Description: Reliable estimations of magnitude of completeness ( M c ) are essential for a correct interpretation of seismic catalogues. The spatial distribution of M c may be strongly variable and difficult to assess in mining environments, owing to the presence of galleries, cavities, fractured regions, porous media and different mineralogical bodies, as well as in consequence of inhomogeneous spatial distribution of the seismicity. We apply a 3-D modification of the probabilistic magnitude of completeness (PMC) method, which relies on the analysis of network detection capabilities. In our approach, the probability to detect an event depends on its magnitude, source–receiver Euclidian distance and source–receiver direction. The suggested method is proposed for study of the spatial distribution of the magnitude of completeness in a mining environment and here is applied to a 2-months acoustic emission (AE) data set recorded at the Morsleben salt mine, Germany. The dense seismic network and the large data set, which includes more than one million events, enable a detailed testing of the method. This method is proposed specifically for strongly heterogeneous media. Besides, it can also be used for specific network installations, with sensors with a sensitivity, dependent on the direction of the incoming wave (e.g. some piezoelectric sensors). In absence of strong heterogeneities, the standards PMC approach should be used. We show that the PMC estimations in mines strongly depend on the source–receiver direction, and cannot be correctly accounted using a standard PMC approach. However, results can be improved, when adopting the proposed 3-D modification of the PMC method. Our analysis of one central horizontal and vertical section yields a magnitude of completeness of about M c 1 (AE magnitude) at the centre of the network, which increases up to M c 4 at further distances outside the network; the best detection performance is estimated for a NNE–SSE elongated region, which corresponds to the strike direction of the low-attenuating salt body. Our approach provides us with small-scale details about the capability of sensors to detect an earthquake, which can be linked to the presence of heterogeneities in specific directions. Reduced detection performance in presence of strong structural heterogeneities (cavities) is confirmed by synthetic waveform modelling in heterogeneous media.

Description: On 2012 May 20 and 29, two damaging earthquakes with magnitudes M w 6.1 and 5.9, respectively, struck the Emilia-Romagna region in the sedimentary Po Plain, Northern Italy, causing 26 fatalities, significant damage to historical buildings and substantial impact to the economy of the region. The earthquake sequence included four more aftershocks with M w  ≥ 5.0, all at shallow depths (about 7–9 km), with similar WNW–ESE striking reverse mechanism. The timeline of the sequence suggests significant static stress interaction between the largest events. We perform here a detailed source inversion, first adopting a point source approximation and considering pure double couple and full moment tensor source models. We compare different extended source inversion approaches for the two largest events, and find that the rupture occurred in both cases along a subhorizontal plane, dipping towards SSW. Directivity is well detected for the May 20 main shock, indicating that the rupture propagated unilaterally towards SE. Based on the focal mechanism solution, we further estimate the co-seismic static stress change induced by the May 20 event. By using the rate-and-state model and a Poissonian earthquake occurrence, we infer that the second largest event of May 29 was induced with a probability in the range 0.2–0.4. This suggests that the segment of fault was already prone to rupture. Finally, we estimate peak ground accelerations for the two main events as occurred separately or simultaneously. For the scenario involving hypothetical rupture areas of both main events, we estimate M w  = 6.3 and an increase of ground acceleration by 50 per cent. The approach we propose may help to quantify rapidly which regions are invested by a significant increase of the hazard, bearing the potential for large aftershocks or even a second main shock.

Description: Tectonic earthquake swarms challenge our understanding of earthquake processes since it is difficult to link observations to the underlying physical mechanisms and to assess the hazard they pose. Transient forcing is thought to initiate and drive the spatio-temporal release of energy during swarms. The nature of the transient forcing may vary across sequences and range from aseismic creeping or transient slip to diffusion of pore pressure pulses to fluid redistribution and migration within the seismogenic crust. Distinguishing between such forcing mechanisms may be critical to reduce epistemic uncertainties in the assessment of hazard due to seismic swarms, because it can provide information on the frequency–magnitude distribution of the earthquakes (often deviating from the assumed Gutenberg–Richter relation) and on the expected source parameters influencing the ground motion (for example the stress drop). Here we study the ongoing Pollino range (Southern Italy) seismic swarm, a long-lasting seismic sequence with more than five thousand events recorded and located since October 2010. The two largest shocks (magnitude M w = 4.2 and M w = 5.1) are among the largest earthquakes ever recorded in an area which represents a seismic gap in the Italian historical earthquake catalogue. We investigate the geometrical, mechanical and statistical characteristics of the largest earthquakes and of the entire swarm. We calculate the focal mechanisms of the M l 〉 3 events in the sequence and the transfer of Coulomb stress on nearby known faults and analyse the statistics of the earthquake catalogue. We find that only 25 per cent of the earthquakes in the sequence can be explained as aftershocks, and the remaining 75 per cent may be attributed to a transient forcing. The b -values change in time throughout the sequence, with low b -values correlated with the period of highest rate of activity and with the occurrence of the largest shock. In the light of recent studies on the palaeoseismic and historical activity in the Pollino area, we identify two scenarios consistent with the observations and our analysis: This and past seismic swarms may have been ‘passive’ features, with small fault patches failing on largely locked faults, or may have been accompanied by an ‘active’, largely aseismic, release of a large portion of the accumulated tectonic strain. Those scenarios have very different implications for the seismic hazard of the area.

