Low-frequency Earthquakes Research Articles

An adaptive 6-dimensional floating-search multi-station seismic-event detector (A6-DFMSD) and its application to low-frequency earthquakes in the East Eifel Volcanic Field, Germany

We introduce a seismic event detector that applies signal analysis in the time and frequency domains. Signals are searched for with matching coincidences at neighbouring recording stations in space and time. No a priori waveform information is needed for the Adaptive 6-Dimensional Floating-search Multi-station Seismic-event Detector (A6-DFMSD). It combines a short / long time average algorithm (STA/LTA), frequency range selection, energy envelope matching, and backprojection techniques to find a robust detection model. As a challenging test example, the new detector is tuned and applied to a dataset with five months of microearthquake (ML < 2) recordings in the East Eifel Volcanic Field (EEVF), Germany. There, both magmatic and tectonic earthquakes occur in a depth range between 3 km and 43 km. A6-DFMSD detected 4.3 times as many events as were already known and it discovered a previously unknown event cluster. After manual localization and classification of the events, we show that A6-DFMSD finds events of different origins: tectonic, magmatic, atmospheric, and anthropogenic. In particular, low-frequency (LF) earthquakes of magmatic origin with a complicated waveform coda are very well identified. We suggest that seismological networks monitoring local seismicity in similar target zones would benefit from the use of A6-DFMSD to allow the detection of a wide range of different seismic signals.

Detection of Hidden Low-Frequency Earthquakes in Southern Vancouver Island with Deep Learning

Low-frequency earthquakes (LFEs) are small-magnitude earthquakes that are depleted in high-frequency content relative to traditional earthquakes of the same magnitude. These events occur in conjunction with slow slip events (SSEs) and can be used to infer the space and time evolution of SSEs. However, because LFEs have weak signals, and the methods used to identify them are computationally expensive, LFEs are not routinely cataloged in most places. Here, we develop a deep-learning model that learns from an existing LFE catalog to detect LFEs in 14 years of continuous waveform data in southern Vancouver Island. The result shows significant increases in detection rates at individual stations. We associate the detections and locate them using a grid search approach in a 3D regional velocity model, resulting in over 1 million LFEs during the performing period. Our resulting catalog is consistent with a widely used tremor catalog during periods of large-magnitude SSEs. However, there are time periods where it registers far more LFEs than the tremor catalog. We highlight a 16-day period in May 2010, when our model detects nearly 3,000 LFEs, whereas the tremor catalog contains only one tremor detection in the same region. This suggests the possibility of hidden small-magnitude SSEs that are undetected by current approaches. Our approach improves the temporal and spatial resolution of the LFE activities and provides new opportunities to understand deep subduction zone processes in this region.

Deep plutonic bodies over low-frequency earthquakes revealed from receiver-side Green's functions

Seismological heterogeneity in subduction zones provides insights into slow earthquakes and potential megathrust earthquakes. Studies at the Kii Peninsula in the Nankai subduction zone suggest that there are high-density and high-velocity plutonic bodies in the accretionary prism over the subducting slab, potentially influencing megathrust earthquakes. The lateral variation of heterogeneity and the spatial extent of plutonic bodies remain to be investigated well. Our passive-source imaging of receiver-side Green's functions, from widely distributed campaign seismic observations, reveals a sharp negative S-wave velocity contrast on the top surface of the subducting Philippine Sea plate common to all along-dip profiles and a positive phase tilted upward in the forearc crust. The low permeability of the forearc crust prevents the infiltration of slab-dehydrated fluid further into the upper crust. In the western area, we also found positive phases tilted upward in the forearc crust. The negative phase extends towards the deeper extent of slow-earthquake sources. Meanwhile, the positive phase likely represents the top surface of plutonic rocks of the Kumano and Ohmine plutons that span all the way down to the plate interface. Together with observations of gravity anomaly, intraslab seismicity, and seismic tomography, our interpretation supports the presence of plutonic bodies which extend deep beneath the forearc crust as well as laterally over the subducting PHS slab, rather than a serpentinized mantle wedge. The upper plate is generally low in permeability, but areas with localized high permeability may exist on the updip side of tremor sources. This condition, wherein fluid can infiltrate upwards locally, may maintain the relatively less active slow earthquakes in the western area. The lateral variation of the upper-plate lithology likely influences fluid processes and slow earthquake activities.

