Improving the Amplitude Source Location (ASL) Method Using Multicomponent Seismic Data: An Assessment with Active Source Seismic Data

2019 ◽  
Vol 110 (1) ◽  
pp. 250-269
Author(s):  
Braden Walsh ◽  
Jonathan Procter ◽  
Arthur Jolly
Keyword(s):  
Debris Flow ◽  
Seismic Data ◽  
Vertical Component ◽  
Source Location ◽  
Flow Channel ◽  
Coda Wave ◽  
F Test ◽  
Active Source ◽  
Mean Square Errors ◽  
Three Components

ABSTRACT Here, all three components of the seismic signal are applied for use with the amplitude source location (ASL) method to investigate if using all three components yield more accurate results than using just the vertical component. Eight active source events along a debris flow channel on Te Maari Volcano, New Zealand, are used as known source locations to conduct the test. Both coda-wave normalization (CWN) and horizontal-to-vertical (H/V) ratio methods are used to calculate amplification factors for station corrections. Average location errors for all the active seismic sources varied between 0.47 km for the vertical component and 0.51 km for three components while using the CWN method, and 0.92 km (vertical) and 0.83 km (three component) using the H/V method. We also conduct statistical analysis through an F-test by calculating root mean square errors (RMSEs) to determine if the results were statistically different. The RMSE analysis for the active source events shows location results for event 1 and 7 producing errors of 2.18±1.33 and 2.37±1.29  km for the vertical-component results, and 2.06±1.16 and 2.33±1.24  km for the three-component results. The F-test indicates that active source events higher up the debris flow channel (centrally located relative to the network) are statistically the same, whereas events lower down the channel (away from the center of the network) are statistically different. Results show that using all three components with the ASL method may not necessarily yield more accurate locations, but nevertheless may average the components to eliminate the extreme error values or amplify the signals, producing more precise results.

Signal detection using multi-channel seismic data

1996 ◽  
Vol 86 (1A) ◽  
pp. 221-231 ◽  
Author(s):  
Gregory S. Wagner ◽  
Thomas J. Owens
Keyword(s):  
Signal Detection ◽  
Seismic Data ◽  
Spatial Coherence ◽  
Vertical Component ◽  
Principal Component ◽  
Minimum Variance ◽  
Data Detection ◽  
Array Data ◽  
Detection Approach ◽  
Sample Covariance

Abstract We outline a simple signal detection approach for multi-channel seismic data. Our approach is based on the premise that the wave-field spatial coherence increases when a signal is present. A measure of spatial coherence is provided by the largest eigenvalue of the multi-channel data's sample covariance matrix. The primary advantages of this approach are its speed and simplicity. For three-component data, this approach provides a more robust statistic than particle motion polarization. For array data, this approach provides beamforming-like signal detection results without the need to form beams. This approach allows several options for the use of three-component array data. Detection statistics for three-component, vertical-component array, and three different three-component array approaches are compared to conventional and minimum-variance vertical-component beamforming. Problems inherent in principal-component analysis (PCA) in general and PCA of high-frequency seismic data in particular are also discussed. Multi-channel beamforming and the differences between principal component and factor analysis are discussed in the appendix.

Multi-temporal analysis of the role of check dams in a debris-flow channel: Linking structural and functional connectivity

Geomorphology ◽  
2019 ◽  
Vol 345 ◽  
pp. 106844 ◽  
Author(s):  
Sara Cucchiaro ◽  
Federico Cazorzi ◽  
Lorenzo Marchi ◽  
Stefano Crema ◽  
Alberto Beinat ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Debris Flow ◽  
Temporal Analysis ◽  
Flow Channel ◽  
Check Dams ◽  
Multi Temporal

Recording the Aurora at Seismometers across Alaska

2020 ◽  
Vol 91 (6) ◽  
pp. 3039-3053 ◽  
Author(s):  
Carl Tape ◽  
Adam T. Ringler ◽  
Don L. Hampton
Keyword(s):  
Magnetic Field ◽  
Seismic Data ◽  
Vertical Component ◽  
Seismic Array ◽  
Magnetic Shielding ◽  
Data Sets ◽  
S Waves ◽  
Auroral Activity ◽  
Seismic Sensors ◽  
Magnetometer Data

