The source scaling of swarm-genic slow slip events

2020 ◽  
Author(s):  
Luigi Passarelli ◽  
Eleonora Rivalta ◽  
Paul Antony Selvadurai ◽  
Sigurjón Jónsson
Keyword(s):  
Subduction Zones ◽  
Volcanic Tremor ◽  
Slow Slip ◽  
Aseismic Slip ◽  
Slow Slip Events ◽  
Seismic Strain ◽  
Source Scaling ◽  
Strain Release ◽  
Seismic Strain Release ◽  
Seismic Moment Release

<p>Slow slip events (SSEs) are slow fault ruptures that do not excite detectable seismic waves although they are often accompanied by some forms of seismic strain release, e.g., clusters of low- and very-low frequency earthquakes, and/or episodic or continuous non-volcanic tremor (i.e. tremor-genic SSEs) and earthquake swarms (swarm-genic SSEs). At subduction zones, increasing evidence indicates that aseismic slip and seismic strain release in the form of non-volcanic tremor represent the evolution of slow fracturing. In addition, aseismic slip rate modulates the release of seismic slip during tremor-genic SSEs. No general agreement has been reached, however, on whether source duration-moment scaling of SSEs is linear or follows that of ordinary earthquakes (cubic). To date, investigations on the source scaling has been based on global compilations of tremor-genic SSEs while no studies have looked into the source scaling of swarm-genic SSEs.</p><p>We present the first compilation of source parameters of swarm-genic slow slip events occurring in subduction zones as well as in extensional, transform and volcanic environments. We find for swarm-genic SSEs a power-law scaling of aseismic to seismic moment release during episodes of slow slip that is independent of the tectonic setting. The earthquake productivity, i.e., the ratio of seismic to aseismic moment released, of shallow SSEs is on average higher than that of deeper ones and scales inversely with rupture velocity. The inferred source scaling indicates a strong interplay between the evolution of aseismic slip and the associated seismic response of the host medium and that swarm-genic SSEs and tremor-genic SSEs arise from similar fracturing mechanisms. Depth dependent rheological conditions modulated by fluid pore pressure, temperature and density of asperities appear to be the main controls on the scaling. Large SSEs have systematically high earthquake productivity suggesting static stress transfer as an additional factor in triggering swarms of ordinary earthquakes. Our data suggest that during the slow slip evolution the proportion of seismic strain release is always smaller than the aseismic part although transient changes in stress and fault rheology imparted by swarm-genic SSEs can lead to delayed triggering of major and devastating earthquakes like in the Tohoku, Iquique and L’Aquila cases. The evidence of source scaling reported here will help constraining theoretical models of SSEs rupture propagation and seismic hazard assessments that should take into account the new scaling between aseismic and seismic moment release. </p>

scholarly journals The source scaling and seismic productivity of slow slip transients

2021 ◽  
Vol 7 (32) ◽  
pp. eabg9718
Author(s):  
Luigi Passarelli ◽  
Paul Antony Selvadurai ◽  
Eleonora Rivalta ◽  
Sigurjón Jónsson
Keyword(s):  
Seismic Moment ◽  
Source Parameters ◽  
Earthquake Swarms ◽  
Slow Slip ◽  
Aseismic Slip ◽  
Slow Slip Events ◽  
Source Scaling ◽  
Strain Release ◽  
Seismic Moment Release ◽  
Physical Phenomena

Slow slip events (SSEs) represent a slow faulting process leading to aseismic strain release often accompanied by seismic tremor or earthquake swarms. The larger SSEs last longer and are often associated with intense and energetic tremor activity, suggesting that aseismic slip controls tremor genesis. A similar pattern has been observed for SSEs that trigger earthquake swarms, although no comparative studies exist on the source parameters of SSEs and tremor or earthquake swarms. We analyze the source scaling of SSEs and associated tremor- or swarm-like seismicity through our newly compiled dataset. We find a correlation between the aseismic and seismic moment release indicating that the shallower SSEs produce larger seismic moment release than deeper SSEs. The scaling may arise from the heterogeneous frictional and rheological properties of faults prone to SSEs and is mainly controlled by temperature. Our results indicate that similar physical phenomena govern tremor and earthquake swarms during SSEs.

