ALBERT

Description: Stress maps show the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In stress maps SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org. The stress map of Taiwan 2022 is based on the WSM database release 2016. However, all data records have been checked and we added a large number of new data from earthquake focal mechanisms from the national earthquake catalog and from publications. The total number of data records has increased from n=401 in the WSM 2016 to n=6,498 (4,234 with A-C quality) in the stress map of Taiwan 2022 The update with earthquake focal mechanims is even larger since another 1313 earthquake focal mechanism data records beyond the scale of this map have been added to the WSM database. The digital version of the stress map is a layered pdf file generated with GMT (Wessel et al., 2019). It also provide estimates of the mean SHmax orientation on a regular 0.1° grid using the tool stress2grid (Ziegler and Heidbach, 2019). Two mean SHmax orientations are estimated with search radii of r=25 and 50 km, respectively, and with weights according to distance and data quality. The stress map and data are available on the landing page at https://doi.org/10.5880/WSM.Taiwan2022 where further information is provided. The earthquake focal mechanism that are used for this stress map are provided by the Taiwan Earthquake Research Center (TEC) available at the TEC Data Center (https://tec.earth.sinica.edu.tw).

Description: The selection of earthquake focal mechanisms (FMs) for stress tensor inversion (STI) is commonly done on a spatial basis, that is, hypocentres. However, this selection approach may include data that are undesired, for example, by mixing events that are caused by different stress tensors when for the STI a single stress tensor is assumed. Due to the significant increase of FM data in the past decades, objective data-driven data selection is feasible, allowing more refined FM catalogues that avoid these issues and provide data weights for the STI routines. We present the application of angular classification with expectation-maximization (ACE) as a tool for data selection. ACE identifies clusters of FM without a priori information. The identified clusters can be used for the classification of the style-of-faulting and as weights of the FM data. We demonstrate that ACE effectively selects data that can be associated with a single stress tensor. Two application examples are given for weighted STI from South America. We use the resulting clusters and weights as a priori information for an STI for these regions and show that uncertainties of the stress tensor estimates are reduced significantly.

Description: Understanding fracturing processes and the hydromechanical relation to induced seismicity is a key question for enhanced geothermal systems (EGS). Commonly massive fluid injection, predominately causing hydroshearing, are used in large-scale EGS but also hydraulic fracturing approaches were discussed. To evaluate the applicability of hydraulic fracturing techniques in EGS, six in situ, multistage hydraulic fracturing experiments with three different injection schemes were performed under controlled conditions in crystalline rock at the A¨ spo¨ Hard Rock Laboratory (Sweden). During the experiments the near-field ground motion was continuously recorded by 11 piezoelectric borehole sensors with a sampling rate of 1 MHz. The sensor network covered a volume of 30×30×30 m around a horizontal, 28-m-long injection borehole at a depth of 410 m. To extract and characterize massive, induced, high-frequency acoustic emission (AE) activity from continuous recordings, a semi-automated workflow was developed relying on full waveform based detection, classification and location procedures. The approach extended the AE catalogue from 196 triggered events in previous studies to more than 19 600 located AEs. The enhanced catalogue, for the first time, allows a detailed analysis of induced seismicity during single hydraulic fracturing experiments, including the individual fracturing stages and the comparison between injection schemes. Beside the detailed study of the spatio-temporal patterns, event clusters and the growth of seismic clouds, we estimate relative magnitudes and b-values of AEs for conventional, cyclic progressive and dynamic pulse injection schemes, the latter two being fatigue hydraulic fracturing techniques. While the conventional fracturing leads to AE patterns clustered in planar regions, indicating the generation of a single main fracture plane, the cyclic progressive injection scheme results in a more diffuse, cloud-like AE distribution, indicating the activation of a more complex fracture network. For a given amount of hydraulic energy (pressure multiplied by injected volume) pumped into the system, the cyclic progressive scheme is characterized by a lower rate of seismicity, lower maximum magnitudes and significantly larger b-values, implying an increased number of small events relative to the large ones. To our knowledge, this is the first direct comparison of high resolution seismicity in a mine-scale experiment induced by different hydraulic fracturing schemes.

