scholarly journals Focal mechanism of seismic events with a dipolar component

1995 ◽  
Vol 38 (3-4) ◽  
Author(s):  
F. Batini ◽  
M. Caputo ◽  
R. Console
Keyword(s):  
Synthetic Data ◽  
High Standard ◽  
Seismic Source ◽  
Real Data ◽  
Computer Code ◽  
Geothermal Field ◽  
Observation Data ◽  
Amplitude Data ◽  
Double Couple ◽  
Fault Mechanism

In this paper we model the geometry of a seismic source as a dislocation occurring on an elemental flat fault in an arbitrary direction with respect to the fault plane. This implies the use of a fourth parameter in addition to the three usual ones describing a simple double couple mechanism. We applied the radiation pattern obtained from the theory to a computer code written for the inversion of the observation data (amplitudes and polarities of the first onsets recorded by a network of stations). It allows the determination of the fault mechanism gener- alized in the above mentioned way. The computer code was verified on synthetic data and then applied to real data recorded by the seismic network operated by the Ente Nazionale per l'Energia Elettrica (ENEL), monitoring the geothermal field of Larderello. The experimental data show that for some events the source mechanism exhibits a significant dipolar component. However, due to the high standard deviation of the amplitude data, F-test applied to the results of the analysis shows that only for two events the confidence level for the general- ized model exceeds 90%.

scholarly journals Monitoring of induced distributed double-couple sources using Marchenko-based virtual receivers

Solid Earth ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 1301-1319 ◽  
Author(s):  
Joeri Brackenhoff ◽  
Jan Thorbecke ◽  
Kees Wapenaar
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Synthetic Data ◽  
Real Data ◽  
Point Sources ◽  
Reflection Data ◽  
Double Couple ◽  
Source Mechanisms ◽  
Source Signal ◽  
Time Part

Abstract. We aim to monitor and characterize signals in the subsurface by combining these passive signals with recorded reflection data at the surface of the Earth. To achieve this, we propose a method to create virtual receivers from reflection data using the Marchenko method. By applying homogeneous Green’s function retrieval, these virtual receivers are then used to monitor the responses from subsurface sources. We consider monopole point sources with a symmetric source signal, for which the full wave field without artifacts in the subsurface can be obtained. Responses from more complex source mechanisms, such as double-couple sources, can also be used and provide results with comparable quality to the monopole responses. If the source signal is not symmetric in time, our technique based on homogeneous Green’s function retrieval provides an incomplete signal, with additional artifacts. The duration of these artifacts is limited and they are only present when the source of the signal is located above the virtual receiver. For sources along a fault rupture, this limitation is also present and more severe due to the source activating over a longer period of time. Part of the correct signal is still retrieved, as is the source location of the signal. These artifacts do not occur in another method that creates virtual sources as well as receivers from reflection data at the surface. This second method can be used to forecast responses to possible future induced seismicity sources (monopoles, double-couple sources and fault ruptures). This method is applied to field data, and similar results to the ones on synthetic data are achieved, which shows the potential for application on real data signals.

scholarly journals Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

2020 ◽  
Author(s):  
Ana Gabriela Bravo-Osuna ◽  
Enrique Gómez-Treviño ◽  
Olaf Josafat Cortés-Arroyo ◽  
Néstor Fernando Delgadillo-Jáuregui ◽  
Rocío Fabiola Arellano-Castro
Keyword(s):  
Synthetic Data ◽  
Real Data ◽  
Electrical Current ◽  
Numerical Approach ◽  
Geothermal Field ◽  
Analytic Formula ◽  
Similar Data ◽  
Phase Tensor ◽  
Electrical Current Flow ◽  
Cerro Prieto

Abstract The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

scholarly journals Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Ana G. Bravo-Osuna ◽  
Enrique Gómez-Treviño ◽  
Olaf J. Cortés-Arroyo ◽  
Nestor F. Delgadillo-Jauregui ◽  
Rocío F. Arellano-Castro
Keyword(s):  
Synthetic Data ◽  
Real Data ◽  
Electrical Current ◽  
Numerical Approach ◽  
Geothermal Field ◽  
Analytic Formula ◽  
Phase Tensor ◽  
The Matrix ◽  
Electrical Current Flow ◽  
Cerro Prieto

