Current challenges for preseismic electromagnetic emissions: shedding light from micro-scale plastic flow, granular packings, phase transitions and self-affinity notion of fracture process

Are there credible electromagnetic (EM) EQ precursors? This a question debated in the scientific community and there may be legitimate reasons for the critical views. The negative view concerning the existence of EM precursors is enhanced by features that accompany their observation which are considered as paradox ones, namely, these signals: (i) are not observed at the time of EQs occurrence and during the aftershock period, (ii) are not accompanied by large precursory strain changes, (iii) are not accompanied by simultaneous geodetic or seismological precursors and (v) their traceability is considered problematic. In this work, the detected candidate EM precursors are studied through a shift in thinking towards the basic science findings relative to granular packings, micron-scale plastic flow, interface depinning, fracture size effects, concepts drawn from phase transitions, self-affine notion of fracture and faulting process, universal features of fracture surfaces, recent high quality laboratory studies, theoretical models and numerical simulations. Strict criteria are established for the definition of an emerged EM anomaly as a preseismic one, while, precursory EM features, which have been considered as paradoxes, are explained. A three-stage model for EQ generation by means of preseismic fracture-induced EM emissions is proposed. The claim that the observed EM precursors may permit a real-time and step-by-step monitoring of the EQ generation is tested

On the puzzling feature of the silence of precursory electromagnetic emissions

It has been suggested that fracture-induced MHz-kHz electromagnetic (EM) emissions, which emerge from a few days up to a few hours before the main seismic shock occurrence permit a real-time monitoring of the damage process during the last stages of earthquake preparation, as it happens at the laboratory scale. Despite fairly abundant evidence, EM precursors have not been adequately accepted as credible physical phenomena. These negative views are enhanced by the fact that certain 'puzzling features' are repetitively observed in candidate fracture-induced pre-seismic EM emissions. More precisely, EM silence in all frequency bands appears before the main seismic shock occurrence, as well as during the aftershock period. Actually, the view that 'acceptance of 'precursive' EM signals without convincing co-seismic signals should not be expected' seems to be reasonable. In this work we focus on this point. We examine whether the aforementioned features of EM silence are really puzzling ones or, instead, reflect well-documented characteristic features of the fracture process, in terms of: universal structural patterns of the fracture process, recent laboratory experiments, numerical and theoretical studies of fracture dynamics, critical phenomena, percolation theory, and micromechanics of granular materials. Our analysis shows that these features should not be considered puzzling.Comment: arXiv admin note: text overlap with arXiv:cond-mat/0603542 by other author

Critical features in electromagnetic anomalies detected prior to the L'Aquila earthquake

Electromagnetic (EM) emissions in a wide frequency spectrum ranging from kHz to MHz are produced by opening cracks, which can be considered as the so-called precursors of general fracture. We emphasize that the MHz radiation appears earlier than the kHz in both laboratory and geophysical scale. An important challenge in this field of research is to distinguish characteristic epochs in the evolution of precursory EM activity and identify them with the equivalent last stages in the earthquake (EQ) preparation process. Recently, we proposed the following two epochs/stages model: (i) The second epoch, which includes the finally emerged strong impulsive kHz EM emission is due to the fracture of the high strength large asperities that are distributed along the activated fault sustaining the system. (ii) The first epoch, which includes the initially emerged MHz EM radiation is thought to be due to the fracture of a highly heterogeneous system that surrounds the family of asperities. A catastrophic EQ of magnitude Mw = 6.3 occurred on 06/04/2009 in central Italy. The majority of the damage occurred in the city of L'Aquila. Clear kHz - MHz EM anomalies have been detected prior to the L'Aquila EQ. Herein, we investigate the seismogenic origin of the detected MHz anomaly. The analysis in terms of intermittent dynamics of critical fluctuations reveals that the candidate EM precursor: (i) can be described in analogy with a thermal continuous phase transition; (ii) has anti-persistent behaviour. These features suggest that the emerged candidate precursor could be triggered by microfractures in the highly disordered system that surrounded the backbone of asperities of the activated fault. We introduce a criterion for an underlying strong critical behavior.Comment: 8 pages, 6 figure

Forecasting the Preparatory Phase of Induced Earthquakes by Recurrent Neural Network

Earthquakes prediction is considered the holy grail of seismology. After almost a century of efforts without convincing results, the recent raise of machine learning (ML) methods in conjunction with the deployment of dense seismic networks has boosted new hope in this field. Even if large earthquakes still occur unanticipated, recent laboratory, field, and theoretical studies support the existence of a preparatory phase preceding earthquakes, where small and stable ruptures progres- sively develop into an unstable and confined zone around the future hypocenter. The problem of recognizing the preparatory phase of earthquakes is of critical importance for mitigating seismic risk for both natural and induced events. Here, we focus on the induced seismicity at The Geysers geothermal field in California. We address the preparatory phase of M~4 earthquakes identification problem by developing a ML approach based on features computed from catalogues, which are used to train a recurrent neural network (RNN). We show that RNN successfully reveal the preparation of M~4 earthquakes. These results confirm the potential of monitoring induced microseismicity and should encourage new research also in predictability of natural earthquakes

