Seismic Catalog Research Articles

Automated Earthquake Detection and Local Travel Time Tomography in the South‐Central Andes (32–35°S): Implications for Regional Tectonics

AbstractIn the South‐Central Andes, the crustal structures driving the tectonic evolution of the Andean Cordillera remain unresolved. So far, most seismological studies focused on the subduction interface, leaving crustal seismicity and its relationship with crustal deformation and Andean volcanism mostly unconstrained. However, because of their large number compared to higher magnitude events, the characterization of small‐magnitude crustal earthquakes is key to identify active structures and better constrain the tectonic models. In this work, we exploit 53 months of continuously recorded, three‐component waveforms from the permanent seismic network in central Chile using a deep‐learning approach to improve the detection of small‐magnitude earthquakes. To increase station coverage, we also use the seismic phases obtained from a previous temporary seismic deployment. We use the obtained seismicity catalog to refine tomographic models of that region, revealing a more detailed architecture of the Chilean forearc. Travel times calculated in the new 3‐D velocity model allowed us to locate ∼14,000 earthquakes. Refined double‐difference relocations of ∼4,900 events located beneath the West Andean Thrust suggest a large‐scale, west‐dipping structure which, together with the west‐verging tectonic front, likely contributed to the uplift and crustal deformation during the past ∼20 Myr.

A multi-objective chimp optimization algorithm for seismicity de-clustering

Earthquakes are random triggering phenomenons that generate clusters in space and time, thus creating a bias in a seismic catalog. Seismic de-clustering separates seismic catalog into mainshocks, aftershocks–foreshocks, and backgrounds, widely used in earthquake prediction models and seismic hazard assessment. The segregation of an optimal number of earthquake clusters and backgrounds is formulated as an unsupervised problem. This manuscript introduces a multi-objective chimp-optimization algorithm (MOCOA) to de-cluster seismicity of earthquake-prone regions. The chimp optimization is inspired by the natural hunting behavior of the chimp to catch the prey. The algorithm effectively balances the exploration of search space (Driving and Chasing) and exploitation around the best solution achieved so far (Attack). In MOCOA, archive controller and archive grid-based approaches are incorporated for selecting non-dominated solutions. The proposed MOCOA is tested on fifteen mathematical test problems and compared with popular algorithms like MOEA/D, MODE, MOPSO, and SPEA2. The binary version of MOCOA is designed for the de-clustering problem. In the time and space domain, respectively, two objective functions, m-Morisita Index (m-MI) and coefficient of variance (COV), are analyzed. The proposed de-clustering algorithm is applied on thirty-two-year historical seismic catalogs of the Himalayas, California, Indonesia, Japan, Iran, and Mexico. Comparative analysis between five existing benchmark de-clustering techniques is performed to check the potential of the proposed MOCOA. The simulation results generated by the proposed algorithm show that obtained de-clustered catalogs COV values lying near unity and m-MI values achieved maximum values. Validation of results using cumulative plots, lambda plots, and inter-event time versus inter-event distance plots signify the accurate discrimination of aftershocks and background events in the catalogs.

Dual threshold search method for asperity boundary determination based on geodetic and seismic catalog data

As an important model for explaining the seismic rupture mode, the asperity model plays an important role in studying the stress accumulation of faults and the location of earthquake initiation. Taking Qilian-Haiyuan fault as an example, this paper combines geodetic method and b-value method to propose a multi-source observation data fusion detection method that accurately determines the asperity boundary named dual threshold search method. The method is based on the criterion that the b-value asperity boundary should be most consistent with the slip deficit rate asperity boundary. Then the optimal threshold combination of slip deficit rate and b-value is obtained through threshold search, which can be used to determine the boundary of the asperity. Based on this method, the study finds that there are four potential asperities on the Qilian-Haiyuan fault: two asperities (A1 and A2) are on the Tuolaishan segment and the other two asperities (B and C) are on Lenglongling segment and Jinqianghe segment, respectively. Among them, the lengths of asperities A1 and A2 on Tuolaishan segment are 17.0 km and 64.8 km, respectively. And the lower boundaries are 5.5 km and 15.5 km, respectively; The length of asperity B on Lenglongling segment is 70.7 km, and the lower boundary is 10.2 km. The length of asperity C on Jinqianghe segment is 42.3 km, and the lower boundary is 8.3 km.

