A benchmark case study for seismic event relative location

'Precision seismology' encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions. Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocentre determination techniques. Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates. We present a Ground Truth (GT) dataset of 55 military surface explosions in northern Finland in 2007 that all took place within 300 m of each other. The explosions were recorded with a high signal-to-noise ratio to distances of about 2 degrees, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements. With exact coordinates for the explosions, we are able to assess the fidelity of relative location estimates made using any location algorithm or implementation. Applying double-difference calculations using two different 1-D velocity models for the region results in hypocentre-to-hypocentre distances which are too short and it is clear that the wavefield leaving the source region is more complicated than predicted by the models. Using the GT event coordinates, we are able to measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted. In practice we would of course need to solve for event hypocentres and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield. We present this data set, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.Peer reviewe

Integrated Seismic Event Detection and Location by Advanced Array Processing

The principal objective of this two-year study is to develop and test a new advanced, automatic approach to seismic detection/location using array processing. We address a strategy to obtain significantly improved precision in the location of low-magnitude events compared with current fully-automatic approaches, combined with a low false alarm rate. We have developed and evaluated a prototype automatic system which uses as a basis regional array processing with fixed, carefully calibrated, site-specific parameters in conjuction with improved automatic phase onset time estimation. We have in parallel developed tools for Matched Field Processing for optimized detection and source-region identification of seismic signals. This narrow-band procedure aims to mitigate some of the causes of difficulty encountered using the standard array processing system, specifically complicated source-time histories of seismic events and shortcomings in the plane-wave approximation for seismic phase arrivals at regional arrays

Seismic noise-based methods for soft-rock landslide characterization

International audienceIn order to better understand the mechanics and dynamic of landslides, it is of primary interest to image correctly their internal structure. Several active geophysical methods are able to provide the geometry of a given landslide, but were rarely applied in 3 dimensions in the past. The main disadvantages of methods like seismic reflection or electrical tomographies are that there are heavy to set up, require for some heavy processing tools to implement, and consequently are expensive and time consuming. Moreover, in the particular case of soft-rock landslides, their respective sensitivity and resolution are not always adequate to locate the potential slip surfaces. The passive methods, which require lighter instrumentation and easier processing tools, can represent an interesting alternative, particularly for difficult accessible landslides. Among them, the seismic noise based methods have shown increasing applications and developments, in particular for seismic hazard mapping in urban environment. In this paper, we present seismic noise investigations carried out on two different sites, a mudslide and a translational clayey landslide where independent measurements (geotechnical and geophysical tests) were performed earlier. Our investigations were composed of H/V measurements, which are fast and easy to perform in the field, in order to image shear wave contrasts (slip surfaces), and seismic noise array method, which is heavier to apply and interpret, but provides S-waves velocity profile versus depth. The comparisons between geophysical investigations and geotechnical information proved the applicability of such passive methods in 3D complexes, but also some limitations. Indeed interpretation of these measurements can be tricky in rough and non-homogeneous terrains

Toward an improved representation of middle atmospheric dynamics thanks to the ARISE project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions

Accurate determination of phase arrival times using autoregressive likelihood estimation

We have investigated the potential automatic use of an onset picker based on autoregressive likelihood estimation. Both a single component version and a three component version of this method have been tested on data from events located in the Khibiny Massif of the Kola peninsula, recorded at the Apatity array, the Apatity three component station and the ARCESS array. Using this method, we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P-phases and 0.15 0.20 s for S phases. These accuracies are as good as for analyst picks, and are considerably better than the accuracies of the current onset procedure used for processing of regional array data at NORSAR. In another application, we have developed a generic procedure to reestimate the onsets of all types of first arriving P phases. By again applying the autoregressive likelihood technique, we have obtained automatic onset times of a quality such that 70% of the automatic picks are within 0.1 s of the best manual pick. For the onset time procedure currently used at NORSAR, the corresponding number is 28%. Clearly, automatic reestimation of first arriving P onsets using the autoregressive likelihood technique has the potential of significantly reducing the retiming efforts of the analyst

Accurate determination of phase arrival times using autoregressive likelihood estimation

