Journal of Seismology最新文献

Earthquake magnitude plays a crucial role in assessing ground shaking severity and formulating mitigation strategies for both natural and induced earthquakes. This study specifically focuses on the Western Canada Sedimentary Basin (WCSB) and examines the estimation of local magnitude (({M}_{L})) by different agencies. The analysis includes the application of various distance calibration functions for the Richter’s methodology, incorporating both Richter's original function (Richter, Elementary Seismology, Freeman, San Francisco, Calif, 1958) and WCSB-specific calibration functions proposed by Yenier 2017 Bull Seismol Soc Am 107:1421-1431 and Babaie Mahani and Kao 2019 Seismol Res Lett 90:203-211, 2020 CSEG Recorder 45:12.

In the WCSB, fluid injection has caused significant increase in the rate of seismicity in several localities, prompting the regulatory agencies to request suspension of injection operations after the occurrence of red-light (i.e., ({M}_{L}) ≥ 4) events. Our investigation, based on a new dataset, sheds light on the significant effects due to distance calibration functions on the ({M}_{L}) estimation. Notably, we observe that using the original Richter’s calibration function designed for southern California results in more than three times the number of red-light events compared to employing more appropriate calibration functions. Our results point to the unnecessary economic consequences when exaggerated ({M}_{L}) values are used in the regulatory process and underscores the need for adopting proper calibration functions for seismic monitoring in the WCSB.

Rapid and accurate estimation of emergency response parameters during earthquakes is important in earthquake early warning (EEW) systems. Because earthquake rupture is not instantaneous, to accurately, safely, and reliably determine parameters and thresholds for emergency response, the cumulative absolute velocity (CAV) is used as the target parameter, and 7 P-wave characteristic parameters of strong ground motion records occurring 3 s after P-wave arrival at K-NET and KiK-net stations in Japan are used as inputs to construct a machine learning (ML) CAV prediction model based on the support vector machine (SVM) algorithm. The results show that compared with a single-parameter prediction algorithm, the proposed ML model can significantly reduce the error standard deviation and effectively address the phenomena of small value overestimation and large value underestimation. A confusion matrix analysis demonstrates that the 6-parameter model P_a&P_v&P_d&CAV&I_a&IV2 shows the best performance in improving the prediction accuracy and provides a threshold selection strategy for threshold-based EEW emergency response.

This work investigates the characteristics of local seismicity within the State of Kuwait and discusses its potential tectonic and anthropogenic drivers. As Kuwait is an oil-producing country, the occurrence of earthquakes simultaneously with oil extraction may suggest a case of triggered or induced seismicity. Seismic activity inside Kuwait is monitored with high accuracy and continuously after the establishment of the Kuwait National Seismic Network (KNSN) in 1997 through an ambitious plan to study the micro-earthquake activity in Kuwait. This network recorded more than 1378 micro/minor local earthquakes. Two seismogenic areas are identified, both characterized by weak magnitudes and shallow focal depths. In the current work, several modern geophysical techniques are performed including earthquake location, waveform-based moment tensor inversion, moment tensor decomposition, stress drop analysis, and stress pattern assessment. The results suggest that local earthquakes in Kuwait involve tectonic and anthropogenic components. Further densification of the network may allow a robust discrimination in the future.

Declustering of earthquake catalogs, that is determining dependent and independent events in an earthquake sequence, is a common feature of many seismological studies. While many different declustering algorithms exist, each has different performance and sensitivity characteristics. Here, we conduct a comparative analysis of the five most commonly used declustering algorithms: Garnder and Knopoff (1974), Uhrhammer (1986), Reasenberg (J Geophys Res: Solid Earth 90(B7):5479–5495, 1985), Zhuang et al. (J Am Stat Assoc 97(458):369–380, 2002), and Zaliapin et al. (Phys Rev Lett 101(1):4–7, 2008) in four different tectonic settings. Overall, we find that the Zaliapin et al. (Phys Rev Lett 101(1):4–7, 2008) algorithm effectively removes aftershock sequences, while simultaneously retaining the most information (i.e. the most events) in the output catalog and only slightly modifying statistical characteristics (i.e. the Gutenberg Richter b-value). Both Gardner and Knopoff (1974) and Zhuang et al. (J Am Stat Assoc 97(458):369–380, 2002) also effectively remove aftershock sequences, though they remove significantly more events than the other algorithms. Uhrhammer (1986) also effectively removes aftershock sequences and removes fewer events than Gardner and Knopoff (1974) or Zhuang et al. (J Am Stat Assoc 97(458):369–380, 2002), except when large magnitude events are present. By contrast, Reasenberg (J Geophys Res: Solid Earth 90(B7):5479–5495, 1985) only effectively removed aftershocks in one of the test regions.