Tracking the Spatio‐Temporal Evolution of Foreshocks Preceding the Mw 6.1 2009 L’Aquila Earthquake

AbstractHow faulting processes lead to a large earthquake is a fundamental question in seismology. To better constrain this pre‐seismic stage, we create a dense seismic catalog via template matching to analyze the precursory phase of the Mw 6.1 L’Aquila earthquake that occurred in central Italy in 2009. We estimate several physical parameters in time, such as the coefficient of variation, the seismic moment release, the effective stress drop, and analyze spatio‐temporal patterns to study the evolution of the sequence and the earthquake interactions. We observe that the precursory phase experiences multiple accelerations of the seismicity rate that we divide into two main sequences with different signatures and features: the first part exhibits weak earthquake interactions, quasi‐continuous moment release, slow spatial migration patterns, and a lower effective stress drop, pointing to aseismic processes. The second sequence exhibits strong temporal clustering, fast seismicity expansion, and a larger effective stress drop typical of a stress transfer process. We interpret the differences in seismicity behaviors between the two sequences as distinct physical mechanisms that are controlled by different physical properties of the fault system. We conclude that the L’Aquila earthquake is preceded by a complex preparation, made up of different physical processes over different time scales on faults with different physical properties.

Physics-Based Simulation of Sequences with Foreshocks, Aftershocks and Multiple Main Shocks in Italy

We applied a new version of physics-based earthquake simulator upon a seismogenic model of the Italian seismicity derived from the latest version of the Database of Individual Seismogenic Sources (DISS). We elaborated appropriately for their use within the simulator all fault systems identified in the study area. We obtained synthetic catalogs spanning hundreds of thousands of years. The resulting synthetic seismic catalogs exhibit typical magnitude, space and time features that are comparable to those obtained by real observations. A typical aspect of the observed seismicity is the occurrence of earthquake sequences characterized by multiple main shocks of similar magnitude. Special attention was devoted to verifying whether the simulated catalogs include this notable aspect, by the use of an especially developed computer code. We found that the phenomenon of Coulomb stress transfer from causative to receiving source patches during an earthquake rupture has a critical role in the behavior of seismicity patterns in the simulated catalogs. We applied the simulator to the seismicity of the northern and central Apennines and compared the resulting synthetic catalog with the observed seismicity for the period 1650–2020. The result of this comparison supports the hypothesis that the occurrence of sequences containing multiple mainshocks is not just a casual circumstance.

Along‐Dip Segmentation of the Slip Behavior and Rheology of the Copiapó Ridge Subducted in North‐Central Chile

AbstractWe studied the along‐dip influence of the Copiapó ridge subduction in the Atacama region, North‐Central Chile by building a new seismicity catalog, including similar events and non‐volcanic tremors (NVTs). We also obtained a 3‐D tomographic model for P and S‐waves velocity (and the implied Vp/Vs ratio). We identify along‐dip segmentation involving four distinct segments: a locked seismogenic zone hosting ordinary seismicity and clusters of similar events; a transition zone with NVTs and low seismicity; an aseismic zone with slow‐slip events; and a deep zone with abundant intraslab seismicity. The velocity models show differences among these zones, with low velocity anomalies of Vp and Vs coinciding with aseismic slip zones, indicating the possible presence of fluids. Due to the spatial distribution along‐strike and along‐dip of the aseismic zones, we propose that these differences in seismogenic behavior are generated by subduction of the heterogeneous seamounts associated with the Copiapó ridge.

