An extraordinary earthquake swarm occurred at Rushan on the Jiaodong Peninsula from October 1, 2013, onwards, and more than 12,000 aftershocks had been detected by December 31, 2015. All the activities of the whole swarm were recorded at the nearest station, RSH, which is located about 12 km from the epicenter. We examine the statistical characteristics of the Rushan swarm in this paper using RSH station data to assess the arrival time difference, t_{{{text{S}} ,-, {text{P}}}}, of Pg and Sg phases. A temporary network comprising 18 seismometers was set up on May 6, 2014, within the area of the epicenter; based on the data from this network and use of the double difference method, we determine precise hypocenter locations. As the distribution of relocated sources reveals migration of seismic activity, we applied the mean-shift cluster method to perform clustering analysis on relocated catalogs. The results of this study show that there were at least 16 clusters of seismic activities between May 6, 2014, and June 30, 2014, and that each was characterized by a hypocenter spreading process. We estimated the hydraulic diffusivity, D, of each cluster using envelope curve fitting; the results show that D values range between 1.2 and 3.5 m2/d and that approximate values for clusters on the edge of the source area are lower than those within the central area. We utilize an epidemic-type aftershock sequence (ETAS) model to separate external triggered events from self-excited aftershocks within the Rushan swarm. The estimated parameters for this model suggest that α = 1.156, equivalent to sequences induced by fluid-injection, and that the forcing rate (μ) implies just 0.15 events per day. These estimates indicate that around 3% of the events within the swarm were externally triggered. The fact that variation in μ is synchronous with swarm activity implies that pulses in fluid pressure likely drove this series of earthquakes.

Earthquake has left much life and property damages. The occurrence of such events necessitates the execution of plans for combating the earthquakes. One of the most important methods for combating earthquakes includes assessing dynamic characteristics of soil and site effect. One of the methods by which one can state dynamic characteristics of the soil of an area is the measurement of microtremors. Microtremors are small-scale vibrations that occur in the ground and have an amplitude range of about 0.1–1 microns. Microtremor measurement is fast, applicable, cost-effective. Microtremor measurements were taken at 15 stations in the Babol, north of Iran. Regarding H/V spectral ratio method, peak frequency and amplification factor were calculated for all microtremor stations. According to the analysis, the peak frequency varies from 0.67 to 8.10 Hz within the study area. Also, the authors investigated the validity of the results by comparing them with SESAME guidelines and geotechnical conditions of study area. The microtremor analysis results are consistent with SESAME guidelines and geotechnical condition of study area. The results show that the microtremor observations are acceptable methods for assessing dynamic characteristics of soil and site effect in the Babol City.

The procedure through which the occurrence time of an impending major earthquake can be determined is reviewed in the light of the recent advances. This can be achieved by analyzing in natural time the seismicity in the candidate area. To apply this general procedure, we need two important elements: first, to know when we should start the analysis, i.e., set the natural time equal to zero. This is the time at which the system enters the critical stage. Second a reliable estimation of the candidate epicentral area. If geoelectrical measurements are taken and the VAN method (after the initials of the three researchers Varotsos, Alexopoulos and Nomicos) is applied, both these elements become available upon the recording of a precursory Seismic Electric Signals (SES) activity, because its initiation marks the time when the system enters the critical stage, and in addition the SES data enable the determination of the epicentral area of the impending mainshock. On the other hand, if geoelectrical data are lacking, we make use of the following two recent findings by means of natural time analysis: First, the fluctuations of the order parameter of seismicity in a large area exhibit a minimum a few months before a major earthquake almost simultaneously with the initiation of an SES activity. Second, a spatiotemporal study of this minimum unveils an estimate of the epicentral area of the impending major earthquake. Two examples are given that refer to the strongest earthquakes that occurred in Greece and Japan during the last 3 decades, i.e., the MW6.9 earthquake in southwestern Greece on 14 February 2008 and the MW9.0 Tohoku earthquake in Japan on 11 March 2011.

A new 3D velocity model of the crust and upper mantle in the southeastern (SE) margin of the Tibetan plateau was obtained by joint inversion of body- and surface-wave data. For the body-wave data, we used 7190 events recorded by 102 stations in the SE margin of the Tibetan plateau. The surface-wave data consist of Rayleigh wave phase velocity dispersion curves obtained from ambient noise cross-correlation analysis recorded by a dense array in the SE margin of the Tibetan plateau. The joint inversion clearly improves the vS model because it is constrained by both data types. The results show that at around 10 km depth there are two low-velocity anomalies embedded within three high-velocity bodies along the Longmenshan fault system. These high-velocity bodies correspond well with the Precambrian massifs, and the two located to the northeast of 2013 MS 7.0 Lushan earthquake are associated with high fault slip areas during the 2008 Wenchuan earthquake. The aftershock gap between 2013 Lushan earthquake and 2008 Wenchuan earthquake is associated with low-velocity anomalies, which also acts as a barrier zone for ruptures of two earthquakes. Generally large earthquakes (M ≥ 5) in the region occurring from 2008 to 2015 are located around the high-velocity zones, indicating that they may act as asperities for these large earthquakes. Joint inversion results also clearly show that there exist low-velocity or weak zones in the mid-lower crust, which are not evenly distributed beneath the SE margin of Tibetan plateau.

Using the order parameter of seismicity defined in natural time, we suggest a simple model for the explanation of Bath law, according to which a mainshock differs in magnitude from its largest aftershock by approximately 1.2 regardless of the mainshock magnitude. In addition, the validity of Bath law is studied in the Global Centroid Moment Tensor catalogue by using two different aftershock definitions. It is found that the mean of this difference, when considering all the pairs mainshock-largest aftershock, does not markedly differ from 1.2 and the corresponding distributions do not depend on the mainshock’s magnitude threshold in a statistically significant manner. Finally, the analysis of the cumulative distribution functions provides evidence in favour of the proposed model.

Abstract Seismic hazard assessment is carried out by utilizing deterministic approach to evaluate the maximum expected earthquake ground motions along the Western Coastal Province of Saudi Arabia. The analysis is accomplished by incorporating seismotectonic source model, determination of earthquake magnitude (M max), set of appropriate ground motion predictive equations (GMPE), and logic tree sequence. The logic tree sequence is built up to assign weight to ground motion scaling relationships. Contour maps of ground acceleration are generated at different spectral periods. These maps show that the largest ground motion values are emerged in northern and southern regions of the western coastal province in Saudi Arabia in comparison with the central region.

Ringing artifact degradations always appear in the deconvolution of geophysical data. To address this problem, we propose a postprocessing approach to suppress ringing artifacts that uses a novel anisotropic diffusion based on a stationary wavelet transform (SWT) algorithm. In this paper, we discuss the ringing artifact suppression problem and analyze the characteristics of the deconvolution ringing artifact. The deconvolution data containing ringing artifacts are decomposed into different SWT subbands for analysis, and a new multiscale adaptive anisotropic filter is developed to suppress these degradations. Finally, we demonstrate the performance of the proposed method and describe the experiments in detail.