in the lower ionosphere as seen by subionospheric VLF (very low frequency, 3 kHz f 30 kHz)/LF (low frequency, 30 kHz f 300 kHz) propagation but also in the upper F region as detected by ionosondes, TEC (total electron content) observations, satellite observations, etc, and the second is DC earth current known as SES (Seismic electric signal). In addition to the above two physical phenomena, this review highlights the following four physical wave phenomena in ULF (ultra low frequency, frequency Hz)/ELF (extremely low frequency, 3 Hz frequency 3 kHz) ranges, including 1) ULF lithospheric radiation (i.e., direct radiation from the lithosphere), 2) ULF magnetic field depression effect (as an indicator of lower ionospheric perturbation), 3) ULF/ELF electromagnetic radiation (radiation in the atmosphere), and 4) Schumann resonance (SR) anomalies (as an indicator of the perturbations in the lower ionosphere and stratosphere). For each physical item, we will repeat the essential points and also discuss recent advances and future perspectives. For the purpose of future real EQ prediction practice, we pay attention to the statistical correlation of each phenomenon with EQs, and its predictability in terms of probability gain. Of course, all of those effects are recommended as plausible candidates for short-term EQ prediction, and they can be physically explained in terms of the unified concept of the lithosphere-atmosphere-ionosphere coupling (LAIC) process, so a brief description of this coupling has been carried out by using these four physical parameters though the mechanism of each phenomenon is still poorly understood. In conclusion, we have to emphasize the importance of more statistical studies for more abundant datasets sometimes with the use of AI (artificial intelligence) techniques, more case studies for huge (M greater than 7) EQ events, recommendation of critical analyses, and finally multi-parameters observation (even though it is tough work).

Order Parameter and Entropy of Seismicity in Natural Time before Major Earthquakes: Recent Results

A lot of work in geosciences has been completed during the last decade on the analysis in the new concept of time, termed natural time, introduced in 2001. The main advances are presented, including, among others, the following: First, the direct experimental verification of the interconnection between a Seismic Electric Signals (SES) activity and seismicity, i.e., the order parameter fluctuations of seismicity exhibit a clearly detectable minimum when an SES activity starts. These two phenomena are also linked closely in space. Second, the identification of the epicentral area and the occurrence time of an impending major earthquake (EQ) by means of the order parameter of seismicity and the entropy change of seismicity under time reversal as well as the extrema of their fluctuations. An indicative example is the M9 Tohoku EQ in Japan on 11 March 2011. Third, to answer the crucial question—when a magnitude 7 class EQ occurs—whether it is a foreshock or a mainshock. This can be answered by means of the key quantities already mentioned, i.e., the order parameter of seismicity and the entropy change of seismicity under time reversal along with their fluctuations. The explanation of the experimental findings identified before major EQs is given in a unified way on the basis of a physical model already proposed in the 1980s.

LSTM-Autoencoder Network for the Detection of Seismic Electric Signals

Seismic electric signals (SESs) are essential short-term precursors of earthquakes. Accurate and efficient detection of SESs is significant to short-term predictions of earthquakes. However, SESs are usually disturbed by various noises and are thus difficult to recognize. Although conventional techniques have made substantial efforts in improving the SES detection accuracy, the success rates of SES detection at certain stations are still less satisfactory due to the complexity and diversity of noises. In this study, we apply deep learning to extract SESs and develop a novel deep learning network based on geoelectric field characteristics by combining the long short-term memory (LSTM) blocks with an autoencoder structure and a time-step attention module. The detection results of both synthetic and real data demonstrate that our proposed network yields superior performance in detecting embedded SESs in the presence of severe noise interference compared with traditional methods and several well-known networks. Moreover, our novel network shows the excellent ability of massive data processing, generalization and migration, which can process one-day’s worth of data in only milliseconds, adapt to SESs whose durations and amplitudes are different from those of the training set and be easily transferred to newly acquired data. The proposed novel method can provide more efficient and accurate detection results, which will broaden the data availability of hazard mitigation based on SESs.

Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean

The variance κ1 of the natural time analysis of earthquake catalogs was proposed in 2005 as an order parameter for seismicity, whose fluctuations proved, in 2011, to be minimized a few months before the strongest mainshock when studying the earthquakes in a given area. After the introduction of earthquake networks based on similar activity patterns, in 2012, the study of their higher order cores revealed, in 2019, the selection of appropriate areas in which the precursory minima βmin of the fluctuations β of the seismicity order parameter κ1 could be observed up to six months before all strong earthquakes above a certain threshold. The eastern Mediterranean region was studied in 2019, where all earthquakes of magnitude M≥7.1 were found to be preceded by βmin without any false alarm. Combining these results with the method of nowcasting earthquakes, introduced in 2016, for seismic risk estimation, here, we show that the epicenter of an impending strong earthquake can be estimated. This is achieved by employing—at the time of observing the βmin—nowcasting earthquakes in a square lattice grid in the study area and by averaging, self-consistently, the results obtained for the earthquake potential score. This is understood in the following context: The minimum βmin is ascertained to almost coincide with the onset of Seismic Electric Signals activity, which is accompanied by the development of long range correlations between earthquake magnitudes in the area that is a candidate for a mainshock.

Electrical and magnetic data time series’ observations as an approach to identify the seismic activity of non-anthropic origin

In this work, the authors tried to identify a possible relationship between electromagnetic signals (EM) and seismic events in the lithospheric system in the central region of Colombia. The data, both seismic records and electromagnetic signals, were taken from the catalog of the Seismological Network of the National University of Colombia (RSUNAL) and the catalog of the National Seismological Network of Colombia (RSNC). The project included the design and instrument testing phases for recording seismic signals, electrical potential variations, and magnetic field variations to try to identify possible relationships between these signals. Possible electromagnetic precursors for seismic events were observed, mainly magnetic disturbances, but it was not possible to locate evident electrical anomalies (Seismic Electric Signals - SES). Thus, although the results are not conclusive, the magnetic disturbances identified deserve further long-term analysis.

Self-organized criticality and earthquake predictability: A long-standing question in the light of natural time analysis

After the Bak-Tang-Wisenfeld seminal work on self-organized criticality (SOC), the following claim appeared by other workers in the 1990s: Earthquakes (EQs) cannot be predicted, since the Earth is in a state of SOC and hence any small earthquake has some probability of cascading into a large event. Here, we discuss that such claims do not stand in the light of natural time analysis, which was shown at the beginning of the 2000s to extract the maximum information possible from complex systems time series. A useful quantity to identify the approach of a dynamical system to criticality is the variance of natural time χ, which becomes equal to 0.070 at the critical state for a variety of dynamical systems. This also holds for experimental results of critical phenomena such as growth of ricepiles, seismic electric signals activities, and the subsequent seismicity before the associated main shock. Another useful quantity is the change of the dynamic entropy under time reversal, which is minimized before a large avalanche upon analyzing the Olami-Feder-Christensen model for EQs in natural time. Such a minimum actually occurred on 22 December 2010, well before the M9 Tohoku EQ in Japan on 11 March 2011, being accompanied by increases of both the complexity measure of the fluctuations and the variability of the order parameter of seismicity (which was minimized two weeks later). These increases conform to the seminal work on phase transitions by Lifshitz and Slyozov and independently by Wagner as well as to more recent work by Penrose et al. In addition, the evolution of the complexity measure of the fluctuations reveals a reliable estimation of the occurrence time of this M9 EQ.

Natural Time Analysis: The Area under the Receiver Operating Characteristic Curve of the Order Parameter Fluctuations Minima Preceding Major Earthquakes.

