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In this study, a multi-source data fusion method was proposed for the development of a Hybrid seismic hazard model (HSHM) in China by using publicly available data of the 5th Seismic Ground Motion Parameter Zoning Map (NSGM) and historical seismic catalogues and integrating with modern ground motion prediction equations (GMPEs). This model incorporates the characteristics of smoothed seismicity and areal sources for regional seismic hazard assessment. The probabilistic seismic hazard for the North China Plain earthquake belt was investigated through sensitivity analysis related to the seismicity model and GMPEs. The analysis results indicate that the Hybrid model can produce a consistent result with the NSGM model in many cases. However, the NSGM model tends to overestimate hazard values in locations where no major events have occurred and underestimate hazard values in locations where major events have occurred. The Hybrid model can mitigate the degree of such biases. Compared to the modern GMPEs, the GMPE with epicentral distance measures significantly underestimate the seismic hazard under near-field and large-magnitude scenarios. In addition, a comparison of the uniform hazard spectra (UHS) obtained by the models, with China’s design spectrum, shows that the current design spectrum is more conservative than the calculated UHS.

Rapid and accurate seismic source characterization significantly influences the performance of earthquake early warning (EEW) systems. However, the complexity of the seismic source modeling and the error accumulation during continuous characterization make it difficult to accurately characterize various source parameters. Furthermore, current artificial intelligence methods focus on a single task, lacking intertask fusion and guidance from specialized knowledge. In this study, we propose a novel deep learning (DL) algorithm (SeisParaNet) to estimate P-wave arrival time, source location, and magnitude simultaneously based on a multitask framework. To exploit seismological knowledge and attenuate the strong intertask dependencies, this study incorporates arrival time differences’ information into the analysis of source localization parameters using the attention mechanism and incorporates source location features into estimating local magnitude (Ml). In addition, SeisParaNet uses a probability-based self-attention mechanism (Prob-Attention) to extract temporal information from waveforms. Experimental results demonstrate that following a limited number of trainings on the STanford EArthquake Dataset (STEAD), SeisParaNet exhibits the capability to capture complex seismic patterns and rapidly characterize seismic sources. Furthermore, the introduction of Prob-Attention reduces computational complexity by 67%, validating the potential of SeisParaNet in EEW applications.

Determining source parameters of submarine earthquakes is fundamental to geotechnical and geodynamic research. However, these remote areas are usually poorly monitored, posing challenges in characterizing seismic behaviors. Here, we propose a wavelet-domain seismic source inversion method based on 3-D Green’s functions for modeling teleseismic body waves to obtain locations and focal mechanisms of submarine earthquakes. We adopt the heat bath algorithm to implement inversions. The wavelet transform allows us to simultaneously investigate source features in different frequencies. Numerical experiments conducted on synthetic data show our method is efficient and suggest that, for ~M6 earthquakes, lower-frequency waveforms (<0.1 Hz) are more sensitive to focal mechanisms, while higher frequencies (0.1~0.2 Hz) work better in constraining source locations. Application to a ~M6 earthquake in the Japan Trench suggests that our approach can provide reliable source parameters (locations and focal mechanisms) for submarine earthquakes.

This study examines the seismic source parameters and high-frequency spectral attenuation factor (κ) of 36 minor to moderate earthquake (EQ) events that have been occurred in the north-west Himalayas and its foothills of north India from 2007 to 2016. A non-reference generalised inversion technique has been used to compute the source spectra, and the point source model is used to estimate the seismic moment (M0) and corner frequency (fc). Further, a scaling relation between M0and fchas been developed for the study area. Additionally, based on the determined fcand M0values, source characteristics such as seismic energy (Es), stress drop (Δσ) and apparent stress drop (σa) are estimated for each of the 36 events. In the present work, σaand ∆σ were found to range from 0.1 MPa to 12.36 MPa and 0.17 MPa to 14.61 MPa, respectively. Low values of σaand ∆σ can be associated with the low effective stress model EQs. Furthermore, a majority of EQs appear to have a partial stress drop mechanism according to the Zúñiga parameter (ε) determined for the region. Also, the parameter κis estimated and is found to range between 0.015 and 0.071 for the horizontal component, and 0.01 and 0.036 for the vertical component. The epicentre distance for various site classes is used to construct a regional model for κ. Finally, stochastic ground motion simulations of historical EQ records utilising estimated source parameters and constructed kappa models are performed in order to validate the findings of the present work. The comparison of the original and simulated EQ records is in very good agreement, demonstrating the efficacy of the obtained parameters in capturing the local ground motion features.

Seismic source location is a classic inverse problem in seismology. In mathematical physics, inverse problems have multiple natural solutions. The objective of this study was to develop a generic theory and method of seeking the true solution from multiple solutions for the location of a coal mine seismic source in an idealized velocity structure model of a coal mine with a small scale and complex geological environment. Starting from the simplest velocity structure model, the complexity of the model gradually increased, until it approached the real velocity structure model, i.e., the multilayered horizontal and inclined velocity structure model, in order to find a generic method for solving the multi-solution inverse problem of coal mine seismic source location. Specifically, the wavefront distribution equation in a two-layer horizontal medium was derived and then expanded to any multi-layer horizontal medium. Based on this equation, a positive definite nonlinear equation system was established from the perspective of any observation system. The equation system contained four unknown variables of the spatiotemporal position of the seismic source. To determine the spatiotemporal parameters of the seismic source, nonlinear equations for four stations were required. To solve the nonlinear equation system, an initial iteration value was determined. In order to reduce the difficulty of determining the initial iteration value, the variable substitution method was used to reduce the number of location parameters. By rotating the original geodetic coordinate system of the station to be parallel and orthogonal to the medium interface, the wavefront method was extended to inclined medium. In conclusion, in this study, the problem of coal mine seismic source location in a multi-layer horizontal or inclined medium was effectively solved. The method proposed in this study provides a reference for solving the true solution from multiple solutions for the location of a coal mine seismic source in small-scale coal mines with complex geological environments.

The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault parameters inversion has nonlinear characteristics, and the gradient-based optimizer (GBO) has the characteristics of fast convergence speed and falling into local optimum hardly. This paper applies GBO algorithm to simulated earthquakes and real LuShan earthquakes in the nonlinear inversion of the Okada model to obtain the source parameters. The simulated earthquake experiment results show that the algorithm is stable, and the seismic source parameters obtained by GBO are slightly closer to the true value than the multi peak particle swarm optimization (MPSO). In the 2013 LuShan earthquake experiment, the root mean square error between the deformation after forwarding of fault parameters obtained by the introduced GBO algorithm and the surface observation deformation was 3.703 mm, slightly better than 3.708 mm calculated by the MPSO. Moreover, the inversion result of GBO algorithm is better than MPSO algorithm in stability. The above results show that the introduced GBO algorithm has a certain practical application value in seismic fault source parameters inversion.

Dynamic failure of rock masses around deep tunnels, such as fault-slip rockburst and seismic-induced collapse, can pose a significant threat to tunnel construction safety. One of the most significant factors that control the accuracy of its risk assessment is the estimation of the ground motion around a tunnel caused by seismicity events. In general, the characteristic parameters of ground motion are estimated in terms of empirical scaling laws. However, these scaling laws make it difficult to accurately estimate the near-field ground motion parameters because the roles of control factors, such as tunnel geometry, damage zone distribution, and seismic source parameters, are not considered. For this, the finite fracturing seismic source model (FFSSM) proposed in this study is used to simulate the near-field ground motion characteristics around deep tunnels. Then, the amplification effects of ground motion caused by the interaction between seismic waves and deep tunnels and corresponding control factors are studied. The control effects of four factors on the near-field ground motion amplification effect are analyzed, including the main seismic source wavelength, tunnel span, tunnel shape, and range of damage zones. An empirical formula for the maximum amplification factor (αm) of the near-field ground motion around deep tunnels is proposed, which consists of four control factors, i.e. the wavelength control factor (Fλ), tunnel span factor (FD), tunnel shape factor (Fs) and excavation damage factor (Fd). This empirical formula provides an easy approach for accurately estimating the ground motion parameters in seismicity-prone regimes and the rock support design of deep tunnels under dynamic loads.

