Refine
Has Fulltext
- yes (6)
Document Type
- Master's Thesis (6) (remove)
Language
- English (6)
Is part of the Bibliography
- yes (6)
Keywords
- Seismologie (2)
- seismology (2)
- Argentinien (1)
- Beamforming (1)
- Bodenunruhe (1)
- DAS (1)
- Erdbebenmodelierung (1)
- Erdbebenquellinversion (1)
- Erdbebenschwärme (1)
- Etna (1)
- Geschwindigkeitsmodell (1)
- H/V (1)
- HVSR (1)
- Kern-Mantel Grenze (1)
- Lumineszenz (1)
- MSPAC (1)
- Mikrozonierung (1)
- Nuklide (1)
- OSL (1)
- Ortscharakterisierung (1)
- Ortseffekte (1)
- Piano delle Concazze (1)
- Quellarray (1)
- Randelementmethode (1)
- SPAC (1)
- Schwarmbeben (1)
- Schwemmfächer (1)
- Steilwinkel-Analyse von PcP (1)
- Tiefbeben und Kernexplosionen (1)
- Ultra-Niedriggeschwindigkeitszonen (1)
- Vogtland (1)
- West Bohemia (1)
- Westböhmen (1)
- alluvial (1)
- ambient vibration (1)
- argentina (1)
- beam forming (1)
- boundary element method (1)
- convolutional neural network (1)
- core-mantle boundary (1)
- cosmogenic (1)
- deep earthquakes and nuclear explosions (1)
- deep learning (1)
- earthquake modeling (1)
- earthquake swarms (1)
- faltendes neuronales Netzwerk (1)
- fan (1)
- gemeinsame Inversion (1)
- geological hyperspectral image classification (1)
- geologische hyperspektrale Bildklassifikation (1)
- horizontal-vertikales Spektralverhältnis (1)
- joint inversion (1)
- kosmogen (1)
- microzonation (1)
- modifizierte räumliche Autkorrelationsmethode (1)
- nuclides (1)
- ortsverteile faseroptische Dehnungsmessung (1)
- räumliche Autkorrelationsmethode (1)
- räumliche Autokorrelation (1)
- seismic noise (1)
- seismisches Rauschen (1)
- site characterization (1)
- site effects (1)
- source array (1)
- source inversion (1)
- spatial autocorrelation (1)
- steep-angle analysis of PcP (1)
- ultra-low velocity zones (1)
- velocity model (1)
- volcanic tremor (1)
- vulkanischer Tremor (1)
- Ätna (1)
Institute
- Institut für Geowissenschaften (6) (remove)
Both horizontal-to-vertical (H/V) spectral ratios and the spatial autocorrelation method (SPAC) have proven to be valuable tools to gain insight into local site effects by ambient noise measurements. Here, the two methods are employed to assess the subsurface velocity structure at the Piano delle Concazze area on Mt Etna. Volcanic tremor records from an array of 26 broadband seismometers is processed and a strong variability of H/V ratios during periods of increased volcanic activity is found. From the spatial distribution of H/V peak frequencies, a geologic structure in the north-east of Piano delle Concazze is imaged which is interpreted as the Ellittico caldera rim. The method is extended to include both velocity data from the broadband stations and distributed acoustic sensing data from a co-located 1.5 km long fibre optic cable. High maximum amplitude values of the resulting ratios along the trajectory of the cable coincide with known faults. The outcome also indicates previously unmapped parts of a fault. The geologic interpretation is in good agreement with inversion results from magnetic survey data. Using the neighborhood algorithm, spatial autocorrelation curves obtained from the modified SPAC are inverted alone and jointly with the H/V peak frequencies for 1D shear wave velocity profiles. The obtained models are largely consistent with published models and were able to validate the results from the fibre optic cable.
