@phdthesis{Hendriyana2017,
  author    = {Hendriyana, Andri},
  title     = {Detection and Kirchhoff-type migration of seismic events by use of a new characteristic function},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-398879},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 139},
  year      = {2017},
  abstract  = {The classical method of seismic event localization is based on the picking of body wave arrivals, ray tracing and inversion of travel time data. Travel time picks with small uncertainties are required to produce reliable and accurate results with this kind of source localization. Hence recordings, with a low Signal-to-Noise Ratio (SNR) cannot be used in a travel time based inversion. Low SNR can be related with weak signals from distant and/or low magnitude sources as well as with a high level of ambient noise. Diffraction stacking is considered as an alternative seismic event localization method that enables also the processing of low SNR recordings by mean of stacking the amplitudes of seismograms along a travel time function. The location of seismic event and its origin time are determined based on the highest stacked amplitudes (coherency) of the image function. The method promotes an automatic processing since it does not need travel time picks as input data. However, applying diffraction stacking may require longer computation times if only limited computer resources are used. Furthermore, a simple diffraction stacking of recorded amplitudes could possibly fail to locate the seismic sources if the focal mechanism leads to complex radiation patterns which typically holds for both natural and induced seismicity. In my PhD project, I have developed a new work flow for the localization of seismic events which is based on a diffraction stacking approach. A parallelized code was implemented for the calculation of travel time tables and for the determination of an image function to reduce computation time. In order to address the effects from complex source radiation patterns, I also suggest to compute diffraction stacking from a characteristic function (CF) instead of stacking the original wave form data. A new CF, which is called in the following mAIC (modified from Akaike Information Criterion) is proposed. I demonstrate that, the performance of the mAIC does not depend on the chosen length of the analyzed time window and that both P- and S-wave onsets can be detected accurately. To avoid cross-talk between P- and S-waves due to inaccurate velocity models, I separate the P- and S-waves from the mAIC function by making use of polarization attributes. Then, eventually the final image function is represented by the largest eigenvalue as a result of the covariance analysis between P- and S-image functions. Before applying diffraction stacking, I also apply seismogram denoising by using Otsu thresholding in the time-frequency domain. Results from synthetic experiments show that the proposed diffraction stacking provides reliable results even from seismograms with low SNR=1. Tests with different presentations of the synthetic seismograms (displacement, velocity, and acceleration) shown that, acceleration seismograms deliver better results in case of high SNR, whereas displacement seismograms provide more accurate results in case of low SNR recordings. In another test, different measures (maximum amplitude, other statistical parameters) were used to determine the source location in the final image function. I found that the statistical approach is the preferred method particularly for low SNR. The work flow of my diffraction stacking method was finally applied to local earthquake data from Sumatra, Indonesia. Recordings from a temporary network of 42 stations deployed for 9 months around the Tarutung pull-apart Basin were analyzed. The seismic event locations resulting from the diffraction stacking method align along a segment of the Sumatran Fault. A more complex distribution of seismicity is imaged within and around the Tarutung Basin. Two lineaments striking N-S were found in the middle of the Tarutung Basin which support independent results from structural geology. These features are interpreted as opening fractures due to local extension. A cluster of seismic events repeatedly occurred in short time which might be related to fluid drainage since two hot springs are observed at the surface near to this cluster.},
  language  = {en}
}
@article{KruegerDahmHannemann2020,
  author    = {Kr{\"u}ger, Frank and Dahm, Torsten and Hannemann, Katrin},
  title     = {Mapping of Eastern North Atlantic Ocean seismicity from Po/So observations at a mid-aperture seismological broad-band deep sea array},
  series = {Geophysical journal international},
  volume    = {221},
  journal   = {Geophysical journal international},
  number    = {2},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0956-540X},
  doi       = {10.1093/gji/ggaa054},
  pages     = {1055 -- 1080},
  year      = {2020},