Afterslip and slow slip events in the postseismic deformation of the 2016 Pedernales earthquake, Ecuador

2020 ◽  
Author(s):  
Frederique Rolandone ◽  
Jean-Mathieu nocquet ◽  
Patricia Mothes ◽  
Paul Jarrin ◽  
Mathilde Vergnolle
Keyword(s):  
Subduction Zones ◽  
Postseismic Deformation ◽  
Slow Slip ◽  
Aseismic Slip ◽  
Plate Interface ◽  
Slow Slip Events ◽  
North East ◽  
Rupture Area ◽  
Slip Event ◽  
Seismic Swarms

<p>In subduction zones, slip along the plate interface occurs in various modes including earthquakes, steady slip, and transient accelerated aseismic slip during either Slow Slip Events (SSE) or afterslip. We analyze continuous GPS measurements along the central Ecuador subduction segment to illuminate how the different slip modes are organized in space and time in the zone of the 2016 Mw 7.8 Pedernales earthquake. The early post-seismic period (1 month after the earthquake) shows large and rapid afterslip developing at discrete areas of the megathrust and a slow slip event remotely triggered (∼100 km) south of the rupture of the Pedernales earthquake. We find that areas of large and rapid early afterslip correlate with areas of the subduction interface that had hosted SSEs in years prior to the 2016 earthquake. Areas along the Ecuadorian margin hosting regular SSEs and large afterslip had a dominant aseismic slip mode that persisted throughout the earthquake cycle during several years and decades: they regularly experienced SSEs during the interseismic phase, they did not rupture during the 2016 Pedernales earthquake, they had large aseismic slip after it. Four years after the Pedernales earthquake, postseismic deformation is still on-going. Afterslip and SSEs are both involved in the postseimsic deformation. Two large aftershocks (Mw 6.7 & 6.8) occurred after the first month of postseismic deformation in May 18, and later in July 7 2016 two other large aftershocks (Mw 5.9 & 6.3) occurred, all were located north east of the rupture. They may have triggered their own postseismic deformation. Several seismic swarms were identified south and north of the rupture area by a dense network of seismic stations installed during one year after the Pedernales earthquakes, suggesting the occurrence of SSEs. Geodetically, several SSEs were detected during the postseismic deformation either in areas where no SSEs were detected previously, or in areas where regular seismic swarms and repeating earthquakes were identified. The SSEs may have been triggered by the stress increment due to aftershocks or due to afterslip.</p>

Episodic fluid pressure cycling controls the interplay between Slow Slip Events and Large Megathrust Earthquakes

2020 ◽  
Author(s):  
Claudio Petrini ◽  
Luca Dal Zilio ◽  
Taras Gerya
Keyword(s):  
Fluid Flow ◽  
Subduction Zones ◽  
Finite Difference Methods ◽  
Fluid Pressure ◽  
Slow Slip ◽  
Aseismic Slip ◽  
Slow Slip Events ◽  
Megathrust Earthquakes ◽  
Pressure Cycling ◽  
Crustal Stresses

