ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    facet.materialart.
    Unknown
    Induced seismicity due to hydraulic fracturing near Blackpool, UK: source modeling and event detection (2021)
    Springer Netherlands
    Details
    Publication Date: 2023-07-20
    Description: Monitoring small magnitude induced seismicity requires a dense network of seismic stations and high-quality recordings in order to precisely determine events’ hypocentral parameters and mechanisms. However, microseismicity (e.g. swarm activity) can also occur in an area where a dense network is unavailable and recordings are limited to a few seismic stations at the surface. In this case, using advanced event detection techniques such as template matching can help to detect small magnitude shallow seismic events and give insights about the ongoing process at the subsurface giving rise to microseismicity. In this paper, we study shallow microseismic events caused by hydrofracking of the PNR-2 well near Blackpool, UK, in 2019 using recordings of a seismic network which was not designed to detect and locate such small events. By utilizing a sparse network of surface stations, small seismic events are detected using template matching technique. In addition, we apply a full-waveform moment tensor inversion to study the focal mechanisms of larger events (ML 〉 1) and used the double-difference location technique for events with high-quality and similar waveforms to obtain accurate relative locations. During the stimulation period, temporal changes in event detection rate were in agreement with injection times. Focal mechanisms of the events with high-quality recordings at multiple stations indicate a strike-slip mechanism, while a cross-section of 34 relocated events matches the dip angle of the active fault.
    Description: Karlsruher Institut für Technologie (KIT) (4220)
    Description: https://earthquakes.bgs.ac.uk/data/broadband_stationbook.html
    Keywords: ddc:551.22 ; Event detection ; Microseismicity ; Source modeling ; Template matching
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 2
    facet.materialart.
    Unknown
    Structure of the seismogenic zone of the southcentral Chilean margin revealed by local earthquake traveltime tomography (2009)
    AGU (American Geophysical Union)
    In:  Journal of Geophysical Research - Solid Earth, 114 (B01317).
    Details
    Publication Date: 2016-04-04
    Description: We use traveltime data of local earthquakes and controlled sources observed by a large, temporary, amphibious seismic network to reveal the anatomy of the southcentral Chilean subduction zone (37–39°S) between the trench and the magmatic arc. At this location the giant 1960 earthquake (M = 9.5) nucleated and ruptured almost 1000 km of the subduction megathrust. For the three-dimensional tomographic inversion we used 17,148 P wave and 10,049 S wave arrival time readings from 439 local earthquakes and 94 shots. The resolution of the tomographic images was explored by analyzing the model resolution matrix and conducting extensive numerical tests. The downgoing lithosphere is delineated by high seismic P wave velocities. High vp/vs ratio in the subducting slab reflects hydrated oceanic crust and serpentinized uppermost oceanic mantle. The subducting oceanic crust can be traced down to a depth of 80 km, as indicated by a low velocity channel. The continental crust extends to approximately a 50-km depth near the intersection with the subducting plate. This suggests a wide contact zone between continental and oceanic crust of about 150 km, potentially supporting the development of large asperities. Eastward the crustal thickness decreases again to a minimum of about a 30-km depth. Relatively low vp/vs at the base of the forearc does not support a large-scale serpentinization of the mantle wedge. Offshore, low vp and high vp/vs reflect young, fluid-saturated sediments of forearc basins and the accretionary prism.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 3
    facet.materialart.
    Unknown
    A high-resolution, time-variable afterslip model for the 2010 Maule Mw = 8.8, Chile megathrust earthquake (2013)
    Elsevier
    In:  Earth and Planetary Science Letters, 383 . pp. 26-36.
    Details
    Publication Date: 2017-03-06
    Description: The excellent spatial coverage of continuous GPS stations in the region affected by the Maule Mw = 8.8 2010 earthquake, combined with the proximity of the coast to the seismogenic zone, allows us to model megathrust afterslip on the plate interface with unprecedented detail. We invert post-seismic observations from continuous GPS sites to derive a time-variable model of the first 420 d of afterslip. We also invert co-seismic GPS displacements to create a new co-seismic slip model. The afterslip pattern appears to be transient and non-stationary, with the cumulative afterslip pattern being formed from afterslip pulses. Changes in static stress on the plate interface from the co- and post-seismic slip cannot solely explain the aftershock patterns, suggesting that another process – perhaps fluid related – is controlling the lower magnitude aftershocks. We use aftershock data to quantify the seismic coupling distribution during the post-seismic phase. Comparison of the post-seismic behaviour to interseismic locking suggests that highly locked regions do not necessarily behave as rate-weakening in the post-seismic period. By comparing the inter-seismic locking, co-seismic slip, afterslip, and aftershocks we attempt to classify the heterogeneous frictional behaviour of the plate interface.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 4
    facet.materialart.