  abstract  = {A mid-aperture broad-band test array (OBS array DOCTAR) was deployed from June 2011 to April 2012 about 100 km north of the Gloria fault in the Eastern North Atlantic in about 5000 m water depth. In addition arrays were installed on Madeira Island and in western Portugal mainland. For the first time in the Eastern North Atlantic, we recorded a large number of high frequency Po and So waves from local and regional small and moderate earthquakes (M-L < 4). An incoherent beamforming method was adapted to scan continuous data for such Po and So arrivals applying a sliding window waveform migration and frequency-wavenumber technique. We identify about 320 Po and 1550 So arrivals and compare the phase onsets with the ISC catalogue (ISC 2015) for the same time span. Up to a distance of 6 degrees to the DOCTAR stations all events listed in the ISC catalogue could be associated to Po and So phases. Arrivals from events in more than 10 degrees distance could be identified only in some cases. Only few Po and/or So arrivals were detected for earthquakes from the European and African continental area, the continental shelf regions and for earthquakes within or northwest of the Azores plateau. Unexpectedly, earthquake clusters are detected within the oceanic plates north and south of the Gloria fault and far from plate boundaries, indicating active intraplate structures. We also observe and locate numerous small magnitude earthquakes on the segment of the Gloria fault directly south of DOCTAR, which likely coincides with the rupture of the 25 November 1941 event. Local small magnitude earthquakes located beneath DOCTAR show hypocentres up to 30 km depth and strike-slip focal mechanisms. A comparison with detections at temporary mid-aperture arrays on Madeira and in western Portugal shows that the deep ocean array performs much better than the island and the continental array regarding the detection threshold for events in the oceanic plates. We conclude that sparsely distributed mid-aperture seismic arrays in the deep ocean could decrease the detection and location threshold for seismicity with M-L < 4 in the oceanic plate and might constitute a valuable tool to monitor oceanic plate seismicity.},
  language  = {en}
}
@article{SteinbergSudhausHeimannetal.2020,
  author    = {Steinberg, Andreas and Sudhaus, Henriette and Heimann, Sebastian and Kr{\"u}ger, Frank},
  title     = {Sensitivity of InSAR and teleseismic observations to earthquake rupture segmentation},
  series = {Geophysical journal international},
  volume    = {223},
  journal   = {Geophysical journal international},
  number    = {2},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0956-540X},
  doi       = {10.1093/gji/ggaa351},
  pages     = {875 -- 907},
  year      = {2020},
  abstract  = {Earthquakes often rupture across more than one fault segment. If such rupture segmentation occurs on a significant scale, a simple point-source or one-fault model may not represent the rupture process well. As a consequence earthquake characteristics inferred, based on one-source assumptions, may become systematically wrong. This might have effects on follow-up analyses, for example regional stress field inversions and seismic hazard assessments. While rupture segmentation is evident for most M-w > 7 earthquakes, also smaller ones with 5.5 < M-w < 7 can be segmented. We investigate the sensitivity of globally available data sets to rupture segmentation and their resolution to reliably estimate the mechanisms in presence of segmentation. We focus on the sensitivity of InSAR (Interferometric Synthetic Aperture Radar) data in the static near-field and seismic waveforms in the far-field of the rupture and carry out non-linear and Bayesian optimizations of single-source and two-sources kinematic models (double-couple point sources and finite, rectangular sources) using InSAR and teleseismic waveforms separately. Our case studies comprises of four M-w 6-7 earthquakes: the 2009 L'Aquila and 2016 Amatrice (Italy) and the 2005 and 2008 Zhongba (Tibet) earthquakes. We contrast the data misfits of different source complexity by using the Akaike informational criterion (AIC). We find that the AIC method is well suited for data-driven inferences on significant rupture segmentation for the given data sets. This is based on our observation that an AIC-stated significant improvement of data fit for two-segment models over one-segment models correlates with significantly different mechanisms of the two source segments and their average compared to the single-segment mechanism. We attribute these modelled differences to a sufficient sensitivity of the data to resolve rupture segmentation. Our results show that near-field data are generally more sensitive to rupture segmentation of shallow earthquakes than far-field data but that also teleseismic data can resolve rupture segmentation in the studied magnitude range. We further conclude that a significant difference in the modelled source mechanisms for different segmentations shows that an appropriate choice of model segmentation matters for a robust estimation of source mechanisms. It reduces systematic biases and trade-off and thereby improves the knowledge on the rupture. Our study presents a strategy and method to detect significant rupture segmentation such that an appropriate model complexity can be used in the source mechanism inference. A similar, systematic investigation of earthquakes in the range of M-w 5.5-7 could provide important hazard-relevant statistics on rupture segmentation. In these cases single-source models introduce a systematic bias. Consideration of rupture segmentation therefore matters for a robust estimation of source mechanisms of the studied earthquakes.},
  language  = {en}
}