<p>Slow slip events (SSEs) are part of a spectrum of aseismic processes that relieve tectonic stress on faults. Their occurrence in subduction zones have been suggested to trigger megathrust earthquakes due to perturbations in fluid pressure. However, examples to date have been poorly recorded and physical observations of temporal fluid pressure fluctuations through slow slip cycles remain elusive. Here, we use a newly developed two-phase flow numerical model — which couples solid rock deformation and pervasive fluid flow — to show how crustal stresses and fluid pressures within subducting megathrust evolve before and during slow slip and regular events. This unified 2D numerical framework couples inertial mechanical deformation and fluid flow by using finite difference methods, marker-in-cell technique, and poro-visco-elasto-plastic rheologies. Furthermore, an adaptive time stepping allows the correct resolution of both long- and short-time scales, ranging from years to milliseconds during the dynamic propagation of earthquake rupture.</p><p>Here we show how permeability and its spatial distribution control the degree of locking along the megathrust interface and the interplay between seismic and aseismic slip. While a constant permeability leads to more regular seismic cycles, a depth dependent permeability contributes substantially to the development of two distinct megathrust zones: a shallow, locked seismogenic zone and a deep, narrow aseismic segment characterized by SSEs. Furthermore, we show that without requiring any specific friction law, our model shows that permeability, episodic stress transfer and fluid pressure cycling control the predominant slip mode along the subduction megathrust. Specifically, we find that the up-dip propagation of episodic SSEs systematically decreases the fault strength due to a continuous accumulation and release of fluid pressure within overpressured subducting interface, thus affecting the timing of large megathrust earthquakes. These results contribute to improve our understanding of the physical driving forces underlying the interplay between seismic and aseismic slip, and demonstrate that slow slip events may prove useful for short-term earthquake forecasts.</p>

scholarly journals Some characteristics of the seismicity of the Tyrrhenian Sea Region

2010 ◽  
Vol 27 (1-2) ◽  
Author(s):  
S. MESZAROS ◽  
P. HEDERVARI
Keyword(s):  
South America ◽  
Elastic Strain ◽  
Seismic Events ◽  
Tyrrhenian Sea ◽  
Seismic Belt ◽  
Maximum Value ◽  
Seismic Strain ◽  
Strain Release ◽  
Seismic Strain Release ◽  
Global Tectonics

In the first p a r t of the paper the seismic strain release of the T y r r h e n i a n Sea Region (including Italy), as the function of time, is examined on the basis of t h e d a t a of the e a r t h q u a k e s t h a t took place f r om 1901.01.01 to 1970.12.31, between the northern l a t i t u d e s of 34° and 44° and between the eastern longitudes of 8° and 18.5°, respectively. All registered shocks with a R i c h t e r - m a g n i t u d e of 5.5 or over it were considered, i n d e p e n d e n t l y f r om t h e focal d e p t h . Three periods were recognized in the a c t i v i t y ; t h e lengths of which are not t h e same, however. I n the second p a r t the elastic strain release in accordance with the focal d e p t h of t h e same e a r t h q u a k e s is t r e a t e d briefly. It was found t h at t h e t o t a l strain-release had a maximum value in t h e depth between 0 and 74 kms and there was a minimum between the depth of 300 and 524 kins with an interval between 375 and 449 kms within which no earthquakes occurred at all. The general p a t t e r n of the d i s t r i b u t i o n of seismicity as t h e f u n c t i o n of hypocentral d e p t h reminds to the well-known picture, one can experience in other regions where i n t e r m e d i a t e and deep shocks occur. This s t a t e m e n t is consistent w i t h t h e idea, according to which t h e seismicity of t h e Tyrrhenian Sea Region can be discussed and explained in t h e light of t h e theory of new global tectonics. F i n a l l y , in the t h i r d p a r t of the study, the authors have s t a t e d t h at in some cases multiple events occurred b e n e a t h t h e Tyrrhenian Sea Region. Such multiple seismic events were detected in the case of other areas, such as the Fiji-Tonga-Kermadec Region, the seismic belt of South America etc., — but, according to the knowledge of t h e authors, this is t h e first occasion when multiple seismic events are demonstrated in the Tyrrhenian Sea Region.