Description: Automated location of seismic events is a very important task in microseismic monitoring operations as well for local and regional seismic monitoring. Since microseismic records are generally characterized by low signal-to-noise ratio, automated location methods are requested to be noise robust and sufficiently accurate. Most of the standard automated location routines are based on the automated picking, identification and association of the first arrivals of P and S waves and on the minimization of the residuals between theoretical and observed arrival times of the considered seismic phases. Although current methods can accurately pick P onsets, the automatic picking of the S onset is still problematic, especially when the P coda overlaps the S wave onset. In this paper, we propose a picking free earthquake location method based on the use of the short-term-average/long-term-average (STA/LTA) traces at different stations as observed data. For the P phases, we use the STA/LTA traces of the vertical energy function, whereas for the S phases, we use the STA/LTA traces of a second characteristic function, which is obtained using the principal component analysis technique. In order to locate the seismic event, we scan the space of possible hypocentral locations and origin times, and stack the STA/LTA traces along the theoretical arrival time surface for both P and S phases. Iterating this procedure on a 3-D grid, we retrieve a multidimensional matrix whose absolute maximum corresponds to the spatial coordinates of the seismic event. A pilot application was performed in the Campania-Lucania region (southern Italy) using a seismic network (Irpinia Seismic Network) with an aperture of about 150 km. We located 196 crustal earthquakes (depth 〈 20 km) with magnitude range 1.1 〈 M L  〈 2.7. A subset of these locations were compared with accurate manual locations refined by using a double-difference technique. Our results indicate a good agreement with manual locations. Moreover, our method is noise robust and performs better than classical location methods based on the automatic picking of the P and S waves first arrivals.

Description: We suggest a new clustering approach to classify focal mechanisms from large moment tensor catalogues, with the purpose of automatically identify families of earthquakes with similar source geometry, recognize the orientation of most active faults, and detect temporal variations of the rupture processes. The approach differs in comparison to waveform similarity methods since clusters are detected even if they occur in large spatial distances. This approach is particularly helpful to analyse large moment tensor catalogues, as in microseismicity applications, where a manual analysis and classification is not feasible. A flexible algorithm is here proposed: it can handle different metrics, norms, and focal mechanism representations. In particular, the method can handle full moment tensor or constrained source model catalogues, for which different metrics are suggested. The method can account for variable uncertainties of different moment tensor components. We verify the method with synthetic catalogues. An application to real data from mining induced seismicity illustrates possible applications of the method and demonstrate the cluster detection and event classification performance with different moment tensor catalogues. Results proof that main earthquake source types occur on spatially separated faults, and that temporal changes in the number and characterization of focal mechanism clusters are detected. We suggest that moment tensor clustering can help assessing time dependent hazard in mines.

Description: Seismicity induced by coal mining in the Ruhr region, Germany, has been monitored continuously over the last 25 yr. In 2006, a dense temporary network (HAMNET) was deployed to locally monitor seismicity induced by longwall mining close to the town of Hamm. Between 2006 July and 2007 July, more than 7000 events with magnitudes M L from –1.7 to 2.0 were detected. The spatiotemporal distribution of seismicity shows high correlation with the mining activity. In order to monitor rupture processes, we set up an automated source inversion routine and successfully perform double couple and full moment tensor (MT) inversions for more than 1000 events with magnitudes above M L  –0.5. The source inversion is based on a full waveform approach, both in the frequency and in the time domain, providing information about the centroid location, focal mechanism, scalar moment and full MT. Inversion results indicate a strong dominance of normal faulting focal mechanisms, with a steeper plane and a subhorizontal one. Fault planes are oriented parallel to the mining stopes. We classify the focal mechanisms based on their orientation and observe different frequency-magnitude distributions for families of events with different focal mechanisms; the overall frequency-magnitude distribution is not fitting the Gutenberg–Richter relation. Full MTs indicate that non-negligible opening tensile components accompanied normal faulting source mechanisms. Finally, extended source models are investigated for largest events. Results suggest that the rupture processes mostly occurred along the subvertical planes.