ALBERT

Description: Spectral analysis of earthquake recordings provides fundamental seismological information. It is used for magnitude calculation, estimation of attenuation, and the determination of fault rupture properties including slip area, stress drop, and radiated energy. Further applications are found in site-effect studies and for the calibration of simulation and empirically based ground-motion prediction equations. We identified two main limitations of the spectral fitting methods currently used in the literature. First, the frequency-dependent noise level is not properly accounted for. Second, there are no mathematically defensible techniques to fit a parametric spectrum to a seismogram with gaps. When analyzing an earthquake recording, it is well known that the noise level is not the same at different frequencies, that is, the noise spectrum is colored. The different, frequency-dependent, noise levels are mainly due to ambient noise and sensor noise. Methods in the literature do not properly account for the presence of colored noise. Seismograms with gaps are usually discarded due to the lack of methodologies to use them. Modern digital seismograms are occasionally clipped at the arrival of the strongest ground motion. This is also critical in the study of historical earthquakes in which few seismograms are available and gaps are common, significantly decreasing the number of useful records. In this work, we propose a method to overcome these two limitations. We show that the spectral fitting can be greatly improved and earthquakes with extremely low signal-to-noise ratio can be fitted. We show that the impact of gaps on the estimated parameters is minor when a small fraction of the total energy is missing. We also present a strategy to reconstruct the missing portion of the seismogram.

Description: Seismic surface waves can be measured by deploying an array of seismometers on the surface of the earth. The goal of such measurement surveys is, usually, to estimate the velocity of propagation and the direction of arrival of the seismic waves. In this paper, we address the issue of sensor placement for the analysis of seismic surface waves from ambient vibration wavefields. First, we explain in detail how the array geometry affects the mean-squared estimation error of parameters of interest, such as the velocity and direction of propagation, both at low and high signal-to-noise ratios (SNRs). Secondly, we propose a cost function suitable for the design of the array geometry with particular focus on the estimation of the wavenumber of both Love and Rayleigh waves. Thirdly, we present and compare several computational approaches to minimize the proposed cost function. Numerical experiments verify the effectiveness of our cost function and resulting array geometry designs, leading to greatly improved estimation performance in comparison to arbitrary array geometries, both at low and high SNR levels.

Description: We investigated the sequence of 2-D resonance modes of the sediment fill of Rhône Valley, Southern Swiss Alps, a strongly overdeepened, glacially carved basin with a sediment fill reaching a thickness of up to 900 m. From synchronous array recordings of ambient vibrations at six locations between Martigny and Sion we were able to identify several resonance modes, in particular, previously unmeasured higher modes. Data processing was performed with frequency domain decomposition of the cross-spectral density matrices of the recordings and with time-frequency dependent polarization analysis. 2-D finite element modal analysis was performed to support the interpretation of processing results and to investigate mode shapes at depth. In addition, several models of realistic bedrock geometries and velocity structures could be used to qualitatively assess the sensitivity of mode shape and particle motion dip angle to subsurface properties. The variability of modal characteristics due to subsurface properties makes an interpretation of the modes purely from surface observations challenging. We conclude that while a wealth of information on subsurface structure is contained in the modal characteristics, a careful strategy for their interpretation is needed to retrieve this information.

Description: Nowadays, an increasing amount of seismic data is collected by daily observatory routines. The basic step for successfully analyzing those data is the correct detection of various event types. However, the visually scanning process is a time-consuming task. Applying standard techniques for detection like the STA/LTA trigger still requires the manual control for classification. Here, we present a useful alternative. The incoming data stream is scanned automatically for events of interest. A stochastic classifier, called hidden Markov model, is learned for each class of interest enabling the recognition of highly variable waveforms. In contrast to other automatic techniques as neural networks or support vector machines the algorithm allows to start the classification from scratch as soon as interesting events are identified. Neither the tedious process of collecting training samples nor a time-consuming configuration of the classifier is required. An approach originally introduced for the volcanic task force action allows to learn classifier properties from a single waveform example and some hours of background recording. Besides a reduction of required workload this also enables to detect very rare events. Especially the latter feature provides a milestone point for the use of seismic devices in alpine warning systems. Furthermore, the system offers the opportunity to flag new signal classes that have not been defined before. We demonstrate the application of the classification system using a data set from the Swiss Seismological Survey achieving very high recognition rates. In detail we document all refinements of the classifier providing a step-by-step guide for the fast set up of a well-working classification system.