In regions of infrequent moderate-to-large earthquakes, historic earthquake catalogs are often insufficient to provide inputs to seismic-hazard analyses (i.e. fault locations and magnitude–frequency relations) or to inform ground-motion predictions for certain seismic sources. In these regions, analysis of relic coseismic evidence, such as paleoliquefaction, is commonly used to infer information about the seismic hazard. However, while paleoliquefaction studies have been performed widely, all existing analysis techniques require a prioriassumptions about the causative earthquake’s location (i.e. rupture magnitude and ground motions can otherwise not be estimated). This may lead to inaccurate assumptions in some settings, and by corollary, erroneous results. Accordingly, this article proposes an inversion framework to probabilistically constrain seismic-source parameters from paleoliquefaction. Analyzing evidence at regional scale leads to (a) a geospatial likelihood surface that constrains the rupture location and (b) a probability distribution of the rupture magnitude, wherein source-location uncertainty is explicitly considered. Simulated paleoliquefaction studies are performed on earthquakes with known parameters. These examples demonstrate the framework’s potential, even in cases of limited field evidence, as well as important caveats and lessons for forward use. The proposed framework has the potential to provide new insights in enigmatic seismic zones worldwide.

The violent eruption of the Hunga (Tonga) submarine volcano on 15 January 2022 caused a 58 km‐heigh ash plume, catastrophic tsunami, and significant global seismic and infrasound waves. However, the physical mechanism underpinning its multiple‐explosive events remains unclear, and its resolvability relies on the seismic waveform source inversion. The studies of two different point‐source models, the seismic moment tensor (MT) and the single force (SF), have been performed separately for this eruption, which, interestingly, can explain the seismic data adequately. Here, we use a joint inversion of MT and SF to unravel a composite source of an explosion‐like MT and a significant upward force for the first major explosive event. Regarding the direction and magnitude, we propose that the upward force is likely a rebound force in response to the pressure drop on the seafloor because the water body above the volcano was abruptly uplifted by the shallow underwater explosion. The physical process of the violent eruption of the Hunga (Tonga) submarine volcano on 15 January 2022 remains unclear. To date, the common source model for volcano eruptions—a single force (SF) and the common source model for earthquakes and explosions—a moment tensor (MT), have been inferred individually for this eruption. Interestingly, both can explain the recorded seismic signals reasonably well. A question arises whether a combination of sources is a better physical model. Therefore, we combine the MT and SF to represent the eruption process in this study. The source analysis for the first major event of this eruption reveals a possible composite process of a shallow underwater explosion and a significant upward force. The upward force is opposite the common downward‐reaction force to the material jetting. It is likely caused by the abrupt displacement of the water above the volcano resulting from the shallow underwater explosion. When the downward water pressure on the seafloor vanishes, the seafloor responds by an upward‐rebound force. We perform probabilistic inversion of seismic waveform data to study the force equivalent system of the 2022 Hunga (Tonga) eruptionThe first major explosive event of the shallow eruption sequences may consist of an explosion‐like moment tensor and a large upward forceA possible mechanism of the accompanying upward force is the rebound force responding to the sudden pressure drop of uplifted water body We perform probabilistic inversion of seismic waveform data to study the force equivalent system of the 2022 Hunga (Tonga) eruption The first major explosive event of the shallow eruption sequences may consist of an explosion‐like moment tensor and a large upward force A possible mechanism of the accompanying upward force is the rebound force responding to the sudden pressure drop of uplifted water body

Teledyne Marine Seismic reported it has been awarded a long-term contract to provide seismic source controllers to PGS ASA. According to a release, Teledyne Real Time Systems' SmartSource system represents [...]

A minequake of magnitude ML4.1 occurred on 18 May 2020 early in the morning at the LKAB underground iron ore mine in Kiruna, Sweden. This is the largest mining‐induced earthquake in Scandinavia. It generated acoustic signals observed at three infrasound arrays at 9.3 (KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance. We perform full‐waveform focal mechanism inversion based on regional seismic data and local infrasound data. These independently highlight that this event was dominated by a shallow‐depth collapse in agreement with in‐mine seismic station data. However, regional infrasound data cannot inform the inversion process without an accurate model of atmospheric winds and temperatures. Yet, our numerical simulations demonstrate a potential of using local and regional infrasound data to constrain an event's focal mechanism and depth. The largest mining‐induced earthquake in Scandinavia (ML4.1) occurred on 18 May 2020 early in the morning at the LKAB underground iron ore mine in Kiruna, Sweden. The seismic waves coupled to the atmosphere and propagated large distances as sound waves which were observed at three infrasound arrays at 9.3 (KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance. Our seismic and acoustic modeling results highlight a strong collapse event within the northern section of the mine. The modeling of acoustic and seismic waves across the Earth‐atmosphere suggests that sound wave data can help when determining the location and properties of a seismic source. Seismic and acoustic records indicate a strong collapse at shallow depth of 1  ±  0.5 km for the 2020 Kiruna minequakeFocal mechanisms and depths of shallow seismic sources can be retrieved from local infrasound recordsInversions using regional infrasound data is possible when accurate weather models are available Seismic and acoustic records indicate a strong collapse at shallow depth of 1  ±  0.5 km for the 2020 Kiruna minequake Focal mechanisms and depths of shallow seismic sources can be retrieved from local infrasound records Inversions using regional infrasound data is possible when accurate weather models are available

Between 2018 and 2021, AIMS and its partners conducted a large-scale experiment to investigate the effect of exposure to a 3D seismic survey on pearl oysters. In August 2018, ≈11 000 adult wild silverlip pearl oysters (Pinctada maxima ) were collected and attached to bottom culture lines to acclimatise for 1 month at a holding lease site, 40 km off Broome, WA. These oysters were split across rows configured parallel to each other at seven horizontal distances up to 6000 m from a ‘zero line’. In September 2018, we sailed a commercial seismic vessel along one 20 km-long inactive (vessel control) sail line along the zero line, followed by six operational (exposure) sail lines, at increasing distances from the zero line, with each line separated in time by either 12 or 24 h. This design resulted in groups of pearl oysters with 35 different exposure histories (seven distances, five exposure distances) that were then transferred to undergo either lethal biophysical sampling or pearl seeding for a ‘grow-out’ study of pearl production. Biophysical sampling included immunology tests, primarily using flow cytometry and gene expression changes in nacre- and stress-associated genes. Audits of oyster growth and condition were conducted at various time points between the exposure period and harvesting of the seeded oysters. The number and quality of pearls produced by each exposure group was assessed 2 years after exposure (December 2020). The results of these analyses are being finalised for presentation.

Seismic source locations are fundamental to many fields of Earth and planetary sciences, such as seismology, volcanology and tectonics. However, seismic source detection and location are challenging when events cluster closely in space and time with signals tangling together at observing stations, such as they often do in major aftershock sequences. Though emerging algorithms and artificial intelligence (AI) models have made processing high volumes of seismic data easier, their performance is still limited, especially for complex aftershock sequences. In this study, we propose a novel approach that utilizes three‐dimensional image segmentation—a computer vision technique—to detect and locate seismic sources, and develop this into a complete workflow, Source Untangler Guided by Artificial intelligence image Recognition (SUGAR). In our synthetic and real data tests, SUGAR can handle complex, energetic earthquake sequences in near real time better than skillful analysts and other AI and non‐AI based algorithms. We apply SUGAR to the 2016 Kaikōura, New Zealand sequence and obtain five times more events than the analyst‐based GeoNet catalog. The improved aftershock distribution illuminates a continuous fault system with extensive fracture zones beneath the segmented, discontinuous surface ruptures. Our method has broader applicability to non‐earthquake sources and other time series image data sets. Detecting and locating earthquakes is fundamental to seismology, volcanology, and tectonics. A number of emerging algorithms, including some based upon artificial intelligence (AI), have made processing large volumes of seismic data much easier. However, their performance is still limited, especially in clustered aftershock sequences whose signals overlap at observing seismographs. We propose a new, AI computer vision‐based approach to this problem, and develop it into a complete earthquake detection and location workflow, named SUGAR. Tests on synthetic and real earthquake data sets show that SUGAR characterizes complex earthquake sequences better than other AI and non‐AI algorithms or professional analysts. We apply SUGAR to the complex aftershock sequence of the 2016 Mw7.8 Kaikōura, New Zealand earthquake, detecting five times more events than the analyst‐based GeoNet catalog. Whereas surface breaks of the Kaikōura earthquake are highly discontinuous, our improved aftershock distribution supports a continuous fault system surrounded by extensive fracture zones at depth. Our method has broader potential for other types of seismic sources and image series. We propose a new seismic source detection and location approach based on the source‐scanning algorithm and 3D image segmentationThis approach outperforms human analysts and popular artificial intelligence (AI) and non‐AI based methods in characterizing intense aftershock sequencesThe resulting catalog of the 2016 Kaikōura earthquake sequence suggests a continuous fault system surrounded by extensive fracturing We propose a new seismic source detection and location approach based on the source‐scanning algorithm and 3D image segmentation This approach outperforms human analysts and popular artificial intelligence (AI) and non‐AI based methods in characterizing intense aftershock sequences The resulting catalog of the 2016 Kaikōura earthquake sequence suggests a continuous fault system surrounded by extensive fracturing