Systematic characterization of slow slip events along the Mexican subduction zone from 2000 to 2019

2020 ◽  
Author(s):  
Mathilde Radiguet ◽  
Ekaterina Kazachkina ◽  
Louise Maubant ◽  
Nathalie Cotte ◽  
Vladimir Kostoglodov ◽  
...  
Keyword(s):  
Subduction Zone ◽  
Subduction Zones ◽  
Scaling Laws ◽  
Temporal Evolution ◽  
Seismic Gap ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Grace Data ◽  
Spatio Temporal ◽  
Mexican Subduction Zone

<p>Slow slip events (SSEs) represent a significant mechanism of strain release along several subduction zones, and understanding their occurrence and relations with major earthquake asperities is essential for a comprehensive understanding of the seismic cycle. Here, we focus on the Mexican subduction zone, characterized by the occurrence of recurrent large slow slip events (SSEs), both in the Guerrero region, where the SSEs are among the largest observed worldwide, and in the Oaxaca region, where smaller, more frequent SSEs occur. Up to now, most slow slip studies in the Mexican subduction zone focused either on the detailed analysis of a single event, were limited to a small area (Guerrero or Oaxaca), or were limited to data before 2012 [e.g.1-4]. In this study, our aim is to build an updated and consistent catalog of major slow slip events in the Guerrero-Oaxaca region.</p><p>We use an approach similar to Michel et al. 2018 [5]. We analyze the GPS time series from 2000 to 2019 using Independent Component Analysis (ICA), in order to separate temporally varying sources of different origins (seasonal signals, SSEs and afterslip of major earthquakes). We are able to isolate a component corresponding to seasonal loading, which matches the temporal evolution of displacement modeled from the GRACE data. The sources (independent components) identified as tectonic sources of deep origin are inverted for slip on the subduction interface. We thus obtain a model of the spatio-temporal evolution of aseismic slip on the subduction interface over 19 years, from which we can isolate around 30 individual slow slip events of M<sub>w </sub>> 6.2.</p><p> The obtained catalog is coherent with previous studies (in terms of number of events detected, magnitude and duration) which validates the methodology. The observed moment-duration scaling is close to M<sub>0</sub>~T<sup>3 </sup>as recently suggested by Michel [6] for Cascadia SSEs, and our study extends the range of magnitude considered in their analysis. Finally, we also investigate the spatio-temporal relations between the SSEs occurring in the adjacent regions of Guerrero and Oaxaca, and their interaction with local and distant earthquakes.</p><p> </p><p>References:</p><ol><li>Kostoglodov, V. et al. A large silent earthquake in the Guerrero seismic gap, Mexico. Geophys. Res. Lett <strong>30</strong>, 1807 (2003).</li> <li>Graham, S. et al. Slow Slip History for the Mexico Subduction Zone: 2005 Through 2011. Pure and Applied Geophysics 1–21 (2015). doi:10.1007/s00024-015-1211-x</li> <li>Larson, K. M., Kostoglodov, V. & Shin’ichi Miyazaki, J. A. S. The 2006 aseismic slow slip event in Guerrero, Mexico: New results from GPS. Geophys. Res. Lett. <strong>34</strong>, L13309 (2007).</li> <li>Radiguet, M. et al. Slow slip events and strain accumulation in the Guerrero gap, Mexico. J. Geophys. Res. <strong>117</strong>, B04305 (2012).</li> <li>Michel, S., Gualandi, A. & Avouac, J.-P. Interseismic Coupling and Slow Slip Events on the Cascadia Megathrust. Pure Appl. Geophys. (2018). doi:10.1007/s00024-018-1991-x</li> <li>Michel, S., Gualandi, A. & Avouac, J. Similar scaling laws for earthquakes and Cascadia slow-slip events. Nature <strong>574, </strong>522–526 (2019) doi:10.1038/s41586-019-1673-6</li> </ol><p> </p>

Towards assessing the link between slow slip and seismicity with a Deep Learning approach