Description: The branch of seismology that deals with strong motion refers to seismic events that are hazardous to society in general.Two aspects drive the development in strong-motion seismology: First comes the societal need to understand the earth-quake hazard and to mitigate the associated risk. While the hazard changed little during human history, the risk in-creases steadily. A growing population—also in the most earthquake-prone regions of the world—and a more and morevulnerable infrastructure contribute to higher exposure to seismic events and higher vulnerability in case an earthquakestruck. The second driver in strong-motion seismology is shared with many other fields: the technological advancement.The available options for processing more and more data is unprecedented in human history and are still not exhausted.Both drivers also pose new challenges as in how to interpret and make use of the data.The scientific question, on the other hand, is clear: What can we learn from the rupture process (the source of earth-quakes), Earth’s structure (the medium through which seismic wave travels), and their interactions (how does an earth-quake affect its surrounding medium)? The question is broad and this thesis can focus only for specific aspects of thisquestion and provide answers for them. To reach the answers, I developed several new algorithms and models, all rootedin the concept of the likelihood function.Seismicity (and population alike) is concentrated along the tectonic plate boundaries. Different earthquake typesoccur at these boundaries and their characteristics in terms of ground shaking are considerably different. It is thereforeimportant to classify earthquakes according to their style of faulting. This classification is the objective of ACE (angularclusterization with expectation-maximization). Founded on the geomechanical principles, ACE provides earthquakeclassifications which can be applied not only for ground-motion related topics but also to study the Earth’s stress field.The development of reliable ground-motion models requires waveform data of high quality. Instrument related errorscan compromise the data quality, however, with large archives of waveform data, the correction for spurious s cannot behandled manually anymore. To alleviate the effect of instrument related data shifts, I developed the integrated combinedbaseline modification (ICBM). This routine is implemented during the data pre-processing and is particularly necessarywhen determining integrated quantities from acceleration records, such as coseismic displacement and radiated seismicenergy.Radiated seismic energy plays a major role in the development of a new type of ground-motion model that uses thesite-dependent energy estimates to model the seismic radiation pattern at lower frequencies of the earthquake amplitudespectrum. This kind of ground-motion model performs better when relating ground motion to earthquake triggeredlandslides, which is demonstrated with the landslides triggered by the 2016MW7.1 Kumamoto earthquake which struckcentral Kyushu (Japan). In this case study, it is also shown that the landslide movement direction is to some extent linkedto the seismic wave polarization.The preferred mathematical model in ground-motion model development is the mixed-effect model. However, themost widely used formalism does not allow data weighting beyond directly related measurement errors and weightsderived from ACE would inadvertently bias the model. To overcome this problem, I derived the model estimators onthe basis of the weighted likelihood. The derivation is exhaustive to allow for any of the currently used model types onthe basis of mixed effects to be augmented with data weighting. This formalism in connection with ACE allows for atransparent model development and also avoids model choices on subjective expert judgment

Description: Der Teil der Seismologie, der sich mit starker Bodenbewegung beschäftigt, bezieht sich auf seismische Ereignisse, dieallgemein ein Gefahrenpotenzial für die Gesellschaft darstellen. Die Seismologie der starken Bodenbewegung wird vonzwei Aspekten angetrieben: An erster Stelle kommt die gesellschaftliche Notwendigkeit, die Erdbebengefährdung zuverstehen und das damit verbundene Risiko zu vermeiden. Während die Gefährdung durch Erdbeben kaum Änderun-gen in der Geschichte der Menschheit unterlag, so wächst das Risiko andererseits kontinuierlich an. Eine wachsendeBevölkerung, insbesondere in den am stärksten von Erdbeben geprägten Regionen der Welt, und eine mehr und mehrstörungsanfällige Infrastruktur, tragen dazu bei, seismische Ereignissen vermehrt ausgesetzt zu sein, bei gleichzeitighöherem Schadenspotenzial. Der zweite Antrieb in der Seismologie wird mit vielen anderen Forschungsfeldern geteilt:der technische Fortschritt. Die verfügbaren Möglichkeiten beim Verarbeiten immer größerer Datenmengen sindbeispiellos in der Geschichte und sind bisher noch nicht erschöpft. Beide Triebfedern stellen aber auch neue Heraus-forderungen dar, inwiefern die Daten zu interpretieren sind und wie man sie nutzbar macht.Andererseits ist die wissenschaftliche Frage klar: Was können wir aus Bruchprozessen (als Erdbebenursachen), demAuf bau der Erde (als Medium, durch welches sich die seismischen Wellen ausbreiten), sowie deren Interaktion (inwiefernbeeinflusst das Beben das umgebende Gesteinsmedium)? Diese Frage ist breit gestellt und diese Abhandlung kann sichletztlich nur auf einige Punkte beziehen und Antworten dazu liefern. Um Antworten zu finden, habe ich mehrere neueAlgorithmen und Modelle entwickelt, die allesamt auf dem Konzept der Likelihood-Funktion beruhen.Seismizität (sowie auch die Bevölkerung) ist stark an den Rändern der tektonischen Platten konzentriert. An denPlattenrändern treten verschiedene Erdbebentypen mit teils erheblich abweichenden Eigenschaften auf. Daher ist esvon Wichtigkeit, Erdbeben nach ihrem Verwerfungstyp zu klassifizieren. Das Ziel von ACE (angular clusterization withexpectation-maximization, zu dt. ungefähr Winkelgruppenbestimmung mit Erwartungswertmaximierung) ist genaudiese Klassifizierung. Auf geomechanischen Prinzipien basierend, können die Erdbebenklassifizierungen mittels ACEnicht nur auf Themen der Bodenbewegungen angewandt werden, sondern auch zur Untersuchung des Spannungsfeldesder Erde herangezogen werden.Der Entwicklung von verlässlichen Bodenbewegungsmodellen bedarf es Wellenformdaten hoher Güte. Instrumentenbezogene Fehler können die Qualität beeinträchtigen, jedoch ist eine manuelle Korrektur großer Datenmengen nichtmehr umsetzbar. Um Instrumentenfehler, die sich in Verschiebungen in den Daten zeigen, zu reduzieren, habe icheine Nulllinienkorrektur entwickelt (ICBM, integrated combined baseline modification, zu dt. integriert kombinierteNulllinienmodifikation). Dieser Algorithmus wird in der Datenvorbereitung eingesetzt und ist insbesondere dannnotwendig, wenn integrierte Größen auf Grundlage von Beschleunigungsdaten bestimmt werden, wie statischer Ver-satz eines Erdbebens als auch abgestrahlte seismische Energie.Abgestrahlte seismische Energie spielt eine herausragende Rolle in der Entwicklung einer neuen Art von Bodenbewe-gungsmodell, welches anstellen von Magnituden stationsabhängige Energieabschätzungen nutzt, um die Erdbebenab-strahlcharakteristik auf tieferen Frequenzen des Erdbebenspektrums zu beschreiben. Diese Art Bodenbewegungsmodellist besser geeignet, wenn Bodenbewegungen in Bezug zu Hangrutschungen, welche durch Erdbeben verursacht wur-den, gesetzt werden. Als Beispiel dienen hier die Hangrutschungen, die 2016 durch das Erdbeben in Zentralkyuschu(Japan) mit einer Momentenmagnitude von 7.1 verursacht wurden. In dieser Fallstudie wird auch aufgezeigt, wie dieBewegungsrichtung der Hangrutschungen zu einem gewissen Grad durch die Ausrichtung des seismischen Wellenfeldesbeeinflusst werden.Das bevorzugte mathematische Modell in der Seismologie zur Beschreibung starker Bodenbewegungen ist das gemis-chte Modell. Jedoch lässt der weitläufig angewendete Formalismus nur die Einbettung von Gewichten in Form vonMessunsicherheiten zu. Gewichte wie sie von ACE erzeugt werden, die in keinem direkten Bezug zur Messgröße stehen,liefern zwangsläufig verzerrte Ergebnisse. Um dieses Problem zu umgehen, habe ich Parameterschätzer auf Basis einergewichteten Likelihood hergeleitet. Die rigorose Herleitung erlaubt sämtliche Arten des gemischten Modells, wie siezur Beschreibung von Bodenbewegungen genutzt werde, mit Datengewichtungen zu kombinieren. Dieser Formalis-mus in Verbindung mit ACE erlaubt die Entwicklung nachvollziehbarer Modelle und vermeidet Entscheidungen aufsubjektiver Expertenmeinung.