Genuine non‐double‐couple (non‐DC) components of a seismic source, defined here as the non‐DC components that are not due to summation of pure double‐couple (DC) components, provide important insight into special physical processes in non‐earthquake sources such as explosion, volcano eruption and collapse etc. Yet they remain challenging to be resolved. To address the issue and explore the physical mechanism of those special events, we develop a waveform‐polarity‐based moment tensor (WPMT) inversion method and employ it to study physical process in the 2014–2015 Bárðarbunga volcano event sequence. The WPMT method incorporates P‐wave polarity data and seismic waveforms in the source inversion, designs a source simplicity test to check possible complex rupture in the seismic source, and employs a simulated annealing algorithm to search the best source solution. The simplicity test checks consistency of the source processes in the initiation stage of the event and the major energy release process of the event, thus ensuring that the inferred non‐DC components are genuine to the seismic source. Real event and synthetic tests indicate that the WPMT method can identify and resolve genuine non‐DC components in a seismic source. The WPMT inversions of the Bárðarbunga sequence yield many genuine non‐DC source components and reveal that the eruptions are accompanied by seismic activities in depths of 1–5 km with magma migrations out of chambers, collapses of conduits, failures of normal faults, and a magma recharge at a depth of 9 km accompanied by a failure on a nearby normal fault. Special seismic events such as explosion, collapse and volcanic eruption possess source components that are different from fault solutions used to represent a typical tectonic earthquake of simple shear. The identification and quantification of the source components of those special seismic sources thus play an important role in deciphering the physical process during those events. Yet, it remains challenging to resolve the source components of special seismic events due to the ambiguity of distinguishing them from an apparent one due to complex earthquake rupture. We develop a waveform‐polarity‐based moment‐tensor inversion to resolve the source components of a special seismic source and employ the method to study the physical process in the 2014–2015 Bárðarbunga volcano event sequence in Iceland. Real event and synthetic tests confirm method's capability of identifying and constraining the source components of special non‐earthquake events. The study of the Bárðarbunga sequence reveals that the eruptions are accompanied by seismic activities in depths of 1–5 km with magma migrations out of chambers, collapses of conduits, failures of normal faults, and a magma recharge at a depth of 9 km accompanied by a failure on a nearby normal fault. We propose a waveform‐polarity‐based moment tensor inversion method to extract non‐double‐couple components of moderate seismic eventsReal event and synthetic tests show the method is effective in distinguishing and resolving genuine non‐double‐couple componentsMethod application reveals magma activities, conduit collapses and induced earthquakes during the 2014–2015 Bárðarbunga eruptions We propose a waveform‐polarity‐based moment tensor inversion method to extract non‐double‐couple components of moderate seismic events Real event and synthetic tests show the method is effective in distinguishing and resolving genuine non‐double‐couple components Method application reveals magma activities, conduit collapses and induced earthquakes during the 2014–2015 Bárðarbunga eruptions

Any device that releases acoustic energy could be considered a seismic source, and there are many. Historically, one would think that just about everything imaginable has been used. However, amazingly, [...]

Up to now, the possibility to obtain images of seismic source from ionospheric Global Navigation Satellite Systems (GNSS) measurements (seismo‐ionospheric imagery) has only been demonstrated for giant earthquakes with moment magnitude Mw ≥ 9.0. In this work, we discuss difficulties and restrictions of this method, and we apply for the first time the seismo‐ionospheric imagery for smaller earthquakes. The latter is done on the example of the Mw7.4 Sanriku‐oki earthquake of 9 March 2011. Analysis of 1‐Hz data of total electron content (TEC) shows that the first coseismic ionospheric disturbances (CID) occur ~470–480 s after the earthquake as TEC enhancement on the east‐northeast from the epicenter. The location of these first CID arrivals corresponds to the location of the coseismic uplift that is known as the source of tsunamis. Our results confirm that despite several difficulties and limitations, high‐rate ionospheric GNSS data can be used for determining the seismic source parameters for both giant and smaller/moderate earthquakes. In addition to these seismo‐ionospheric applications, we raise several fundamental questions on CID nature and evolution, namely, one of the most challenging queries—can moderate earthquake generate shock‐acoustic waves? Ionosphere is a layer of charged particles of the Earth's atmosphere located at altitudes ~60–800 km. However, despite being high above the Earth's surface, the ionosphere is sensible to numerous near‐ground geophysical events (earthquakes, tsunamis, volcano eruptions, etc). Acoustic and gravity waves emitted by these events propagate upward and generate atmospheric/ionospheric perturbations. Ionospheric disturbances generated by earthquakes are known as coseismic ionospheric disturbances (CID). Recently, it has been suggested that analysis of CID and their first arrivals can provide information on the position and on the structure of seismic fault ruptured in earthquake. This method is known as ionospheric imagery of seismic source. However, so far, this method has been only applied to giant earthquakes (Mw ≥ 9.0). In this work, for the first time, we apply the ionospheric imagery for smaller earthquakes on the example of the M7.4 Sanriku‐oki earthquake that occurred on 9 March 2011 in Japan. Our results show that this method is applicable to smaller earthquakes, and despite some difficulties, it can indicate the position of coseismic uplift ~8 min after the earthquake. The uplift generates CID but also tsunamis. Therefore, our method can be used as independent or complementary one for near–real‐time tsunami warning systems. By applying the method of seismo‐ionospheric imagery, we show the location of the seismic source for the Mw7.4 2011 Sanriku‐oki earthquakeWe discuss possibilities, difficulties, and challenges of the method of ionospheric imagery of seismic sourceSimultaneous use of the ray‐tracing technique and GNSS observations can be useful to resolve some difficulties of the ionospheric imagery

The variability in obtaining estimates of tsunami inundation and runup on a near‐real‐time tsunami hazard assessment setting is evaluated. To this end, 19 different source models of the Maule Earthquake were considered as if they represented the best available knowledge an early tsunami warning system could consider. Results show that large variability can be observed in both coseismic deformation and tsunami variables such as inundated area and maximum runup. This suggests that using single source model solutions might not be appropriate unless categorical thresholds are used. Nevertheless, the tsunami forecast obtained from aggregating all source models is in good agreement with observed quantities, suggesting that the development of seismic source inversion techniques in a Bayesian framework or generating stochastic finite fault models from a reference inversion solution could be a viable way of dealing with epistemic uncertainties in the framework of nearly‐real‐time tsunami hazard mapping. Owing to recent advancements in rapid seismic source characterization and tsunami simulation, nearly‐real‐time tsunami hazard forecasts in the framework of tsunami early warning systems are starting to be within reach. However, in this study we bring a note of caution regarding its future operational implementation since the level of uncertainty associated to a single rupture inversion is high and thus calls for the use of multiple realizations of seismic inversions to forecast inundation maps and assess their uncertainty bounds. We provide an empirical assessment of the variability of finite fault inversions and its consequences for rapid tsunami hazard mappingThe variability in modeled tsunami maximum amplitudes, runups, and inundated 16 areas is of the same order as their median values evidencing a high inherent uncertaintyCombining the available knowledge to build a distribution of the tsunami source allows to obtain sound predictions of tsunami variables

As powerful as air gun, Distributed Seismic Source™ eliminates explosive blasting that has been blamed for harming whales, porpoises, and other marine life. DSS puts array of powerful sources downhole, [...]

