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We estimated the seismic attenuation (Q factor) of the Greenland Ice Sheet (GrIS) by comparing observed and theoretical Rayleigh waveforms. Observed waveforms are obtained by interfering noise waveforms in vertical‐component seismograms between stations belonging to the latest broadband seismic network distributed throughout Greenland (GLISN network). Theoretical waveforms are calculated by parallel computation using the latest 3‐D seismic waveform modeling method. Comparing the observed waveforms with the theoretical waveforms at different Q factors reveals that the GrIS has a low Q of 10 ≤ QP, QS ≤ 50, indicating very high attenuation of seismic waves due to the ice. This study is the first to establish the low Q factor of ice sheets via ultra‐long‐distance propagation (350−1,000 km). The Q factors obtained in this study are indispensable for estimating the thermal state and density distribution of the GrIS, as well as for interpreting the characteristics of seismic waveform that propagates through the GrIS. Plain Language Summary: Seismic anelastic attenuation refers to the energy loss caused by anelastic processes or internal friction during wave propagation and is quantified by the quality (Q) factor. The Q factor of ice sheets and glacial ice is especially important because it is highly sensitive to the thermal state and density distribution. We estimated the Q factor of the Greenland Ice Sheet (GrIS) by comparing observed and theoretical surface (Rayleigh) waveforms. Observed waveforms are extracted by the latest broadband seismic network distributed throughout Greenland (GLISN network). Theoretical waveforms are calculated using the latest 3‐D seismic waveform modeling method. The results showed an extremely low Q (10–50) for the GrIS, indicating very high attenuation of seismic waves. Although previous studies have obtained similar results, they all used high frequency (≥30 Hz) seismic waves with short propagation distances (<∼10 km). This study is the first to infer the large‐scale, bulk Q property of the GrIS using low‐frequency (0.1–0.3 Hz) waves and long (350−1,000 km) propagation distances. The Q factors obtained in this study are essential for estimating the internal state of the GrIS, as well as for interpreting the characteristics of seismic waveforms that propagate through it. Key Points: Seismic attenuation of the Greenland Ice Sheet is estimated by comparing the observed and theoretical Rayleigh waveformsThe quality (Q) factor of the ice sheet is 10–50 for both P and S waves, indicating extremely high attenuationThis is the first Q estimation targeting the ice sheet using waves with a propagation distance of more than 100 km [ABSTRACT FROM AUTHOR]

Understanding of the potential to injection‐induced seismicity along faults requires the response of fault zone system to spatiotemporal perturbations in pore pressure and stress. In this study, three‐dimensional (3‐D) model system consisting of the caprock, reservoir, and basement is intersected by vertical strike‐slip faults. We examine the full poroelastic behavior of the formation and perform the mechanical analysis along each fault zone using the Coulomb stress change. The magnitude, rate, and location of potential earthquakes are predicted using the spatial distribution of stresses and pore pressure over time. Rapid diffusion of pore pressure into conductive faults initiates failure, but the majority of induced seismicity occurs at deep fault zones due to poroelastic stabilization near the injection interval. Less permeable faults can be destabilized by either delayed pore pressure diffusion or poroelastic stressing. A two‐dimensional (2‐D) horizontal model, representing the interface between the reservoir and the basement, limits diffusion of pore pressure and deformation of the formation in the vertical direction that may overestimate or underestimate the potential of earthquakes along the fault. Our numerical results suggest that the 3‐D modeling of faulting system including poroelastic coupling can reduce the uncertainty in the seismic hazard prediction by considering the hydraulic and mechanical interaction between faults and bounding formations. Key Points: Multiple faulting system is modeled in a three‐dimensional (3‐D) domain, including poroelastic couplingPore pressure diffusion and/or poroelastic stressing induce seismicity along the fault with any hydraulic typeThe 3‐D modeling captures properly the hydraulic and mechanical interaction between faults and surrounding formations [ABSTRACT FROM AUTHOR]

The characterization of the fracturing state of a potentially unstable rock cliff is a crucial requirement for stability assessments and mitigation purposes. Classical measurements of fracture location and orientation can however be limited by inaccessible rock exposures. The steep topography and high-rise morphology of these cliffs, together with the widespread presence of fractures, can additionally condition the success of geophysical prospecting on these sites. In order to mitigate these limitations, an innovative approach combining noncontact geomechanical measurements, active and passive seismic surveys, and 3-D numerical modeling is proposed in this work to characterize the 3-D fracture setting of an unstable rock mass, located in NW Italian Alps (Madonna del Sasso, VB). The 3-D fracture geometry was achieved through a combination of field observations and noncontact geomechanical measurements on oriented pictures of the cliff, resulting from a previous laser-scanning and photogrammetric survey. The estimation of fracture persistence within the rock mass was obtained from surface active seismic surveys. Ambient seismic noise and earthquakes recordings were used to assess the fracture control on the site response. Processing of both data sets highlighted the resonance properties of the unstable rock volume decoupling from the stable massif. A finite element 3-D model of the site, including all the retrieved fracture information, enabled both validation and interpretation of the field measurements. The integration of these different methodologies, applied for the first time to a complex 3-D prone-to-fall mass, provided consistent information on the internal fracturing conditions, supplying key parameters for future monitoring purposes and mitigation strategies. [ABSTRACT FROM AUTHOR]