2020 ◽  
Author(s):  
Giuseppe Costantino ◽  
Mauro Dalla Mura ◽  
David Marsan ◽  
Sophie Giffard-Roisin ◽  
Mathilde Radiguet ◽  
...  
Keyword(s):  
Deep Learning ◽  
Subduction Zones ◽  
Surface Deformation ◽  
Short Term Memory ◽  
Ground Deformation ◽  
Japan Meteorological Agency ◽  
Joint Analysis ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Seismicity Rate

<p>The deployment of increasingly dense geophysical networks in many geologically active regions on the Earth has given the possibility to reveal deformation signals that were not detectable beforehand. An example of these newly discovered signals are those associated with low-frequency earthquakes, which can be linked with the slow slip (aseismic slip) of faults. Aseismic fault slip is a crucial phenomenon as it might play a key role in the precursory phase before large earthquakes (in particular in subduction zones), during which the seismicity rate grows as well as does the ground deformation. Geodetic measurements, e.g. the Global Positioning System (GPS), are capable to track surface deformation transients likely induced by an episode of slow slip. However, very little is known about the mechanisms underlying this precursory phase, in particular regarding to how slow slip and seismicity relate.</p><p>The analysis done in this work focuses on recordings acquired by the Japan Meteorological Agency in the Boso area, Japan. In the Boso peninsula, interactions between seismicity and slow slip events can be observed over different time spans: regular slow slip events occur every 4 to 5 years, lasting about 10 days, and are associated with a burst of seismicity (Hirose et al. 2012, 2014, Gardonio et al. 2018), whereas an accelerated seismicity rate has been observed over decades that is likely associated with an increasing shear stress rate (i.e., tectonic loading) on the subduction interface (Ozawa et al. 2014, Reverso et al. 2016, Marsan et al. 2017).</p><p>This work aims to explore the potential of  Deep Learning  for better characterizing the interplay between seismicity and ground surface deformation. The analysis is based on a data-driven approach for building a model for assessing if a link seismicity – surface deformation exists and to characterize the nature of this link. This has potentially strong implications, as (small) earthquakes are the prime observable, so that better understanding the seismicity rate response to potentially small slow slip (so far undetected by GPS) could help monitoring those small slow slip events. The statistical problem is expressed as a regression between some features extracted from the seismic data and the GPS displacements registered at one or more stations.</p><p>The proposed method, based on a Long-Short Term Memory (LSTM) neural network, has been designed in a way that it is possible to estimate which features are more relevant in the estimation process. From a geophysical point of view, this can provide interesting insights for validating the results, assessing the robustness of the algorithms and giving insights on the underlying process. This kind of approach represents a novelty in this field, since it opens original perspectives for the joint analysis of seismic / aseismic phenomena with respect to traditional methods based on more classical geophysical data exploration.</p>

scholarly journals Short-Term Interaction between Silent and Devastating Earthquakes in Mexico

2020 ◽  
Author(s):  
Víctor Cruz-Atienza ◽  
Josué Tago ◽  
Carlos Villafuerte ◽  
Meng Wei ◽  
Ricardo Garza-Girón ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Seismic Waves ◽  
Regional Scale ◽  
Slow Slip ◽  
Aseismic Slip ◽  
Short Term ◽  
Plate Interface ◽  
Slow Slip Events ◽  
Large Earthquakes

Abstract Triggering of large earthquakes on a fault that hosts aseismic slip or, conversely, triggering of slow slip events (SSE) by passing seismic waves involves seismological questions with major hazard implications. Just a few observations plausibly suggest that such interactions actually happen in nature. In this study we show that three recent devastating earthquakes in Mexico are likely related to SSEs, describing a cascade of events interacting with each other on a regional scale via quasi-static and/or dynamic perturbations. Such interaction seems to be conditioned by the transient memory of Earth materials subject to the “traumatic” stressing produced by the seismic waves of the great Mw8.2 Tehuantepec earthquake, which strongly disturbed the aseismic beating over a 650 km long segment of the subduction plate interface. Our results imply that seismic hazard in large populated areas is a short-term evolving function of seismotectonic processes that are often observable.

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