The development of reliable systems for monitoring injected CO2is essential in carbon capture and storage projects. We applied time‐lapse surface wave analysis to measure temporal variations of the shallow subsurface among 11 periods (0.2–21.6 days) of continuous seismic data acquired from 2014 to 2016 at the Aquistore CO2storage site in Canada. We focused on monitoring environmental influences on shallow seismic velocity, which are unrelated to CO2injection into deep reservoirs. A continuous, controlled seismic source system called Accurately Controlled Routinely Operated Signal System was used to enhance the temporal resolution and source repeatability. Observed phase velocities were clearly higher in winter than in warmer seasons. The seasonal variation could be reproduced by an increase in the shallow Swave velocity during winter associated with the greater extent of freezing of partially saturated rock. We also observed gradual increases or decreases in phase velocities as the seasons changed, which could be related to gradual freezing or melting of ice. Our monitoring system thus could be effective for monitoring temporal variations of the shallow subsurface associated with the degree of freezing. Furthermore, the high temporal stability of our monitoring approach in warm seasons may make it possible to immediately identify CO2leakage in the shallow subsurface. We monitored the shallow subsurface at the Aquistore CO2storage site using the ACROSS source systemWe estimated near‐surface Swave velocity variations possibly related to changes in the degree of freezing of partially saturated rockHigh temporal stability of our monitoring approach may make it possible to immediately identify CO2leakage in the shallow subsurface

The detection of deformation in Global Navigation Satellite System (GNSS) time series associated with (a)seismic events down to a low magnitude is still a challenging issue. The presence of a considerable amount of noise in the data makes it difficult to reveal patterns of small ground deformation. Traditional analyses and methodologies are able to effectively retrieve the deformation associated with medium to large magnitude events. However, the automatic detection and characterization of such events is still a complex task, because traditionally employed methods often separate the time series analysis from the source characterization. Here we propose a first end‐to‐end framework to characterize seismic sources using geodetic data by means of deep learning, which can be an efficient alternative to the traditional workflow, possibly overcoming its performance. We exploit three different geodetic data representations in order to leverage the intrinsic spatio‐temporal structure of the GNSS noise and the target signal associated with (slow) earthquake deformation. We employ time series, images, and image time series to account for the temporal, spatial, and spatio‐temporal domain, respectively. Thereafter, we design and develop a specific deep learning model for each dataset. We analyze the performance of the tested models both on synthetic and real data from North Japan, showing that image time series of geodetic deformation can be an effective data representation to embed the spatio‐temporal evolution, with the associated deep learning method outperforming the other two. Therefore, jointly accounting for the spatial and temporal evolution may be the key to effectively detect and characterize fast or slow earthquakes. The continuous monitoring of ground displacement with Global Navigation Satellite System allowed, at the beginning of the 2000s, the discovery of slow earthquakes—a transient slow slippage of tectonic faults that releases stress without generating seismic waves. Nevertheless, the detection of small events is still a challenge, because they are hidden in the noise. Most of the methods which are traditionally employed are able to extract the deformation down to a certain signal‐to‐noise level. However, one can ask if deep learning can be a more efficient and powerful alternative. To this end, we address the problem by using deep learning, as it stands as a powerful way to automatize and possibly overcome traditional methods. We use and compare three data representations, that is time series, images, and image time series of deformation, which account for the temporal, spatial, and spatio‐temporal variability, respectively. We train our methods on synthetic data, since real datasets are still not enough to be effectively employed with deep learning, and we test on synthetic and real data as well, claiming that image time series and its associated deep learning model may be more effective toward the study of the slow deformation. We develop deep learning approaches on synthetics mimicking the spatio‐temporal structure of static deformation and realistic Global Navigation Satellite System (GNSS) noiseWe design three deep learning models and we train and test them against three GNSS data representationsTransformers and image time series of deformation can effectively characterize small deformation patterns associated with the seismic source We develop deep learning approaches on synthetics mimicking the spatio‐temporal structure of static deformation and realistic Global Navigation Satellite System (GNSS) noise We design three deep learning models and we train and test them against three GNSS data representations Transformers and image time series of deformation can effectively characterize small deformation patterns associated with the seismic source

The potential for devastating earthquakes in the Himalayan orogeny has long been recognized. The 2015 MW7.8 Gorkha, Nepal earthquake has heightened the likelihood that major earthquakes will occur along this orogenic belt in the future. Reliable seismic hazard assessment is a critical element in development of policy for seismic hazard mitigation and risk reduction. In this study, we conduct probabilistic seismic hazard assessment using three different seismogenic source models (smoothed gridded, linear, and areal sources) based on the complicated tectonics of the study area. Two sets of ground motion prediction equations are combined in a standard logic tree by taking into account the epistemic uncertainties in hazard estimation. Long‐term slip rates and paleoseismic records are also incorporated in the linear source model. Peak ground acceleration and spectral acceleration at 0.2 s and 1.0 s for 2% and 10% probabilities of exceedance in 50 years are estimated. The resulting maps show significant spatial variation in seismic hazard levels. The region of the Lesser Himalaya is found to have high seismic hazard potential. Along the Main Himalayan Thrust from east to west beneath the Main Central Thrust, large earthquakes have occurred regularly in history; hazard values in this region are found to be higher than those shown on existing hazard maps. In essence, the combination of long span earthquake catalogs and multiple seismogenic source models gives improved seismic hazard constraints in Nepal.

Seismic imaging during piling may reduce construction costs in sensitive areas, and combined with technology to look ahead of the pile tip, the risk of stopping the piling before reaching the bedrock may be reduced. Seismic images obtained during piling can give vital information about the subsurface structure in the vicinity of the pile. In this paper, we discuss how to produce seismic images as a part of the piling procedure without using any external seismic sources. Using surface and borehole synthetic data examples, we show that it is possible to use pressure (P) waves emitted from the pile tip for imaging purposes. A pilot field study was carried out to test the feasibility of this method. The field study revealed that high‐frequency pressure waves are emitted from the pile tip. However, they are masked by strong surface and shear waves, especially at the nearer offsets. The data processing approach allowed us to achieve reasonable signal‐to‐noise ratio for pressure waves at the further offsets, while the signal was not as well recovered at the nearer offsets. This study demonstrates that it is possible to acquire fair‐quality signals without using any seismic source other than the impact on the pile itself. More field data are needed and some acquisition procedures need to be optimized before the method can be applied for practical imaging.

We present the updated seismic source characterization (SSC) for the 2014 update of the National Seismic Hazard Model (NSHM) for the conterminous United States. Construction of the seismic source models employs the methodology that was developed for the 1996 NSHM but includes new and updated data, data types, source models, and source parameters that reflect the current state of knowledge of earthquake occurrence and state of practice for seismic hazard analyses. We review the SSC parameterization and describe the methods used to estimate earthquake rates, magnitudes, locations, and geometries for all seismic source models, with an emphasis on new source model components. We highlight the effects that two new model components—incorporation of slip rates from combined geodetic-geologic inversions and the incorporation of adaptively smoothed seismicity models—have on probabilistic ground motions, because these sources span multiple regions of the conterminous United States and provide important additional epistemic uncertainty for the 2014 NSHM.

Influence of different models and assumptions with respect to seismic source modelling and magnitude distribution on seismic hazard results is examined, taking Jordan as a case study. Four alternative models, which are based on different combinations of seismic source models and magnitude-recurrence relationships, are considered. Seismic hazard curves obtained at four different sites in Jordan according to these four models are compared. In order to display the magnitude of spatial variation of peak ground acceleration (PGA) values obtained from these models, difference maps for return periods of 475 and 2475 years are constructed. Logic tree method is applied to aggregate the results calculated based on different models and assumptions. Then, best estimate seismic hazard maps for PGA and spectral acceleration at 0.2 and 1.0 s corresponding to return periods of 475 and 2475 years are plotted.

The sources of ambient seismic noise are extensively studied both to better understand their influence on ambient noise tomography and related techniques, and to infer constraints on their excitation mechanisms. Here we develop a gradient‐based inversion method to infer the space‐dependent and time‐varying source power spectral density of the Earth's hum from cross correlations of continuous seismic data. The precomputation of wavefields using spectral elements allows us to account for both finite‐frequency sensitivity and for three‐dimensional Earth structure. Although similar methods have been proposed previously, they have not yet been applied to data to the best of our knowledge. We apply this method to image the seasonally varying sources of Earth's hum during North and South Hemisphere winter. The resulting models suggest that hum sources are localized, persistent features that occur at Pacific coasts or shelves and in the North Atlantic during North Hemisphere winter, as well as South Pacific coasts and several distinct locations in the Southern Ocean in South Hemisphere winter. The contribution of pelagic sources from the central North Pacific cannot be constrained. Besides improving the accuracy of noise source locations through the incorporation of finite‐frequency effects and 3‐D Earth structure, this method may be used in future cross‐correlation waveform inversion studies to provide initial source models and source model updates. The Earth's hum is a low‐frequency, background seismic signal excited by the interplay of long periodic ocean waves with the Earth's solid crust. We present the first real‐data application of a new localization technique for the sources of hum, which can be used for similar ambient sources in future studies. This technique can account for realistic wave propagation effects of seismic waves in the Earth. This is achieved by storing simulated responses of the Earth to impulsive sources, so‐called Green's functions, in order to use them during localization. Our results confirm previous findings that the sources of the Earth's hum vary seasonally, occurring at Pacific coasts or shelves and in the North Atlantic during North Hemisphere winter, as well as South Pacific coasts and several distinct locations in the Southern Ocean in South Hemisphere winter. Our results also appear to indicate that hum sources are rather localized in space. We apply gradient‐based ambient noise source inversion to long periodic “hum” cross correlationsThe inversion procedure fully accounts for heterogeneous Earth structure and finite‐frequency sensitivityHum sources appear persistent and narrowly localized at coasts or shelves and high bathymetry