Description: The Taiwan Milun fault zone located at the boundary between the Eurasian and Philippine Sea plates. This fault slips frequently and produced large earthquakes, as for example the Mw6.4 Hualien earthquake (6 February 2018). We map and observe the fault zone and its behavior at depth by high spatial resolution dynamic strain sensing with optical fiber. In 2021-2022, we drilled and cored the fault, and deployed a 3D multi-cross-fault fiber array comprising a borehole loop with a depth of 700 m (Hole-A, Hanging wall site, crossing the fault at depth), a surface array crossing the fault rupture zone using commercial fiber, and a second borehole loop of 500m fiber (Hole-B, Footwall site). The high spatial resolution from distributed acoustic sensing (DAS) and the retrieved core combined with geophysical logs allow us to characterize the structure on meter-scale. Within the Milun fault zone, we identified a 20-m wide fault core comprised of gray and black gouge in the core sample. DAS strain-rate records associated with the same depth as the fault core show a distinct amplification. The amplification ratio of 2.5-3 is constant as for all types of events (local, teleseismic ), when compared to DAS channels at larger depth, related to a consolidated rock material. Although the fault gouge is narrow, the nature of the amplification in strain is due to its strong material contrast from fault gouge. This result may shed the light on the understanding of fault-zone dynamics in terms of remote earthquake triggering and near-fault ground motion.

Description: Distributed Acoustic Sensing (DAS) is used to record high-spatial resolution strain-rate data. For ground motion observation, the DAS data can be converted from strain rate to acceleration or velocity by array-based measurements with coherent plane waves. DAS provides an opportunity to map high-resolution shaking patterns near faults. We installed collocated geophones and optical fiber in Hualien City (a very seismically active area in Taiwan) from the end of January to the end of February in 2022. Earthquakes with magnitudes (Mw) between 3.2 and 5.4 have been recorded. These records illustrate the typical magnitude-distance dependence of ground-motion but also show saturation for higher magnitudes and/or at shorter distances (e.g for an earthquake of Mw 5.2 earthquake recorded at 100 km). For frequency-based analyses, clipped signals on DAS result in challenges not present in classical instruments (seismometers). The upper limit in dynamic range of seismometers results in easily identifiable trapezoidal signals. The dynamic range of DAS interrogators is limited by gauge length, sampling frequency, and wrapped phase in the interferometric phase demodulation. We observe that clipped DAS signals not only affect time series but also contaminate their spectra on all frequencies, due to the random nature of clipping in DAS—contrasting to the flat plateaus in clipped time series on seismometers. Therefore, the identification of the start and end points of clipped DAS records poses a major challenge, which we aim to resolve with a neural network. This approach enhances the efficiency for quality control of massive DAS datasets.