It has been reported that major earthquakes are preceded by Seismic Electric Signals (SES). Observations show that in the natural time analysis of an earthquake (EQ) catalog, an SES activity starts when the fluctuations of the order parameter of seismicity exhibit a minimum. Fifteen distinct minima—observed simultaneously at two different natural time scales and deeper than a certain threshold—are found on analyzing the seismicity of Japan from 1 January 1984 to 11 March 2011 (the time of the M9 Tohoku EQ occurrence) 1 to 3 months before large EQs. Six (out of 15) of these minima preceded all shallow EQs of magnitude 7.6 or larger, while nine are followed by smaller EQs. The latter false positives can be excluded by a proper procedure (J. Geophys. Res. Space Physics 2014, 119, 9192–9206) that considers aspects of EQ networks based on similar activity patterns. These results are studied here by means of the receiver operating characteristics (ROC) technique by focusing on the area under the ROC curve (AUC). If this area, which is currently considered an effective way to summarize the overall diagnostic accuracy of a test, has the value 1, it corresponds to a perfectly accurate test. Here, we find that the AUC is around 0.95 which is evaluated as outstanding.

Seismic electric signals (SES) and earthquakes: A review of an updated VAN method and competing hypotheses for SES generation and earthquake triggering

Electromagnetic phenomena are sometimes associated with seismic events, but earthquake prediction using seismic electric signals (SES) has not been seriously considered since the early 1990s. There are several causes: (1) false alarms that have created panics in Greece, and (2) a strong critique of the Varotsos-Alexopoulos-Nomicos (VAN) method used there. An updated VAN method that includes time series analysis has made successful medium-range predictions, and short-range predictions when coupled with seismic time series analysis. Four types of potential mechanisms to create precursory SES relying on deformation effects, temperature effects, ore-mineral movement or groundwater variation are reviewed. Data relevant to each are insufficient to favor a single mechanism. Records of the number of false positive and missed events for an updated VAN method have not been well maintained. False positives appear to be abundant and render the method unusable. Co-seismic groundwater fluctuations are addressed, and two novel hypotheses of earthquake trigger mechanism are also presented: ionospherically induced electric (and resultant magnetic) fields to weaken rock thereby causing failure; and volatiles liberated from minerals additionally promoting rock failure. Recommendations for further study are included.

Fluctuations of the entropy change under time reversal: Further investigations on identifying the occurrence time of an impending major earthquake

A procedure has been developed in a previous publication (Skordas E. S. et al., EPL, 128 (2019) 49001) for the identification of the occurrence time of the Tohoku earthquake of magnitude that occurred in Japan on 11 March 2011 based on natural time analysis of seismicity. Using the complexity measure that quantifies the fluctuations of the entropy change of seismicity under time reversal, we show here that, in the longer scales, the complexity measure of the entire Japanese region starts increasing from 22 December 2010 (the date at which is minimized) reaching a maximum close to the appearance of a Seismic Electric Signals activity (evidenced from the recording of anomalous magnetic field variations on the z-component) in the beginning of January 2011; then it gradually diminishes until just before the mega earthquake. On the other hand, around two days before its occurrence, the complexity measure in the candidate epicentral area exhibits an abrupt increase. This difference reveals, well in advance, that the M7.3 earthquake on 9 March 2011 was a foreshock.

On the biophysical mechanism of sensing upcoming earthquakes by animals

It is documented that a few days or weeks before major Earthquakes (EQs) there are changes in animal behavior within distances up to 500 km from the seismic epicenter. At the same time Seismic Electric Signals (SES), geomagnetic and ionospheric perturbations, are detected within similar distances. SES consist of single unipolar pulses, and/or groups of such pulses called “SES activities” with an average frequency between successive pulses on the order of ~0.01 Hz and electric field intensity on the order of ~10−5–10−4 V/m (Frazer-Smith et al., 1990; Rikitake, 1998; Varotsos et al., 1993, 2011, 2019; Hayakawa et al., 2013; Grant et al., 2015). We show that the SES activities can be sensed by living organisms through the “Ion Forced-Oscillation Mechanism” for the action of Electromagnetic Fields (EMFs) on cells, according to which polarized EMFs can cause irregular gating of electro-sensitive ion channels on the cell membranes with consequent disruption of the cell electrochemical balance (Panagopoulos et al., 2000, 2002, 2015). This can be sensed by sensitive animals as discomfort in cases of weak and transient exposures, and may even lead to DNA damage and serious health implications in cases of intense exposure conditions (as in certain cases of man-made EMF exposures). Moreover, we show that the geomagnetic and ionospheric perturbations cannot be sensed through this mechanism. The same mechanism has explained meteoropathy, the sensing of upcoming thunderstorms by sensitive individuals, through the action of the EMFs of lightning discharges (Panagopoulos and Balmori, 2017). The present study shows that centuries-long anecdotal rumors of animals sensing intense upcoming EQs and displaying unusual behavior, lately documented by systematic studies, are now explained for the first time on the basis of the electromagnetic nature of all living organisms, and the electromagnetic signals emitted prior to EQs.