AbstractThe magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar datasets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula, this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

scholarly journals Monitoring induced distributed double-couple sources using Marchenko-based virtual receivers

2019 ◽  
Author(s):  
Joeri Brackenhoff ◽  
Jan Thorbecke ◽  
Kees Wapenaar
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Synthetic Data ◽  
Real Data ◽  
Point Sources ◽  
Reflection Data ◽  
Double Couple ◽  
Source Mechanisms ◽  
Source Signal ◽  
Time Part

Abstract. We aim to monitor and characterize signals in the subsurface by combining these passive signals with recorded reflection data at the surface of the Earth. To achieve this, we propose a method to create virtual receivers from reflection data using the Marchenko method. By applying homogeneous Green’s function retrieval, these virtual receivers are then used to monitor the responses from subsurface sources. We consider monopole point sources with a symmetric source signal, where the full wavefield without artefacts in the subsurface can be obtained. Responses from more complex source mechanisms, such as double-couple sources, can also be used and provide results with comparable quality as the monopole responses. If the source signal is not symmetric in time, our technique that is based on homogeneous Green’s function retrieval provides an incomplete signal, with additional artefacts. The duration of these artefacts is limited and they are only present when the source of the signal is located above the virtual receiver. For sources along a fault rupture, this limitation is also present and more severe due to the source activating over a longer period of time. Part of the correct signal is still retrieved, as well as the source location of the signal. These aretefacts do not occur in another method which creates virtual sources as well as receivers from reflection data at the surface. This second method can be used to forecast responses to possible future induced seismicity sources (monopoles, double-couple sources and fault ruptures). This method is applied to field data, where similar results to synthetic data are achieved, which shows the potential for the application on real data signals.

scholarly journals Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

2020 ◽  
Author(s):  
Ana Gabriela Bravo-Osuna ◽  
Enrique Gómez-Treviño ◽  
Olaf Josafat Cortés-Arroyo ◽  
Néstor Fernando Delgadillo-Jáuregui ◽  
Rocío Fabiola Arellano-Castro
Keyword(s):  
Analytical Formula ◽  
Synthetic Data ◽  
Noisy Data ◽  
Real Data ◽  
Electrical Current ◽  
Geothermal Field ◽  
Similar Data ◽  
Phase Tensor ◽  
Electrical Current Flow ◽  
Cerro Prieto

Abstract The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. On the other hand, the classical Swift’s approach for strike is very stable for noisy data but it is severely affected by galvanic distortions. In this paper we impose the criterion of Swift’s approach to the phase tensor. Rather than developing an analytical formula we optimize numerically the same criterion. This stabilizes the estimation of strike by relaxing an exact condition to an optimal condition in the presence of noise. This has the added benefit that it can be applied to windows of several periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

Estimation of seismic source parameters in 3D elastic media using the reciprocity theorem

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R963-R976
Author(s):  
Petr V. Petrov ◽  
Gregory A. Newman
Keyword(s):  
Heterogeneous Media ◽  
Source Parameters ◽  
Synthetic Data ◽  
Seismic Source ◽  
Optimization Methods ◽  
Geothermal Field ◽  
Second Order ◽  
Order Moment ◽  
Elastic Media ◽  
Moment Tensors

We have developed a novel method based upon reciprocity principles to simultaneously estimate the location of a seismic event and its source mechanism in 3D heterogeneous media. The method finds double-couple (DC) and non-DC mechanisms of microearthquakes arising from localized induced and natural seismicity. Because the method uses an exhaustive search of the 3D elastic media, it is globally convergent. It does not suffer from local minima realization observed with local optimization methods, including Newton, Gauss-Newton, or gradient-descent algorithms. The computational efficiency of our scheme is derived from the reciprocity principle, in which the number of 3D model realizations corresponds to the number of measurement receivers. The 3D forward modeling is carried out in the damped Fourier domain with a 3D finite-difference frequency-domain fourth- and second-order code developed to simulate elastic waves generated by seismic sources defined by forces and second-order moment density tensors. We evaluate the results of testing this new methodology on synthetic data for the Raft River geothermal field, Idaho, as well as determine its applicability in designing optimal borehole monitoring arrays in a fracking experiment at the Homestake Mine, South Dakota. We also find that the method proposed here can retrieve the moment tensors of the space distributed source with data arising from spatially restricted arrays with limited aperture. The effects of uncertainties on the source parameter estimation are also examined with respect to data noise and model uncertainty.

scholarly journals Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations.

