Fluids on faults facilitate triggering of earthquakes and affect seismic energy release. Their detection in the focal zone is, however, difficult. Here, we present mapping of stress changes and fluid flow based on determining seismic moment tensors (MTs), which describe focal mechanisms and shear/tensile/compressive fracturing modes of earthquake sources. We calculate highly accurate MTs of 4,500 microearthquakes that occurred in the West Bohemia swarm region in the period of 2008–2018. The extent and quality of the moment tensor data are unique and allow us to study detailed behavior of the nondouble‐couple (nonDC) components of MTs along the fault. The nonDC components were mostly zero or negative and indicated shear/compressive fracturing. However, also a patch with positive nonDC components, indicating tensile fracturing, was revealed. The inversion for stress and modeling of the Coulomb stress change confirmed that this patch is under anomalous stress conditions. Tensile fractures in the patch were opened due to interaction of tensile fault steps and filled by overpressurized fluids. Hence, evaluating nonDC components of earthquakes might help for tracing stress variations and fault interactions, identifying pathways of fluids and locating areas with overpressure prone to being activated.

Surface arrays became an important tool for monitoring the induced seismicity in hydraulic fracturing experiments and for assessing the impact of fluid injection on the fracturing process of microearthquakes. The layout of sensors plays a key role in this task because it controls the accuracy of event locations and retrieved seismic moment tensors. We simulate various configurations of grid sensor arrays characterized by a different number of sensors, array span, sensor spacing, depth of sources and various shear/tensile source mechanisms of events. The moment tensor inversion is carried out using synthetically calculated P‐wave amplitudes with added random noise. A bias in the solutions is evaluated by errors in the double‐couple percentage of inverted moment tensors because the double‐couple errors inform us about the sensitivity of the network to detect the shear/tensile fracturing mode of induced microearthquakes. The results show that the accuracy of the double‐couple percentage is mostly controlled by the offset‐to‐depth ratio R defined as the ratio of half of the network size to the event depth. The optimum value of R is in the range of 0.75–1.5 irrespective of the type of the focal mechanism. If 121 (11 × 11) sensors are distributed in a regular grid and recorded data are characterized by a 10% random noise, the double‐couple error is less than 6%. This error increases, if R is not optimum or if the number of sensors is reduced. However, even sparse arrays with 49 (7 × 7) or 16 (4 × 4) sensors can yield a reasonable accuracy, provided the surface grid arrays are designed to have an optimum size.

Accurate landslide time prediction holds critical significance for ensuring safety and efficient production in open-pit mining operations. While the inverse velocity method serves as a prevalent data-driven forecasting approach, conventional single-point monitoring implementations frequently yield substantial deviations. This study proposes a multi-point collaborative inverse velocity landslide time prediction methodology using nonlinear least squares, which is based on slope radar multi-point group displacement monitoring data. Systematic stability evaluations were conducted for both single-point predictions and multi-point ensemble forecasts. Experimental results demonstrate that single-point-based predictions generally confine errors within 5 h, including the case of traditional smoothing treatments of velocity curves. The developed multi-point collaborative methodology achieves prediction errors below 1 h, with temporal forecast position variations and spatial point quantity adjustments inducing marginal error fluctuations under 2 h based on strict data exclusion. Enhanced data volume implementation significantly improves prediction accuracy and stability. These findings will provide substantive technical references and methodological guidance for advancing landslide temporal prediction research in open-pit mining engineering.

This work aims to reveal the macro-meso fracture evolution responses of fault zone samples subjected to repeated freeze-thaw (FT) weathering utilizing digital image correlation technology (DIC). Remolded specimens were prepared and then subjection to FT cycles of 0, 20, 40, and 60, respectively. Testing results show that the degradation effect of freeze-thaw on the uniaxial compressive strength of the fault fracture zone rock masses is significant, with peak strengths deteriorating by 20.2%, 32.7%, and 45.2% for specimens subjected to 20, 40, and 60 cycles, respectively, compared to specimens without FT treatment. Due to the elastic mismatch between the fine-grained matrix and the rock blocks within the fault fracture zone, the strain and displacement fields during loading exhibit pronounced heterogeneous characteristics. It is shown that freeze-thaw treatment leads to increasingly complex failure modes, with the fracture patterns transitioning from tensile failure to conjugate shear failure as the number of FT cycle increases. It is suggested that the impact of freeze-thaw on the internal components of the fault fracture zone rock masses varies considerably, with frost heave forces readily developing at rock-soil interfaces, pores, and microcracks, resulting in damage propagation, and ultimately diminishing the rock mass’s resistance to deformation.

SUMMARY: As an alternative to the moment tensor (MT) model for earthquake sources, the shear-tensile-compressive (STC) model offers a kinematic description of the source mechanism and leads to a more robust inversion problem. However, the premise of the source inversion based on STC is to ensure the accuracy of parameter $\kappa $ defined as the ratio of the Lamé constants, $\kappa $=$\lambda /\mu $, in a fault zone. In this study, we carry out a series of synthetic experiments using P-wave amplitudes in source mechanism inversions based on both the STC and MT models, and consider the influence of noise, the uncertainties in source locations and in the velocity model. We show that the nonlinear STC inversion with an appropriate value of $\kappa $ leads to more accurate result compared to the linear MT inversion. We also propose a new joint-STC inversion method to jointly invert for parameter $\kappa $ and the remaining parameters of the STC model (magnitude and the strike, dip, rake and slope angles). The results indicate that our proposed method yields robust results for both the parameter $\kappa $ and focal mechanisms. We apply our joint-STC inversion method to field microearthquake data observed in the West Bohemia region to validate some of the conclusions drawn from the synthetic experiments.