Single-station SVD-based Polarization Filtering – Theoretical and Synthetic Data Investigations

2010 ◽  
Author(s):  
O. Tiapkina ◽  
M. Landrø ◽  
Y. Tyapkin
Keyword(s):  
Synthetic Data ◽  
Single Station ◽  
Polarization Filtering

Single-station SVD-based polarization filtering of ground roll: Perfection and investigation of limitations and pitfalls

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. V41-V59 ◽  
Author(s):  
Olena Tiapkina ◽  
Martin Landrø ◽  
Yuriy Tyapkin ◽  
Brian Link
Keyword(s):  
Time Window ◽  
Synthetic Data ◽  
Vertical Component ◽  
Horizontal Component ◽  
Frequency Bandwidth ◽  
Polarization Filter ◽  
Data Set ◽  
Single Station ◽  
Ground Roll ◽  
Polarization Filtering

The advent of single receiver point, multi-component geophones has necessitated that ground roll be removed in the processing flow rather than through acquisition design. A wide class of processing methods for ground-roll elimination is polarization filtering. A number of these methods use singular value decomposition (SVD) or some related transformations. We focus on a single-station SVD-based polarization filter that we consider to be one of the best in the industry. The method is comprised of two stages: (1) ground-roll detection and (2) ground-roll estimation and filtering. To detect the ground roll, a special attribute dependent on the singular values of a three-column matrix formed by a sliding time window is used. The ground roll is approximated and subtracted using the first two eigenimages of this matrix. To limit the possible damage to the signal, the filter operates within the record intervals where the ground roll is detected and within the ground-roll frequency bandwidth only. We improve the ground-roll detector to make it theoretically insensitive to ambient noise and more sensitive to the presence of ground roll. The advantage of the new detector is demonstrated on synthetic and field data sets. We estimate theoretically and with synthetic data the attenuation of the underlying reflections that can be caused by the polarization filter. We show that the underlying signal always loses almost all the energy on the vertical component and on the horizontal component in the ground-roll propagation plane and within the ground-roll frequency bandwidth. The only signal component, if it exists, that can retain a significant part of its energy is the horizontal component orthogonal to the above plane. When 2D 3C field operations are conducted, the signal particle motion can deviate from the ground-roll propagation plane and can therefore retain some of its energy due to a set of offline reflections. In the case of 3D 3C seismic surveys, the reflected signal always deviates from the ground-roll propagation plane on the receiver lines that do not contain the source. This is confirmed with a 2.5D 3C synthetic data set. We discuss when the ability of the filter to effectively subtract the ground roll may, or may not, allow us to ignore the inevitable harm that is done to the underlying reflected waves.

scholarly journals Earthquake source arrays: optimal configuration and applications in crustal structure studies

2020 ◽  
Vol 221 (1) ◽  
pp. 352-370
Author(s):  
N Karamzadeh ◽  
S Heimann ◽  
T Dahm ◽  
F Krüger
Keyword(s):  
Search Algorithm ◽  
Synthetic Data ◽  
Velocity Model ◽  
High Energy ◽  
Earthquake Source ◽  
Origin Time ◽  
Earthquake Sources ◽  
Slowness Vector ◽  
Single Station ◽  
Source Array

SUMMARY A collection of earthquake sources recorded at a single station, under specific conditions, are considered as a source array (SA), that is interpreted as if earthquake sources originate at the station location and are recorded at the source location. Then, array processing methods, that is array beamforming, are applicable to analyse the recorded signals. A possible application is to use source array multiple event techniques to locate and characterize near-source scatterers and structural interfaces. In this work the aim is to facilitate the use of earthquake source arrays by presenting an automatic search algorithm to configure the source array elements. We developed a procedure to search for an optimal source array element distribution given an earthquake catalogue including accurate origin time and hypocentre locations. The objective function of the optimization process can be flexibly defined for each application to ensure the prerequisites (criteria) of making a source array. We formulated four quantitative criteria as subfunctions and used the weighted sum technique to combine them in one single scalar function. The criteria are: (1) to control the accuracy of the slowness vector estimation using the time domain beamforming method, (2) to measure the waveform coherency of the array elements, (3) to select events with lower location error and (4) to select traces with high energy of specific phases, that is, sp- or ps-phases. The proposed procedure is verified using synthetic data as well as real examples for the Vogtland region in Northwest Bohemia. We discussed the possible application of the optimized source arrays to identify the location of scatterers in the velocity model by presenting a synthetic test and an example using real waveforms.