Fault strength, healing and stability in the Nankai Trough accretionary prism off Kii Peninsula, Japan, as illustrated by friction experiments on gouge of a cored sample

In order to investigate fault strength, healing and stability in the Nankai Trough accretionary prism off Kii Peninsula, Japan, we conducted two series of triaxial friction experiments on gouge of a silty-claystone sample cored from 2183.6 mbsf (meters below seafloor) at IODP Site C0002, at confining pressure (Pc), pore-water pressure (PH2O) and temperature (T) conditions simulating those in situ at 1000–6000 mbsf there; rate-stepping tests at axial displacement rates (Vaxial) changed stepwise among 0.1, 1 and 10 μm/s, and slide-hold-slide tests at Vaxial = 1 μm/s with hold time (th) ranging from 10 to 104 s.Experimentally determined steady-state and static friction coefficients, μss and μs, respectively, and the log-linear th dependence of frictional healing, β, exhibit a decrease with simulated depth down to 3000 mbsf at which condition T was 100 °C, followed by an increase toward 6000 mbsf. On the other hand, the rate dependence of μss, a – b, gradually decreases with simulated depth, changing from positive at ≤4000 mbsf through ~0 at 5000 mbsf to negative at 6000 mbsf at which condition stick slips were observed.Our experimental results suggest the presence of a low fault-strength and weak fault-healing zone at ~3000 mbsf beneath IODP Site C0002, possibly due to elevated pore pressure induced by smectite dehydration. This zone correlates well with the previously reported low seismic-velocity zone and the source area of very low-frequency earthquakes to the south. Our experimental results also suggest that faulting beneath IODP Site C0002 is stable and aseismic at ≤4000 mbsf, transitional at 5000 mbsf, and potentially unstable and seismic at 6000 mbsf. In fact, stick slips corresponding to seismic faulting were observed at the 6000 mbsf condition. This implies that faulting along the plate-boundary thrust located at ~5200 mbsf beneath IODP Site C0002 is potentially seismogenic.

Investigating the influence of an approach bridge on a pile-supported wharf at a liquefiable site under horizontal and vertical seismic excitations

The approach bridge of the pile-supported wharf is an important structure that connects the pile foundation platform and the land, and it has a significant impact on the safety of the high-pile wharf. However, the influence of an approach bridge on the seismic dynamic response of a pile-supported wharf has often been neglected in previous studies. Besides, the excess pore water pressure (Δu) generated under combined vertical and horizontal seismic components is typically greater than that induced by unidirectional excitations, which may further impact the dynamic response of pile-supported wharf. Firstly, this study developed a numerical method for simulating the approach bridge of a pile-supported wharf. Secondly, the three-dimensional finite element model of a pile-supported wharf with an approach bridge is established to investigate the dynamic response during horizontal and vertical seismic components. Additionally, the effects of seismic frequency and relative density of liquefied layer on the dynamic response of pile-supported wharf were also studied. By comparing with the experimental results, the numerical model effectively simulated the overall response of the pile-supported wharf and the liquefaction behavior of the surrounding soil. During high-frequency earthquakes, the influence of the approach bridge on the dynamic response of the pile-supported wharf is minimal, whereas it has a more significant impact during low-frequency earthquakes. Furthermore, vertical seismic components significantly amplify the effect of approach bridge on the lateral displacement and internal forces of piles. The effect of the approach bridge on the lateral displacement and internal force of the pile decreases with the increase of the relative density of the liquefaction layer.

Co‐Occurrence of Low and Very Low Frequency Earthquakes Explained From Dynamic Modeling

AbstractVery low‐frequency earthquakes (VLFs) are characterized by longer source duration and smaller stress drop than regular earthquakes of similar magnitude. Recent studies have shown their frequent correlation with low‐frequency earthquakes (LFEs) on shared faults. The underlying source processes governing the occurrence of VLFs and their interaction with LFEs remain elusive. Here, we employ a slip‐weakening model for slow earthquakes. By comparing the source parameters of simulations and observations, it is suggested that VLFs are slow self‐arresting earthquakes that self‐terminate within the nucleation patch. Additionally, we adopt a composite model to reproduce the records of the simultaneous occurrences of a VLF and an LFE in the Nankai area. Our results present the possibility that VLFs, LFEs, and regular earthquakes can be distinguished using a unified dynamic framework.