Active seismotectonics of the East Anatolian Fault

SUMMARYThe East Anatolian Fault (EAF) is a 700-km-long left-lateral transform fault located between the Anatolian and Arabian plates. The proximity of the Euler Pole to the Arabia–Anatolia Plate boundary leads to rapid changes in plate velocity along the boundary, which is manifested by the decreasing slip rates from east (10 mm yr–1) to west (∼1–4 mm yr–1). The EAF displays heterogeneous seismicity patterns with seismic gaps, localized clusters and broad diffuse zones. In this study, in order to understand the origin of these complexities and quantify the seismic hazard along the EAF, we present an improved seismicity catalogue with more than 26 000 earthquakes and 160 focal mechanisms from regional moment tensor inversion between 2007 and 2020. The focal mechanisms and seismicity show that the EAF dips towards north and forms a well-defined plate boundary in the east between Palu and Çelikhan with almost pure left-lateral motion. Further west, the boundary becomes broader with activity along subparallel faults. Focal mechanisms show heterogeneous stress orientations in consistence with geodetically determined strain rate field. The stress orientations show a transition from strike-slip to extension towards the west of Çelikhan. Amongst all segments of EAF, the Pütürge segment, which holds the near-repeating earthquakes in the vicinity of the nucleation of the 2020 Mw 6.8 earthquake, is distinguished with its steady and high rate of seismicity. Further east, the neighbouring Palu segment is characterized by several distinct moderate earthquakes. We do not observe any change in the seismicity rate on these segments of the EAF following large earthquakes. In order to quantify the seismic hazard along the EAF, we calculate the recurrence time and maximum magnitude for each segment by using an extended seismicity catalogue of 150 yr including the large historical earthquakes and the geodetic strain rate. The results show ∼150 yr recurrence time with Mmax∼6.7–7.0 along the seismically active Palu and Pütürge segments on the east, while relatively silent western segments yield longer recurrence times; 237–772 for Pazarcık and 414–917 for Amanos segments with slightly larger magnitudes (Mmax ∼7–7.4). We infer that the seismicity patterns and strain-rate field along the EAF are shaped by several factors such as strong geometrical irregularities, heterogeneous coupling and complex plate motion leading to rapid change of fault slip rate.

Analyzing the 2020 Mw 6.4 Puerto Rico Earthquake Sequence Based on the Epidemic-Type Aftershock Sequence Model

Abstract On 7 January 2020, an Mw 6.4 earthquake occurred on the southwest coast of Puerto Rico, causing severe infrastructure damage and economic property losses. Accompanied with the mainshock, a large number of aftershocks occurred. For investigating the seismological activities, the earthquake sequence is fitted using the ETAS (epidemic-type aftershock sequence) model, based on a seismic catalog with 360 days in the region. The background intensity and the triggered intensity of the sequence are compared, and the variation trend of the parameters of the seismic catalog under different cut-off times are analyzed. Results show that the seismicity has been significantly enhanced during this event. Within 40 days after the mainshock, the background intensity reached the maximum value of 7.26 events/day, while the value is 0.013 events/day before the mainshock. The sequence may be clustered. Both large-magnitude earthquakes and small-magnitude earthquakes are likely to trigger secondary aftershocks. The spatial attenuation of the triggered intensity gradually becomes faster.

Technique Improves Neural Network Training To Quantify Rock Properties From Seismic