2021 ◽  
Author(s):  
Ana Gabriela Bravo-Osuna ◽  
Enrique Gómez-Treviño ◽  
Olaf Josafat Cortés-Arroyo ◽  
Néstor Fernando Delgadillo-Jáuregui ◽  
Rocío Fabiola Arellano-Castro
Keyword(s):  
Synthetic Data ◽  
Real Data ◽  
Electrical Current ◽  
Numerical Approach ◽  
Geothermal Field ◽  
Analytic Formula ◽  
Similar Data ◽  
Phase Tensor ◽  
Electrical Current Flow ◽  
Cerro Prieto

Abstract The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

Seismic Data Inversion with Acquisition Adaptive CNN for Geological Forward-prospecting in Tunnels

Geophysics ◽  
2021 ◽  
pp. 1-60
Author(s):  
Yuxiao Ren ◽  
Bin Liu ◽  
Senlin Yang ◽  
Duo Li ◽  
Peng Jiang
Keyword(s):  
Velocity Distribution ◽  
Seismic Velocity ◽  
Synthetic Data ◽  
Seismic Source ◽  
Structural Similarity ◽  
Superior Performance ◽  
Observation Data ◽  
Feature Maps ◽  
Tunnel Face ◽  
Acquisition Information

Seismic forward-prospecting is essential because it can identify the velocity distribution in front of the tunnel face and provide guidance for safe excavation activities. We propose a convolutional neural network (CNN)-based method to invert forward-prospecting data recorded in tunnels for accurate and rapid estimation of seismic velocity distribution. Targeting the unusual seismic acquisition setup in tunnels, we design two separate encoders to extract features from observation data recorded on both tunnel sidewalls. Subsequently, these features are concatenated to a decoder for velocity prediction. Considering the various acquisition setups used in different tunneling projects, the deep learning inversion network must be flexible in terms of the seismic source/receiver positions for practical application. We generate two auxiliary feature maps that can be used to feed acquisition information to the proposed network. The proposed network, acquisition adaptive CNN ( A2-CNN) can be trained by defining the loss function based on the L2-norm and multiscale structural similarity (MSSIM). Compared with traditional CNNs, the proposed method shows superior performance on datasets with both fixed and random acquisition setups, and also demonstrates certain robustness when handling synthetic data with field noise. Finally, we test how the network performs when feeding the modified acquisition setup information. It turns out that the inversion result will demonstrate a shift when the provided acquisition setup information shift, which verified the validity of the network and its utilization of acquisition information.

scholarly journals Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

2020 ◽  
Author(s):  
Ana Gabriela Bravo-Osuna ◽  
Enrique Gómez-Treviño ◽  
Olaf Josafat Cortés-Arroyo ◽  
Néstor Fernando Delgadillo-Jáuregui ◽  
Rocío Fabiola Arellano-Castro
Keyword(s):  
Analytical Formula ◽  
Synthetic Data ◽  
Noisy Data ◽  
Real Data ◽  
Electrical Current ◽  
Geothermal Field ◽  
Similar Data ◽  
Phase Tensor ◽  
Electrical Current Flow ◽  
Cerro Prieto

Abstract The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. On the other hand, the classical Swift’s approach for strike is very stable for noisy data but it is severely affected by galvanic distortions. In this paper we impose the criterion of Swift’s approach to the phase tensor. Rather than developing an analytical formula we optimize numerically the same criterion. This stabilizes the estimation of strike by relaxing an exact condition to an optimal condition in the presence of noise. This has the added benefit that it can be applied to windows of several periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

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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