TY - JOUR A1 - Haney, Frank A1 - Kummerow, J. A1 - Langenbruch, C. A1 - Dinske, C. A1 - Shapiro, Serge A. A1 - Scherbaum, Frank T1 - Magnitude estimation for microseismicity induced during the KTB 2004/2005 injection experiment JF - Geophysics N2 - We determined the magnitudes of 2540 microseismic events measured at one single 3C borehole geophone at the German Deep Drilling Site (known by the German acronym, KTB) during the injection phase 2004/2005. For this task we developed a three-step approach. First, we estimated local magnitudes of 104 larger events with a standard method based on amplitude measurements at near-surface stations. Second, we investigated a series of parameters to characterize the size of these events using the seismograms of the borehole sensor, and we compared them statistically with the local magnitudes. Third, we extrapolated the regression curve to obtain the magnitudes of 2436 events that were only measured at the borehole geophone. This method improved the magnitude of completeness for the KTB data set by more than one order down to M = -2.75. The resulting b-value for all events was 0.78, which is similar to the b-value obtained from taking only the greater events with standard local magnitude estimation from near-surface stations, b = 0.86. The more complete magnitude catalog was required to study the magnitude distribution with time and to characterize the seismotectonic state of the KTB injection site. The event distribution with time was consistent with prediction from theory assuming pore pressure diffusion as the underlying mechanism to trigger the events. The value we obtained for the seismogenic index of -4 suggested that the seismic hazard potential at the KTB site is comparatively low. Y1 - 2011 U6 - https://doi.org/10.1190/GEO2011-0020.1 SN - 0016-8033 VL - 76 IS - 6 SP - WC47 EP - WC53 PB - Society of Exploration Geophysicists CY - Tulsa ER - TY - JOUR A1 - Hiemer, Stefan A1 - Scherbaum, Frank A1 - Rößler, Dirk A1 - Kühn, Nicolas T1 - Determination of tau(0) and Rock Site kappa from Records of the 2008/2009 Earthquake Swarm in Western Bohemia JF - Seismological research letters Y1 - 2011 U6 - https://doi.org/10.1785/gssrl.82.3.387 SN - 0895-0695 VL - 82 IS - 3 SP - 387 EP - 393 PB - Seismological Society of America CY - El Cerrito ER - TY - JOUR A1 - Kühn, Nicolas M. A1 - Riggelsen, Carsten A1 - Scherbaum, Frank T1 - Modeling the joint probability of earthquake, site, and ground-motion parameters using bayesian networks JF - Bulletin of the Seismological Society of America N2 - Bayesian networks are a powerful and increasingly popular tool for reasoning under uncertainty, offering intuitive insight into (probabilistic) data-generating processes. They have been successfully applied to many different fields, including bioinformatics. In this paper, Bayesian networks are used to model the joint-probability distribution of selected earthquake, site, and ground-motion parameters. This provides a probabilistic representation of the independencies and dependencies between these variables. In particular, contrary to classical regression, Bayesian networks do not distinguish between target and predictors, treating each variable as random variable. The capability of Bayesian networks to model the ground-motion domain in probabilistic seismic hazard analysis is shown for a generic situation. A Bayesian network is learned based on a subset of the Next Generation Attenuation (NGA) dataset, using 3342 records from 154 earthquakes. Because no prior assumptions about dependencies between particular parameters are made, the learned network displays the most probable model given the data. The learned network shows that the ground-motion parameter (horizontal peak ground acceleration, PGA) is directly connected only to the moment magnitude, Joyner-Boore distance, fault mechanism, source-to-site azimuth, and depth to a shear-wave horizon of 2: 5 km/s (Z2.5). In particular, the effect of V-S30 is mediated by Z2.5. Comparisons of the PGA distributions based on the Bayesian networks with the NGA model of Boore and Atkinson (2008) show a reasonable agreement in ranges of good data coverage. Y1 - 2011 U6 - https://doi.org/10.1785/0120100080 SN - 0037-1106 VL - 101 IS - 1 SP - 235 EP - 249 PB - Seismological Society of America CY - El Cerrito ER - TY - JOUR A1 - Tran Thanh Tuan, A1 - Scherbaum, Frank A1 - Malischewsky, Peter G. T1 - On the relationship of peaks and troughs of the ellipticity (H/V) of Rayleigh waves and the transmission response of single layer over half-space models JF - Geophysical journal international N2 - One of the key challenges in the context of local site effect studies is the determination of frequencies where the shakeability of the ground is enhanced. In this context, the H/V technique has become increasingly popular and peak frequencies of H/V spectral ratio are sometimes interpreted as resonance frequencies of the transmission response. In the present study, assuming that Rayleigh surface wave is dominant in H/V spectral ratio, we analyse theoretically under which conditions this may be justified and when not. We focus on 'layer over half-space' models which, although seemingly simple, capture many aspects of local site effects in real sedimentary structures. Our starting point is the ellipticity of Rayleigh waves. We use the exact formula of the H/V-ratio presented by Malischewsky & Scherbaum (2004) to investigate the main characteristics of peak and trough frequencies. We present a simple formula illustrating if and where H/V-ratio curves have sharp peaks in dependence of model parameters. In addition, we have constructed a map, which demonstrates the relation between the H/V-peak frequency and the peak frequency of the transmission response in the domain of the layer's Poisson ratio and the impedance contrast. Finally, we have derived maps showing the relationship between the H/V-peak and trough frequency and key parameters of the model such as impedance contrast. These maps are seen as diagnostic tools, which can help to guide the interpretation of H/V spectral ratio diagrams in the context of site effect studies. KW - Site effects KW - Theoretical seismology KW - Wave propagation Y1 - 2011 U6 - https://doi.org/10.1111/j.1365-246X.2010.04863.x SN - 0956-540X VL - 184 IS - 2 SP - 793 EP - 800 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Scherbaum, Frank A1 - Kühn, Nicolas M. T1 - Logic tree branch weights and probabilities summing up to one is not enough JF - Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute N2 - Logic trees have become the most popular tool for the quantification of epistemic uncertainties in probabilistic seismic hazard assessment (PSHA). In a logic-tree framework, epistemic uncertainty is expressed in a set of branch weights, by which an expert or an expert group assigns degree-of-belief values to the applicability of the corresponding branch models. Despite the popularity of logic-trees, however, one finds surprisingly few clear commitments to what logic-tree branch weights are assumed to be (even by hazard analysts designing logic trees). In the present paper we argue that it is important for hazard analysts to accept the probabilistic framework from the beginning for assigning logic-tree branch weights. In other words, to accept that logic-tree branch weights are probabilities in the axiomatic sense, independent of one's preference for the philosophical interpretation of probabilities. We demonstrate that interpreting logic-tree branch weights merely as a numerical measure of "model quality," which are then subsequently normalized to sum up to unity, will with increasing number of models inevitably lead to an apparent insensitivity of hazard curves on the logic-tree branch weights, which may even be mistaken for robustness of the results. Finally, we argue that assigning logic-tree branch weights in a sequential fashion may improve their logical consistency. Y1 - 2011 U6 - https://doi.org/10.1193/1.3652744 SN - 8755-2930 VL - 27 IS - 4 SP - 1237 EP - 1251 PB - Earthquake Engineering Research Institute CY - Oakland ER - TY - JOUR A1 - Schmelzbach, C. A1 - Scherbaum, Frank A1 - Tronicke, Jens A1 - Dietrich, P. T1 - Bayesian frequency-domain blind deconvolution of ground-penetrating radar data JF - Journal of applied geophysics N2 - Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing. KW - Deconvolution KW - Inverse filtering KW - Ground penetrating radar KW - GPR KW - Data processing KW - Vertical resolution Y1 - 2011 U6 - https://doi.org/10.1016/j.jappgeo.2011.08.010 SN - 0926-9851 VL - 75 IS - 4 SP - 615 EP - 630 PB - Elsevier CY - Amsterdam ER -