Earthquake source properties such as seismic moment and stress drop are routinely estimated from far‐field body wave amplitude spectra. Some quantitative but model‐dependent relations have been established between seismic spectra and source parameters. However, large variability is seen in the parameter estimates, and it is uncertain how the variability is partitioned among real variability in the source parameters, observational error, and modeling error due to complexity of earthquake behaviors. Earthquake models with dynamic weakening have been found to exhibit two different modes of rupture: expanding‐crack and self‐healing pulse modes. Four representative models are generated to model the transition from crack‐like to pulse‐like. Pulse‐like rupture leads to development of a second corner frequency, and the intermediate spectral slope is approximately 2 in most cases. The focal‐sphere‐averaged lower Pand Swave corner frequencies are systematically higher for pulse‐like models than crack models of comparable rupture velocity. The slip‐weighted stress drop ΔσEexceeds the moment‐based stress drop ΔσMfor pulse‐like ruptures, with the ratio ranging from about 1.3 to 1.65, while they are equal for the crack‐like case. The variations in rupture mode introduce variability of the order of a factor of 2 in standard (i.e., crack model‐based) spectral estimates of stress drop. The transition from arresting‐ to growing‐pulse rupture is accompanied by a large (factor of ∼1.6) increase in the radiation ratio. Thus, variations in rupture mode may account for the portion of the scatter in observational spectral estimates of source parameters. Corner frequency changes in crack‐like and pulse‐like modelsStress drop estimate varies with source characteristicsDouble spectral decay slopes

The accurate determination of stress drop, seismic efficiency, and how source parameters scale with earthquake size is an important issue for seismic hazard assessment of induced seismicity. We propose an improved nonparametric, data-driven strategy suitable for monitoring induced seismicity, which combines the generalized inversion technique together with genetic algorithms. In the first step of the analysis the generalized inversion technique allows for an effective correction of waveforms for attenuation and site contributions. Then, the retrieved source spectra are inverted by a nonlinear sensitivity-driven inversion scheme that allows accurate estimation of source parameters. We therefore investigate the earthquake source characteristics of 633 induced earthquakes (Mw2–3.8) recorded at The Geysers geothermal field (California) by a dense seismic network (i.e., 32 stations, more than 17.000 velocity records). We find a nonself-similar behavior, empirical source spectra that require an ??source model with ?> 2 to be well fit and small radiation efficiency ?SW. All these findings suggest different dynamic rupture processes for smaller and larger earthquakes and that the proportion of high-frequency energy radiation and the amount of energy required to overcome the friction or for the creation of new fractures surface changes with earthquake size. Furthermore, we observe also two distinct families of events with peculiar source parameters that in one case suggests the reactivation of deep structures linked to the regional tectonics, while in the other supports the idea of an important role of steeply dipping faults in the fluid pressure diffusion. A novel data-driven strategy for monitoring induced seismicity that combines generalized inversion and genetic algorithm is presentedStudying the seismicity at The Geysers geothermal field, we found different dynamic rupture processes for smaller and larger earthquakesTwo groups of events suggest the reactivation of deep structures and an important role of steeply dipping fault in fluid pressure diffusion

Since 2008, eruptive activity at the summit of Kı̄lauea Volcano, Hawai‘i has been confined to the new Overlook pit crater within the Halema‘uma‘u Crater. Among the broad range of magmatic processes observed in the new pit are recurring episodes of gas pistoning. The gas‐piston activity is accompanied by seismic signals that are recorded by a broadband network deployed in the summit caldera. We use raw data recorded with this network to model the source mechanism of representative gas‐piston events in a sequence that occurred on 20–25 August 2011 during a gentle inflation of the Kı̄lauea summit. To determine the source centroid location and source mechanism, we minimize the residual error between data and synthetics calculated by the finite difference method for a point source embedded in a homogeneous medium that takes topography into account. We apply a new waveform inversion method that accounts for the contributions from both translation and tilt in horizontal seismograms through the use of Green's functions representing the seismometer response to translation and tilt ground motions. This method enables a robust description of the source mechanism over the period range 1–10,000 s. Most of the seismic wavefield produced by gas‐pistoning originates in a source region ∼1 km below the eastern perimeter of the Halema‘uma‘u pit crater. The observed waveforms are well explained by a simple volumetric source with geometry composed of two intersecting cracks featuring an east striking crack (dike) dipping 80°to the north, intersecting a north striking crack (another dike) dipping 65° to the east. Each gas‐piston event is marked by a similar rapid inflation lasting a few minutes, trailed by a slower deflation ramp extending up to 15 min, attributed to the efficient coupling at the source centroid location of the pressure and momentum changes accompanying the growth and collapse of a layer of foam at the top of the lava column. Assuming a simple lumped parameter representation of the shallow magmatic system, the observed pressure and volume variations can be modeled with the following attributes : foam thickness (10–50 m), foam cell diameter (0.04–0.10 m), and gas‐injection velocity (0.01–0.06 m s−1). Gas‐piston activity occurs in a narrow pipe with diameter of 6 m connecting the Halema‘uma‘u pit crater to the subjacent dike system. The height of the magma column is estimated at ∼104 m at the start of the sequence based on the period of very long period (VLP) oscillations accompanying the onset of the gas‐piston signal. Based on the change in the period of VLP oscillations and tilt evidence, the height of the magma column is inferred to have risen by up to ∼23 m by the end of the 5 day long sequence. A penny‐shaped crack model of the dike geometry yields effective diameters of ∼1.2–2.9 km for the east dike and 0.7 km for the north dike. The shallower north dike segment is embedded in a relatively weak medium, compatible with expected mechanical properties in the hydrothermal environment of this dike. The near‐field ground response to gas pistoning is dominated by tiltGas‐pistoning activity is simulated with a foam growth and collapse modelFoam‐wall friction plays a key role in the seismic source dynamics

To explain how fracture roughness affects seismic source and transport response of deformed fractured rock, we developed a microscale fluid flow‐geomechanics‐seismicity model. The modeling method considers comprehensive grains and cement interactions. Fluid flow behavior is obtained through realistic network models of the pore space in the compacted assembly. In addition, forces and displacements in the grains involved in the bond breakage are measured to determine seismic moment tensor. The results of our work show that in addition to stress conditions in the target formation, geological properties of preexisting fractures affect volumetric deformation of the seismic source as well. The results of the model proves that roughness of fractures, applied in a Berea sample, causes deviation of source mechanism of acoustic emission events toward opening tensile part and enhances the permeability of the sample significantly during its failure even under confining pressure. Hydro‐mechanical‐seismic model is applied to study fracture deformationVolumetric deformation of fracture is affected by its geological propertiesFracture roughness affect its transport and seismic source responses

Both natural and anthropogenic seismic sources generate so‐called ambient seismic waves. One in turn can use ambient seismic waves to estimate these source distributions and study source characteristics, for instance the source mechanism. A commonly used estimation method is called matched field processing (MFP), and the MFP results are inherently smeared by the array geometry. Another approach to estimate ambient seismic sources is to apply full waveform inversion (FWI) to the crosscorrelations of ambient seismic wave recordings. Both methods have pros and cons, but the model resolution and uncertainty in these two methods are important for the interpretation. Unfortunately, this topic has attracted little attention in the past. We propose to estimate both the model resolution matrix and model covariance matrix of the inversion using singular value decomposition. We demonstrate our estimates using two examples, one of which is an actual field array geometry. We quantitatively compare the model resolution of the two methods and discuss the model null space. We demonstrate that FWI has superior resolution with enough independent data and should be used when computational resources permit. Many natural phenomena (such as ocean waves due to a hurricane or glacier tremor due to subglacial water flow) can shake the ground and generate seismic waves. By studying the seismic waves, we can image these natural phenomena in space and monitor the temporal evolution of these phenomena. We focus on two common methods to image these passive sources: matched field processing (MFP) and full waveform inversion (FWI). The resolution and uncertainties of these two methods are important for interpreting imaging results. Thus, we derive and calculate the model resolution for each method. We also study the model trade‐off of full waveform inversion to quantify the uncertainty in the inversion results. We compare the resolution of the two methods using a realistic field seismic array form a past experiment. We show that FWI has better resolution than MFP when all seismic sensors in the array are used, indicating that FWI should be the preferred method for ambient noise source imaging when computational resources permit its use. We present the model resolution and point spread function for two ambient seismic source estimation methods, FWI and MFPWe demonstrate that with enough independent data, FWI possesses higher resolution than MFPWe quantify the model covariance of FWI to provide the source strength trade‐offs We present the model resolution and point spread function for two ambient seismic source estimation methods, FWI and MFP We demonstrate that with enough independent data, FWI possesses higher resolution than MFP We quantify the model covariance of FWI to provide the source strength trade‐offs

Weight drop systems were some of the earliest, and in some areas most successful, seismic source systems ever used. Traditional systems typically used a 3-ton weight mounted on the back [...]