In this study, we took a close look at the Ocean Networks Canada’s earthquake early warning system in southwestern British Columbia through analysis of the magnitude estimates by this system and characterization of site conditions for both onshore and offshore stations. Using magnitude values estimated at each station, over hundreds of notifications, we provided station terms to correct the magnitudes for stations that systematically generate high or low magnitude values. Moreover, by compiling a rich ground motion amplitude dataset and applying the horizontal-to-vertical spectral ratio method from Fourier amplitude of acceleration and response spectral acceleration, we investigated site characterization through evaluation of non-linear site response behavior and estimation of the site dominant frequency (f_peak) and its peak amplitude (A_peak) for each station. In general, no strong evidence of non-linearity is observed at any stations considering the magnitude-distance distribution of ground motions in this study. Offshore sites show f_peak and A_peak in the range of approximately 1.7–6 Hz and 0.4–1.2 (in base-10 log unit), respectively, whereas onshore sites show approximately 1–6 Hz for f_peak and 0.3–0.7 (in base-10 log unit) for A_peak.

Kalimantan and Sulawesi are located within the complex tectonic setting of central Indonesia. The tectonic evolution process during the Mesozoic and Cenozoic led to the formation of this region. Studies of Moho depth variation beneath this region are still limited due to the lack of local to regional scale seismic stations covering the entire Kalimantan and Sulawesi region. The availability of seismic data has doubled and tripled recently, here, we conduct receiver function study using reliable dense seismic data from BMKG seismic network (IA) to obtain more detail Moho depth variation in Kalimatan and Sulawesi. We analyzed P–waveforms recorded at 60 seismic stations of BMKG seismic network (IA) distributed in Kalimantan and Sulawesi from more than 150 earthquakes with M ≥ 6 distributed within the epicentral distance range of 30^o – 90^o. The receiver function signals of each seismic station were computed using the iterative time-domain deconvolution method, then the Moho depths and bulk composition (Vp/Vs ratio) were computed using the modified H-κ stacking method which consider the sediment thickness. Our results show that the crustal thickness in Kalimantan varies from ~25 to ~37 km and Vp/Vs ratio varies from ~1.61 to ~1.96, which reflect a characteristic of stable Mesozoic-Cenozoic regions, while Sulawesi is observed within broad thickness range of ~22 – 50 km and Vp/Vs ratio of ~1.56 – 1.97. The extremely thick crust in Sulawesi reflects the rapid uplift and exhumation zones achieved by tectonic process sequences that had been occurred in this region.

The Alborz Mountains are among the areas exhibiting high tectonic and seismic activity in northern Iran. Studying key parameters of tectonic structures, including quantitative analysis and observational studies, in such active regions is essential to identify potential active faults and assess the consequent seismic hazards. This study focuses on seismicity and seismotectonics by analyzing seismic parameters, including b-value, mean seismic activity rate, earthquake recurrence time, seismic moment, and fractal dimension derived from micro and teleseismic data. The b-values vary between 0.6 and 1.1 in the tectonically active parts of the study area, corresponding with the reverse/thrust and strike-slip active faults. Large earthquakes might be prone to occur at 10–25 km depth because both catalogues show low b-values (b < 1.0) concentrations at this depth range. The high fractal dimension (> 1.5), high seismic activity rate, large seismic moment parameters, and its continuously increasing trend. Short recurrence periods (20–50 years) of M 6.5 events also emphasize the high seismic activity and high seismic hazard. On the other hand, the prevalence of low b-values is notably observed in areas encompassing densely populated cities such as Rasht, Lahijan, Amol, Babol, Sari, Behshahr, Gorgan, and the megacity of Tehran. Furthermore, we have identified asperities where the Gorgan Plain, the Khazar, and the Alamutrud Fault Zones are located. These findings emphasize the seismic hazard potential in the identified areas and urban centers within the study area. Therefore, particular attention should be directed towards areas exhibiting low b-values when assessing and mitigating seismic hazards. It underscores the necessity for additional focus on seismic hazard assessment and implementation of mitigation strategies in the Alborz region.