We have investigated the potential automatic use of an onset picker based on autoregressive likelihood estimation. Both a single component version and a three component version of this method have been tested on data from events located in the Khibiny Massif of the Kola peninsula, recorded at the Apatity array, the Apatity three component station and the ARCESS array. Using this method, we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P-phases and 0.15 0.20 s for S phases. These accuracies are as good as for analyst picks, and are considerably better than the accuracies of the current onset procedure used for processing of regional array data at NORSAR. In another application, we have developed a generic procedure to reestimate the onsets of all types of first arriving P phases. By again applying the autoregressive likelihood technique, we have obtained automatic onset times of a quality such that 70% of the automatic picks are within 0.1 s of the best manual pick. For the onset time procedure currently used at NORSAR, the corresponding number is 28%. Clearly, automatic reestimation of first arriving P onsets using the autoregressive likelihood technique has the potential of significantly reducing the retiming efforts of the analyst

Intelligent post processing of seismic events

The Intelligent Monitoring Systern (IMS) currently provides for joint processing of data from six arrays located in Northern and Central Europe. From experience with analyst review of events automatically defined by the IMS, we bave realized that the quality of the automatic event locations can be significantly improved if the event intervals are reprocessed with signal processing pararneters tuned to phases from events in the given region. The tuned processing parameters are obtained from off line analysis of events located in the region of interest. The primary goal of such intelligent post processing is to provide event definitions of a quality that minimizes the need for subsequent manual analysis. The first step in this post processing is to subdivide the arca to be monitored in order to identify sites of interest. Clearly, calibration will be the easiest and potential savings in manpower are the largest for areas of high, recurring seismicity. We bave identified 8 mining sites in Fennoscandia/NW Russia and noted that 65.6% of the events of ML > 2.0 in this region can be associated with one of these sites. This result is based on 1 year and a half of data. The second step is to refine the phase arrival and azimuth estimates using frequency filters and processing parameters that are tuned to the initial event location provided by the IMS. In this study, we have analyzed a set of 52 mining explosions from the Khibiny Massif mining area in the Kola peninsula of Russia. Very accurate locations of these events bave been provided by the seismologists from the Kola Regional Seismology Centre. Using an autoregressive likelihood technique we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P phases and 0.15 0.20 s for S phases. Using fixed frequency bands, azimuth can be estimated to an accuracy (one standard deviation) of 0.9 degrees for the ARCESS array and 3 4 degrees for the small array recently established near Apatity on the Kola peninsula. The third step in the post processing is a relocation of the event, using refined arrivai times and recomputed azimuths from broad band flk analysis. By introducing region specific travel time corrections, a median error of 1.4 km from the reported location has been obtained. This should be compared to the median error of 10.8 km for the automatie IMS processing for these events. This improvement in location accuracy clearly demonstrates the usefulness of the intelligent post processing approach

Final Technical Report, 30 SEPTEMBER 2002 - 31 JANUARY 2006; ENERGY PARTIONING FOR SEISMIC EVENTS IN FENNOSCANDIA AND NW RUSSIA

