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Understanding the fracturing mechanisms of rock on both macro- and micro-scale is important for properly designing rock engineering applications. However, there is still a lack of understanding of why macro and micro-scale fracturing mechanisms differ. In this study, acoustic emission (AE) and digital image correlation (DIC) techniques were employed to track the microcracking processes in granite specimens subjected to indirect (Brazilian) and direct tensile loadings. The moment tensor inversion of the AE waveforms and the DIC strain field data revealed that the ultimate so-called tensile macro-fracture was predominantly composed of shear microcracks in Brazilian tests and tensile microcracks in the direct tension tests. The different contributions of shear and tensile microcracks to the formation of the macro-fracture explain the difference between direct and indirect tensile strengths. Our results showed that the compressive stress in the Brazilian test due to its biaxial stress field and the grain size are the two critical factors affecting the microcracking mechanisms in the tested coarse-grained granite. Characterizing the surface of the generated macro-fractures and the results of a series of complementary tensile tests performed on fine-grained mortar specimens suggested that reducing the compressive stress and grain size decreases the contribution of shear microcracks. The results of this study can be used in rock fracture applications in granitic rocks such as hydraulic fracturing for geothermal energy extraction, where the knowledge of the cracking location and mechanisms is critical for enhancing the reservoir's productivity.HighlightsSo-called tensile macro-fractures are composed of both shear and tensile cracks at the microscale.The ratio of shear-to-tensile microcracks depends on the grain size and stress states.Microcracks are predominantly shear in Brazilian and tensile in the direct tensile loading.

Accurate characterisation of seismic source mechanisms in mining environments is crucial for effective hazard mitigation, but it is complicated by the presence of anisotropic geological conditions. Neglecting anisotropic effects during moment tensor (MT) inversion introduces significant distortions in the retrieved source characteristics. In this study, we investigated the impact of ignoring anisotropy during MT inversion on the reliability of hazard assessment. We investigated a high-energy (2.18 10 6 J) induced by mining activities in the Nantun coal mine in China. The subsurface was modelled as a vertically transversely isotropic medium, incorporating four different levels of anisotropy derived from site-specific geological and tomographic data. The results demonstrate that neglecting anisotropy led to significant distortions in the retrieved source parameters, including polarity flips and the introduction of spurious non-double-couple components. These artefacts compromised the accuracy of hazard analysis and undermined the effectiveness of risk management strategies. In contrast, the sequential inversion method yields a MT solution with a 0.14 misfit, accurately retrieving the focal mechanism, which is interpreted as a normal right-lateral oblique shear failure along the F3 fault. This study highlights the importance of properly incorporating anisotropy effects when analysing induced seismicity in heterogeneous mining environments. The use of a homogeneous Green’s function for MT inversion may be inadequate for reliable hazard assessment, underscoring the need for advanced techniques that can effectively model the influence of subsurface anisotropy on seismic wave propagation and source retrieval.

A crustal earthquake of the 2024 Noto Peninsula earthquake with a moment magnitude of 7.5 occurred on January 1, 2024, and was followed by many aftershocks distributed in both onshore and offshore regions. The mainshock was characterized as a reverse fault with NW–SE pressure- (P-) axes. We conducted centroid moment tensor (CMT) inversions for the aftershocks using a three-dimensional seismic velocity structure model to capture the detailed stress state and fault geometries around the source region. CMT solutions were obtained for 221 aftershocks with moment magnitudes of 3.2–6.1 at depths shallower than 15 km. Our approach showed substantial improvement in depth determination of CMT solutions, compared with that of the hypocenter determination using P- and S-wave arrival times, even for the early aftershock period when no seismic station was available close to the earthquake source region. Our CMT solutions were characterized as follows: (1) reverse faults with an NW–SE P-axis, which is consistent with that of the mainshock mechanism; (2) strike-slip faults in predominantly shallower regions compared with those of type 1; (3) reverse faults with ENE-WSW P-axes, possibly activated following the mainshock in the shallow southwestern aftershock region; and (4) earthquakes predominantly featuring normal and strike-slip faults localizing at a depth of approximately 5 km around the dip transition zone in geologically constructed fault models. Additionally, we conducted the same CMT inversion for earthquakes that occurred between 2007 and 2023 to further understand the effect of the mainshock on the aftershock dynamics. We confirmed that CMT solutions of types 3 and 4 appeared as new earthquake categories after the mainshock, suggesting that the mainshock could have triggered them. Our results provide a deeper understanding of complex stress fields and fault geometries in the source region. Graphical Abstract