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202685, “Rock-Physics-Guided Data-Science Technique To Improve Neural Network Training To Accurately Quantify Rock Properties From Seismic Data,” by Shraddha Chatterjee, Tanya Colwell, and Jon Downton, CGG, et al. The paper has not been peer reviewed. The success or failure of neural networks in discerning rock properties through a quantitative approach from seismic data and associated seismic attributes is dependent on the amount of available data. Past researchers developed a hybrid theory-guided-data-science (TGDS) technique that augmented the amount of data used for training. This paper shows the application of this method of TGDS-based synthetic seismic catalog generation followed by the application of a deep feed-forward neural network (DFNN) to a real seismic data set for a commercially oil-producing field in the North Sea. Introduction Machine-learning algorithms have been used for several applications in the field of reservoir characterization. Using neural network techniques for supervised learning applications to predict log properties from seismic and seismic attributes is an established technique. However, a known limitation of neural networks is that they depend greatly on the amounts of training data, also called labeled data. Generally, the source of the labeled data during geophysical applications is well-log data. Hence, a need to increase the amount of labeled data was required to increase the accuracy of predictions. The accuracy of neural networks suffers because of the lack of labeled data, especially in exploration study areas where well data are scarce. The hybrid TGDS model augments the amount of data used to train the neural network. During the process, theory-based generated outputs are used as inputs to the data-science component of this work flow. The theory-based components are generated models of rock physics that help in estimating the elastic parameters of a rock caused by changes in fluid and other petrophysical rock properties; this approach then is used to generate a large set of pseudowells. In the next step, synthetic seismic gathers are generated based on the large set of generated pseudowells that are used for training a DFNN. The parameters that are derived for training the neural network are further applied on a real data set. In the complete paper, the authors show an example of this work flow in which it was applied to a North Sea field that produces commercial volumes of oil. The reservoir of interest is of the Paeocene age and is a remobilized injectite sand that cross-cuts the stratigraphy at high angles. The injectite sands can be excellent pay zones with good porosity and permeability, even though their imaging can be challenging.

EARTHQUAKE HAZARD ASSESSMENT STUDIES IN THE STATE OF KUWAIT

This study addresses the first and most important step in measuring the level of seismic hazard in Kuwait. As a result of development, there has been a rise in urban growth leading to the establishment of massive structures and skyscrapers in Kuwait. Therefore, there is demand for seismic risk assessment and the creation of a single seismic code for the country. Consequently, the historical and instrumental data were compiled into seismic catalogs of Kuwait and the active Zagros Seismic Belt. The magnitudes have been unified, extraneous earthquakes removed, and the catalogs' entirety has been taken into account. A seismotectonic model for the Kuwait region has been built to minimize the epistemic uncertainties. The model functions by combining seismicity patterns and structural geological conditions. The probability of experiencing the largest predicted earthquake emerging from every seismic source was calculated together with the parameters set for recurrence. Furthermore, the creation of hazard maps required a suitable ground motion attenuation relation within a logic tree design. Considering recurrence intervals of 100, 475, 975, and 2475 years (corresponding to 39.3 percent, 10%, 5%, and 2%, accordingly, the likelihood of exceedance in 50 years), a probability-based technique is utilized in the study to construct hazard maps at the following 0, 0.1, 0.2, 0.5, 1, 2, 3 and 4 seconds. The maps of scaling hazard areas were created using a 0.2 ° x 0.2 ° spacing grid throughout Kuwait. The five regions of Kuwait (Kuwait City, Salmiya Area, Sabriya Area, Managish Area, and Um Gudair Area) have all implemented a consistent spectrum of hazards. The findings of this study plus the vulnerability index serve the essential features required to calculate Kuwait's seismic risk.

The unexpected Mayotte 2018–2020 seismic sequence: a reappraisal of the regional seismicity of the Comoros

The Mayotte seismic sequence that started on 10 May 2018, with a main shock of magnitude Mw 5.9 on May 15, followed by a major offshore volcanic activity, raises several questions of seismovolcanic hazards in the Comoros region. The unexpected size and duration of the crisis is an opportunity to reassess the distribution and magnitude of the seismicity near Mayotte Island, but also regionally. We present a comprehensive seismicity catalogue of the region including the Mozambique Channel, the Mozambique coast and Madagascar, based partly on previously published data in the region and partly on unpublished data from local catalogues for the Comoros and Madagascar. Our catalogue extends from 1900 onward with a completeness of magnitude 5.5 until 1980s and decreasing only recently to 4.5 after 2010. It comprises the events of magnitude Mlv ≥3.5 for the seismic sequence of Mayotte from May 2018 to October 2020 as the crisis is still ongoing. Present knowledge of the seismicity, largely partial in distribution and magnitude before 1980, makes the seismic sequence of 2018-2020 an exceptional and unprecedented seismo-volcanic event in the region. We discuss the distribution of seismicity in time and space within the context of the south eastward propagation of the East African rift system towards Madagascar.

