TY - JOUR A1 - Petersen, Gesa Maria A1 - Cesca, Simone A1 - Kriegerowski, Marius T1 - Automated quality control for large seismic networks BT - implementation and application to the AlpArray seismic network JF - Seismological research letters N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1785/0220180342 SN - 0895-0695 SN - 1938-2057 VL - 90 IS - 3 SP - 1177 EP - 1190 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Negi, Sanjay S. A1 - Paul, Ajay A1 - Cesca, Simone A1 - Kamal, A1 - Kriegerowski, Marius A1 - Mahesh, P. A1 - Gupta, Sandeep T1 - Crustal velocity structure and earthquake processes of Garhwal-Kumaun Himalaya: Constraints from regional waveform inversion and array beam modeling JF - Tectonophysics : international journal of geotectonics and the geology and physics of the interior of the earth N2 - In order to understand present day earthquake kinematics at the Indian plate boundary, we analyse seismic broadband data recorded between 2007 and 2015 by the regional network in the Garhwal-Kumaun region, northwest Himalaya. We first estimate a local 1-D velocity model for the computation of reliable Green's functions, based on 2837 P-wave and 2680 S-wave arrivals from 251 well located earthquakes. The resulting 1-D crustal structure yields a 4-layer velocity model down to the depths of 20 km. A fifth homogeneous layer extends down to 46 km, constraining the Moho using travel-time distance curve method. We then employ a multistep moment tensor (MT) inversion algorithm to infer seismic moment tensors of 11 moderate earthquakes with Mw magnitude in the range 4.0–5.0. The method provides a fast MT inversion for future monitoring of local seismicity, since Green's functions database has been prepared. To further support the moment tensor solutions, we additionally model P phase beams at seismic arrays at teleseismic distances. The MT inversion result reveals the presence of dominant thrust fault kinematics persisting along the Himalayan belt. Shallow low and high angle thrust faulting is the dominating mechanism in the Garhwal-Kumaun Himalaya. The centroid depths for these moderate earthquakes are shallow between 1 and 12 km. The beam modeling result confirm hypocentral depth estimates between 1 and 7 km. The updated seismicity, constrained source mechanism and depth results indicate typical setting of duplexes above the mid crustal ramp where slip is confirmed along out-of-sequence thrusting. The involvement of Tons thrust sheet in out-of-sequence thrusting indicate Tons thrust to be the principal active thrust at shallow depth in the Himalayan region. Our results thus support the critical taper wedge theory, where we infer the microseismicity cluster as a result of intense activity within the Lesser Himalayan Duplex (LHD) system. KW - Critical taper wedge KW - Lesser Himalayan Duplex KW - Out-of-sequence thrust Y1 - 2017 U6 - https://doi.org/10.1016/j.tecto.2017.05.007 SN - 0040-1951 SN - 1879-3266 VL - 712 SP - 45 EP - 63 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kriegerowski, Marius A1 - Petersen, Gesa Maria A1 - Vasyura-Bathke, Hannes A1 - Ohrnberger, Matthias T1 - A Deep Convolutional Neural Network for Localization of Clustered Earthquakes Based on Multistation Full Waveforms JF - Seismological research letters N2 - Earthquake localization is both a necessity within the field of seismology, and a prerequisite for further analysis such as source studies and hazard assessment. Traditional localization methods often rely on manually picked phases. We present an alternative approach using deep learning that once trained can predict hypocenter locations efficiently. In seismology, neural networks have typically been trained with either single-station records or based on features that have been extracted previously from the waveforms. We use three-component full-waveform records of multiple stations directly. This means no information is lost during preprocessing and preparation of the data does not require expert knowledge. The first convolutional layer of our deep convolutional neural network (CNN) becomes sensitive to features that characterize the waveforms it is trained on. We show that this layer can therefore additionally be used as an event detector. As a test case, we trained our CNN using more than 2000 earthquake swarm events from West Bohemia, recorded by nine local three-component stations. The CNN successfully located 908 validation events with standard deviations of 56.4 m in east-west, 123.8 m in north-south, and 136.3 m in vertical