DeepGeoMap
(2021)
In recent years, deep learning improved the way remote sensing data is processed. The classification of hyperspectral data is no exception. 2D or 3D convolutional neural networks have outperformed classical algorithms on hyperspectral image classification in many cases. However, geological hyperspectral image classification includes several challenges, often including spatially more complex objects than found in other disciplines of hyperspectral imaging that have more spatially similar objects (e.g., as in industrial applications, aerial urban- or farming land cover types). In geological hyperspectral image classification, classical algorithms that focus on the spectral domain still often show higher accuracy, more sensible results, or flexibility due to spatial information independence. In the framework of this thesis, inspired by classical machine learning algorithms that focus on the spectral domain like the binary feature fitting- (BFF) and the EnGeoMap algorithm, the author of this thesis proposes, develops, tests, and discusses a novel, spectrally focused, spatial information independent, deep multi-layer convolutional neural network, named 'DeepGeoMap’, for hyperspectral geological data classification. More specifically, the architecture of DeepGeoMap uses a sequential series of different 1D convolutional neural networks layers and fully connected dense layers and utilizes rectified linear unit and softmax activation, 1D max and 1D global average pooling layers, additional dropout to prevent overfitting, and a categorical cross-entropy loss function with Adam gradient descent optimization. DeepGeoMap was realized using Python 3.7 and the machine and deep learning interface TensorFlow with graphical processing unit (GPU) acceleration. This 1D spectrally focused architecture allows DeepGeoMap models to be trained with hyperspectral laboratory image data of geochemically validated samples (e.g., ground truth samples for aerial or mine face images) and then use this laboratory trained model to classify other or larger scenes, similar to classical algorithms that use a spectral library of validated samples for image classification. The classification capabilities of DeepGeoMap have been tested using two geological hyperspectral image data sets. Both are geochemically validated hyperspectral data sets one based on iron ore and the other based on copper ore samples. The copper ore laboratory data set was used to train a DeepGeoMap model for the classification and analysis of a larger mine face scene within the Republic of Cyprus, where the samples originated from. Additionally, a benchmark satellite-based dataset, the Indian Pines data set, was used for training and testing. The classification accuracy of DeepGeoMap was compared to classical algorithms and other convolutional neural networks. It was shown that DeepGeoMap could achieve higher accuracies and outperform these classical algorithms and other neural networks in the geological hyperspectral image classification test cases. The spectral focus of DeepGeoMap was found to be the most considerable advantage compared to spectral-spatial classifiers like 2D or 3D neural networks. This enables DeepGeoMap models to train data independently of different spatial entities, shapes, and/or resolutions.
Dynamic earthquake rupture modeling provides information on the rupture physics as the rupture velocity, frictions or tractions acting during the rupture process. Nevertheless, as often based on spatial gridded preset geometries, dynamic modeling is depending on many free parameters leading to both a high non-uniqueness of the results and large computation times. That decreases the possibilities of full Bayesian error analysis.
To assess the named problems we developed the quasi-dynamic rupture model which is presented in this work. It combines the kinematic Eikonal rupture model with a boundary element method for quasi-static slip calculation.
The orientation of the modeled rupture plane is defined by a previously performed moment tensor inversion. The simultanously inverted scalar seismic moment allows an estimation of the extension of the rupture. The modeled rupture plane is discretized by a set of rectangular boundary elements. For each boundary element an applied traction vector is defined as the boundary value.
For insights in the dynamic rupture behaviour the rupture front propagation is calculated for incremental time steps based on the 2D Eikonal equation. The needed location-dependent rupture velocity field is assumed to scale linearly with a layered shear wave velocity field.
At each time all boundary elements enclosed within the rupture front are used to calculate the quasi-static slip distribution. Neither friction nor stress propagation are considered. Therefore the algorithm is assumed to be “quasi-static”. A series of the resulting quasi-static slip snapshots can be used as a quasi-dynamic model of the rupture process.
As many a priori information is used from the earth model (shear wave velocity and elastic parameters) and the moment tensor inversion (rupture extension and orientation) our model is depending on few free parameters as the traction field, the linear factor between rupture and shear wave velocity and the nucleation point and time. Hence stable and fast modeling results are obtained as proven from the comparison to different infinite and finite static crack solutions.
First dynamic applications show promissing results. The location-dependent rise time is automatically derived by the model. Different simple kinematic models as the slip-pulse or the penny-shaped crack model can be reproduced as well as their corresponding slip rate functions. A source time function (STF) approximation calculated from the cumulative sum of moment rates of each boundary element gives results similar to theoretical and empirical known STFs.
The model was also applied to the 2015 Illapel earthquake. Using a simple rectangular rupture geometry and a 2-layered traction regime yields good estimates of both the rupture front propagation and the slip patterns which are comparable to literature results. The STF approximation shows a good fit with previously published STFs.
The quasi-dynamic rupture model is hence able to fastly calculate reproducable slip results. That allows to test full Bayesian error analysis in the future. Further work on a full seismic source inversion or even a traction field inversion can also extend the scope of our model.
Alluvial fans are important geomorphic markers and sedimentary archives of tectonic and climatic changes. Hence, basins providing perfect studying conditions can often be found in arid regions due to the low weathering impact and thus well preservation of sedimentary features. Twelve samples for optically/infrared stimulated luminescence (OSL/IRSL) dating and one depth profile for cosmogenic radionuclide dating (10Be) were collected in the Santa Maria Valley in NW Argentina, where the exceptional preservation of several generations of alluvial fans allow exploring the external forcing conditions that led to repeated cycles of incision and aggradation. The results of the OSL/IRSL dating yielded ages ranging between 0.4 ± 0.1 ka and 271.8 ± 24.5 ka. Previous studies next to the study area indicate a depositional age of 1.5-2 Mio years for the oldest generation of alluvial fans, which might still be supported by our ongoing 10Be dating. Due to field observations, sediment provenance, stratigraphic characteristics and the geomorphic pattern of erosion, seven (/eight) generations of alluvial fan deposits were recognized. Comparing my ages with global glaciation cycles as well as linking them to temperature proxies retrieved from a lake on the Altiplano Plateau, a good fit between alluvial fan accumulation phases and global glacial periods (corresponding to cold/wet phases within the central Andes) is observed. This suggests that aggradation occurs during the early stages of glacial periods, while incision is expected at the end of glacial phases. This pattern might be linked to variations in the vegetational cover (controlled by water availability), which will decrease/increase during hot and dry/cold and wet interglacial/glacial phases favoring/limiting sediment production and will increase/decrease during cold and wet/hot and dry glacial/interglacial phases. Even though the eastern Andean margin is showing neotectonic activities and is assumed to be active up to recent times, deformation and seismicity might most probably have played only a minor role in relation to the rather short timescale reflected by the data.