An Optimized Learning Model Augment Analyst Decisions for Seismic Source Discrimination

Efficient handling and planning for the urban regions’ sustainable development require a vast range of up-to-date and thematic information. Besides, obtaining an uncontaminated catalog of seismic activity is desirable to study the earthquake (EQ) clusters’ spatial allocation, which is a key role in mitigating seismic hazards and alleviating EQ losses by enhancing the assessment of seismic hazards. This article considers the northeastern part of Egypt where the seismicity catalog is contaminated by quarry blasts (QBs) operated throughout the mapped area. Consequently, it is desirable to discriminate these QBs from the EQs for genuine seismicity and hazard analysis. Accordingly, we provide an efficient machine learning (ML) model for decontaminating the seismicity database so that EQ clusters can be properly delineated by relying on 870 events (EQs and QBs) observed by only one seismic station called “GLL,” a member of the Egyptian National Seismic Network (ENSN). The model focuses on magnitudes < 3 that have high uncertainty of being EQs or QBs and take a long time for analysis. The approach examines several linear and nonlinear ML models and, finally, selects the best model with only two features leading to the optimal classification between the EQs and QBs. The optimization process is accomplished throughout two stages. The obtained results prove that the proposed scheme achieves 100% discrimination between the EQs and QBs relying on the extreme gradient boosting (XGB) model.

Statistical analysis of static and dynamic predictors for seismicb-value variations in the Groningen gas field

AbstractWe perform statistical analyses on spatiotemporal patterns in the magnitude distribution of induced earthquakes in the Groningen natural gas field. The seismic catalogue contains 336 earthquakes with (local) magnitudes above$1.45$, observed in the period between 1 January 1995 and 1 January 2022. An exploratory moving-window analysis of maximum-likelihoodb-values in both time and space does not reveal any significant variation in time, but does reveal a spatial variation that exceeds the$0.05$significance level.In search for improved understanding of the observed spatial variations in physical terms we test five physical reservoir properties as possibleb-value predictors. The predictors include two static (spatial, time-independent) properties: the reservoir layer thickness, and the topographic gradient (a measure of the degree of faulting intensity in the reservoir); and three dynamic (spatiotemporal, time-dependent) properties: the pressure drop due to gas extraction, the resulting reservoir compaction, and a measure for the resulting induced stress. The latter property is the one that is currently used in the seismic source models that feed into the state-of-the-art hazard and risk assessment.We assess the predictive capabilities of the five properties by statistical evaluation of both moving window analysis, and maximum-likelihood parameter estimation for a number of simple functional forms that express theb-value as a function of the predictor. We find significant linear trends of theb-value for both topographic gradient and induced stress, but even more pronouncedly for reservoir thickness. Also for the moving window analysis and the step function fit, the reservoir thickness provides the most significant results.We conclude that reservoir thickness is a strong predictor for spatialb-value variations in the Groningen field. We propose to develop a forecasting model for Groningen magnitude distributions conditioned on reservoir thickness, to be used alongside, or as a replacement, for the current models conditioned on induced stress.

ВЫБОР ЭНЕРГЕТИЧЕСКОЙ ХАРАКТЕРИСТИКИ ДЛЯ УНИФИЦИРОВАННОГО СЕЙСМИЧЕСКОГО КАТАЛОГА КЫРГЫЗСТАНА

The paper substantiates the choice of the Rautian KP class as the main energy characteristic for the unified catalog of Kyrgyzstan.KP class introduced into the practice of seismological observations by T.G. Rautian in 1960 and widely used in the USSR and post-Soviet countries. Comparison of the calibration function σ(∆) used to calculate the energy class of the KP for four independent catalogs containing the most complete information on seismic events in Kyrgyzstan is presented. The need to recalculate the KP of seismic events included in the KNET catalog obtained at the Research Station of the Russian Academy of Sciences has been revealed. A good agreement between of the new KP values with the KP values for common events from other seismic catalogs of Kyrgyzstan is shown. The obtained KP values for the KNET catalog can be used to compile when compiling the composite catalog without violating the uniformity of the methodology for calculating the magnitude of seismic events.