Relationship Between Seismic Electric Signals and Tectonics Derived from Dense Geoelectric Observations in Taiwan

Some researchers have suggested that significant electromagnetic changes that can be detected prior to strong earthquakes are associated with the tectonics and subsurface structures beneath monitoring stations. Numerical simulation seems to support this phenomenon. However, to date, few field measurement data are available to address this issue. In this work, we used the shifting correlation method to analyze 2-month recordings of 20 geoelectric stations in Taiwan and found at least two stations had recorded geoelectric signals significantly correlated with known seismic events. These two stations are installed on large reverse faults, which are probably characterized by high stress concentrations before earthquakes. In addition, they share the same resistivity variation pattern, namely, a conductor layer sandwiched between two high-resistivity layers. Moreover, both stations are above the electrical resistivity boundaries, which means they have an increased probability of recording the abnormal disturbance once EM signals have been emitted from EQs. Our analysis results support the viewpoint that lateral and vertical electrical resistivity variation and conductors in the subsurface may be able to amplify seismic electric signals.

Study in Natural Time of Geoelectric Field and Seismicity Changes Preceding the Mw6.8 Earthquake on 25 October 2018 in Greece.

A strong earthquake of magnitude M6.8 struck Western Greece on 25 October 2018 with an epicenter at 37.515 N 20.564 E. It was preceded by an anomalous geolectric signal that was recorded on 2 October 2018 at a measuring station 70 km away from the epicenter. Upon analyzing this signal in natural time, we find that it conforms to the conditions suggested for its identification as precursory Seismic Electric Signal (SES) activity. Notably, the observed lead time of 23 days lies within the range of values that has been very recently identified as being statistically significant for the precursory variations of the electric field of the Earth. Moreover, the analysis in natural time of the seismicity subsequent to the SES activity in the area candidate to suffer this strong earthquake reveals that the criticality conditions were obeyed early in the morning of 18 October 2018, i.e., almost a week before the strong earthquake occurrence, in agreement with earlier findings. Finally, when employing the recent method of nowcasting earthquakes, which is based on natural time, we find an earthquake potential score around 80%.

Study of Geo-Electric Data Collected by the Joint EMSEV-Bishkek RS-RAS Cooperation: Possible Earthquake Precursors

By employing the cross-correlogram method, in geo-electric data from the area of Kyrgyzstan for the period 30 June 2014–10 June 2015, we identified Anomalous Telluric Currents (ATC). From a total of 32 ATC after taking into consideration the electric current source properties, we found that three of them are possible Seismic Electric Signal (SES) activities. These three SES activities are likely to be linked with three local seismic events. Finally, by studying the corresponding recordings when a DC alternating source injects current into the Earth, we found that the subsurface resistivity seems to be reduced before one of these three earthquakes, but a similar analysis for the other two cannot be done due to their large epicentral distance and the lack of data.

Seismic electric signals in seismic prone areas

Seismic electric signals in seismic prone areas

MW9 Tohoku earthquake in 2011 in Japan: precursors uncovered by natural time analysis

This paper reviews the precursory phenomena of the 2011 MW9 Tohoku earthquake in Japan that emerge solely when we analyze the seismicity data in a new time domain termed natural time. If we do not consider this analysis, important precursory changes cannot be identified and hence are missed. Natural time analysis has the privilege that enables the introduction of an order parameter of seismicity. In this frame, we find that the fluctuations of this parameter exhibit an unprecedented characteristic change, i.e., an evident minimum, approximately two months before Tohoku earthquake, which strikingly is almost simultaneous with unique anomalous geomagnetic field variations recorded mainly on the z component. This is consistent with our finding that such a characteristic change in seismicity appears when a seismic electric signal (SES) activity of the VAN method (from the initials of Varotsos, Alexopoulos, Nomicos) initiates, and provides a direct confirmation of the physical interconnection between SES and seismicity.

