Geoelectrical Signals Research Articles

Vertical dipoles to detect self potential signals in a seismic area of southern Italy: Tito station

Abstract. Since 2000 the Institute of Methodologies for the Environmental Analysis (National Council of Research, Tito, Italy) installed a geophysical monitoring network able to detect geoelectric, geochemic and seismometric parameters in seismic areas of southern Italy. During this period a very large data-base of geophysical time series has been organized and it is actually available to assess robust statistical methodologies to identify geophysical anomalous patterns linked with local seismicity. To better understand the influence of rain and cultural noise on geoelectrical signals (Self Potential), during May 2004 we drilled in Tito station a 20 m-depth hole to measure the SP vertical component. The array is characterized by five Pb-PbCl2 electrodes put at different depths. The common electrode is fixed at 20 m. In this work we present some electrical anomalies probably correlated with local seismic activity on vertical dipoles recorded in Tito station.

Fisher Information Analysis of earthquake-related geoelectrical signals

Abstract. We studied the time fluctuations in the dynamics of geoelectrical data, recorded in Tito site, which is located in a seismic area of southern Italy. We used the Fisher Information Measure, which is a powerful tool to investigate complex and nonstationary signals. The time evolution of the Fisher Information Measure calculated for our signal reveals links with the earthquakes occurring in the investigated area.

Analysis of Extreme Events in Geoelectrical Time Series Measured in a Seismic Area of Southern Appenine Chain (Italy)

In the present paper we analyse the series of extreme events in geoelectrical signals recorded at the monitoring station Tito located in a seismic area of southern Italy. Applying an objective criterion to estimate the probability of occurrence of extreme events in the time series (Cuomo et al., 1996; Cuomo et al., 1997), we found a correlation between the geoelectrical anomalies and earthquakes in the area monitored during the period of recording.

Fisher information measure of geoelectrical signals

We analyzed the time fluctuations in the dynamics of geoelectrical data, recorded in a seismic area of southern Italy, by means of Fisher information measure, which is a powerful tool to investigate complex and nonstationary signals. The time evolution of the Fisher information measure calculated for our signal reveals some links with the earthquakes which occurred in the investigated area.

Fractal approaches in investigating the time dynamics of self-potential hourly variability

Fractal tools have been used to investigate the time dynamics of hourly self-potential data, recorded during the year 2001 by five geoelectrical stations located in one of the most seismic areas of southern Italy. Scaling behaviour has been revealed by means of different statistics: the Lomb Periodogram method, the Detrended Fluctuation Analysis, the Higuchi analysis and the mean distance spanned within the time L. The values of the scaling exponents estimated by means of these methods indicate that the temporal fluctuations of the geoelectrical signals are not typical of purely random stochastic processes (i.e. white noise), but evidence the presence of long-range correlations. Furthermore, it is found that these correlations are linear.

Principal component analysis of geoelectrical signals measured in the seismically active area of Basilicata Region (southern Italy)

Abstract. Geoelectrical fluctuations are the end product of several geophysical phenomena. In particular geoelectrical signals measured in seismically active areas can be attributed to stress and strain changes, associated with earthquakes. The complexity of this problem has suggested the development of advanced statistical methods to investigate the heterogeneous nature of these fluctuations. In this paper we analysed the time dynamics of short-term variability of geoelectrical field measured at Giuliano station, located in Basilicata Region, one of the most seismically active areas of southern Italy. We applied the principal component analysis (PCA). The analysis has shown earthquake precursory patterns in the daily variation of the principal components, revealing that the PCA approach is promising for monitoring seismic areas.

Magnitude and sign scaling in power-law correlated geoelectrical time series measured in southern Italy

Abstract. Recently, it has been proposed a new method to investigate the linear/nonlinear properties of a time series by decomposing it into two sub-series: magnitude and sign sub-series (Ashkenazy et al., 2003). The long-range correlation properties of the magnitude and sign sub-series relate to nonlinear and linear behavior of the original time series respectively. We apply this method to the hourly time variability of geoelectrical signals, measured from January 2001 to September 2002 by four stations installed in Basilicata region (southern Italy). Three stations (Giuliano, Marsico and Tito) are located in a seismic area, and one (Laterza) in a low-seismicity area. A site-dependence of the linear/nonlinear properties has been shown, revealing that different dynamics govern signals measured in seismic and low-seismicity areas.