The Vogtland, located at the border region between the Czech Republic and Germany, is known for Holocene volcanism, gas and fluid emissions as well as for reoccurring earthquake swarms, pointing towards a high geodynamic activity. During the earthquake swarm in 2008/2009, a temporary array was installed close to Rohrbach (Germany), at an epicentral distance of about 10 km from the Nový Kostel focal zone (aperture ~0.75 km).
22 events of the recorded swarm were selected to set up a source array. Source arrays are spatially clustered earthquakes, which can be used in a similar manner as receiver array recordings of single events (Green’s functions reciprocity). The application of array seismology techniques like beam forming requires similar waveforms and precisely known origin times and locations. The resemblance of waveforms was assured by visual selection of events and quantified with the calculation of cross-correlation coefficients. We observed that the different events recorded at a single station generally show greater resemblances than the recordings of one event at all stations of the receiver array. This indicates a heterogeneous subsurface beneath the receiver array and a comparably homogeneous source array volume with respect to the frequency-dependent resolution of both arrays.
Beam forming was applied on the Z, N and E component recordings of the source array events at 11 stations, and the results were analysed with respect to converted or reflected crustal phases. While the theoretical back azimuth of the direct phases match the beam forming results in case of the source array analysis, in case of receiver array beam forming derivations of 15°-25° are observed.
PS phases, closely following the direct P phase and presumably SP phases, arriving shortly before the direct S phase can be observed on several stations. Based on the time differences to the direct P and S phases we inferred a conversion depth of about 0.6-0.9 km. A second deeper source array was set up in order to interpret a structural phase arriving 0.85 s after the direct P phase on records of deeper events only.
Additionally to the source array beam forming method an analytical method with a fixed medium velocity and a grid search method, both for determining conversion/ reflection locations of phases traveling off the direct line between source and receiver array, were developed and applied to other observed phases.
In conclusion, we think that the distinct beam forming results along with the striking waveform resemblance reveal the opportunities of using source arrays consisting of small swarm events for the analysis of crustal structures.
Assuming that liquid iron alloy from the outer core interacts with the solid silicate-rich lower mantle the influence on the core-mantle reflected phase PcP is studied. If the core-mantle boundary is not a sharp discontinuity, this becomes apparent in the waveform and amplitude of PcP. Iron-silicate mixing would lead to regions of partial melting with higher density which in turn reduces the velocity of seismic waves. On the basis of the calculation and interpretation of short-period synthetic seismograms, using the reflectivity and Gauss Beam method, a model space is evaluated for these ultra-low velocity zones (ULVZs). The aim of this thesis is to analyse the behaviour of PcP between 10° and 40° source distance for such models using different velocity and density configurations. Furthermore, the resolution limits of seismic data are discussed. The influence of the assumed layer thickness, dominant source frequency and ULVZ topography are analysed. The Gräfenberg and NORSAR arrays are then used to investigate PcP from deep earthquakes and nuclear explosions. The seismic resolution of an ULVZ is limited both for velocity and density contrasts and layer thicknesses. Even a very thin global core-mantle transition zone (CMTZ), rather than a discrete boundary and also with strong impedance contrasts, seems possible: If no precursor is observable but the PcP_model /PcP_smooth amplitude reduction amounts to more than 10%, a very thin ULVZ of 5 km with a first-order discontinuity may exist. Otherwise, if amplitude reductions of less than 10% are obtained, this could indicate either a moderate, thin ULVZ or a gradient mantle-side CMTZ. Synthetic computations reveal notable amplitude variations as function of the distance and the impedance contrasts. Thereby a primary density effect in the very steep-angle range and a pronounced velocity dependency in the wide-angle region can be predicted. In view of the modelled findings, there is evidence for a 10 to 13.5 km thick ULVZ 600 km south-eastern of Moscow with a NW-SE extension of about 450 km. Here a single specific assumption about the velocity and density anomaly is not possible. This is in agreement with the synthetic results in which several models create similar amplitude-waveform characteristics. For example, a ULVZ model with contrasts of -5% VP , -15% VS and +5% density explain the measured PcP amplitudes. Moreover, below SW Finland and NNW of the Caspian Sea a CMB topography can be assumed. The amplitude measurements indicate a wavelength of 200 km and a height of 1 km topography, previously also shown in the study by Kampfmann and Müller (1989). Better constraints might be provided by a joined analysis of seismological data, mineralogical experiments and geodynamic modelling.