    Unknown
    Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers (2022)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches and even achieve human-like performance under certain circumstances. However, as most studies differ in the datasets and exact evaluation tasks studied, it is yet unclear how the different approaches compare to each other. Furthermore, there are no systematic studies how the models perform in a cross-domain scenario, i.e., when applied to data with different characteristics. Here, we address these questions by conducting a large-scale benchmark study. We compare six previously published deep learning models on eight datasets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker. Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with EQTransformer having a small advantage for teleseismic data. Furthermore, we conduct a cross-domain study, in which we analyze model performance on datasets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but not from regional to teleseismic data or vice versa. As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily compare new models or evaluate performance on new datasets, beyond those presented here. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models in seismological analysis.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 5
    facet.materialart.
    Unknown
    SeisBench - A Toolbox for Machine Learning in Seismology (2022)
    SSA (Seismological Society of America)
    Details
    Publication Date: 2024-02-07
    Description: Machine‐learning (ML) methods have seen widespread adoption in seismology in recent years. The ability of these techniques to efficiently infer the statistical properties of large datasets often provides significant improvements over traditional techniques when the number of data are large (millions of examples). With the entire spectrum of seismological tasks, for example, seismic picking and detection, magnitude and source property estimation, ground‐motion prediction, hypocenter determination, among others, now incorporating ML approaches, numerous models are emerging as these techniques are further adopted within seismology. To evaluate these algorithms, quality‐controlled benchmark datasets that contain representative class distributions are vital. In addition to this, models require implementation through a common framework to facilitate comparison. Accessing these various benchmark datasets for training and implementing the standardization of models is currently a time‐consuming process, hindering further advancement of ML techniques within seismology. These development bottlenecks also affect “practitioners” seeking to deploy the latest models on seismic data, without having to necessarily learn entirely new ML frameworks to perform this task. We present SeisBench as a software package to tackle these issues. SeisBench is an open‐source framework for deploying ML in seismology—available via GitHub. SeisBench standardizes access to both models and datasets, while also providing a range of common processing and data augmentation operations through the API. Through SeisBench, users can access several seismological ML models and benchmark datasets available in the literature via a single interface. SeisBench is built to be extensible, with community involvement encouraged to expand the package. Having such frameworks available for accessing leading ML models forms an essential tool for seismologists seeking to iterate and apply the next generation of ML techniques to seismic data.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 6
    facet.materialart.
    Unknown
    PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning (2024)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-04-11
    Description: Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data, machine learning methods have already found widespread adoption. However, deep learning approaches are not yet commonly applied to ocean bottom data due to a lack of appropriate training data and models. Here, we compiled an extensive and labeled ocean bottom seismometer (OBS) data set from 15 deployments in different tectonic settings, comprising ∼90,000 P and ∼63,000 S manual picks from 13,190 events and 355 stations. We propose PickBlue, an adaptation of the two popular deep learning networks EQTransformer and PhaseNet. PickBlue joint processes three seismometer recordings in conjunction with a hydrophone component and is trained with the waveforms in the new database. The performance is enhanced by employing transfer learning, where initial weights are derived from models trained with land earthquake data. PickBlue significantly outperforms neural networks trained with land stations and models trained without hydrophone data. The model achieves a mean absolute deviation of 0.05 s for P-waves and 0.12 s for S-waves, and we apply the picker on the Hikurangi Ocean Bottom Tremor and Slow Slip OBS deployment offshore New Zealand. We integrate our data set and trained models into SeisBench to enable an easy and direct application in future deployments. Key Points We assembled a database of ocean Bottom Seismometer (OBS) waveforms and manual P and S picks, on which we train PickBlue, a deep learning picker Our picker significantly outperforms pickers trained with land-based data with confidence values reflecting the likelihood of outlier picks The picker and database are available in the SeisBench platform, allowing easy and direct application to OBS traces and hydrophone records
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 7
    facet.materialart.