Study on the variation characteristics of the geoelectric field preceding earthquakes

Earthquake events occurred in Nantong, Jiangsu Province on Nov. 3, and Dec. 25, 2001 in which the biggest magnitudes were M L=3.8 and M L=4.1, respectively. This paper firstly explains the principle of the eliminating noise method by the multi-dipole observation system of geoelectric field. Then based on the observation data of the multi-dipole observation system obtained by ZD9A telluric current monitors installed in Chongming and Nanjing stations, we study the abnormal variation of the geoelectric field preceding the earthquakes. The study shows that: a) Eliminating noise method of multi-dipole observation is an excellent method by which many kinds of geoelectric field noises can be eliminated successfully and the geoelectric precursor information can be recognized; b) The geoelectric precursor signals for the events were recorded on the NS and NE dipoles in Chongming station 42 days, 20 days and 2 days before the earthquakes respectively, in which the station is near the epicenter, and the longest time of persisting period was 9 days. The abnormal variation signals of geoelectric field observed in Nanjing station are all the noises but not the seismic electric signals, in which the station is not near the epicenter; c) Dipole distribution method of common electrode is not good in the multi-dipole observation system of the geoelectric field.

Analyzing cross-correlations between earthquakes and geoelectrical extreme events, measured in a seismic area of Southern Italy

Correlations between geoelectrical extreme events and earthquakes have been investigated by means of the normalized wavelet cross-correlation function (NWCCF) and the cross-periodogram (CP). These methods allow to detect subtle forms of interdependence between sequences of events. In particular, we analyzed the correlation between the sequence of extreme events in geoelectrical signals, measured by the monitoring station Tito, located in a seismic area of southern Italy, and the series of earthquakes occurred in the same area during the 2001–2002. The NWCCF analysis highlights the presence of non-random cross-correlation between the series of geoelectrical anomalous values and the seismicity; the CP analysis reveals a co-fractal behavior between the self-potential extreme events and earthquakes, indicating that both sequences are subject to a common fractal modulation.

Investigating the multifractal properties of geoelectrical signals measured in southern Italy

Multifractal investigation of the time fluctuations in the hourly time variability of geoelectrical signals, measured from January 2001 to September 2002 by four stations installed in Basilicata region (southern Italy) has been performed. Three stations (Giuliano, Marsico and Tito) are located in a seismic area and one (Laterza) in an aseismic area. The set of the multifractal parameters reveals the larger “complexity” of data measured in seismic areas respect to those recorded in aseismic areas, suggesting their potential in discriminating the two types of signals.

Flicker-noise spectroscopy: a new approach to investigate the time dynamics of geoelectrical signals measured in seismic areas

The Flicker-Noise Spectroscopy (FNS) is an innovative method of extracting quantitative dynamical information from time series. The method represents the signal as sequences of irregularities (spikes, jumps, discontinuities of derivatives), derived on the basis of power spectra and structural functions of different orders. By means of this method we investigated one-year hourly geoelectrical data measured during 2002 in the station Giuliano, southern Italy, one of the most seismically active areas of Mediterranean region. The analysis performed seems to reveal the potential of the FNS to identify seismic precursors.

Monofractal and multifractal characterization of geoelectrical signals measured in southern Italy

Fractal tools have been used to characterize the temporal fluctuations in the dynamics of hourly geoelectrical signals, measured from January 2001 to February 2002 by four stations installed in Basilicata region (southern Italy). Three stations (Giuliano, Marsico and Tito) are located in a seismic area, and one (Laterza) in an aseismic area. Monofractal approaches (Lomb Periodogram, Higuchi method and detrended fluctuation analysis) have been used to identify in a wide range of timescales scaling behaviour, that indicates the presence of correlated temporal fluctuations and long-range dependence. The multifractal formalism leads to the identification of a set of parameters, derived from the shape of the multifractal spectrum (the maximum α 0, the asymmetry B and the width W) and measuring the “complexity” of the signals. Furthermore, the multifractal parameters have revealed to well discriminate geoelectrical signals measured in seismic areas from those recorded in aseismic areas.

