This paper collects 227 marine gravity datasets obtained by Japan through ship borne surveys in its surrounding waters and the northwest Pacific. Statistical analysis, visualization mapping, and correlation analysis methods are used to analyze the gravity survey situation and data quality. This paper systematically analyzes the history, spatiotemporal distribution characteristics, and quality of gravity data surveys in Japan. The results show that ship measured gravity data has good consistency with GEBCO terrain data and DTU gravity model data, while the gravity data has a correlation of 0.98 and a root mean square error of 7.7 mGal with the DTU21. This paper establishes a trajectory intersection point difference model and analyzes the data measurement accuracy using intersection point difference error. The total crossover points are 73 979 with an crossover error of 11.85 mGal, the internal crossover point are 24 822 with an crossover error of 9.56 mGal, and the external crossover point are 49 157 with an crossover error of 12.85 mGal. The overall accuracy of the gravity data measurement accuracy is high, and the consistency is good.

The microtremor noise data of 24 stations in the western Anhui region are used to calculate site response based on HVSR method. The results showed that 4 out of 24 stations had abnormal HVSR curves due to observation system failures. All 20 stations have varying degrees of amplification(attenuation) effects, with 4 stations showing flat HVSR curves in the 0.5 Hz to 30 Hz frequency band and site response values of 1 to 2 times. The HVSR curves of the remaining 16 stations exhibit both unimodal and complex bimodal and multimodal shapes, with peak frequencies ranging from 8.5 Hz to 30 Hz, an average of 18.8 Hz, a median of 17.9 Hz, and a standard deviation of 5.66 Hz. The overall trend is relatively large, possibly due to the installation of seismometers on pendulum piers, which reduces the influence of sedimentary layers on measurement results; The peak amplitude ranges from 2.6 to 10.5 times, with an average of 6.0 times, a median of 5.3 times, and a standard deviation of 2.3 times. This may be due to the fact that surface seismometers are more susceptible to surface conditions.

In this paper, based on microseismic monitoring data and 49 microseismic feature parameters of a marble mine in Perugia, central Italy, we compare and analyze the accuracy of three machine learning models, namely, neural networks, decision trees and random forests, in the automated classification of microseismic signals, and optimize the model parameters to improve the performance of the model through the grid searcher algorithm, with an emphasis on discussing the effects of the feature parameter selection and the size of the classification set on the classification results. The results show that the random forest classifier obtains the highest accuracy in microseismic signal classification, with 98.11% classification accuracy after optimization, meanwhile, by reducing some of the feature parameters with small weights, the efficiency of the classification computation is greatly improved and the accuracy decreases less, and the optimal allocation ratio of the training set to the test set is 8 ∶2.

Taking the southern section of the Jiayuguan fault as the research subject, the morphology of the hidden segment of the fault was determined through shallow artificial seismic exploration. Based on remote sensing image interpretation and field geological surveys, the fault was found to be exposed at the surface at the southern end of the Jiayuguan fault, forming an anticline fault scarp. Through aerial photogrammetry, combined with dating tests, it was determined that the fault has been active since the late Pleistocene. Using high-precision topographic data, the height of the fault scarp was obtained, and combined with the corresponding geomorphological age, the vertical slip rate of the southern section of the Jiayuguan fault was estimated to be 0.03±0.01 mm/a.

By conducting a comprehensive analysis of two shallow seismic profiles, VSP-measured P-wave velocity data, and one drilling joint geological profile from the Shenqiu depression in the southern north China basin, this study investigates the geometric characteristics and discernible upper fault depths of a series of negative flower-like structures in the shallow part of the strike-slip fault zone. The results indicate that the fault displaces the Quaternary strata upwards, with the discernible upper fault depth on the shallow seismic exploration profile being approximately 60 meters, and the discernible upper fault depth on the drilling joint geological profile ranging from 38.6 to 40.1 meters, suggesting that the fault displaces the middle Pleistocene strata. The exploration findings reveal that the fault is a set of left-lateral strike-slip faults arranged in a NWW direction, resembling a line of geese. This indicates that the southern north China basin has experienced NW-directed strike-slip shearing during the Quaternary, suggesting that the NW-directed tectonic system, controlled by the Qinling orogeny, has remained active since the Quaternary. This has significant implications for analyzing the evolution of the basins in the eastern plains of the north China block.