    Unknown
    3D Local Earthquake Tomography of the Ecuadorian Margin in the Source Area of the 2016 Mw 7.8 Pedernales Earthquake (2021)
    Details
    Publication Date: 2021-07-21
    Description: Based on manually analyzed waveforms recorded by the permanent Ecuadorian network and our large aftershock deployment installed after the Pedernales earthquake, we derive three‐dimensional Vp and Vp/Vs structures and earthquake locations for central coastal Ecuador using local earthquake tomography. Images highlight the features in the subducting and overriding plates down to 35 km depth. Vp anomalies (∼4.5–7.5 km/s) show the roughness of the incoming oceanic crust (OC). Vp/Vs varies from ∼1.75 to ∼1.94, averaging a value of 1.82 consistent with terranes of oceanic nature. We identify a low Vp (∼5.5 km/s) region extending along strike, in the marine forearc. To the North, we relate this low Vp and Vp/Vs (〈1.80) region to a subducted seamount that might be part of the Carnegie Ridge (CR). To the South, the low Vp region is associated with high Vp/Vs (〉1.85) which we interpret as deeply fractured, probably hydrated OC caused by the CR being subducted. These features play an important role in controlling the seismic behavior of the margin. While subducted seamounts might contribute to the nucleation of intermediate megathrust earthquakes in the northern segment, the CR seems to be the main feature controlling the seismicity in the region by promoting creeping and slow slip events offshore that can be linked to the updip limit of large megathrust earthquakes in the northern segment and the absence of them in the southern region over the instrumental period.
    Description: Plain Language Summary: Using seismic data recorded by the permanent Ecuadorian network and the large emergency installation after the 2016 Pedernales earthquake, we obtained the seismic velocity structure together with precise earthquake locations for the coastal Ecuadorian margin. Our images highlight the heterogeneities of the subduction zone affected by seamounts and ridges comprising the oceanic crust. These features play an important role in controlling the seismic behavior of the margin. While seamounts can contribute to the occurrence of intermediate (M ∼ 7–7.5) megathrust earthquakes in the north, the Carnegie Ridge seems to be the main feature controlling the seismicity in the region by promoting creeping and slow slip events offshore that can be linked to the updip limit of large megathrust earthquakes in the northern segment and the absence of them in the southern region.
    Description: Key Points: 3D Vp and Vp/Vs models were calculated using local earthquake tomography in the region affected by the 2016 Pedernales, Ecuador earthquake Tomographic images highlight the heterogeneities of the margin affected by seamounts and ridges comprising the oceanic crust Carnegie Ridge seems the main feature controlling the seismic activity and the offshore extent of large megathrust earthquakes in the region
    Description: IGEPN
    Description: IRD
    Description: INSU‐CNRS
    Description: ANR
    Description: NERC
    Description: IRIS PASSCAL and NSF RAPID Program Award
    Description: ANID under Programa Formación de Capital Humano Avanzado, Becas Chile
    Description: UCA/JEDI project
    Keywords: 551.22 ; aftershocks ; Ecuador ; megathrust earthquake ; seismic tomography ; subduction zone ; velocity structure
    Type: article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 8
    facet.materialart.
    Unknown
    Brittle-Ductile Deformation and Tensile Rupture of Dome Lava During Inflation at Santiaguito, Guatemala (2021)
    Details
    Publication Date: 2021-10-14
    Description: Gas-and-ash explosions at the Santiaguito dome complex, Guatemala, commonly occur through arcuate fractures, following a 5- to 6-min period of inflation observed in long-period seismic signals. Observation of active faults across the dome suggests a strong shear component, but as fault propagation generally proceeds through the coalescence of tensile fractures, we surmise that explosive eruptions require tensile rupture. Here, we assess the effects of temperature and strain rate on fracture propagation and the tensile strength of Santiaguito dome lavas. Indirect tensile tests were conducted on samples with a porosity range of 3–30% and over diametral displacement rates of 0.04, 0.004, and 0.0004 mm/s. At room temperature, the tensile strength of dome rock is rate independent (within the range tested) and inversely proportional to the porosity of the material. At eruptive temperatures we observe an increasingly ductile response at either higher temperature or lower displacement rate, where ductile deformation is manifest by a reduction in loading rate during constant deformation rate tests, resulting in slow tearing, viscous flow, and pervasive damage. We propose a method to conduct indirect tensile tests under volcanic conditions using a modification of the Brazilian disc testing protocol and use brittleness indices to classify deformation modes across the brittle-ductile transition. We show that a degree of ductile damage is inevitable in the lava core during explosions at the Santiaguito dome complex and discuss how strain leading to rupture controls fracture geometry, which would impact gas pressure release or buildup and regulate explosive activity.
    Keywords: 551.21 ; 551.8 ; tensile strength ; Santiaguito ; Brittleness Index ; brittle-ductile ; indirect tensile tests ; Brazilian disc tests
    Language: English
    Type: map
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...