In this project we have addressed the problem of energy partitioning at distances ranging from very local to regional for various kinds of seismic sources. On the local and regional scale (20-220 km) we have targeted events from the region offshore Western Norway where we have both natural earthquake activity as well as frequent occurrence of underwater explosions carried out by the Norwegian Navy. On the small scale we have focused on analysis of observations from an in-mine network of 16-18 sensors in the Pyhasalmi mine in central Finland. This analysis has been supplemented with 3-D finite difference wave propagation simulations in a realistic mine model to investigate the physical mechanisms that partition seismic energy in the near source region in and around the underground mine. The results from modeling and analysis of local and regional data show that mean S/P amplitude ratios for explosions and natural events differ at individual stations and are in general higher for natural events and frequency bands above 3 Hz. However, the distributions of S/P ratios for explosions and natural events overlap in all analyzed frequency bands. Thus, for individual events in our study area, S/P amplitude ratios can only assist the discrimination between an explosion or a natural event. This observation is supported by synthetic seismograms calculated for simple 1-D models which demonstrate that explosions also generate shear-wave energy if they are fired close to an interface with a strong material contrast (as is the case for most explosions), e.g., free surface or the ocean bottom. The larger difference in S/P ratios between earthquakes and explosions for higher frequencies can be explained by the fact that at low frequencies (larger wavelengths), discontinuities and structural heterogeneities in the explosion source region are stronger generators of converted S energy. The S*-phase, for example, is most efficiently generated whenever an explosion source is located close (within one wavelength) to a strong discontinuity. The Pyhasalmi explosions have generally lower S/P ratios than the rockbursts for all frequencies, but the difference is far too small to be significant for classification purposes. The maxima for the explosion distributions are all below 2, whereas they are all above 2 for the rockbursts. The rockbursts also have a wider distribution of S/P ratios, which can be explained by the variability of the radiation patterns from the rockburst sources. S/P ratios for explosions and rockbursts located in the same small area of the mine show results very similar to those for the full data set. This indicates that the observed differences in S/P ratios between explosions and rockbursts are due to differences in the source characteristics, and not due to propagation effects along paths in the mine. 3-D finite-difference simulations were used to model seismic events within the Pyhasalmi mine. In particular, a January 26, 2003 rockburst was modeled at frequencies of 50 Hz (4 meter grid) and 100 Hz (2 meter grid). We were able to match the characteristics of the observed data at 50 Hz particularly well, and the characteristics of the 100 Hz data reasonably well. These results help validate the 3-D geologic mine model and the reliability of our simulations. The simulations showed that significant shear-energy can be produced due to the geologic and structural heterogeneities within the mine. In fact, mode-converted shear-energy generated from mine heterogeneity can dominate the compressional energy from an explosive source. A strong correlation is observed between the distance of a source from a mine heterogeneity and the magnitude of generated shear-energy. The ratio of shear to compressional energy is about a factor of two larger when the source is located within one wavelength from a mine heterogeneity. The simulations also suggest that excavated mine volumes are significantly stronger contributors to shear-energy generation than geologic heterogeneities. However, the simulations reveal that the magnitude of shear-energy generated as part of a shear-producing source mechanism (e.g., rockburst, mine collapse) can be as large or larger than that caused by heterogeneity within the mine

Intelligent post processing of seismic events

The Intelligent Monitoring Systern (IMS) currently provides for joint processing of data from six arrays located in Northern and Central Europe. From experience with analyst review of events automatically defined by the IMS, we bave realized that the quality of the automatic event locations can be significantly improved if the event intervals are reprocessed with signal processing pararneters tuned to phases from events in the given region. The tuned processing parameters are obtained from off line analysis of events located in the region of interest. The primary goal of such intelligent post processing is to provide event definitions of a quality that minimizes the need for subsequent manual analysis. The first step in this post processing is to subdivide the arca to be monitored in order to identify sites of interest. Clearly, calibration will be the easiest and potential savings in manpower are the largest for areas of high, recurring seismicity. We bave identified 8 mining sites in Fennoscandia/NW Russia and noted that 65.6% of the events of ML > 2.0 in this region can be associated with one of these sites. This result is based on 1 year and a half of data. The second step is to refine the phase arrival and azimuth estimates using frequency filters and processing parameters that are tuned to the initial event location provided by the IMS. In this study, we have analyzed a set of 52 mining explosions from the Khibiny Massif mining area in the Kola peninsula of Russia. Very accurate locations of these events bave been provided by the seismologists from the Kola Regional Seismology Centre. Using an autoregressive likelihood technique we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P phases and 0.15 0.20 s for S phases. Using fixed frequency bands, azimuth can be estimated to an accuracy (one standard deviation) of 0.9 degrees for the ARCESS array and 3 4 degrees for the small array recently established near Apatity on the Kola peninsula. The third step in the post processing is a relocation of the event, using refined arrivai times and recomputed azimuths from broad band flk analysis. By introducing region specific travel time corrections, a median error of 1.4 km from the reported location has been obtained. This should be compared to the median error of 10.8 km for the automatie IMS processing for these events. This improvement in location accuracy clearly demonstrates the usefulness of the intelligent post processing approach