FLUCTUATION ANALYSIS OF THE HOURLY TIME VARIABILITY IN OBSERVATIONAL GEOELECTRICAL SIGNALS

We investigate, by the Detrended Fluctuation Analysis (DFA), the long-range correlations in the hourly time variability of geoelectrical signals measured by the station Tramutola, located in one of the most seismic area of southern Italy. The DFA power-law exponent, characterizing the temporal fluctuations of these signals, shows significant variation, possibly related with the seismic activity of the area investigated.

1/ fα Fluctuations in geoelectrical signals observed in a seismic area of Southern Italy

Recent studies have shown that many natural systems display temporal fluctuations with long-range power-law correlations, suggesting a fractal geometry of the underlying dynamical system. Four geoelectrical time series, measured in a seismic area of Southern Italy, are investigated by means of spectral tools in order to evidence the existence of power-law correlations. Results show the scaling behaviour for all the signals recorded, pointing to the presence of fractal features expressing a long-term correlation with scaling exponents which indicate stabilizing mechanisms. Furthermore, our findings suggest an observational evidence of correlations between the variation of parameters describing the temporal fluctuations of geoelectrical signals and earthquakes that occurred in the area investigated.

A new approach to investigate the correlation between geoelectrical time fluctuations and earthquakes in a seismic area of southern Italy

We propose a new approach to investigate the possible correlation between electrical signals and earthquakes. Good correlation has been found between the spectral power‐law exponent of geoelectrical signals and the Hurst exponent of the seismicity of the area investigated. A tendency of both parameters to converge toward unity, typical of self‐organized critical dynamics, is evident before the occurrence of the major event recorded in the area during the observation period.

On the time dynamics of geoelectrical signals recorded in a seismic area of Southern Apennine Chain (Italy)

In this work we analyse the hourly geoelectrical time series recorded by means of three stations located in a seismically active area of Southern Apennine Chain (Italy): Tito station (January 1992 – December 1997), Tramutola station (January 1995 – December 1995) and Giuliano station (January 1996 – December 1997). The time dynamics of the geoelectrical time series was investigated to obtain information regarding: i) the stochastic or chaotic behaviour of the time series; ii) the presence of scaling laws in their power spectral density and the estimation of the power-law index; iii) the possible correlation between the temporal variation of the power-law index and the local seismic activity. Autoregressive models and the Lomb Periodogram method have been applied to get the most quantitative information about the time dynamics from geoelectrical signals. Firstly, the predictability of geoelectrical measurements has been investigated using autoregressive models. The procedure is based on two forecasting approaches: the global and the local autoregressive approximation. The comparison of the predictive skill of the two techniques is a strong test to discriminate between low-dimensional chaos and stochastic dynamics. Our findings suggest that the physical system governing the electrical phenomena in active seismic areas is characterized by a stochastic dynamics. In a second step we investigated the stochastic properties of the geolectrical signals searching for scaling laws in the power spectral density, identifying for it a power-law P(f) ∝ lfα, with the scaling exponent α being a typical fingerprint of fractional brownian processes. In this analysis we apply the Lomb Periodogram method, which allows to calculate the power spectral density for time series with missing data. Finally the possible correlation between the time fluctuations of power-law index and the local seismic sequences has been investigated. An interesting coseismic variation of the scaling exponent in power spectra of geoelectrical time series recorded at Tito station has been identified on April 3, 1996. During the same period significant anomalous patterns are indentified in geoelectrical time series measured at Giuliano and Tramutola stations.

