scholarly journals Sensitivity maps for time-reverse imaging: an accuracy study for the Los Humeros Geothermal Field (Mexico)

2020 ◽  
Vol 222 (1) ◽  
pp. 231-246
Author(s):  
C Finger ◽  
E H Saenger
Keyword(s):  
A Priori ◽  
Velocity Model ◽  
Source Location ◽  
Geothermal Field ◽  
Location Accuracy ◽  
Accurate Localization ◽  
Localization Scheme ◽  
Priori Information ◽  
Initial Source ◽  
Sensitivity Maps

SUMMARY The estimation of the source–location accuracy of microseismic events in reservoirs is of significant importance. Time-reverse imaging (TRI) provides a highly accurate localization scheme to locate events by time-reversing the recorded full wavefield and back propagating it through a velocity model. So far, the influence of the station geometry and the velocity model on the source–location accuracy is not well known. Therefore, sensitivity maps are developed using the geothermal site of Los Humeros in Mexico to evaluate the spatial variability of the source–location accuracy. Sensitivity maps are created with an assumed gradient velocity model with a constant vp–vs ratio and with a realistic velocity model for the region of Los Humeros. The positions of 27 stations deployed in Los Humeros from September 2017 to September 2018 are used as surface receivers. An automatic localization scheme is proposed that does not rely on any a priori information about the sources and thus negates any user bias in the source locations. The sensitivity maps are created by simulating numerous uniformly distributed sources simultaneously and locating these sources using TRI. The found source locations are compared to the initial source locations to estimate the achieved accuracy. The resulting sensitivity maps show that the station geometry introduces complex patterns in the spatial variation of accuracy. Furthermore, the influence of the station geometry on the source–location accuracy is larger than the influence of the velocity model. Finally, a microearthquake recorded at the geothermal site of Los Humeros is located to demonstrate the usability of the derived sensitivity maps. This study stresses the importance of optimizing station networks to enhance the accuracy when locating seismic events using TRI.

Smoothing operators for waveform tomographic imaging

Geophysics ◽  
1993 ◽  
Vol 58 (11) ◽  
pp. 1646-1654 ◽  
Author(s):  
Steve Cardimona ◽  
Jan Garmany
Keyword(s):  
Fresnel Zone ◽  
A Priori ◽  
Approximate Solutions ◽  
Velocity Model ◽  
Forward Problem ◽  
Nonlinear Inversion ◽  
Approximation Solution ◽  
Waveform Data ◽  
Sensitivity Functions ◽  
Priori Information

The analytic kernel in the space‐time domain for the Frechet derivative of acoustic waveform data with respect to changes in the slowness model is given by the Born approximation solution to the integral equation of waveform scattering. Preconditioning operators in the solution of this forward problem, which may incorporate a priori information and approximate solutions, are smoothing operators in the imaging problem, the first iteration of a nonlinear inversion for the slowness model. Some preconditioning operators are determined for solutions to the parabolic wave equation, and then used to create new sensitivity functions that retain appropriate characteristics of the true Frechet kernel in forward calculations. The new sensitivity functions define near‐source, near‐receiver and far‐field kernels, as well as kernels that exhibit an amplitude decay off the ray yielding ray‐perpendicular sensitivity that scales with the Fresnel zone size. A sample calculation from a synthetic cross‐well imaging experiment shows the usefulness of introducing physically appropriate model smoothing directly into the sensitivity function of the forward problem, helping to obtain a geologically reasonable image of the velocity model when ray coverage is insufficient.

Determination of the time-dependent moment tensor using time-reverse imaging

Geophysics ◽  
2020 ◽  
pp. 1-61
Author(s):  
Claudia Finger ◽  
Erik Saenger
Keyword(s):  
Moment Tensor ◽  
Back Propagation ◽  
Velocity Model ◽  
Source Location ◽  
Geothermal Field ◽  
Time Dependent ◽  
Signal To Noise ◽  
Origin Time ◽  
Moment Tensors ◽  
Velocity Models

