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

Helman, Daniel S.

doi:10.1016/j.pepi.2020.106484

Cited by 18 publications

(5 citation statements)

References 119 publications

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“…This rules out mechanisms that rely on abrupt changes to the local stress field that match the stress drop that occurs with seismicity. Likewise, the magnitudes of the observed electric signals at the surface are high (with fields of about 2 x 10 -5 V m -1 ), and events at earthquake-focus depth might need to produce immense signals (10 5 A • m or more) to match observation (Honkura and Kuwata, 1993). Thus mechanisms that occur close to the surface are to be favored (Johnston, 1997;Park et al, 1993;Park, 1996), for example, fluctuations in groudnwater (Varotsos et al, 2019).…”

Section: Criticism Of the Van Methodsmentioning

confidence: 99%

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

Helman¹

2020

Preprint

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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.

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Section: Criticism Of the Van Methodsmentioning

confidence: 99%

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

Helman¹

2020

Preprint

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“…Despite several attempts through theoretical and numerical studies (Mizutani et al 1976;Huang & Ikeya 1998;Huang 2002Huang , 2011aFreund 2010;Huang & Lin 2010a, b;Wang 2020;Hu et al 2023a), as well as laboratory measurements (Jouniaux & Pozzi 1995Lacidogna et al 2011), our understanding of these geoelectric precursors remains inadequate at the present stage (Huang et al 2015). For reviews including pre-earthquake geoelectric anomalies, we recommend readers consult the publications by Lighthill (1996), Uyeda et al (2009), Huang (2011c), Helman (2020), Chen et al (2022), and Zhao et al (2022).…”

Section: Introductionmentioning

confidence: 99%

A Numerical Study of Electrokinetically Generated Pre-Earthquake Geoelectric Fields in Layered Porous Media

Zheng,

Ren,

Ren

et al. 2024

Preprint

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The investigation into the physical mechanisms and behavior of geoelectric fields as potential precursors of earthquakes is a crucial yet challenging task in seismo-electromagnetics. Assuming the electrokinetic effect as a mechanism, we propose a novel numerical modeling algorithm based on the framework of the LAC GRTM to explore the behavior of geoelectric fields in stratified porous media during earthquake preparation. This algorithm incorporates two innovative aspects: (1) employing the Jordan decomposition to address the degeneracy problem encountered in quasi-stationary scenarios, and (2) utilizing digital linear filters for Hankel transforms to conduct the wavenumber integration. The accuracy of the algorithm in computing static displacements in an extremely low porosity half-space model is verified through comparison with analytical solutions. Numerical results from a half-space model demonstrate a strong consistency between the vertical electric field and filtration displacement. Notably, the maximum amplitude of the vertical electric field can reach approximately 2878.8 mV/km, which is detectable by receivers located at considerable distances from the epicenter. In addition, three distinct types of pre-earthquake electric fields are identified: (1) the localized electric field induced by slow P waves, (2) the interface electric responses, and (3) the direct converted electric field from the source. Results from a multi-layer porous model show the significant influence of the water table on the amplitude of the vertical electric field. This can be attributed to the influence of water saturation and permeability on the coefficient that combines the vertical electric field and the vertical filtration displacement.We also analyze the temporal evolution of different fields during earthquake preparation, which demonstrates a robust correlation between the temporal characteristics of pore pressure and that of the vertical electric field. This indicates that the vertical electric field offers an effective means to detect pore pressure evolution during earthquake preparation. Its sensitivity to the strike, rake, and dip angles of potential faults indicates its potential for determining fault geometry related to an impending earthquake. Furthermore, fluctuations in displacements enable a rough estimation of variations in stress and confining pressure. These observations underscore the advantage of integrating geoelectric precursor data with continuous displacement observations to enhance our understanding of earthquake preparation mechanisms.

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“…During these last decades, several thousands of scientific publications on various lithospheric, atmospheric and ionospheric parameters, proposed as potential seismic precursors, have also been produced. Here is a selection of the main reviews on the subject: [4][5][6][7][8][9][10][11][12], the last five, whose first authors are respectively Helman, Sokorin, Picozza, Conti and Chen are the most recent (after 2020) and therefore contain the most complete and updated information.…”

Section: Introductionmentioning

confidence: 99%

Optimal Setting of Earthquake-Related Ionospheric TEC (Total Electron Content) Anomalies Detection Methods: Long-Term Validation over the Italian Region

et al. 2023

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Over the last decade, thanks to the availability of historical satellite observations that have begun to be significantly large and thanks to the exponential growth of artificial intelligence techniques, many advances have been made in the detection of geophysical parameters such as seismic-related anomalies. In this study, the variations of the ionospheric Total Electron Content (TEC), one of the main parameters historically proposed as a seismic-connected indicator, are analyzed. To make a statistically robust analysis of the complex phenomena involved, we propose a completely innovative machine-learning approach developed in the R programming language. Through this approach, an optimal setting of the multitude of methodological inputs currently proposed for the detection of ionospheric anomalies is performed. The setting is optimized by analyzing, for the first time, multi-year—mostly twenty-year—time series of TEC satellite data measured by global navigation satellite systems (GNSS) over the Italian region, matched with the corresponding multi-year time series of seismic events. Seismic events including all the countries of the Mediterranean area, up to Turkey, are involved in the analysis. Tens of thousands of possible combinations of input methodological parameters are simulated and classified according to pre-established criteria. Several inputs examined return clear results. These results combined with each other highlight the presence of anomalous seismic-related sequences that have an extremely low probability of having been detected randomly (up to 2 out of 1 million). The anomalies identified represent the most anomalous behaviors of the TEC recorded during the entire period under investigation (e.g., 20 years). Some of the main conclusions are that, at mid-latitudes, ① the detection of seismic-TEC anomalies can be more efficient looking for punctual rather than persistent phenomena; ② the optimal thresholds for the identification of co-seismic anomalies can assume different values depending on type of anomaly (positive or negative) and type of observation; ③ single GNSS receiver data can be useful for capturing local earthquake-ionospheric effects and Global Ionospheric Maps (GIM) data can be functional in detecting large-scale earthquake-ionospheric effects; ④ earthquakes deeper than 50 km are less likely to affect the ionosphere.

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

Cited by 18 publications

References 119 publications

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

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

A Numerical Study of Electrokinetically Generated Pre-Earthquake Geoelectric Fields in Layered Porous Media

Optimal Setting of Earthquake-Related Ionospheric TEC (Total Electron Content) Anomalies Detection Methods: Long-Term Validation over the Italian Region

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