@article{KaramzadehKuehnKriegerowskietal.2019,
  author    = {Karamzadeh, Nasim Toularoud and K{\"u}hn, Daniela and Kriegerowski, Marius and L{\´o}pez-Comino, Jos{\´e} {\´A}ngel and Cesca, Simone and Dahm, Torsten},
  title     = {Small-aperture array as a tool to monitor fluid injection- and extraction-induced microseismicity},
  series = {Acta Geophysica},
  volume    = {67},
  journal   = {Acta Geophysica},
  number    = {1},
  publisher = {Springer},
  address   = {Cham},
  issn      = {1895-6572},
  doi       = {10.1007/s11600-018-0231-1},
  pages     = {311 -- 326},
  year      = {2019},
  abstract  = {The monitoring of microseismicity during temporary human activities such as fluid injections for hydrofracturing, hydrothermal stimulations or wastewater disposal is a difficult task. The seismic stations often cannot be installed on hard rock, and at quiet places, noise is strongly increased during the operation itself and the installation of sensors in deep wells is costly and often not feasible. The combination of small-aperture seismic arrays with shallow borehole sensors offers a solution. We tested this monitoring approach at two different sites: (1) accompanying a fracking experiment in sedimentary shale at 4km depth and (2) above a gas field under depletion. The small-aperture arrays were planned according to theoretical wavenumber studies combined with simulations considering the local noise conditions. We compared array recordings with recordings available from shallow borehole sensors and give examples of detection and location performance. Although the high-frequency noise on the 50-m-deep borehole sensors was smaller compared to the surface noise before the injection experiment, the signals were highly contaminated during injection by the pumping activities. Therefore, a set of three small-aperture arrays at different azimuths was more suited to detect small events, since noise recorded on these arrays is uncorrelated with each other. Further, we developed recommendations for the adaptation of the monitoring concept to other sites experiencing induced seismicity.},
  language  = {en}
}
@article{PetersenCescaKriegerowski2019,
  author    = {Petersen, Gesa Maria and Cesca, Simone and Kriegerowski, Marius},
  title     = {Automated quality control for large seismic networks},
  series = {Seismological research letters},
  volume    = {90},
  journal   = {Seismological research letters},
  number    = {3},
  publisher = {Seismological Society of America},
  address   = {Albany},
  organization    = {AlpArray Working Grp},
  issn      = {0895-0695},
  doi       = {10.1785/0220180342},
  pages     = {1177 -- 1190},
  year      = {2019},
  abstract  = {As a consequence of the rapid growing worldwide seismic data set, a huge variety of automatized data-processing methods have been developed. To perform automatized waveform-based seismological studies aiming for magnitudes or source process inversion, it is crucial to identify network stations with erroneous transfer functions, gain factors, or component orientations. We developed a new tool dedicated to automated station quality control of dense seismic networks and arrays. The python-based AutoStatsQ toolbox uses the pyrocko seismic data-processing environment. The toolbox automatically downloads data and metadata for selected teleseismic events and performs different tests. As a result, relative gain factors, sensor orientation corrections, and reliable frequency bands are computed for all stations in a chosen time period. Relative gain factors are calculated for all stations and events in a time domain based on maximum P-phase amplitudes. A Rayleigh-wave polarization analysis is used to identify deviating sensor orientations. The power spectra of all stations in a given frequency range are compared with synthetic ones, accessing Global Centroid Moment Tensor (CMT) solutions. Frequency ranges of coinciding synthetic and recorded power spectral densities (PSDs) may serve as guidelines for choosing band-pass filters for moment tensor (MT) inversion and help confirm the corner frequency of the instrument. The toolbox was applied to the permanent and temporary AlpArray networks as well as to the denser SWATH-D network, a total of over 750 stations. Stations with significantly deviating gain factors were identified, as well as stations with inverse polarity and misorientations of the horizontal components. The tool can be used to quickly access network quality and to omit or correct stations before MT inversion. Electronic Supplement: List of teleseismic events and tables of median, mean, and standard deviation of relative gain factors, and figures of relative gain factors of all event-station pairs, waveform example showing inverse polarity of horizontal components on ZS.D125, histograms of median, mean, and standard deviation of the correction angles, examples of synthetic and recorded frequency spectra of ZS.D046 and NI.VINO.},
  language  = {en}
}
@article{HeimannVasyuraBathkeSudhausetal.2019,
  author    = {Heimann, Sebastian and Vasyura-Bathke, Hannes and Sudhaus, Henriette and Isken, Marius Paul and Kriegerowski, Marius and Steinberg, Andreas and Dahm, Torsten},
  title     = {A Python framework for efficient use of pre-computed Green's functions in seismological and other physical forward and inverse source problems},
  series = {Solid earth},
  volume    = {10},
  journal   = {Solid earth},
  number    = {6},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1869-9510},
  doi       = {10.5194/se-10-1921-2019},
  pages     = {1921 -- 1935},
  year      = {2019},
  abstract  = {The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.},
  language  = {en}
}
@phdthesis{Kriegerowski2019,
  author    = {Kriegerowski, Marius},
  title     = {Development of waveform-based, automatic analysis tools for the spatio-temporal characterization of massive earthquake clusters and swarms},
  doi       = {10.25932/publishup-44404},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-444040},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xv, 83},
  year      = {2019},