Irregular coal pillars left in longwall working faces are prone to stress concentration, resulting in failure and instability of coal pillar. Revealing the failure mechanism of the coal pillars is essential for the accurate prevention of coal pillar-type rockburst. Based on the geological conditions and the residual coal pillars in the 14320 working face of the Dongtan coal mine, this study investigates the failure mechanism and stress evolution characteristics in the abnormal area with irregular coal pillars through microseismic (MS) monitoring, moment tensor inversion, and velocity tomography of MS. The results show that (1) the MS events at the edge of the coal pillars are significantly more greater than those in the core area, in which, failure types of tension and compression occur in the edge and core areas, respectively; (2) the spatial parameters (strike φ, dip angle δ, slip angle γ) of the failure plane in the irregular coal pillar area were determined. The boundary of the irregular coal pillars was dominated by reverse fault sliding, and the core area is dominated by normal fault sliding; and (3) the stress field distribution characteristics of the working face and irregular coal pillars were determined using P-wave velocity tomography. The research findings provide a reference for analyzing the mechanisms of coal pillar failure, instability and the induced rockbursts.HighlightsMoment tensor theory is used to analyze the fracture mechanism of coal pillar in mines.Moment tensor theory reveals rupture types and occurrence of the rupture face in different regions of coal pillar.Stress evolution law of coal pillar is obtained by microseismic velocity tomography.

The Farnsworth Unit in northern Texas is a field site for studying geologic carbon storage during enhanced oil recovery (EOR) using CO2. Microseismic monitoring is essential for risk assessment by detecting fluid leakage and fractures. We analyzed borehole microseismic data acquired during CO2 injection and migration, including data denoising, event detection, event location, magnitude estimation, moment tensor inversion, and stress field inversion. We detected and located two shallow clusters, which occurred during increasing injection pressure. The two shallow clusters were also featured by large b values and tensile cracking moment tensors that are obtained based on a newly developed moment tensor inversion method using single-borehole data. The inverted stress fields at the two clusters showed large deviations from the regional stress field. The results provide evidence for microseismic responses to CO2/fluid injection and migration.

It is essential to investigate focal mechanisms of induced seismicity for understanding the rock fracturing, the failure mode, and the hazard evolution in underground mines. But the conventional methods using empiricism to infer the source mechanisms usually lead to ambiguous results for individual events. An optimized moment tensor inversion method using full waveforms was employed to quantitatively determine the rock fracturing orientation and the type of rupture process. Source parameters including the scalar moment, the moment magnitude, the full moment tensor, and the fault plane solutions were resolved of a seismic sequence in fault zones. Results show that the shear failure events in the fault F1 vicinities have similar focal mechanisms and suggest that the fault F1 is a reverse fault. The resolved strikes and dips are basically constant with the orientation of the fault. The events in the fault F2 vicinities are mainly dominated by shear-tensional failure. But the shear events experienced shear rupture and crack opening simultaneously, resulting in slippages not along the actual fault plane. There are more events in the fault F3 area which are characterized by complicated focal mechanisms. Three of the non-shear events are dominated by compressional failure and related to rock collapse, while the other non-shear events are dominated by tensional failure and related to crack opening. The shear dominated events experienced dual effects of shear failure and compression failure. The resolved fault plane solutions cannot reflect the actual geometry of the fault. It is proved that the moment tensor inversion is able to quantitatively analyze the focal mechanism of mining-induced seismicity in fault zones and it provides beneficial understandings of mining-induced fault slips.

High-magnitude events (HMEs) are commonly observed in underground mines, and they can lead to violent rock failures, such as rockbursts. While moment tensors (MTs) have been widely used to investigate the triggering mechanism of HMEs, the cluster properties of MTs before HMEs have rarely been systematically studied. This hinders the application of MTs to predict HMEs and manage dynamic hazard risks. This study aims to characterize the cluster properties of MTs before HMEs and apply them to predict HMEs. A seismic clustering method suitable for the hybrid MT inversion was proposed to acquire reliable source mechanism solutions. Based on a case study, the MTs and decompositions were retrieved for seventeen HMEs and seismic events in the week preceding their occurrence. Cluster analysis results show that HMEs are close in location but still have entirely different source mechanisms. Pre-HME events show a distinct difference in strikes and dips in the cases dominated by roof movement or coal mass failure. The analysis of the cluster probabilities associated with source location errors, radius, and mechanisms was then conducted based on the seismic failure mechanisms; and a refined cluster possibility index, the number of possible clustered events (NPCE), was proposed to identify abnormal risk zones. A risk assessment index, namely the number of possible clustered events (INPCE), was proposed to evaluate the degree of a cluster of seismic events. A posteriori analysis of seventeen cases showed a prediction accuracy of up to 60% of HMEs, and a risk threshold of 0.4 was recommended in the case of acceptable completeness of seismic data. The low sensitivity of the monitoring system and the poor seismicity would be the two main limitations, and deep learning based automatic location and source mechanism inversion techniques could be used to improve the application.HighlightsAn agglomerative hierarchical cluster-based source cluster determination method is proposed for hybrid moment tensor inversion.The moment tensor solutions of seismic events before high-magnitude events (HMEs) are analyzed.A rockburst assessment method is proposed based on cluster probability associated with source location errors, radius, and mechanisms.A risk-based assessment back analysis is conducted to discuss the advantages and limitations of the method.