Abstract We examine three continuously recording data sets related to the aurora: all-sky camera images, three-component magnetometer data, and vertical-component, broadband seismic data as part of the EarthScope project (2014 to present). Across Alaska there are six all-sky cameras, 13 magnetometers, and >200 seismometers. The all-sky images and magnetometers have the same objective, which is to monitor space weather and improve our understanding of auroral activity, including the influence on magnetic fields in the ground. These variations in the magnetic field are also visible on seismometers, to the extent that during an auroral event, the long-period (40–800 s) waves recorded by a seismometer are magnetic field variations, not true ground motion. Although this is a problem—one that can be rectified with magnetic shielding at each seismometer site—it is also an opportunity because the present seismic array in Alaska is much broader than the coverage by magnetometers and all-sky cameras. Here we focus on three aurora events and document a direct link between aurora images in the night sky and seismometer recordings on ground. Simultaneous recordings by magnetometers provide a critical link between the sky images and the seismometer recordings. We document qualitative correlations among sky, magnetic, and seismic data. The findings suggest that the signature of auroral activity is widespread across seismometers in Alaska, implying that the seismic array could be used to enhance the spatial resolution of the existing network of all-sky cameras and magnetometers. Future efforts to improve the multisensor seismic stations in Alaska, for the purpose of monitoring seismic and auroral activity, should consider installation of all-sky cameras, installation of magnetometers, and magnetic shielding of seismic sensors.

scholarly journals Relative source location using coda-wave interferometry: Method, code package, and application to mining-induced earthquakes

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. F73-F84 ◽  
Author(s):  
Youqian Zhao ◽  
Andrew Curtis
Keyword(s):  
Single Channel ◽  
Source Region ◽  
Source Location ◽  
Coda Wave ◽  
Data Set ◽  
Seismic Stations ◽  
Location Method ◽  
Wide Range ◽  
Single Station ◽  
Coda Wave Interferometry

A wide range of applications requires the relative locations of sources of energy to be known accurately. Most conventional location methods are either subject to errors that depend strongly on inaccuracy in the model of propagation velocity used or demand a well-distributed network of surrounding seismic stations to produce reliable results. A new source location method based on coda-wave interferometry (CWI) is relatively insensitive to the number of seismic stations and to the source-to-station azimuthal coverage. Therefore, it opens new avenues for research, for applications in areas with unfavorable recording geometries, and for applications that require a complementary method. This method uses CWI to estimate distances between pairs of seismic events with a similar source mechanism recorded at the same station. These separation estimates are used to solve for the locations of clusters of events relative to one another within a probabilistic framework through optimization. It is even possible to find the relative locations of clusters of events with one single-channel station. Given these advantages, it is likely that one reason that the method is not used more widely is the lack of reliable code that implements this multistage method. Therefore, we have developed a well-commented MATLAB code that does so, and we evaluate examples of its applications. It can be used with seismic data from a single-station channel, and it enables data recorded by different channels and stations to be used simultaneously. It is therefore possible to combine data from permanent yet sparse networks and from temporary arrays closer to the source region. We use the code to apply the location method to a selected data set of the New Ollerton earthquakes in England to demonstrate the validity of the code. The worked example is provided within the package. A way to assess the quality of the location results is also provided.

SOME DATA PROCESSING RESULTS FOR A VERTICAL ARRAY OF TRIAXIAL SEISMOMETERS

Geophysics ◽  
1970 ◽  
Vol 35 (2) ◽  
pp. 337-343 ◽  
Author(s):  
Zoltan A. Der
Keyword(s):  
Data Processing ◽  
Signal To Noise Ratio ◽  
Vertical Component ◽  
Poor Performance ◽  
P Wave ◽  
Oil Well ◽  
Vertical Array ◽  
Signal To Noise ◽  
Vertical Arrays ◽  
Three Components

A vertical array of three component (triaxial) seismometers was operated in an abandoned oil well near Grapevine, Texas. The experiment was designed to investigate the effectiveness of teleseismic P‐wave enhancement by utilization of all three components of motion at various depths within the well. Previous experiments with vertical arrays which only recorded the vertical component of motion showed that optimum processors did not significantly improve the signal‐to‐noise ratio (Roden, 1968). The reason for this poor performance was found to be a similarity in the changes of signal and noise properties with depth.