direction compared to a double-difference relocated reference catalog. The detector is sensitive to events with magnitudes down to M-L = -0.8 with 3.5% false positive detections. Y1 - 2018 U6 - https://doi.org/10.1785/0220180320 SN - 0895-0695 SN - 1938-2057 VL - 90 IS - 2 SP - 510 EP - 516 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Kriegerowski, Marius A1 - Cesca, Simone A1 - Ohrnberger, Matthias A1 - Dahm, Torsten A1 - Krüger, Frank T1 - Event couple spectral ratio Q method for earthquake clusters BT - application to northwest Bohemia JF - Solid Earth N2 - 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. KW - west bohemia KW - attenuation tomography KW - swarm earthquakes KW - focal zone KW - parameters KW - locations KW - fault Y1 - 2019 U6 - https://doi.org/10.5194/se-10-317-2019 SN - 1869-9529 IS - 10 SP - 317 EP - 328 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Karamzadeh, Nasim Toularoud A1 - Kühn, Daniela A1 - Kriegerowski, Marius A1 - López-Comino, José Ángel A1 - Cesca, Simone A1 - Dahm, Torsten T1 - Small-aperture array as a tool to monitor fluid injection- and extraction-induced microseismicity BT - applications and recommendations JF - Acta Geophysica N2 - 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. KW - Microseismic monitoring KW - Induced seismicity KW - Array seismology KW - Shallow borehole sensors Y1 - 2019 U6 - https://doi.org/10.1007/s11600-018-0231-1 SN - 1895-6572 SN - 1895-7455 VL - 67 IS - 1 SP - 311 EP - 326 PB - Springer CY - Cham ER - TY - JOUR A1 - Heimann, Sebastian A1 - Vasyura-Bathke, Hannes A1 - Sudhaus, Henriette A1 - Isken, Marius Paul A1 - Kriegerowski, Marius A1 - Steinberg, Andreas A1 - Dahm, Torsten T1 - A Python framework for efficient use of pre-computed Green's functions in seismological and other physical forward and inverse source problems JF - Solid earth N2 - 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. Y1 - 2019 U6 - https://doi.org/10.5194/se-10-1921-2019 SN - 1869-9510 SN - 1869-9529 VL - 10 IS - 6 SP - 1921 EP - 1935 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Esfahani, Reza Dokht Dolatabadi A1 - Vogel, Kristin A1 - Cotton, Fabrice A1 - Ohrnberger, Matthias A1 - Scherbaum, Frank A1 - Kriegerowski, Marius T1 - Exploring the dimensionality of ground-motion data by applying autoencoder techniques JF - Bulletin of the Seismological Society of America : BSSA N2 - In this article, we address the question of how observed ground-motion data can most effectively be modeled for engineering seismological purposes. Toward this goal, we use a data-driven method, based on a deep-learning autoencoder with a variable number of nodes in the bottleneck layer, to determine how many parameters are needed to reconstruct synthetic and observed ground-motion data in terms of their median values and scatter. The reconstruction error as a function of the number of nodes in the bottleneck is used as an indicator of the underlying dimensionality of ground-motion data, that is, the minimum number of predictor variables needed in a ground-motion model. Two synthetic and one observed datasets are studied to prove the performance of the proposed method. We find that mapping ground-motion data to a 2D manifold primarily captures magnitude and distance information and is suited for an approximate data reconstruction. The data reconstruction improves with an increasing number of bottleneck nodes of up to three and four, but it saturates if more nodes are added to the bottleneck. Y1 - 2021 U6 - https://doi.org/10.1785/0120200285 SN - 0037-1106 SN - 1943-3573 VL - 111 IS - 3 SP - 1563 EP - 1576 PB - Seismological Society of America CY - El Cerito, Calif. ER - TY - JOUR A1 - Cesca, Simone A1 - Heimann, Sebastian A1 - Kriegerowski, Marius A1 - Saul, Joachim A1 - Dahm, Torsten T1 - Moment tensor inversion for nuclear explosions BT - what can we learn from the 6 January and 9 September 2016 Nuclear Tests, North Korea? JF - Seismological research letters N2 - Two nuclear explosions were carried out by the Democratic People’s Republic of North Korea in January and September 2016. Epicenters were located close to those of the 2006, 2009, and 2013 previous explosions. We perform a seismological analysis of the 2016 events combining the analysis of full waveforms at regional distances and seismic array beams at teleseismic distances. We estimate the most relevant source parameters, such as source depth, moment release, and full moment tensor (MT). The best MT solution can be decomposed into an isotropic source, directly related