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Information on the contemporary in-situ stress state of the earth’s crust is essential for geotechnical applications and physics-based seismic hazard assessment. Yet, stress data records for a data point are incomplete and their availability is usually not dense enough to allow conclusive statements. This demands a thorough examination of the in-situ stress field which is achieved by 3D geomechanicalnumerical models. However, the models spatial resolution is limited and the resulting local stress state is subject to large uncertainties that confine the significance of the findings. In addition, temporal variations of the in-situ stress field are naturally or anthropogenically induced. In my thesis I address these challenges in three manuscripts that investigate (1) the current crustal stress field orientation, (2) the 3D geomechanical-numerical modelling of the in-situ stress state, and (3) the phenomenon of injection induced temporal stress tensor rotations. In the first manuscript I present the first comprehensive stress data compilation of Iceland with 495 data records. Therefore, I analysed image logs from 57 boreholes in Iceland for indicators of the orientation of the maximum horizontal stress component. The study is the first stress survey from different kinds of stress indicators in a geologically very young and tectonically active area of an onshore spreading ridge. It reveals a distinct stress field with a depth independent stress orientation even very close to the spreading centre. In the second manuscript I present a calibrated 3D geomechanical-numerical modelling approach of the in-situ stress state of the Bavarian Molasse Basin that investigates the regional (70x70x10km³) and local (10x10x10km³) stress state. To link these two models I develop a multi-stage modelling approach that provides a reliable and efficient method to derive from the larger scale model initial and boundary conditions for the smaller scale model. Furthermore, I quantify the uncertainties in the models results which are inherent to geomechanical-numerical modelling in general and the multi-stage approach in particular. I show that the significance of the models results is mainly reduced due to the uncertainties in the material properties and the low number of available stress magnitude data records for calibration. In the third manuscript I investigate the phenomenon of injection induced temporal stress tensor rotation and its controlling factors. I conduct a sensitivity study with a 3D generic thermo-hydro-mechanical model. I show that the key control factors for the stress tensor rotation are the permeability as the decisive factor, the injection rate, and the initial differential stress. In particular for enhanced geothermal systems with a low permeability large rotations of the stress tensor are indicated. According to these findings the estimation of the initial differential stress in a reservoir is possible provided the permeability is known and the angle of stress rotation is observed. I propose that the stress tensor rotations can be a key factor in terms of the potential for induced seismicity on pre-existing faults due to the reorientation of the stress field that changes the optimal orientation of faults.

The purpose of this thesis is to develop an automated inversion scheme to derive point and finite source parameters for weak earthquakes, here intended with the unusual meaning of earthquakes with magnitudes at the limit or below the bottom magnitude threshold of standard source inversion routines. The adopted inversion approaches entirely rely on existing inversion software, the methodological work mostly targeting the development and tuning of optimized inversion flows. The resulting inversion scheme is tested for very different datasets, and thus allows the discussion on the source inversion problem at different scales. In the first application, dealing with mining induced seismicity, the source parameters determination is addressed at a local scale, with source-sensor distance of less than 3 km. In this context, weak seismicity corresponds to event below magnitude MW 2.0, which are rarely target of automated source inversion routines. The second application considers a regional dataset, namely the aftershock sequence of the 2010 Maule earthquake (Chile), using broadband stations at regional distances, below 300 km. In this case, the magnitude range of the target aftershocks range down to MW 4.0. This dataset is here considered as a weak seismicity case, since the analysis of such moderate seismicity is generally investigated only by moment tensor inversion routines, with no attempt to resolve source duration or finite source parameters. In this work, automated multi-step inversion schemes are applied to both datasets with the aim of resolving point source parameters, both using double couple (DC) and full moment tensor (MT) models, source duration and finite source parameters. A major result of the analysis of weaker events is the increased size of resulting moment tensor catalogues, which interpretation may become not trivial. For this reason, a novel focal mechanism clustering approach is used to automatically classify focal mechanisms, allowing the investigation of the most relevant and repetitive rupture features. The inversion of the mining induced seismicity dataset reveals the repetitive occurrence of similar rupture processes, where the source geometry is controlled by the shape of the mined panel. Moreover, moment tensor solutions indicate a significant contribution of tensile processes. Also the second application highlights some characteristic geometrical features of the fault planes, which show a general consistency with the orientation of the slab. The additional inversion for source duration allowed to verify the empirical correlation for moment normalized earthquakes in subduction zones among a decreasing rupture duration with increasing source depth, which was so far only observed for larger events.

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 characterised by low signal-to-noise ratio, such 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 thesis I developed a picking free automated method based on the Short-Term-Average/Long-Term-Average (STA/LTA) traces at different stations as observed data. I used the STA/LTA of several characteristic functions in order to increase the sensitiveness to the P wave and the S waves. For the P phases we use the STA/LTA traces of the vertical energy function, while for the S phases, we use the STA/LTA traces of the horizontal energy trace and then a more optimized characteristic function which is obtained using the principal component analysis technique. The orientation of the horizontal components can be retrieved by robust and linear approach of waveform comparison between stations within a network using seismic sources outside the network (chapter 2). 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 three-dimensional grid we retrieve a multidimensional matrix whose absolute maximum corresponds to the spatial and temporal coordinates of the seismic event. Location uncertainties are then estimated by perturbing the STA/LTA parameters (i.e the length of both long and short time windows) and relocating each event several times. In order to test the location method I firstly applied it to a set of 200 synthetic events. Then we applied it to two different real datasets. A first one related to mining induced microseismicity in a coal mine in the northern Germany (chapter 3). In this case we successfully located 391 microseismic event with magnitude range between 0.5 and 2.0 Ml. To further validate the location method I compared the retrieved locations with those obtained by manual picking procedure. The second dataset consist in a pilot application performed in the Campania-Lucania region (southern Italy) using a 33 stations seismic network (Irpinia Seismic Network) with an aperture of about 150 km (chapter 4). We located 196 crustal earthquakes (depth < 20 km) with magnitude range 1.1 < Ml < 2.7. A subset of these locations were compared with accurate locations retrieved by a manual location procedure based on the use of a double difference technique. In both cases results indicate good agreement with manual locations. Moreover, the waveform stacking location method results noise robust and performs better than classical location methods based on the automatic picking of the P and S waves first arrivals.