Accurate localization of shallow subsurface seismic events recorded by an array of receivers might be challenging given the near‐surface complexity and its inadequate spatial sampling, low velocities, and limited frequency content. A novel approach that performs a joint localization and velocity analysis is presented. In this study, we utilize non‐conventional migrated common image gathers as a tool for velocity and location analysis, based on the diffractive nature of the source. Only when the correct velocity model is used energy from all receivers is coherently focused at the true subsurface location. However, if the used model or CIG location is wrong, the migrated event does not have a flat moveout. The effectiveness of this technique is greatly improved by the use of vertical arrays of receivers. Through synthetic and real data examples, we show the usefulness of the method in a fully automatic workflow.

The present work is intended to study the effect of variation of seismic area source zone on hazard value for Chennai, India. In the conventional Cornell-McGuire approach to probabilistic seismic hazard analysis, the seismic activity rate for an area source is most often determined using the Gutenberg-Richter (G-R) recurrence law. The seismic area is delineated using geology, geography and/or seismotectonic characteristics of the region. However if the area lies in a distributed seismicity region, the delineation into different area zones introduces subjectivity. The impact of the areal extent of seismic area zone on the final hazard value is studied using two approaches - the conventional Cornell-McGuire and zone-free approaches. It is observed that in the conventional Cornell-McGuire approach, the peak ground acceleration decreases when the area source zone is increased while maintaining all other seismicity parameters same. In the kernel method, the PGA remained unchanged though the seismic source area is increased. This is due to the fact that in the kernel method, the seismic activity rate is a spatially varying parameter unlike the seismic activity rate determined from the G-R recurrence law, which assumes a homogeneous distribution of the activity rate for each of the area source zones. The uniform hazard spectra are obtained for various return periods by both the approaches. It is observed that in the Cornell-McGuire approach, the variation in the extent of seismic source area has little effect on longer return periods as compared to the smaller return periods.

The delineation of seismic source zones plays an important role in the evaluation of seismic hazard. In most of the studies the seismic source delineation is done based on geological features. In the present study, an attempt has been made to delineate seismic source zones in the study area (south India) based on the seismicity parameters. Seismicity parameters and the maximum probable earthquake for these source zones were evaluated and were used in the hazard evaluation. The probabilistic evaluation of seismic hazard for south India was carried out using a logic tree approach. Two different types of seismic sources, linear and areal, were considered in the present study to model the seismic sources in the region more precisely. In order to properly account for the attenuation characteristics of the region, three different attenuation relations were used with different weightage factors. Seismic hazard evaluation was done for the probability of exceedance (PE) of 10% and 2% in 50 years. The spatial variation of rock level peak horizontal acceleration (PHA) and spectral acceleration (Sa) values corresponding to return periods of 475 and 2500 years for the entire study area are presented in this work. The peak ground acceleration (PGA) values at ground surface level were estimated based on different NEHRP site classes by considering local site effects.

Considering the signal attenuation in deep well affects the use of the new wellbore anti-collision technology based on vibration wave, a kind of borehole seismic source designed. The distance among the risk wells can be identified by collecting the vibration signal produced by this borehole seismic source. The whole device includes energy storage and impact part, control part and auxiliary part. This borehole seismic source bases on the spring energy storage as basic principle. The impact hammer impacts the anvil as the impact institutions. The stuck points consist of arc fastener and arc grooves. The structure is simple and reliable. The function is easy to realize. The laboratory experiment results showed that this mechanical borehole seismic source can generate certain intensity and independent signals. The volume of the impact strength can fulfill the basis prevention warning of the monitoring the wellbore collision in deep layers.

Under the direction of National Cooperative for the Disposal of Radioactive Waste (NAGRA), a probabilistic seismic hazard analysis was conducted for the Swiss nuclear power plant sites. The study has become known under the name “PEGASOS Project.” This is the first of a group of papers in this volume that describes the seismic source characterization methodology and the main results of the project. A formal expert elicitation process was used, including dissemination of a comprehensive database, multiple workshops for identification and discussion of alternative models and interpretations, elicitation interviews, feedback to provide the experts with the implications of their preliminary assessments, and full documentation of the assessments. A number of innovative approaches to the seismic source characterization methodology were developed by four expert groups and implemented in the study. The identification of epistemic uncertainties and treatment using logic trees were important elements of the assessments. Relative to the assessment of the seismotectonic framework, the four expert teams identified similar main seismotectonic elements: the Rhine Graben, the Jura / Molasse regions, Helvetic and crystalline subdivisions of the Alps, and the southern Germany region. In defining seismic sources, the expert teams used a variety of approaches. These range from large regional source zones having spatially-smoothed seismicity to smaller local zones, to account for spatial variations in observed seismicity. All of the teams discussed the issue of identification of feature-specific seismic sources (i.e. individual mapped faults) as well as the potential reactivation of the boundary faults of the Permo-Carboniferous grabens. Other important seismic source definition elements are the specification of earthquake rupture dimensions and the earthquake depth distribution. Maximum earthquake magnitudes were assessed for each seismic source using approaches that consider the magnitudes of observed earthquakes within analogous tectonic regions. All four expert teams used the PEGASOS earthquake catalogue for estimating earthquake recurrence parameters. This catalogue was developed by the Swiss Seismological Service and provided all historical and instrumental events in a uniform moment magnitude. The teams evaluated alternative declustering approaches and used available historical data to assess catalog completeness as a function of location, magnitude, and time period.

We present probabilistic centroid‐moment tensor solutions inferred from the combination of Hamiltonian Monte Carlo sampling and a 3‐D full‐waveform inversion Earth model of the Japanese islands. While the former provides complete posterior probability densities, the latter allows us to exploit waveform data with periods as low as 15 s. For the computation of Green's functions, we employ spectral‐element simulations through the radially anisotropic and visco‐elastic model, leading to substantial improvements of data fit compared to layered models. Focusing on 13 Mw4.8–Mw5.3 offshore earthquakes with a significant non‐double‐couple (non‐DC) component, we simultaneously infer the centroid location, time and moment tensor without any a priori constraints on the faulting mechanism. Furthermore, we perform the inversions across several period bands, varying the minimum period between 15 and 50 s. Accounting for 3‐D Earth structure at shorter periods can increase the double‐couple (DC) component of an event, compared to the GCMT solution, by tens of percent. This suggests that non‐DC events in the GCMT catalog may result from unmodeled Earth structure and the related limitation to longer‐period data. We also observe that significant changes in source parameters, and the DC component in particular, may be related to only small waveform changes, thereby accentuating the importance of a reliable Earth model. Posterior probability density distributions become increasingly multimodal for shorter‐period data that provide tighter constraints on source parameters. This implies, in our specific case, that stochastic approaches to the source inversion problem are required for periods below ∼20 s to avoid trapping in local minima. In the majority of global earthquake catalogs, the earthquake solution, that is, centroid location, time and a rupture mechanism, is typically inferred assuming a 1‐D Earth model. However, both earthquake source and Earth structure contribute to seismic recordings, meaning that unaccounted structure might map into and pollute the source solution. In this study we use a 3‐D Earth structure of the Japanese islands to model the waveforms and infer earthquake parameters of 13 small‐to‐moderate magnitude offshore events. We do not put any a priori constraints on the faulting mechanism and let it be determined by the data. We perform stochastic inversions, which provide us with a collection of all plausible models ranked by their respective probability. When a 3‐D Earth structure at shorter periods is taken into account, the earthquake mechanisms, investigated in this study, can be largely explained by a slip on the fault. We also observe that significant changes in source parameters may be related to tiny waveform changes, thereby accentuating the importance of a reliable Earth model. Full‐waveform inversion models enable the use of shorter‐period data in earthquake source inversionUsing regional waveforms at 15 s period may reduce non‐double‐couple components by tens of percentProbability densities of source parameters below 20 s are non‐Gaussian, thus demanding stochastic inversion approaches Full‐waveform inversion models enable the use of shorter‐period data in earthquake source inversion Using regional waveforms at 15 s period may reduce non‐double‐couple components by tens of percent Probability densities of source parameters below 20 s are non‐Gaussian, thus demanding stochastic inversion approaches

When Tim Snape of Abbotsbury Software, a company based in southern England, set out to develop the Portland Horn in the early 1990's, he had in mind a simple device [...]