Identifying the occurrence time of an impending major earthquake: a review

The procedure through which the occurrence time of an impending major earthquake can be determined is reviewed in the light of the recent advances. This can be achieved by analyzing in natural time the seismicity in the candidate area. To apply this general procedure, we need two important elements: first, to know when we should start the analysis, i.e., set the natural time equal to zero. This is the time at which the system enters the critical stage. Second a reliable estimation of the candidate epicentral area. If geoelectrical measurements are taken and the VAN method (after the initials of the three researchers Varotsos, Alexopoulos and Nomicos) is applied, both these elements become available upon the recording of a precursory Seismic Electric Signals (SES) activity, because its initiation marks the time when the system enters the critical stage, and in addition the SES data enable the determination of the epicentral area of the impending mainshock. On the other hand, if geoelectrical data are lacking, we make use of the following two recent findings by means of natural time analysis: First, the fluctuations of the order parameter of seismicity in a large area exhibit a minimum a few months before a major earthquake almost simultaneously with the initiation of an SES activity. Second, a spatiotemporal study of this minimum unveils an estimate of the epicentral area of the impending major earthquake. Two examples are given that refer to the strongest earthquakes that occurred in Greece and Japan during the last 3 decades, i.e., the MW6.9 earthquake in southwestern Greece on 14 February 2008 and the MW9.0 Tohoku earthquake in Japan on 11 March 2011.

Symmetry-based electricity in minerals and rocks: A summary of extant data, with examples of centrosymmetric minerals that exhibit pyro- and piezoelectricity

The Earth's core, mantle and crust are composed of rocks and minerals, and exhibit electrical and magnetic phenomena. Electrical data in particular are extremely sparse for Earth materials; fewer than one hundred minerals have piezoelectric data associated with them, for example. More data would help to constrain Earth processes and structures, such as core and mantle composition, geomagnetic anomalies, seismic electric signals, and others. Herein, two hundred seventeen minerals exhibiting ferroelectricity, pyroelectricity or piezoelectricity are presented, with quantitative data where known. Fifty-three of these are centrosymmetric, and explanations are given for their apparent violations of crystal theory. Some thermoelectric and magnetic data are also presented for minerals, and an overview of rock electricity is included. Recommendations for further study are given, as well, such as determining the dielectric behavior of rocks and minerals at depth, and testing minerals for alternative energy applications.

On the Motivation and Foundation of Natural Time Analysis: Useful Remarks

Since its introduction in 2001, natural time analysis has been applied to diverse fields with remarkable results. Its validity has not been doubted by any publication to date. Here, we indicate that frequently asked questions on the motivation and the foundation of natural time analysis are directly answered if one takes into account the following two key points that we have considered as widely accepted when natural time analysis was proposed: First, the aspects on the energy of a system forwarded by Max Planck in his Treatise on Thermodynamics. Second, the theorem on the characteristic functions of probability distributions which Gauss called Ein Sch\"ones Theorem der Wahrscheinlichkeitsrechnung (beautiful theorem of probability calculus). The case of the time series of earthquakes and of the precursory Seismic Electric Signals are discussed as typical examples.

Patterns of criticality in the recent seismic activity in the vicinity of Athens, Greece

New data from the Mw 5.4 earthquake on 17 November 2014 in the vicinity of Athens and its seismic electric signal (SES) precursor confirm patterns of criticality in the pre-seismic region during the last preparatory phase. In detail, the stress drop of the main shock and the lead time of the associated SES are interconnected through a power law with an exponent a = 0.327 falling in the range of critical exponents for fracture. We note that this exponent is derived from a large amount of data and successfully passes the z-score statistical test. This fact supports the hypothesis that upon the emission of the SES the pre-focal area enters a critical stage where nonlinear dynamic processes dominate.