with the explosion and an additional deviatoric term, likely due to near‐source interactions with topographic and/or underground facilities features. We additionally perform an accurate resolution test to assess source parameters uncertainties and trade‐offs. This analysis sheds light on source parameters inconsistencies among studies on previous shallow explosive sources. The resolution of the true MT is hindered by strong source parameters trade‐offs, so that a broad range of well‐fitting MT solutions can be found, spanning from a dominant positive isotropic term to a dominant negative vertical compensated linear vector dipole. The true mechanism can be discriminated by additionally modeling first‐motion polarities at seismic arrays at teleseismic distances. A comparative assessment of the 2016 explosion with earlier nuclear tests documents similar vertical waveforms but a significant increase of amplitude for the 2016 explosions, which proves that the 9 September 2016 was the largest nuclear explosion ever performed in North Korea with a magnitude Mw 4.9 and a shallow depth of less than 2 km, although there are no proofs of a fusion explosion. Modeling transversal component waveforms suggests variable size and orientation of the double‐couple components of the 2009, 2013, and 2016 sources. Y1 - 2017 U6 - https://doi.org/10.1785/0220160139 SN - 0895-0695 SN - 1938-2057 VL - 88 IS - 2A SP - 300 EP - 310 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Cesca, Simone A1 - Grigoli, Francesco A1 - Heimann, Sebastian A1 - Dahm, Torsten A1 - Kriegerowski, Marius A1 - Sobiesiak, M. A1 - Tassara, C. A1 - Olcay, M. T1 - The M-w 8.1 2014 Iquique, Chile, seismic sequence: a tale of foreshocks and aftershocks JF - Geophysical journal international N2 - The 2014 April 1, M-w 8.1 Iquique (Chile) earthquake struck in the Northern Chile seismic gap. With a rupture length of less than 200 km, it left unbroken large segments of the former gap. Early studies were able to model the main rupture features but results are ambiguous with respect to the role of aseismic slip and left open questions on the remaining hazard at the Northern Chile gap. A striking observation of the 2014 earthquake has been its extensive preparation phase, with more than 1300 events with magnitude above M-L 3, occurring during the 15 months preceding the main shock. Increasing seismicity rates and observed peak magnitudes accompanied the last three weeks before the main shock. Thanks to the large data sets of regional recordings, we assess the precursor activity, compare foreshocks and aftershocks and model rupture preparation and rupture effects. To tackle inversion challenges for moderate events with an asymmetric network geometry, we use full waveforms techniques to locate events, map the seismicity rate and derive source parameters, obtaining moment tensors for more than 300 events (magnitudes M-w 4.0-8.1) in the period 2013 January 1-2014 April 30. This unique data set of fore- and aftershocks is investigated to distinguish rupture process models and models of strain and stress rotation during an earthquake. Results indicate that the spatial distributions of foreshocks delineated the shallower part of the rupture areas of the main shock and its largest aftershock, well matching the spatial extension of the aftershocks cloud. Most moment tensors correspond to almost pure double couple thrust mechanisms, consistent with the slab orientation. Whereas no significant differences are observed among thrust mechanisms in different areas, nor among thrust foreshocks and aftershocks, the early aftershock sequence is characterized by the presence of normal fault mechanisms, striking parallel to the trench but dipping westward. These events likely occurred in the shallow wedge structure close to the slab interface and are consequence of the increased extensional stress in this region after the largest events. The overall stress inversion result suggests a minor stress rotation after the main shock, but a significant release of the deviatoric stress. The temporal change in the distribution of focal mechanisms can also be explained in terms of the spatial heterogeneity of the stress field: under such interpretation, the potential of a large megathrust earthquake breaking a larger segment offshore Northern Chile remains high. KW - Earthquake source observations KW - South America Y1 - 2016 U6 - https://doi.org/10.1093/gji/ggv544 SN - 0956-540X SN - 1365-246X VL - 204 SP - 1766 EP - 1780 PB - Oxford Univ. Press CY - Oxford ER -