Nowcasting ETAS Earthquakes: Information Entropy of Earthquake Catalogs

Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes can be computed using Receiver Operating Characteristic (ROC) methods. Furthermore, analysis of the Shannon information content of the earthquake catalogs has been used to show that there is information contained in the catalogs, and that it can vary in time. So an important question remains, where does the information originate? In this paper, we examine this question using statistical simulations of earthquake catalogs computed using Epidemic Type Aftershock Sequence (ETAS) simulations. ETAS earthquake simulations are currently in widespread use for a variety of tasks, in modeling, analysis and forecasting. After examining several of the standard ETAS models, we propose a version of the ETAS model that conforms to the standard ETAS statistical relations of magnitude-frequency scaling, aftershock scaling, Bath's law, and the productivity relation, but with an additional property. We modify the model to introduce variable non-Poisson aftershock clustering, inasmuch as we test the hypothesis that the information in the catalogs originates from aftershock clustering. We find that significant information in the catalogs arises from the non-Poisson aftershock clustering, implying that the common practice of de-clustering catalogs may remove information that would otherwise be useful in forecasting and nowcasting. We also show that the nowcasting method provides similar results with the the ETAS models as it does with observed seismicity.Comment: 17 pages, 3 figures, 1 tabl

Application of Artificial Intelligence in predicting earthquakes: state-of-the-art and future challenges

Predicting the time, location and magnitude of an earthquake is a challenging job as an earthquake does not show specific patterns resulting in inaccurate predictions. Techniques based on Artificial Intelligence (AI) are well known for their capability to find hidden patterns in data. In the case of earthquake prediction, these models also produce a promising outcome. This work systematically explores the contributions made to date in earthquake prediction using AI-based techniques. A total of 84 scientific research papers, which reported the use of AI-based techniques in earthquake prediction, have been selected from different academic databases. These studies include a range of AI techniques including rule-based methods, shallow machine learning and deep learning algorithms. Covering all existing AI-based techniques in earthquake prediction, this paper provides an account of the available methodologies and a comparative analysis of their performances. The performance comparison has been reported from the perspective of used datasets and evaluation metrics. Furthermore, using comparative analysis of performances the paper aims to facilitate the selection of appropriate techniques for earthquake prediction. Towards the end, it outlines some open challenges and potential research directions in the field

Scaling similarities of multiple fracturing of solid materials

It has recently reported that electromagnetic flashes of low-energy <IMG WIDTH='12' HEIGHT='29' ALIGN='MIDDLE' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img1.gif' ALT='$gamma$'>-rays emitted during multi-fracturing on a neutron star, and electromagnetic pulses emitted in the laboratory by a disordered material subjected to an increasing external load, share distinctive statistical properties with earthquakes, such as power-law energy distributions (Cheng et al., 1996; Kossobokov et al., 2000; Rabinovitch et al., 2001; Sornette and Helmstetter, 2002). The neutron starquakes may release strain energies up to <IMG WIDTH='32' HEIGHT='16' ALIGN='BOTTOM' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img2.gif' ALT='$10^{46}$'>erg, while, the fractures in laboratory samples release strain energies approximately a fraction of an erg. An earthquake fault region can build up strain energy up to approximately <IMG WIDTH='32' HEIGHT='16' ALIGN='BOTTOM' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img3.gif' ALT='$10^{26}$'>erg for the strongest earthquakes. Clear sequences of kilohertz-megahertz electromagnetic avalanches have been detected from a few days up to a few hours prior to recent destructive earthquakes in Greece. A question that arises effortlessly is if the pre-seismic electromagnetic fluctuations also share the same statistical properties. Our study justifies a positive answer. Our analysis also reveals 'symptoms' of a transition to the main rupture common with earthquake sequences and acoustic emission pulses observed during laboratory experiments (Maes et al., 1998)

Shaking earth: Non-linear seismic processes and the second law of thermodynamics: A case study from Canterbury (New Zealand) earthquakes

We would like to express our gratitude to GeoNet for making available the data used in this work. This work was partially sup-ported by the RNM104 and RNM194 (Research Groups belonging to Junta de Andalucia, Spain) , the Spanish National Projects [grant project PID2019-109608GB-I00] , and the Junta de Andalucia Project [grant project A-RNM-421-UGR18] . English language editing was performed by Tornillo Scientific.Earthquakes are non-linear phenomena that are often treated as a chaotic natural processes. We propose the use of the Second Law of Thermodynamics and entropy, H, as an indicator of the equilibrium state of a seismically active region (a seismic system). In this sense, in this paper we demonstrate the exportability of first principles (e.g., thermodynamics laws) to others scientific fields (e.g., seismology). We suggest that the relationship between increasing H and the occurrence of large earthquakes reflects the irreversible transition of a system. From this point of view, a seismic system evolves from an unstable initial state (due to external stresses) to a state of reduced stress after an earthquake. This is an irreversible transition that entails an increase in entropy. In other words, a seismic system is in a metastable situation that can be characterised by the Second Law of Thermodynamics. We investigated two seismic episodes in the Canterbury area of New Zealand: the 2010 Christchurch earthquake (M = 7.2) and the 2016 Kaikoura earthquake (M = 7.8). The results are remarkably in line with our theoretical forecasts. In other words, an earthquake, understood as an irreversible transition, must results in an increase in entropy.Research Groups belonging to Junta de Andalucia, Spain RNM104- RNM194Spanish National Projects PID2019-109608GB-I00Junta de Andalucia A-RNM-421-UGR1