ABSTRACT
The seismic hazard and risk analysis for the onshore Groningen gas field requires information about local soil properties, in particular shear-wave velocity (VS). A fieldwork campaign was conducted at 18 surface accelerograph stations of the monitoring network. The subsurface in the region consists of unconsolidated sediments and is heterogeneous in composition and properties. A range of different methods was applied to acquire in situ VS values to a target depth of at least 30 m. The techniques include seismic cone penetration tests (SCPT) with varying source offsets, multichannel analysis of surface waves (MASW) on Rayleigh waves with different processing approaches, microtremor array, cross-hole tomography and suspension P-S logging. The offset SCPT, cross-hole tomography and common midpoint cross-correlation (CMPcc) processing of MASW data all revealed lateral variations on length scales of several to tens of metres in this geological setting. SCPTs resulted in very detailed VS profiles with depth, but represent point measurements in a heterogeneous environment. The MASW results represent VS information on a larger spatial scale and smooth some of the heterogeneity encountered at the sites. The combination of MASW and SCPT proved to be a powerful and cost-effective approach in determining representative VS profiles at the accelerograph station sites. The measured VS profiles correspond well with the modelled profiles and they significantly enhance the ground motion model derivation. The similarity between the theoretical transfer function from the VS profile and the observed amplification from vertical array stations is also excellent.
ABSTRACT
An areal distribution of sensors can be used for estimating the direction of incoming waves through beamforming. Beamforming may be implemented as a phase-shifting and stacking of data recorded on the different sensors (i.e., conventional beamforming). Alternatively, beamforming can be applied to cross-correlations between the waveforms on the different sensors. We derive a kernel for beamforming cross-correlated data and call it cross-correlation beamforming (CCBF). We point out that CCBF has slightly better resolution and aliasing characteristics than conventional beamforming. When auto-correlations are added to CCBF, the array response functions are the same as for conventional beamforming. We show numerically that CCBF is more resilient to non-coherent noise. Furthermore, we illustrate that with CCBF individual receiver-pairs can be removed to improve mapping to the slowness domain. An additional flexibility of CCBF is that cross-correlations can be time-windowed prior to beamforming, e.g., to remove the directionality of a scattered wavefield. The observations on synthetic data are confirmed with field data from the SPITS array (Svalbard). Both when beamforming an earthquake arrival and when beamforming ambient noise, CCBF focuses more of the energy to a central beam. Overall, the main advantage of CCBF is noise suppression and its flexibility to remove station pairs that deteriorate the signal-related beampower. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10950-016-9612-6) contains supplementary material, which is available to authorized users.
ABSTRACT
The atmospheric wind and temperature can be estimated through the traveltimes of infrasound between pairs of receivers. The traveltimes can be obtained by infrasonic interferometry. In this study, the theory of infrasonic interferometry is verified and applied to modeled stratospherically refracted waves. Synthetic barograms are generated using a raytracing model and taking into account atmospheric attenuation, geometrical spreading, and phase shifts due to caustics. Two types of source wavelets are implemented for the experiments: blast waves and microbaroms. In both numerical experiments, the traveltimes between the receivers are accurately retrieved by applying interferometry to the synthetic barograms. It is shown that microbaroms can be used in practice to obtain the traveltimes of infrasound through the stratosphere, which forms the basis for retrieving the wind and temperature profiles.