Over the past two decades, the Al-Refaei district, a substantial town located in the Thi-Qar governorate in southern Iraq, has been subjected to numerous small to moderate-size earthquakes. A network of seven short-period seismic stations was installed in the Al-Refaei district to monitor seismic activity, a project that was initiated in 2014 and continued until 2018. The short-period seismic stations supplement the broadband seismic stations of the Mesopotamian Seismological Network (MPSN), which also serves this area. During the monitoring period, more than 56 earthquakes were recorded, of which 31 were detected by the short-period seismic stations and not reported by any other local or international seismic observatories. Data from the short-period and broadband seismic stations were analyzed using Geiger’s least-squares method to determine accurate locations. The relocated earthquakes delineate a possible fault source with a northwest-southeast trend. The possible fault is not related to any known or previously studied fault. 3D seismic data of the area were evaluated and further supported the interpretation of a northwest-southeast trending fault, named the Al-Refaei fault. Integration of the seismological and 3D seismic data suggests that the Al-Refaei fault is a reverse fault with a S62˚E strike direction and a 43˚ dip angle. The strike and dip of the Al-Refaei fault were calculated from the analysis of the 3D seismic data. The reverse style of faulting was derived from the composite first motion method using the seismic station records of the short-period network.

This study has developed Intensity Prediction Equations (IPEs) for the Himalayas and its sub-regions (divided into North-West Himalaya, Central Himalaya, and North-East Himalaya). For this purpose, intensity data reported in previous studies using traditional methods (like field surveys, media reports, and newspapers) and internet-based questionnaires (such as USGS’s Did You Feel It? or DYFI) were used to catalogue two separate intensity datasets. Intensities of traditional datasets were also reassessed for some earthquake events by different studies in the different scales of assignment, which was homogenized for the same intensity scale. IPEs are derived for both datasets separately using a two-stage and one-stage regression technique. These IPEs are developed for a first- and second-order relation with respect to earthquake magnitude. A “maximum intensity vs. magnitude approximation of the IPE” approach relying on an optimal hypocentral depth has also been proposed to select the best-suited IPEs. The information-theoretic approach-based Log-likelihood method (Scherbaum et al. 2009) has been used to check and compare developed IPE performance for events not used for IPE development. These newly developed equations can be used to assess the damage potential of future earthquakes.

We have applied the empirical Green’s function (EGF) method to 53 pairs of earthquakes, with magnitudes ranging from M = 0.4 to M = 3.4, induced by gas production from the Groningen field in the Netherlands. For a subset of the events processed, we find that the relative source time functions obtained by the EGF deconvolution show clear indications of a horizontal component of rupture propagation. The earthquake monitoring network used has dense azimuthal coverage for nearly all events such that wavelet duration times can be picked as a function of source-station azimuth and inverted using the usual Doppler broadening model to estimate rupture propagation strike, distance, and velocity. Average slip velocities have also been estimated and found to be in agreement with typical published values. We have used synthetic data, from both a simple convolutional model of the seismogram and more sophisticated finite difference rupture simulations, to validate our data processing workflow and develop kinematic models which can explain the observed characteristics of the field data. Using a measure based on the L1-norm to discriminate results of differing quality, we find that the highest quality results show very good alignment of the rupture propagation with directions of the detailed fault map, obtained from the full-field 3D seismic data. The dip direction rupture extents were estimated from the horizontal rupture propagation distances and catalogue magnitudes showing that, for all but the largest magnitude event (the M = 3.4 event of 8th January 2018), the dip-direction extent is sufficiently small to be contained wholly within the reservoir.