We compared spatiotemporal slip‐rate and high‐frequency (around 1 Hz) radiation distributions from teleseismic Pwave data to infer the seismic rupture process of the 2015 Gorkha, Nepal, earthquake. For these estimates, we applied a novel waveform inversion formulation that mitigates the effect of Green's functions uncertainty and a hybrid backprojection method that mitigates contamination by depth phases. Our model showed that the dynamic rupture front propagated eastward from the hypocenter at 3.0 km/s and triggered a large‐slip event centered about 50 km to the east. It also showed that the large‐slip event included a rapid rupture acceleration event and an irregular deceleration of rupture propagation before the rupture termination. Heterogeneity of the stress drop or fracture energy in the eastern part of the rupture area, where aftershock activity was high, inhibited rupture growth. High‐frequency radiation sources tended to be in the deeper part of the large‐slip area, which suggests that heterogeneity of the stress drop or fracture energy there may have contributed to the damage in and around Kathmandu. Novel formulations were used to obtain the 2015 Nepal earthquake rupture processDynamic rupture propagated eastward from the hypocenter to KathmanduHeterogeneity of the stress drop or fracture energy inhibited rupture growth

Reduced displacement potentials (RDPs) for chemical explosions of the Source Physics Experiments (SPE) in granite at the Nevada Nuclear Security Site are estimated from free‐field ground motion recordings. Far‐field Pwave source functions are proportional to the time derivative of RDPs. Frequency domain comparisons between measured source functions and model predictions show that high‐frequency amplitudes roll off as ω− 2, but models fail to predict the observed seismic moment, corner frequency, and spectral overshoot. All three features are fit satisfactorily for the SPE‐2 test after cavity radius Rcis reduced by 12%, elastic radius is reduced by 58%, and peak‐to‐static pressure ratio on the elastic radius is increased by 100%, all with respect to the Mueller‐Murphy model modified with the Denny‐Johnson Rcscaling law. A large discrepancy is found between the cavity volume inferred from RDPs and the volume estimated from laser scans of the emplacement hole. The measurements imply a scaled Rcof ~5 m/kt1/3, more than a factor of 2 smaller than nuclear explosions. Less than 25% of the seismic moment can be attributed to cavity formation. A breakdown of the incompressibility assumption due to shear dilatancy of the source medium around the cavity is the likely explanation. New formulas are developed for volume changes due to medium bulking (or compaction). A 0.04% decrease of average density inside the elastic radius accounts for the missing volumetric moment. Assuming incompressibility, established Rcscaling laws predicted the moment reasonable well, but it was only fortuitous because dilation of the source medium compensated for the small cavity volume. Current models cannot predict source functions of small, shallow chemical explosionsCavity formation is not the main mechanism for seismic moment releaseBulking of the medium is responsible for more than 75% of the seismic moment

This paper provides an overview of the ground motion and seismic source aspects of the Canterbury earthquake sequence. Common reported attributes among the largest earthquakes in this sequence are complex ruptures, large displacements per unit fault length, and high stress drops. The Darfield earthquake produced an approximately 30 km surface rupture in the Canterbury Plains with dextral surface displacements of several meters, and a subordinate amount of vertical displacement, impacting residential structures, agricultural land, and river channels. The dense set of strong ground motions recorded in the near-source region of all the major events in the sequence provides significant insight into the spatial variability in ground motion characteristics, as well as the significance of directivity, basin-generated surface waves, and nonlinear local site effects. The ground motion amplitudes in the 22 February 2011 earthquake, in particular, produced horizontal ground motion amplitudes in the Central Business District (CBD) well above those specified for the design of conventional structures.

The number of gigaton‐sized iceberg‐calving events occurring annually at Greenland glaciers is increasing, part of a larger trend of accelerating mass loss from the Greenland Ice Sheet. Though visual observation of large calving events is rare, ∼60 glacial earthquakes generated by these calving events are currently recorded each year by regional and global seismic stations. An empirical relationship between iceberg size and MCSF, a summary measure of glacial‐earthquake size, was recently demonstrated by Olsen and Nettles (2019), https://doi.org/10.1029/2019JF005054. However, MCSFis known to be sensitive to choices made in modeling the seismic source. We incorporate constraints on the seismic source from laboratory studies of calving and test multiple source time functions using synthetic and observed glacial‐earthquake waveforms. We find that a simple, fixed time function with a shape informed by laboratory results greatly improves estimates of earthquake size. The average ratio of estimated to true peak force values is 1.03 for experiments using our preferred source model, compared with an average of 0.3 for models used in previous studies. We find that maximum‐force values estimated from waveform modeling depend far less on model choices than does MCSF, and therefore prefer maximum force as a measure of glacial‐earthquake size. Using both synthetic and real data, we confirm a correlation between maximum force and iceberg mass. Our results support the possibility of developing useful scaling relationships between seismic observables and physical parameters controlling glacier calving. The Greenland Ice Sheet is losing ice mass. About half of that ice is lost when large icebergs break off, or calve, from the fronts of glaciers into the ocean. Knowing the sizes of these icebergs would be valuable, but iceberg calving is rarely captured on camera. However, the largest icebergs produce seismic signals when they calve, referred to as glacial earthquakes. We investigate the relationship between the size of an iceberg and the magnitude of the glacial earthquake it produces, building new models to describe the forces that generate a glacial earthquake. Previously, most details of the force evolution during iceberg calving were unknown. We use observations from laboratory experiments conducted using a plastic block in a tank of water, built to mimic the glacier‐ocean setting. We find that incorporating information from these laboratory experiments into our seismic model greatly improves estimates of earthquake size. Using our new models, we confirm a correlation between glacial‐earthquake magnitude and iceberg size, and show that our improved estimates are likely to be more realistic. Our results suggest that using seismic information to estimate iceberg size and related quantities is a promising path forward. A physics‐based source model for glacial‐earthquake modeling improves recovery of seismic‐magnitude valuesMaximum force is less sensitive to model choices than MCSFand is preferred for describing glacial‐earthquake sizeA rapid force reversal during iceberg calving is the most important feature to capture in a glacial‐earthquake source model A physics‐based source model for glacial‐earthquake modeling improves recovery of seismic‐magnitude values Maximum force is less sensitive to model choices than MCSFand is preferred for describing glacial‐earthquake size A rapid force reversal during iceberg calving is the most important feature to capture in a glacial‐earthquake source model

We analyze seismic waves excited by small Strombolian explosions to understand the source process of volcanic explosions. We deployed five broadband seismometers at only 100–300 m away from the active craters of Stromboli volcano, Italy. Moment tensor inversion of the entire seismic signals in the 0.05–0.2 Hz band locates the source at a depth of 170 and 150–200 m west/southwest of the crater where acoustic waves are excited. Contrary, the sources of seismic waves in the 0.2–0.5 and 0.5–1.0 Hz bands are excited almost at the explosion onset and are located close to the crater. We show for the first time that explosions are preceded of about 10–20 s by a small amplitude seismic phase. Semblance analysis shows that this phase is radiated from a depth of 170 m beneath the western part of the crater area. Our analysis indicates that the source moves about 50 m toward the active crater 10–20 s before the explosion occurs at the surface. At the explosion onset, the source moves back to the same location of the small preceding phase. These lateral migrations of the seismic source are estimated by moment tensor inversion and semblance analysis. We suggest that migration reflects the bending of the shallow feeding system toward northeast. Seismic waves are thus reflecting the history pressure generated by the rising of a gas‐rich pocket in the very shallow portion of a magma mush and by the following restoring force occurring after the explosion. We analyze seismic waves repeatedly excited before, during and after small explosions at the summit crater of Stromboli volcano, Italy, to understand the magma motions in the shallow conduit and reservoir system. To improve the spatio‐temporal resolution and detect slight movement of magma, we deployed broad‐band seismometers very close to the active craters with a distance range of 100–300 m. As a result, we succeeded in clarifying detailed horizontal spatio‐temporal change of seismic sources for about 1 min before and after each explosion. First seismic source, which is for the first time detected in seismogram as a very small amplitude phase, appears at a depth of about 170 m beneath the western part of the active craters. About 20 s later, the seismic source moves about 50 m toward the craters to generate an explosion. Just after the explosion, the seismic source moves back to the west where the initial small seismic source is located. Such detailed horizontal spatio‐temporal change reflects the migration and/or the resonance of gas‐rich magma batch in the very shallow reservoir. Migration of seismic source in a set of explosion at Stromboli is estimated by moment tensor inversion and semblance analysesSource laterally migrates from the west to the crater just before an explosion, and moves back to the initial location during the explosionSmall seismic signal in the 0.05–0.2 Hz frequency band is detected 10–20 s before the explosive onset Migration of seismic source in a set of explosion at Stromboli is estimated by moment tensor inversion and semblance analyses Source laterally migrates from the west to the crater just before an explosion, and moves back to the initial location during the explosion Small seismic signal in the 0.05–0.2 Hz frequency band is detected 10–20 s before the explosive onset

Most modern ground-motion prediction equations (GMPE) use definitions of the source-to-site distance that reflect the dimensions of the fault rupture for larger earthquakes rather than using point-source measures relative to the epicenter or hypocenter. This is a positive development since it more realistically reflects the fact that energy is released from the crust around the entire fault rupture during a large earthquake. However, seismic source configurations defined for probabilistic seismic hazard analysis (PSHA) almost invariably include areas of distributed point-source seismicity in addition to linear fault sources, particularly in regions of lower earthquake activity. Herein, two GMPEs are derived from the same dataset to demonstrate the errors that can result from combining point-source simulations and extended-source distance metrics. The case is made for all ground-motion model developers to consider deriving pairs of equations, one using an extended-source distance metric, the other a point-source measure.