Seismic imaging of the site response using microearthquake recordings. Part I. Method

1987 ◽  
Vol 77 (6) ◽  
pp. 1905-1923
Author(s):  
Frank Scherbaum
Keyword(s):  
Blind Deconvolution ◽  
Site Response ◽  
Synthetic Data ◽  
Propagation Path ◽  
Inversion Method ◽  
Original Form ◽  
Sh Waves ◽  
Geographical Regions ◽  
Short Period ◽  
Single Station

Abstract Microearthquake signals from widely distributed geographical regions have been noticed repeatedly to be strongly affected by local site effects. The corresponding seismograms contain important information on the individual propagation path. A single station inversion method is presented which allows the imaging of the subsurface impedance structure from locally recorded SH waves records. The technique is based on the Kunetz-Claerbout equation which in its original form states the relationship between the transmission response and the reflection response for P waves in a horizontally layered medium and vertical incidence (Claerbout 1968). By adapting Claerbout's formulation to the transmission problem for SH waves under oblique incidence, microearthquake recordings can be used to calculate corresponding pseudo-reflection seismograms which in turn can be inverted for the impedance structure by exploiting Levinson recursion. Limitations in the high-frequency content of the signals due to the combined effects of absorption, recording system, and bandlimited source signals, as well as the influence of noise, drastically reduce the resolutional power of the inversion procedure. A number of different deconvolution techniques have been tested with synthetic seismograms for the applicability to reduce these effects. Good results have been obtained with the blind deconvolution technique of Scherbaum and Stoll (1985), utilizing the minimum phase property of the Green's function. From the analysis of synthetic data, it can be expected that for realistic source-receiver situations and short-period recording systems, the main reflectors down to a depth of several hundreds of meters could be resolved.

scholarly journals Relative earthquake location procedure for clustered seismicity with a single station

2020 ◽  
Author(s):  
Francesco Grigoli ◽  
William Ellsworth ◽  
Miao Zhang ◽  
Mostafa Mousavi ◽  
Simone Cesca ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Distance Geometry ◽  
Synthetic Data ◽  
Earthquake Location ◽  
Double Difference ◽  
Monitoring Networks ◽  
Seismic Stations ◽  
Single Station ◽  
Active Research ◽  
Distance Geometry Problem

Summary Earthquake location is one of the oldest problems in seismology, yet remains an active research topic. With dense seismic monitoring networks it is possible to obtain reliable locations for microearthquakes; however, in many cases dense networks are lacking, limiting the location accuracy, or preventing location when there are too few observations. For small events in all settings, recording may be sparse and location may be difficult due to low signal-to-noise ratio. In this work we introduce a new, distance-geometry-based method to locate seismicity clusters using only one or two seismic stations. A Distance Geometry Problem determines the location of sets of points based only on the distances between some member pairs. Applied to seismology, our approach allows earthquake location using the inter-event distance between earthquakes pairs, which can be estimated using only one or two seismic stations. We first validate the method with synthetic data that resemble common cluster shapes, and then test the method with two seismic sequences in California: the August 2014 Mw 6.0 Napa earthquake band the July 2019 Mw 6.4 Ridgecrest earthquake sequence. We demonstrate that our approach provides robust and reliable results even for a single station. When using two seismic stations, the results capture the same structures recovered with high resolution Double Difference locations based on multiple stations. The proposed method is particularly useful for poorly monitored areas, where only a limited number of stations are available.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

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