Geological fingerprints of deep slow earthquakes: A review of field constraints and directions for future research

Abstract Slow earthquakes, including low-frequency earthquakes, tremor, and geodetically detected slow-slip events, have been widely detected, most commonly at depths of 40–60 km in active subduction zones around the Pacific Ocean Basin. Rocks exhumed from these depths allow us to search for structures that may initiate slow earthquakes. The evidence for high pore-fluid pressures in subduction zones suggests that they may be associated with hydraulic fractures (e.g., veins) and with metamorphic reactions that release or consume water. Loss of continuity and resulting slip at rates exceeding 10−4 m s–1 are required to produce the quasi-seismic signature of low-frequency earthquakes, but the subseismic displacement rates require that the slip rate is slowed by a viscous process, such as low permeability, limiting the rate at which fluid can access a propagating fracture. Displacements during individual low-frequency earthquakes are unlikely to exceed 1 mm, but they need to be more than 0.1 mm and act over an area of ~105 m2 to produce a detectable effective seismic moment. This limits candidate structures to those that have lateral dimensions of ~300 m and move in increments of &amp;lt;1 mm. Possible candidates include arrays of sheeted shear veins showing crack-seal structures; dilational arcs in microfold hinges that form crenulation cleavages; brittle-ductile shear zones in which the viscous component of deformation can limit the displacement rate during slow-slip events; slip surfaces coated with materials, such as chlorite or serpentine, that exhibit a transition from velocity-weakening to velocity-strengthening behavior with increasing slip velocity; and block-in-matrix mélanges.

Deep learning detects uncataloged low-frequency earthquakes across regions

Documenting the interplay between slow deformation and seismic ruptures is essential to understand the physics of earthquakes nucleation. However, slow deformation is often difficult to detect and characterize. The most pervasive seismic markers of slow slip are low-frequency earthquakes (LFEs) that allow resolving deformation at minute-scale. Detecting LFEs is hard, due to their emergent onsets and low signal-to-noise ratios, usually requiring region-specific template matching approaches. These approaches suffer from low flexibility and might miss LFEs as they are constrained to sources identified a priori. Here, we develop a deep learning-based workflow for LFE detection and location, modeled after classical earthquake detection with phase picking, phase association, and location. Across three regions with known LFE activity, we detect LFEs from both previously cataloged sources and newly identified sources. Furthermore, the approach is transferable across regions, enabling systematic studies of LFEs in regions without known LFE activity.

Link Between Geometrical and Physical Property Changes Along Nankai Trough With Slow Earthquake Activity Revealed by Dense Reflection Survey

AbstractWe examined the possible factors affecting the spatial distribution of very low frequency earthquakes and tremors in the shallow megathrust of Nankai Trough (&lt;30 km) using a dense network of prestack depth migrated profiles at the frontal wedge. Geometrical parameters examined were decollement roughness, taper angle, and underthrust thickness. Physical properties such as effective basal friction (μb) and pore pressure ratio (λ*) were calculated from the taper angle and p‐wave velocity. Regions of low λ* (0.39 ± 0.08) and smooth decollement showed no slow earthquake activity. In contrast, high activity of slow earthquakes was observed in areas with a rough decollement due to the presence of subducted seamounts or bathymetric highs. The low taper angle (3.8°) off Muroto where slow earthquakes also occur translates to a wide zone of low μb (0.21 ± 0.06) and high λ* (0.66 ± 0.06). However, our results also show that slow earthquakes don't always occur in areas with high λ*.

Comparison of statistical low-frequency earthquake activity models

Slow earthquakes are slow fault slip events. Quantifying and monitoring slow earthquake activity characteristics are important, because they may change before large earthquakes occur. Statistical seismicity models are useful for quantifying seismicity characteristics. However, no standard statistical model exists for slow earthquake activity. This study used a high-quality catalog of low-frequency earthquakes (LFEs), a type of slow earthquake, in the Nankai subduction zone from April 2004 to August 2015 and conducted the first comparison of existing statistical LFE activity models to determine which model better describes LFE activity. Based on this comparison, this study proposes a new hybrid model that incorporates existing model features. The new model considers the LFE activity history in a manner similar to the epidemic-type aftershock sequence (ETAS) model and represents the LFE aftershock rate (subsequent LFE occurrence rate) with a small number of model parameters, as in the Omori–Utsu aftershock law for regular earthquakes. The results show that the proposed model outperforms other existing models. However, the new model cannot reproduce a feature of LFE activity: the sudden cessation of intense LFE bursts. This is because the new model superimposes multiple aftershock activities and predicts extremely high seismicity rates during and after the LFE bursts. I suggest that reproducing and successfully predicting the sudden cessation of intense LFE bursts is critical for the further improvement of statistical LFE activity models. In addition, the empirical equations formulated in this study for the LFE aftershock rates may be useful for future statistical and physical modeling of LFE activity.Graphical