Stochastic behaviour and scaling laws in geoelectrical signals measured in a seismic area of southern Italy

SUMMARY We explore the inner dynamics of daily geoelectrical time series measured in a seismic area of the southern Apennine chain (southern Italy). Autoregressive models and the Higuchi fractal method are applied to extract maximum quantitative information about the time dynamics from these geoelectrical signals. First, the predictability of the geoelectrical measurements is investigated using autoregressive models. The procedure is based on two forecasting approaches: the global and the local autoregressive approximations. The first views the data as a realization of a linear stochastic process, whereas the second considers the data points as a realization of a deterministic process, which may be non-linear. Comparison of the predictive skills of the two techniques allows discrimination between low-dimensional chaos and stochastic dynamics. Our findings suggest that the physical systems governing electrical phenomena are characterized by a very large number of degrees of freedom and can be described only with statistical laws. Second, we investigate the stochastic properties of the same geoelectrical signals, searching for scaling laws in the power spectrum. The spectrum fits a power law P( f )3 f ’a, with the scaling exponent a a typical fingerprint of fractional Brownian processes. In this analysis we apply the Higuchi method, which gives a linear relationship between the fractal dimension D S and the spectral power law scaling index a: D S =(3’a)/2. This analysis highlights the stochastic nature of geoelectrical signals recorded in this seismic area of southern Italy.

Candidate precursors: pulse-like geoelectric signals possibly related to recent seismic activity in Japan

Telemetric network observations of pulse-like geoelectric charge signals using a vertical dipole buried under the ground were undertaken at various observation sites over a wide area in Japan from April 1996. From continuous records of the signals during the six months following that, we attempted to select anomalous signals, possibly related to seismic electric activity. Special attention was paid to the elimination of noise resulting from industrial and meteorological electric activity, comparison with other electromagnetic signals in the VLF band and the relation between the precursor period and the distance from the eventual main shock that occurred in Japan. Four candidate precursor electric signals, which were not contaminated by industrial and meteorological electric activity, were then selected, of which the second appeared before the Akita-ken Nairiku-nanbu earthquake swarm, for which the maximum M= 5.9 occurred on 1996 August 11, and the third and fourth before the Chiba-ken Toho-oki earthquake, M= 6.6, on 1996 September 11. A tentative qualitative model explaining why the candidate precursory signal is related to stress building up before an earthquake is presented in terms of the electrification of gases released from fracturing rocks immediately prior to the main shock.

Correction [to “Geoelectric signals in China and the earthquake generation process” by Jean J. Chu, Xietai Gui, Jingan Dai, Chris Marone, Marc W. Spiegelman, Leonardo Seeber, and John G. Armbruster

Correction [to “Geoelectric signals in China and the earthquake generation process” by Jean J. Chu, Xietai Gui, Jingan Dai, Chris Marone, Marc W. Spiegelman, Leonardo Seeber, and John G. Armbruster

Geoelectric signals in China and the earthquake generation process

We present original apparent resistivity records for stations located in the Chinese provinces of Hebei and Sichuan, along with seismicity patterns, fault maps, and limited hydrologic data. These records are part of a 30‐year database of geoelectric signals that have been recorded in China by a nationwide network of more than 100 stations set up by the State Seismological Bureau of the People's Republic of China. The database includes the time period during which the M 7.8 1976 Tangshan and M 7.2 1976 Songpan earthquakes occurred. Resistivity data recorded in and around the epicentral region of the Tangshan event show coherent changes, both temporal and in areal distribution, years and months before and after the earthquakes. A regional change in water table occurred more than 3 years prior to the Tangshan earthquake. The resistivity and water table signals appear to correlate in the 2‐ to 3‐year period prior to the earthquake. Rainfall records from the region around Tangshan, extending to the cities of Beijing and Tianjin, do not appear to account for the resistivity changes. Regional seismicity and active fault patterns in north China indicate that deformation occurs mainly along the borders of large tectonic blocks. The source region for the geoelectric signals appears to lie within a large shear zone, at the edge of a tectonic block undergoing rotation. The Tangshan epicentral area is thus only part of a larger zone of deformation. We suggest that dilational strain associated with the opening of fractures may lower resistivity and water table. For shallow crustal depths, such as those monitored by the Chinese geoelectric network, dilation and resistivity changes are expected to begin at stress levels well below the peak values of the seismic cycle. Our study suggests that in some cases the areal extent of geoelectric signals may be significantly larger than that of the eventual earthquake source dimension. The Chinese geoelectric database offers an opportunity to improve our understanding of possible geoelectric precursors to earthquakes.