An approach is presented to determine the time-dependent moment tensor and the origin time in addition to commonly derived locations of seismic events using time-reverse imaging (TRI). It is crucial to locate and characterize the occurring micro-seismicity without making a priori assumptions about the sources to fully understand the subsurface processes inducing seismicity. Low signal-to-noise ratios often force standard methods to make assumptions about sources or only characterize selected larger-magnitude events. In TRI, micro-earthquakes are located by back propagating the full recorded time-reversed wavefield through a velocity model until it ideally convergences on the source location. Therefore, it is less affected by low signal-to-noise ratios and potentially locates and characterizes most of the events. After distinguishing artificial convergence locations from source locations, the quality of the source location and the moment tensors are derived by recording the stress at the determined source locations during the back propagation of the time-reversed wavefield. A robust workflow is derived using synthetic test cases in a realistic scenario with velocity models that only approximate the true velocity model and/or noisy displacement traces. The influence of a rudimentary velocity model on the source-location accuracy and characterisation is significant. The proposed workflow handles these less-than optimal station distributions and velocity models. Finally, the derived workflow is successfully applied to field data recorded at the geothermal field of Los Humeros, Mexico. Although only a one-dimensional velocity model is currently available, source locations and (time-dependent) moment tensors could be determined for selected events.

Characterisation of seismic events using time-reverse imaging 

2021 ◽  
Author(s):  
Claudia Finger ◽  
Erik H. Saenger
Keyword(s):  
Moment Tensor ◽  
A Priori ◽  
Velocity Model ◽  
Geothermal Field ◽  
Time Dependent ◽  
Seismic Events ◽  
Origin Time ◽  
Moment Tensors ◽  
Stress Components ◽  
True Source

<p>In addition to stable and accurate hypocenters of seismic events, the characterisation of events is crucial for the investigation of seismicity in the context of geothermal reservoirs, CO2-sequestration and other geotechnical applications. Since the origin and nature of the seismicity in such cases is still under investigation, tools should rely on as few a priori assumptions about the sources as possible. Here, an approach is presented to determine the time-dependent moment tensor and origin time in addition to commonly derived hypocenter locations of seismic events using time-reverse imaging (TRI). The full six component moment tensor is derived and may be used to display for example focal mechanisms. The workflow consists of determining the location of potential sources, discriminating artificial and true source locations and obtaining the time-dependent moment tensors by recording the stress components at the derived source locations. Since TRI does not rely on the identification of seismic phases but on the simulation of the time-reversed wavefield through an adequate velocity model, no assumptions about the source location or the type of source mechanism is made. TRI is less affected by low signal-to-noise ratios and is thus promising for noisier sites and quasi-simultaneous events. However, a sufficient number of seismic stations are needed to accurately sample the wavefield spatially. The proposed workflow is demonstrated by locating and characterising microseismic events in the geothermal field of Los Humeros, Mexico. Although higher levels of noise are present and only a one-dimensional velocity model is available at this time, selected events could be located and characterised.</p>

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

scholarly journals Computational Method for Wavefront Sensing Based on Transport-Of-Intensity Equation

Photonics ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 177
Author(s):  
Iliya Gritsenko ◽  
Michael Kovalev ◽  
George Krasin ◽  
Matvey Konoplyov ◽  
Nikita Stsepuro
Keyword(s):  
A Priori ◽  
Spherical Wave ◽  
Computational Method ◽  
Optical Systems ◽  
Radius Of Curvature ◽  
Imaging Method ◽  
Wavefront Sensing ◽  
Phase Imaging ◽  
Transport Of Intensity Equation ◽  
Priori Information

Recently the transport-of-intensity equation as a phase imaging method turned out as an effective microscopy method that does not require the use of high-resolution optical systems and a priori information about the object. In this paper we propose a mathematical model that adapts the transport-of-intensity equation for the purpose of wavefront sensing of the given light wave. The analysis of the influence of the longitudinal displacement z and the step between intensity distributions measurements on the error in determining the wavefront radius of curvature of a spherical wave is carried out. The proposed method is compared with the traditional Shack–Hartmann method and the method based on computer-generated Fourier holograms. Numerical simulation showed that the proposed method allows measurement of the wavefront radius of curvature with radius of 40 mm and with accuracy of ~200 μm.

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