  abstract  = {Earthquake swarms are characterized by large numbers of events occurring in a short period of time within a confined source volume and without significant mainshock aftershock pattern as opposed to tectonic sequences. Intraplate swarms in the absence of active volcanism usually occur in continental rifts as for example in the Eger Rift zone in North West Bohemia, Czech Republic. A common hypothesis links event triggering to pressurized fluids. However, the exact causal chain is often poorly understood since the underlying geotectonic processes are slow compared to tectonic sequences. The high event rate during active periods challenges standard seismological routines as these are often designed for single events and therefore costly in terms of human resources when working with phase picks or computationally costly when exploiting full waveforms. This methodological thesis develops new approaches to analyze earthquake swarm seismicity as well as the underlying seismogenic volume. It focuses on the region of North West (NW) Bohemia, a well studied, well monitored earthquake swarm region. In this work I develop and test an innovative approach to detect and locate earthquakes using deep convolutional neural networks. This technology offers great potential as it allows to efficiently process large amounts of data which becomes increasingly important given that seismological data storage grows at increasing pace. The proposed deep neural network trained on NW Bohemian earthquake swarm records is able to locate 1000 events in less than 1 second using full waveforms while approaching precision of double difference relocated catalogs. A further technological novelty is that the trained filters of the deep neural network's first layer can be repurposed to function as a pattern matching event detector without additional training on noise datasets. For further methodological development and benchmarking, I present a new toolbox to generate realistic earthquake cluster catalogs as well as synthetic full waveforms of those clusters in an automated fashion. The input is parameterized using constraints on source volume geometry, nucleation and frequency-magnitude relations. It harnesses recorded noise to produce highly realistic synthetic data for benchmarking and development. This tool is used to study and assess detection performance in terms of magnitude of completeness Mc of a full waveform detector applied to synthetic data of a hydrofracturing experiment at the Wysin site, Poland. Finally, I present and demonstrate a novel approach to overcome the masking effects of wave propagation between earthquake and stations and to determine source volume attenuation directly in the source volume where clustered earthquakes occur. The new event couple spectral ratio approach exploits high frequency spectral slopes of two events sharing the greater part of their rays. Synthetic tests based on the toolbox mentioned before show that this method is able to infer seismic wave attenuation within the source volume at high spatial resolution. Furthermore, it is independent from the distance towards a station as well as the complexity of the attenuation and velocity structure outside of the source volume of swarms. The application to recordings of the NW Bohemian earthquake swarm shows increased P phase attenuation within the source volume (Qp < 100) based on results at a station located close to the village Luby (LBC). The recordings of a station located in epicentral proximity, close to Nov{\´y} Kostel (NKC), show a relatively high complexity indicating that waves arriving at that station experience more scattering than signals recorded at other stations. The high level of complexity destabilizes the inversion. Therefore, the Q estimate at NKC is not reliable and an independent proof of the high attenuation finding given the geometrical and frequency constraints is still to be done. However, a high attenuation in the source volume of NW Bohemian swarms has been postulated before in relation to an expected, highly damaged zone bearing CO 2 at high pressure. The methods developed in the course of this thesis yield the potential to improve our understanding regarding the role of fluids and gases in intraplate event clustering.},
  language  = {en}
}
@article{KriegerowskiCescaOhrnbergeretal.2019,
  author    = {Kriegerowski, Marius and Cesca, Simone and Ohrnberger, Matthias and Dahm, Torsten and Kr{\"u}ger, Frank},
  title     = {Event couple spectral ratio Q method for earthquake clusters},
  series = {Solid Earth},
  journal   = {Solid Earth},
  number    = {10},
  publisher = {Copernicus Publications},
  address   = {G{\"o}ttingen},
  issn      = {1869-9529},
  doi       = {10.5194/se-10-317-2019},
  pages     = {317 -- 328},
  year      = {2019},
  abstract  = {We develop an amplitude spectral ratio method for event couples from clustered earthquakes to estimate seismic wave attenuation (Q-1) in the source volume. The method allows to study attenuation within the source region of earthquake swarms or aftershocks at depth, independent of wave path and attenuation between source region and surface station. We exploit the high-frequency slope of phase spectra using multitaper spectral estimates. The method is tested using simulated full wave-field seismograms affected by recorded noise and finite source rupture. The synthetic tests verify the approach and show that solutions are independent of focal mechanisms but also show that seismic noise may broaden the scatter of results. We apply the event couple spectral ratio method to northwest Bohemia, Czech Republic, a region characterized by the persistent occurrence of earthquake swarms in a confined source region at mid-crustal depth. Our method indicates a strong anomaly of high attenuation in the source region of the swarm with an averaged attenuation factor of Qp < 100. The application to S phases fails due to scattered P-phase energy interfering with S phases. The Qp anomaly supports the common hypothesis of highly fractured and fluid saturated rocks in the source region of the swarms in northwest Bohemia. However, high temperatures in a small volume around the swarms cannot be excluded to explain our observations.},
  language  = {en}
}