Characteristics and generation mechanism of low-frequency earthquakes in the continental plate

Characteristics and generation mechanism of low-frequency earthquakes in the continental plate

Correction to: Cubic moment–duration relationship of low-frequency earthquakes

Correction to: Cubic moment–duration relationship of low-frequency earthquakes

Tremor along the Dead Sea Transform remotely triggered by the 2023 MW7.6 Kahramanmaraş earthquake

Tremor signals are weak and emergent, and the physics governing their generation is not well understood. Here, I report on tremor occurring along the Dead Sea Transform (DST), and a microearthquake on the Carmel-Fari’a Fault (CFF), both remotely triggered by the 2023 MW7.6 Kahramanmaraş earthquake. The triggered events location coincides with maxima of long-period velocity gradients, concentrated in the CFF-DST intersection and near a CFF fault-jump. Relative to other remotely triggered tremors, the DST tremor is strong and deficient in high-frequency seismic energy. Furthermore, analysis of several remotely triggered tremor episodes suggests that tremors spectral fall-off rates are not universal. I discuss the seismological attributes that may give rise to these observations in the context of two models. In the first, tremor is produced due to inertial vibrations of a frictionally-controlled oscillator, and in the second it is produced by a swarm of Low-Frequency Earthquakes.

Spatial variation in shallow slow earthquake activity in Hyuga-nada, southwest Japan

SUMMARY Hyuga-nada, off the Pacific coast of Kyushu along the Nankai Trough in southwest Japan, is one of the most active slow earthquake regions around Japan. We estimated the energies of shallow tremors and moments of shallow very low frequency earthquakes (VLFEs) in Hyuga-nada using data from a permanent onshore broadband network and temporary ocean–bottom seismometer observations. The energies and moments of these slow earthquakes have a similar along-strike variation and are generally higher south of the subducted Kyushu–Palau Ridge than near the top of the ridge. This spatial variation is also related to the characteristics of slow earthquake migration. The along-strike migration speed was faster at initiation in the south, where the moments of slow earthquakes are higher. After migration entered the subducted Kyushu–Palau Ridge, its speed was decelerated with a parabolic pattern and their moments became smaller. Assuming a constant patch size of slow earthquakes, we estimated that the stress drop of VLFEs in the south of the subducted ridge was approximately three times higher than that near the top of the subducted ridge. According to our observations and a physical model, this stress drop difference between adjacent regions may cause parabolic migration. We also estimated the scaled energy of slow earthquakes from the ratio of the seismic energy rates of tremors to the seismic moment rates of accompanying VLFEs. The spatial variation in scaled energy is not identified inside the Hyuga-nada. Since the range of scaled energy is similar between the south and near the top of the subducted ridge, the apparent stress may be similar if the rigidity is the same. The dominant range of scaled energy of slow earthquakes in Hyuga-nada is 10−11.5–10−8.5. In addition to having similar or one order smaller values compared to other slow earthquake regions, the range of scaled energy in Hyuga-nada is broader. This broader range suggests wide range of characteristic time and various spectral features of slow earthquakes in Hyuga-nada. Based on a Brownian slow earthquake model, the wide range of characteristic time in this area suggests width variations of slow earthquake source area.

Detectability analysis of very low frequency earthquakes: methods and application in Nankai using F-net and DONET broad-band seismometers

SUMMARY For a more quantitative discussion of slow earthquake activity, we evaluated the detectable limits of very low frequency earthquakes (VLFEs), which are seismic slow earthquakes observed in very low-frequency (&amp;lt; 0.05 Hz) bands in the Nankai subduction zone. We performed numerical simulations using a local 3-D model and used the observed noise level of permanent broad-band seismometers. First, we investigated the effects of the source-time functions on the maximum amplitudes of the VLFE signals at a certain station. The maximum amplitudes of the VLFE signals were controlled by the VLFE moment rate. The detectable limit of VLFEs at each source location can be defined as the lowest moment rate of detectable VLFEs, which radiate signals larger than the noise levels of any component at ≥ 3 stations. For inland seismometers only, the detectable limits of VLFEs at deep (30–40 km) and shallow (≤ 10 km) depths were 1012–1012.3 and 1012.7 N·m s−1, respectively. Due to the geometrical spreading of VLFE signals and large noise levels in horizontal components, offshore seismometers improved the detectability of shallow VLFEs in regions where seismometers were densely deployed. Based on our detectability and published catalogues, shallow slow earthquakes are less active south-southwest off the Kii Peninsula, where geodetic studies expect mechanical coupling.