A New Smoothed Seismicity Approach to Include Aftershocks and Foreshocks in Spatial Earthquake Forecasting: Application to the Global Mw ≥ 5.5 Seismicity

Seismicity-based earthquake forecasting models have been primarily studied and developed over the past twenty years. These models mainly rely on seismicity catalogs as their data source and provide forecasts in time, space, and magnitude in a quantifiable manner. In this study, we presented a technique to better determine future earthquakes in space based on spatially smoothed seismicity. The improvement’s main objective is to use foreshock and aftershock events together with their mainshocks. Time-independent earthquake forecast models are often developed using declustered catalogs, where smaller-magnitude events regarding their mainshocks are removed from the catalog. Declustered catalogs are required in the probabilistic seismic hazard analysis (PSHA) to hold the Poisson assumption that the events are independent in time and space. However, as highlighted and presented by many recent studies, removing such events from seismic catalogs may lead to underestimating seismicity rates and, consequently, the final seismic hazard in terms of ground shaking. Our study also demonstrated that considering the complete catalog may improve future earthquakes’ spatial forecast. To do so, we adopted two different smoothed seismicity methods: (1) the fixed smoothing method, which uses spatially uniform smoothing parameters, and (2) the adaptive smoothing method, which relates an individual smoothing distance for each earthquake. The smoothed seismicity models are constructed by using the global earthquake catalog with Mw ≥ 5.5 events. We reported progress on comparing smoothed seismicity models developed by calculating and evaluating the joint log-likelihoods. Our resulting forecast shows a significant information gain concerning both fixed and adaptive smoothing model forecasts. Our findings indicate that complete catalogs are a notable feature for increasing the spatial variation skill of seismicity forecasts.

THE RESIZING OF THE MOST POWERFUL ITALIAN INSTRUMENTAL EARTHQUAKE (SEPTEMBER 8, 1905, CALABRIA REGION, SOUTHERN ITALY)

The 8 September 1905 Calabria earthquake is the seismic event for which the Italian Seismic Catalogue shows the highest instrumental magnitude of the whole dataset. However, the reported Ms=7.47 was calculated over only two stations, and leaves room for a revision. In this work I provide a new estimate of the surface-wave magnitude of the earthquake calculated over sixteen individual values of magnitude from seven different stations. The new estimate is Ms=7.06±0.13, a value that is consistently lined up with other estimates provided by means of macroseismic or geological evidence. The novel estimate is stable despite alternative epicentral locations and different depths proposed for this event by several investigators. The net variation of almost half a unit magnitude implies a resizing of the seismogenic source of the event in the frame of the seismotectonics of the region, and highlights the strong need for a systematic revision of the instrumental magnitude estimates for several ‘historical’ earthquakes that occurred at the dawning of the instrumental seismology.

The capabilities of analyzing the seismo-electromagnetic satellite CSES-01 data for monitoring of seismic activity of the Northern Tien Shan

The relationship between space weather and earthquakes occurring in seismically active areas with the seismo-electromagnetic satellite CSES-01 data are observed. The study assumes the presence of possible ionospheric precursors of strong earthquakes. The sets of measuring instruments of the satellite and data are considered. Subsequently, to prove the non-random nature of the space weather effects, the results of ground-based geomagnetic or electromagnetic observations should be used, for example, magnetotelluric soundings (MTS). Stationary and regime points of the MTS network of the Research Station RAS in Bishkek (RS RAS) are suitable for these purposes in the Northern Tien Shan. The MTS data are presented in the form of hourly frequency-time series with system rotation from 0° to 180°. To obtain information on earthquakes, it is proposed to use data from the NEIC or ISC seismic catalog, since they aggregate data from regional catalogs, including the KNET seismological network maintained by the RS RAS. It is concluded that it is necessary to select the CSES-01 trajectories and times of flight over the territory of Kyrgyzstan and download the electric field detector (EFD) data. The results of comparing satellite and ground-based observations can be used in future technologies for short-term earthquake prediction.