Satellite SAR Interferometry (InSAR) has already proved its effectiveness in the analysis of seismic events. In fact, measuring the surface displacement field generated by an earthquake can be useful to define fault parameters regarding the geometry (such as dip and strike angles, width, length), the extension of the rupture and the distribution of slip on the fault plain. However, to retrieve the source parameters from InSAR measurements is rather complex since the inversion problem is ill-posed. In this work we propose an inversion approach for retrieving the fault parameters based on neural networks, trained by simulated data sets generated by means of the Okada forward model. The developed work-flow implements a pre-processing step, aiming to reducing the data dimensionality, in order to improve the performance of the neural network inversion. The methodology has been validated by using experimental data sets obtained using different wavelength and representative of different kind of seismic source mechanisms.

A comprehensive study of the seismic hazard related to the four NNP sites in NW Switzerland was performed within the project PEGASOS. To account for the epistemic uncertainties involved in the process of the characterization of seismic source zones in the frame of probabilistic seismic hazard assessments, four different expert teams have developed and defended their models in the frame of an intensive elicitation process.

Seismic source characterization is performed as part of the PEGASOS project for the assessment of the seismic hazard at the 4 sites of the Swiss Nuclear Power Plants. The analysis is performed according to the Level 4 procedures for expert elicitation defined in the guidelines of the US Nuclear Regulatory Committee whereby the quantification of uncertainties plays a crucial role. According to our analysis, which is one amongst four that were performed in the frame of PEGASOS, the most important epistemic uncertainty is related to the question as to weather basement-rooted faults at the margins of pre-existing Permo-Carboniferous troughs are prone for compressive or transpressive reactivation under the present-day stress field or not. The question after the present-day style of deformation in the Alpine foreland (thick-skinned versus thin-skinned) is closely related to this key question. Together with the consideration of uncertainties regarding the mapping of seismogenic zones and/or line sources alternative zonations are presented in form of a logic tree with 21 branches. Area sources play a predominant role in the working area located at the margin of a diffuse plate boundary.

We report the results of continuous monitoring—using a seismometer array—of the travel time of seismic waves generated by an ACROSS artificial seismic source. The seismometer array, which was deployed in a surface vault located 2.4 km from the source, recorded both direct P- and S-waves and refracted P- and S-waves that traveled along a velocity boundary between the granite basement and overlying sedimentary rocks. We analyzed temporal variation in differential travel time and apparent velocity for these phases for a period of 1 month and found significant temporal variation in the differential travel time. Most of the variation can be attributed to changes in environmental conditions, such as atmospheric temperature and rainfall. Variation is even observed in the seismogram that is located 50 m from the vibration source, although much smaller variation is observed in the vibration of the foundation to which the source is attached. The spectral study revealed that the effects of temperature and rainfall depend strongly on the frequency range used by ACROSS and that a large variation occurs in the 15- to 20-Hz range, especially between 17 and 20 Hz. The environmental effect on the temporal variation is comparable to the record of refracted Swaves and that of a distance of 50 m, whereas a larger variation was observed in the direct Swave. This result shows that the signal is affected by the environmental change near the vibration source. The environmental effect can be drastically reduced when the signal from the 15- to 20-Hz range is eliminated in the analysis.

Abstract: We demonstrate that the idea of symmetropy can be used for quantification of earthquake patterns. The symmetropy can be considered as a measure of asymmetry. A pattern is richer in asymmetry when the symmetropy is smaller. The specific results of its applications are obtained as follows. In a discrete model of a seismic source with self-organized criticality, the spatial patterns of earthquakes during critical states and sub-critical states are distinguished by the behaviour of the symmetropy: sub-critical patterns show that the symmetropy is approximately a constant but this has various values during critical states. The critical patterns show asymmetric property without any asymmetric force from the outside and without asymmetric intracellular rule. We show that the emergence of asymmetric patterns is a generic feature of dynamic ruptures in our model. Such a generic asymmetry results from the model which is an inherently discrete system consisting of finite-sized cells. These cells may represent geometrical disordered fault zones. We further discuss rotational motions that generate seismic rotational waves. In micromorphic continuum theory, such rotations are attributed to dynamic ruptures in disordered systems. We note that the concept of disorder in this theory is expressed by a set of finite-sized microstructures and is consistent with the concept of disorder modelled in the present study. Thus, we suggest that the spatially asymmetric patterns of earthquakes might be related to the rotational motions, because both come from dynamic ruptures in a discrete fault zone without a well-defined continuum limit.

Earthquake source parameters are important for understanding earthquake physics and crustal fault properties. However, strong trade‐offs between parameters (e.g., depth and origin time) and a lack of accurate velocity models and near‐field seismic stations could cause large uncertainties of these parameters in seismic catalogs, particularly for shallow events. To further improve the resolution of earthquake source parameters, we use Interferometric Synthetic Aperture Radar (InSAR) images to derive source solutions of 33 moderate‐size (Mw4.1–6.6) earthquakes that occurred at shallow depths (<20 km) from November 2014 to July 2020 in western China. After evaluating the uncertainties of the InSAR solutions, we systematically compare the location, centroid depth, focal mechanism and magnitude from InSAR models with that from seismic catalogs. We find that all seismic catalogs generally report deeper (4–10 km) hypocenters or centroid depths. The uncertainties of moment tensor solutions are partially related to the percentage of the non‐double‐couple components in the seismic catalogs. The InSAR solutions indicate that considerable seismic moments (i.e., ∼2×1018${2\times 10}^{18}$Nm) were released in the uppermost crust (i.e., <5 km) in a period of ∼6 years, which is not resolvable in the seismic catalogs. The smooth seismic moment distribution along depth indicates a gradual change of the frictional properties from the surface to the middle crust. As most of the studied earthquakes are located on secondary and/or unmapped faults, these findings imply a considerable portion of velocity‐weakening friction in the uppermost crust along immature, secondary fault systems, which should be included in the seismic hazard evaluation. Uncertainties of parameters that describe earthquake location, fault geometry, and fault slip are generally poorly known in the seismological catalogs. Due to these unknown uncertainties, the distribution of earthquakes in the shallow crust (e.g., <10 km) is not well understood, hindering our understanding of its seismic capacity. Here, we study the moderate‐size earthquakes that occurred in western China from November 2014 to July 2020. We use Interferometric Synthetic Aperture Radar (InSAR) data to obtain surface deformations caused by earthquakes in the shallow crust. We find 33 events (Mw4.1–6.6) out of 310 earthquakes that have clear InSAR signals, which are used to constrain the source parameters of these earthquakes. We estimate the uncertainties of these InSAR solutions and systematically compare them with the solutions in the seismic catalogs. Our analysis shows that all seismic catalogs report deeper source depth and the horizontal mislocations of the Global Centroid Moment Tensor catalog show geographic correlation features. InSAR solutions also show fault geometry and rupture complexity more precisely than the seismic catalogs. Our results indicate considerable earthquake energy released in the uppermost crust that is not resolvable in the seismic catalogs, which raises additional concerns on the seismic hazard possessed by the shallow earthquakes. Coseismic deformations and source solutions of 33 shallow moderate‐size earthquakes (Mw4.1–6.6) derived from Interferometric Synthetic Aperture Radar (InSAR) dataSource parameters from InSAR solutions and seismic catalogs are systematically compared to estimate their uncertaintiesInSAR solutions show considerable moments released in the uppermost crust, revealing the seismogenic capacity of the shallow crust Coseismic deformations and source solutions of 33 shallow moderate‐size earthquakes (Mw4.1–6.6) derived from Interferometric Synthetic Aperture Radar (InSAR) data Source parameters from InSAR solutions and seismic catalogs are systematically compared to estimate their uncertainties InSAR solutions show considerable moments released in the uppermost crust, revealing the seismogenic capacity of the shallow crust