In recent years, strong seisms are triggered frequently during deep coal mining process, which seriously threatens the safety of underground miners and ground residents, as well as restricts the productivity and effectiveness of mining activities. It is essential to investigate focal mechanisms and source parameters of seisms for understanding the rock fracturing, the rupture scale and the failure mode. However, the focal mechanism and the internal relationship among source parameters lack systematic research in deep mines. More than 11473 seismic events have been recorded so far in the No.6 mining area of Dongtan Coal Mine, among which 27 events with moment magnitude MW ≥ 1.0 occur in panel 06/63. Results show that Savage model (ω3) has well applicability for spectral analysis in 27 observed seismic events and accords with the characteristics of fast attenuation of displacement amplitude in high frequency. Focal mechanisms of seism events are mainly dominated by pure shear failure and mixed shear failure. Based on the moment tensor inversion (MTI) method and genetic algorithm (GA, a deep learning method), the correlation of source parameters is revealed, and the scale and occurrence of source rupture are calculated effectively. The new preliminary criterion for determining rock fracture type by the dip angle δ and inclination angle θ of fracture surfaces is proposed. Formation mechanisms of strong seisms can be categorized into two types by using the spatial distribution characteristics of fracture surfaces and P–T projection. Meanwhile, we believe that the two mechanisms cross and promote each other under mining disturbance and overburden loads.HighlightsThe moment tensor inversion (MTI) method is used to distinguish the focal mechanism of mine seisms.The correlation of source parameters is developed based on Fourier transform (FFT) method and Savage model.A new preliminary criterion is proposed by the dip angle δ and inclination angle θ of fracture surfaces to determine the fracture types of the rock mass.Formation mechanisms of strong seisms are discussed in detail by using the P–T projection and the fracture surface occurrence.

Precise stochastic approaches to quantitatively calculate the source uncertainties offers the opportunity to eliminate the influence of anisotropy on moment tensor inversion. The effects of ignoring anisotropy were tested by using homogeneous Green’s functions. Results indicate the influence of anisotropy and noise on fault plane rotation is very small for a pure shear source whether it is restricted to double couple solution or full moment tensor solution. Green’s functions with different prior rough anisotropy information were tested, indicating that the complex source is more sensitive to velocity models than the pure shear source and the fault plane rotation caused by full moment tensor solution is larger than the pure double couple solution. Collaborative P-wave velocity inversion with active measurements and passive acoustic emission data using the fast-marching method were conducted, and new Green’s functions established based on the tomography results. The resolved fault plane solution rotated only 3.5° when using the new Green’s functions, but the presence of spurious isotropic and compensated linear vector dipole components was not completely eliminated. It is concluded that the cooperative inversion is capable of greatly improving the accuracy of the fault plane solutions and reducing the spurious components in the full moment tensor solution.

The article investigates the reliability of moment tensor (MT) inversion in time domain with use of first P-wave amplitude, a method used to determine the source mechanisms of earthquakes, across four different seismic networks. The study compares the synthetic tests results of MT inversion for two underground mining and two artificial reservoir monitoring seismic networks. The analysis was performed to assesses how consistency and accuracy of the results depend on different factors like: network configuration, events depth, velocity model, focal mechanism of event and applied noise. The findings highlight the impact of network configuration compared to other variables and data quality on the reliability of moment tensor inversion and provide insights into different factors which have to be considered to enhance MT accuracy. The significance of events depth in P-wave amplitude MT inversion and the necessity to consider velocity model influence, especially presence of high velocity gradient, is highlighted by the presented results.