Migration of Fluid‐Induced Seismicity Reveals the Seismogenic State of Faults

AbstractSeismic swarms, in natural contexts or induced by anthropogenic fluid injections, commonly show migrations of earthquake hypocenters. Classically, such migrations are interpreted as the diffusion of the fluid pressure. However, recent studies show that the seismic front maps the stress concentration at the tips of propagating aseismic slip that is primarily induced by the fluid pressure increase. In this case, seismic migration might depend on the hydromechanical properties that control the dynamics of aseismic slip propagation rather than the hydraulic diffusivity. Here, we use synthetic seismic catalogs obtained from the hydromechanical modeling of a slip‐weakening, permeable fault response to a fluid injection. By varying the fault permeability and the stress state, we show that the shape of the seismic front in a distance‐time plot depends on the initial fault criticality to failure, and not on the hydraulic properties. We then extrapolate this numerical result to seven observed injection‐induced earthquake swarms by showing that the shape of the migration front directly depends on the seismogenic index. The seismic front has a diffusive behavior when the aseismic slip is directly driven by the pressure increase, either at the swarm beginning or later if the faults are not initially critically stressed. On the contrary, an accelerating seismic front indicates a high‐criticality stressed fault, on which the aseismic slip runs away from the fluid pressurized area. Therefore, this study highlights that the seismic front shape may prove a useful indicator to characterize the initial stress state of faults over which the swarms occur.

Historical seismic catalogue updates and site effects considerations for southern Piedmont (Northwest Italy)

In Northwest Italy, the definition of the seismic districts is a debated topic, with relatively scarce literature to pursue the goal of assessing the relative seismic potential. In particular, the southern Piedmont, despite being part of the lowest categories in the Italian seismic zonation map, has been affected by four relevant earthquakes between 5.5 and 6.5 Mw in the last six centuries.Starting from the Italian Historical Macroseismic Archive catalogue, a consultation of ten historical archives (in parishes, municipalities, and administrations of Alessandria, Asti, Cuneo, and Turin Provinces) improved the historical seismicity information reported in the Italian Macroseismic Database, verifying the presence of unknown Macroseismic Data Point (MDPs). An analysis of the density of instrumental seismicity epicentres of the last 35 years provides consistency with MDPs density, qualitatively finding spatial correlation between them. In addition, a deepening of earthquake- induced landslide issue has been performed in a georeferenced environment with the purpose to assess eventual local amplification effects through a geostatistical analysis.

Analysis of the 2016\u20132018 fluid-injection induced seismicity in the High Agri Valley (Southern Italy) from improved detections using template matching

Improving the capability of seismic network to detect weak seismic events is one of the timeless challenges in seismology: the greater is the number of detected and locatable seismic events, the greater insights on the mechanisms responsible for seismic activation may be gained. Here we implement and apply a single-station template matching algorithm to detect events belonging to the fluid-injection induced seismicity cluster located in the High Agri Valley, Southern Italy, using the continuous seismic data stream of the closest station of the INSIEME network. To take into account the diversity of waveforms, albeit belonging to the same seismic cluster, eight different master templates were adopted. Afterwards, using all the stations of the network, we provide a seismic catalogue consisting of 196 located earthquakes, in the magnitude range − 1.2 ≤ Ml ≤ 1.2, with a completeness magnitude Mc = − 0.5 ± 0.1. This rich seismic catalogue allows us to describe the damage zone of a SW dipping fault, characterized by a variety of fractures critically stressed in the dip range between ~ 45° and ~ 75°. The time-evolution of seismicity clearly shows seismic swarm distribution characteristics with many events of similar magnitude, and the seismicity well correlates with injection operational parameters (i.e. injected volumes and injection pressures).