A robust workflow for performing joint impedance inversion and its applications

2020 ◽  
Vol 8 (1) ◽  
pp. T141-T149
Author(s):  
Ritesh Kumar Sharma ◽  
Satinder Chopra ◽  
Larry R. Lines
Keyword(s):  
Time Domain ◽  
Seismic Data ◽  
Sedimentary Basin ◽  
Vertical Component ◽  
Data Sets ◽  
Data Set ◽  
Matching Process ◽  
Multicomponent Seismic ◽  
Impedance Inversion ◽  
Straightforward Approach

Multicomponent seismic data offer several advantages for characterizing reservoirs with the use of the vertical component (PP) and mode-converted (PS) data. Joint impedance inversion inverts both of these data sets simultaneously; hence, it is considered superior to simultaneous impedance inversion. However, the success of joint impedance inversion depends on how accurately the PS data are mapped on the PP time domain. Normally, this is attempted by performing well-to-seismic ties for PP and PS data sets and matching different horizons picked on PP and PS data. Although it seems to be a straightforward approach, there are a few issues associated with it. One of them is the lower resolution of the PS data compared with the PP data that presents difficulties in the correlation of the equivalent reflection events on both the data sets. Even after a few consistent horizons get tracked, the horizon matching process introduces some artifacts on the PS data when mapped into PP time. We have evaluated such challenges using a data set from the Western Canadian Sedimentary Basin and then develop a novel workflow for addressing them. The importance of our workflow was determined by comparing data examples generated with and without its adoption.

Active source location and beamforming

2000 ◽  
Vol 107 (5) ◽  
pp. 2790-2790 ◽  
Author(s):  
Ramani Duraiswami ◽  
Dmitry Zotkin ◽  
Eugene A. Borovikov ◽  
Larry S. Davis
Keyword(s):  
Source Location ◽  
Active Source

A workflow to discern 1D and 2D ground resonances with single-station microtremor measurements

2021 ◽  
Author(s):  
Giulia Sgattoni ◽  
Silvia Castellaro
Keyword(s):  
Site Response ◽  
Vertical Component ◽  
Sediment Layer ◽  
Resonance Frequencies ◽  
Single Station ◽  
Spectral Components ◽  
Bedrock Depth ◽  
A Site ◽  
Microtremor Measurements ◽  
Three Components

<p>Measuring ground resonances is of great importance for seismic site amplification studies. The task is usually addressed with the common H/V (horizontal to vertical spectral ratio) approach, which is widely used for both microzonation studies and stratigraphic imaging. Peaks on the H/V function are used to identify ground resonance frequencies, usually assuming 1D site conditions, i.e. with plane-parallel stratigraphy. In the simple case of a horizontal soft layer overlying a bedrock, 1D resonance is linked to the local bedrock depth (as a function of the shear wave velocity of the sediment layer). Therefore, when the 1D approximation holds, spatial variations of the resonance frequency reflect changes of bedrock depth (when lateral homogeneity of the sediment cover can be assumed). However, at sites with non-plane subsurface geometries, more complex resonance patterns may develop, such as 2D resonance patterns that typically occur within sediment-filled valleys. In this case, 2D resonance involves simultaneous vibration of the whole sedimentary infill at the same frequency, which may lead to large seismic amplification. 2D ground resonances can no longer be linked to the local depth-to-bedrock directly below the measurement site, but depend on the whole valley geometry and mechanic properties. Distinguishing between the 1D and 2D nature of a site is mandatory to avoid wrong stratigraphic and dynamic interpretations, which is in turn extremely relevant for seismic site response assessment.</p><p>We investigated the problem in the Bolzano sedimentary basin (Northern Italy), which lies at the intersection between three valleys, using a single-station microtremor approach, the same usually applied for H/V surveys. We observed that the footprints of 1D and 2D resonances reside in different behaviors along the three components of motion. This is because, while the dynamic behavior of a 1D-site is the same along all horizontal directions, 2D resonances differ along the longitudinal and transversal directions of the resonating body, e.g. parallel and perpendicular to the valley axis. In addition, 2D resonance modes involve also a vertical component. This implies that the H/V method, by mixing the information along the three components, is not suitable to detect 2D resonances, that can be acknowledged only by looking at the individual spectral components and not at the H/V curves alone.</p><p>By analyzing several hundred single-station microtremor measurements, we identified a list of frequency and amplitude features that characterize 1D and 2D resonances on individual spectral components of motion and on H/V ratios, on a single measurement and on several measurements acquired along profiles across the investigated valleys. We identified valleys characterized by 1D-only, 1D+2D and 2D-only resonance patterns and we propose a workflow scheme to conduct experimental measurements and data analysis in order to directly assess the 1D or 2D resonance nature of a site with a single-station approach, rather than evaluating this indirectly with numerical modelling.</p>

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