Cubic moment–duration relationship of low-frequency earthquakes

SUMMARY Low-frequency earthquakes (LFEs) are seismic phenomena with the shortest timescale among various slow earthquakes observed on broad-band timescales. To understand the nature of such a broad-band slow phenomenon, it is important to investigate the rupture evolution process of individual slow events, such as LFEs. Here, we investigated the moment–duration relationship of LFEs at plate interfaces and volcanic regions, and showed that the moment–duration relationship of both tectonic and volcanic LFEs is characterized by a moment proportional to the cubic duration, similar to that in ordinary earthquakes. The difference between our obtained moment–duration relationship and the broad-band scaling suggests that the evolution process of LFEs may not be controlled, but only triggered by the slow earthquakes with longer durations, such as slow slip events driven by aseismic diffusion. The seismic moments of the LFEs are approximately three orders of magnitude smaller than those of ordinary earthquakes with similar durations. This result indicates that LFEs have rupture growth similar to that of ordinary earthquakes, although the rupture velocity and/or stress drop are much smaller. Considering the hypocentre spread of LFEs, the estimated rupture velocity and stress drop were approximately 100 m /s–1 km /s and 2 kPa–1 MPa, respectively. Additionally, the estimated moment magnitudes are much larger than the local magnitudes determined based on the maximum amplitudes, which is due to the longer durations and resultant smaller amplitudes of LFEs than those of ordinary earthquakes.

Feasibility Study of a Novel Modal Decomposition Method for Low-Frequency Structure with Nonproportionally Distributed Rate-Independent Linear Damping

Compared with conventional linear viscous damping (LVD), rate-independent linear damping (RILD) mitigates floor response acceleration in low-frequency structures more effectively without compromising the control performance of displacement responses during long-period or low-frequency earthquakes. Although theoretical and experimental attempts have been made to overcome the noncausality of RILD devices and realize RILD using passive or semiactive devices, only a few studies have highlighted the impulse-response precursor and modal analysis method of multistory structures incorporated into RILD devices. This study investigated the impulse-response precursor of a noncausal RILD system and proposed a novel modal decomposition method for the structures equipped with nonproportionally distributed RILD devices. Additionally, real-time hybrid simulation was conducted to validate the effectiveness of the proposed modal analysis method and the feasibility of realizing ideal RILD using mechanical devices. This study is the first to demonstrate the differences between RILD and LVD devices in terms of controlling the modal responses of low-frequency structures and how RILD can lower the floor response acceleration more effectively compared to LVD.

Three-Dimensional Low-Frequency Earthquake Monitoring Vibration Sensor Based on FBG

Three-Dimensional Low-Frequency Earthquake Monitoring Vibration Sensor Based on FBG

Hidden Markov Models for Low-Frequency Earthquake Recurrence

Low-frequency earthquakes (LFEs) are small magnitude earthquakes with frequencies of 1–10 Hertz which often occur in overlapping sequence forming persistent seismic tremors. They provide insights into large earthquake processes along plate boundaries. LFEs occur stochastically in time, often forming temporally recurring clusters. The occurrence times are typically modeled using point processes and their intensity functions. We demonstrate how to use hidden Markov models coupled with visualization techniques to model inter-arrival times directly, classify LFE occurrence patterns along the San Andreas Fault, and perform model selection. We highlight two subsystems of LFE activity corresponding to periods of alternating episodic and quiescent behavior.

Reappraisal of volcanic seismicity at the Kirishima volcano using machine learning

Volcanic earthquakes provide essential information for evaluating volcanic activity. Because volcanic earthquakes are often characterized by swarm-like features, conventional methods using manual picking require considerable time to construct seismic catalogs. In this study, using a machine learning framework and a trained model from a volcanic earthquake catalog, we obtained a detailed picture of volcanic earthquakes during the past 12 years at the Kirishima volcano, southwestern Japan. We detected ~ 6.2 times as many earthquakes as a conventional seismic catalog and obtained a high-resolution hypocenter distribution through waveform correlation analysis. Earthquake clusters were estimated below the craters, where magmatic or phreatic eruptions occurred in recent years. Increases in seismic activities, b values, and the number low-frequency earthquakes were detected before the eruptions. The process can be conducted in real time, and monitoring volcanic earthquakes through machine learning methods contributes to understanding the changes in volcanic activity and improving eruption predictions.Graphical