This article collected seismic waveform data for events of magnitude M_L≥2.0 in Changzhi, Shanxi province, and its surrounding areas since 2009. The focal mechanisms of these events were determined using the Snoke first motion polarity and amplitude ratio method. Ultimately, 42 focal mechanisms were obtained for natural earthquakes with M_L≥2.4 and RMS≤ 0.45, alongside 6 for non-natural earthquakes. The results indicate that the focal mechanisms of natural earthquakes in the study area are predominantly strike-slip and normal strike-slip, primarily influenced by NEE-SWW compression and NNW-SSE extension. The Changzhi basin exhibits a complex and unique local stress field characterized by a nearly NS-oriented T-axes direction. The P-axes along the Wenwangshan fault follow an NEE-SWW orientation, while in other regions, NE-SW is the dominant direction, showing good consistency in fault plane solutions and high dip angles. The study also explores the focal mechanisms of non-natural earthquakes in the region. Mining-induced earthquakes are mostly normal faulting, while collapse events are reverse faulting. The stress axis characteristics of these non-natural events exhibit significant deviations, with the P-axes or T-axes showing large rotations and the angles between the two axes are about 180°, which is distinctly different from the natural earthquakes where the P-axis/T-axis are nearly perpendicular. These features can assist in distinguishing between different types of earthquakes.

Based on the mobile gravity data from Hebei province and its neighboring areas, we select the 2016-06-23 Shangyi M_S4.0, 2017-09-04 Lincheng M_S3.7, 2018-02-12 Yongqing M_S4.3, and 2019-12-05 Fengnan M_S4.5 earthquakes to analyze dynamic changes of gravity field. Combining with geological structure information, we investigate the relationship between seismicity and gravity changes. The results show that: 1) For earthquakes of approximately M4, significant pre-seismic changes of gravity field are observed, with notable positive and negative anomaly high-value areas and high-gradient zones, suggesting potential precursor information. 2) Earthquakes tend to occur near fault. The direction of contour lines of high-gradient zones of gravity field is mostly consistent with the orientations of major active fault in the region, indicating a close relationship between earthquakes occurrence, gravity changes, and fault structures. 3) The physical parameters of subsurface media are important for earthquake occurrence. Therefore, it is essential to integrate other disciplines for comprehensive assessments when conducting earthquake prediction.

Based on continuous waveform data from the M_S4.7 earthquake in Ar Horqin Banner on October 15, 2021, for three months post-earthquake, machine learning methods were utilized for picking earthquake phases and associating them. The preliminary machine learning-based earthquake catalog constructed includes 386 seismic events, which is 17 times the number of events in the manual catalog of the Inner Mongolia seismic network for the same period. Subsequently, using the P/S phase arrival time information from the event waveforms, a double-difference location method was applied to precisely locate the aforementioned aftershocks and study the seismogenic structure of the earthquake. The results indicate that the aftershocks of the M_S4.7 earthquake in Ar Horqin Banner have two main directions of distribution, nearly NW and nearly NEE, within a 1-5 km range around the mainshock. Based on the relocation results and combined with linear geological structures on the topography, it is suggested that there exists an unidentified hidden faults. The distribution of the 4.7 magnitude earthquake and its aftershocks is primarily controlled by the nearly NW-oriented hidden faults and the nearly NEE-oriented structures.

In order to deeply study the dynamic characteristics of muddy soft soil layer in the Jianghan basin, we conduct a series of undrained dynamic tests using a self-vibrating column tester, and analyze the characteristics of dynamic shear modulus ratio G/G₀ and damping ratio λ with the change of shear strain γ for the soft soil samples in this area. Different dynamic constitutive models are used to fit the G/G₀-γ and λ-γ curves of the muddy soft soil, and the optimal fitting curves are obtained. The results indicate that the nonlinear characteristics of soft soils in the Jianghan basin show strong regional features and are obviously different from the average level in China. The findings can provide more knowledge about dynamic characteristics of the muddy soft soils in this area, and can be used as a reference when the measured dynamic parameters of muddy soft soils are insufficient.

Aiming at the problems of poor positioning accuracy, slow convergence speed, and large influence of clock drift in the case of single-satellite positioning methods, a joint pseudo-ranging/Doppler positioning model with clock-difference correction is proposed, which combines the mathematical model of clock-difference with the pseudo-ranging observation equations and Doppler observation equations, and eliminates the influence of the change of the receiver's clock-difference on the positioning accuracy through the simultaneous estimation of clock drift by the mathematical model of clock-difference and the Doppler observation equations. The proposed method is validated in a simulation scenario, and the results show that the optimal positioning accuracy of the pseudorange/Doppler joint positioning with clock difference correction can reach 219 m under different working conditions, which is 59.4% higher than that of the Doppler localization method; when the pseudorange measurement error is 1 m, the positioning accuracy can be up to 169 m, and the convergence time is around 300 s; when the frequency measurement error is 0.5 Hz, the positioning accuracy can be around 140 m.