Description: The analysis of rotational seismic motions has received considerable attention in the last years. Recent advances in sensor technologies allow us to measure directly the rotational components of the seismic wavefield. Today this is achieved with improved accuracy and at an affordable cost. The analysis and the study of rotational motions are, to a certain extent, less developed than other aspects of seismology due to the historical lack of instrumental observations. This is due to both the technical challenges involved in measuring rotational motions and to the widespread belief that rotational motions are insignificant. This paper addresses the joint processing of translational and rotational motions from both the theoretical and the practical perspectives. Our attention focuses on the analysis of motions of both Rayleigh waves and Love waves from recordings of single sensors and from an array of sensors. From the theoretical standpoint, analysis of Fisher information (FI) allows us to understand how the different measurement types contribute to the estimation of quantities of geophysical interest. In addition, we show how rotational measurements resolve ambiguity on parameter estimation in the single sensor setting. We quantify the achievable estimation accuracy by means of Cramér–Rao bound (CRB). From the practical standpoint, a method for the joint processing of rotational and translational recordings to perform maximum likelihood (ML) estimation is presented. The proposed technique estimates parameters of Love waves and Rayleigh waves from single sensor or array recordings. We support and illustrate our findings with a comprehensive collection of numerical examples. Applications to real recordings are also shown.

Description: The definition of a reference bedrock condition representative of a region of interest is of great significance in seismic-hazard assessment. It is highly beneficial when ground-motion prediction equations are referenced to a specific site condition, particularly in the case of site-specific seismic-hazard analyses. When known, the effect of any given site with respect to the reference can then be applied to the predicted ground motion. However, the choice of a reference velocity profile is not straightforward, mainly due to the high variability of the velocity structure in the shallower layers. A new method to define the regional reference rock profile is proposed. The method relates quarter-wavelength average velocity at a site to frequency-dependent amplification. A reference bedrock velocity profile can then be directly defined in relation to expected amplification characteristics over a number of sites. We compare 27 quarter-wavelength velocity profiles from seismic station locations in Switzerland with empirical amplification functions derived from spectral modeling. From this comparison, a set of frequency-dependent calibration relationships is established. Assuming that the reference profile is defined by a lack of any relative amplification, the quarter-wavelength velocity profile that corresponds to unitary spectral amplification can be extracted. The reference velocity profile can then be obtained through an inversion procedure and defines the reference for the ground-motion prediction equation (GMPE). The proposed reference velocity profile is compared with previous reference velocity profiles. A good agreement is found between the different methods. Additionally, an estimation of the transfer function for the Swiss reference rock condition is provided. This can be used to correct recorded or estimated spectral amplitudes for the local response of the reference site. Finally, it is shown that the coefficients from the aforementioned correlations can be used to estimate a generic amplification function at any site with a known quarter-wavelength velocity profile.

Description: In the framework of the renewal project of the Swiss Strong Motion Network (SSMNet), a procedure for site characterization has been established. The aim of the procedure was to systematically derive realistic 1D velocity profiles at each station. It is mainly based on the analysis of surface waves, particularly from passive experiments, and includes cross checks of the derived amplification functions with those obtained through spectral modeling of recorded earthquakes. The systematic use of three component surface-wave analysis, allowing the derivation of both Rayleigh and Love dispersion curves, also contributes to the improvement of the quality of the retrieved profiles. The procedure is applied to the 30 SSMNet stations installed on various site types within the project, covering different aspects of seismic risk. The characterization of these 30 sites gives an overview of the variety of possible effects of surface geology on ground motion in the Alpine area. Such effects ranged from deamplification at hard-rock sites to amplification up to a factor of 15 in lacustrine sediments with respect to the Swiss reference rock velocity model. The derived velocity profiles are shown to reproduce observed amplification functions from empirical spectral modeling. Although many sites are found to exhibit 1D behavior, the procedure allows the detection and qualification of 2D and 3D effects. The sites are therefore classified with respect to the occurrence of 2D/3D resonance and edge-generated surface waves. In addition to the large and deeply incised alpine valleys of the Rhone, the Rhine, and the Aar, smaller structures such as local alpine valleys and alluvial fans are shown to exhibit 2D/3D behavior.