Comparison of 2D and 3D time-reverse imaging—A numerical case study

Steiner, Brian; Saenger, Erik H.

doi:10.1016/j.cageo.2011.12.005

Cited by 7 publications

(3 citation statements)

References 27 publications

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“…The new possibilities of the full probabilistic seismic data inversion for hypocenter coordinates open when the time reversal mirroring technique is employed. This technique, carefully analyzed in laboratory experiments (see, e.g., Fink 1997, Ulrich et al 2008, by numerical simulations (see, e.g., Kremers et al 2011, Scalerandi et al 2009, Steiner and Saenger 2012, and theoretical investigations (see, e.g., Masson et al 2014, Tromp et al 2005, Ulrich et al 2009 has already found application in seismic prospecting (see, e.g., Gajewski and Tessmer 2010, Witten and Artman 2011) and location of seismic tremors (see, e.g., Artman et al 2010, Larmat et al 2008, O'Brien et al 2011. Combaining this technique with a modern eikonal solver has lead us to the proposition of the new TRMLOC location algorithm which enables very fast Bayesian inversion of travel time onset data for hypocenter location.…”

Section: Location Algorithmsmentioning

confidence: 99%

The New Algorithm for Fast Probabilistic Hypocenter Locations

Dębski

Klejment

2016

Acta Geophys.

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The spatial location of sources of seismic waves is one of the first tasks when transient waves from natural (uncontrolled) sources are analysed in many branches of physics, including seismology, oceanology, to name a few. It is well recognised that there is no single universal location algorithm which performs equally well in all situations. Source activity and its spatial variability in time, the geometry of recording network, the complexity and heterogeneity of wave velocity distribution are all factors influencing the performance of location algorithms. In this paper we propose a new location algorithm which exploits the reciprocity and time-inverse invariance property of the wave equation. Basing on these symmetries and using a modern finite-difference-type eikonal solver, we have developed a new very fast algorithm performing the full probabilistic (Bayesian) source location. We illustrate an efficiency of the algorithm performing an advanced error analysis for 1647 seismic events from the Rudna copper mine operating in southwestern Poland.

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Section: Location Algorithmsmentioning

confidence: 99%

The New Algorithm for Fast Probabilistic Hypocenter Locations

Dębski

Klejment

2016

Acta Geophys.

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“…There are also many studies investigating the use of various imaging parameters. Although TRI methods are mostly based on the maximum value, the following were tested as imaging parameters: maximum horizontal and vertical displacement components (Hu and McMechan 1988;Steiner and Saenger 2012;Saenger 2011); maximum particle velocity (Steiner et al 2008); strain components (Blomgren et al 2002); maximum amplitude of pressure value (Gajewski and Tessmer 2005); energy density of stress components (Gajewski and Tessmer 2005; Saenger 2011); maximum P wave and S wave energy density, maximum energy density, geometric mean (Nakata and Beroza 2016), and maximum stress components (Saenger 2011). Microseismic events were also refocused using separate P and S waves's backpropagation to the original source location (Douma and Snieder, 2015).…”

Section: Introductionmentioning

confidence: 99%

Using the Morris sensitivity analysis method to assess the importance of input variables on time-reversal imaging of seismic sources

Franczyk

2019

Acta Geophys.

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The time-reversal imaging method has become a standard technique for seismic source location using both acoustic and elastic wave equations. Although there are many studies on the determination of the relevant parameter for visualization of the time-reversal method, little has been done so far to investigate the accuracy of seismic source location depending on parameters such as the geometry of the seismic network or underestimation of the velocity model. This paper investigates the importance of the accuracy of seismic source location using the time-reversal imaging method of input variables such as seismic network geometry and the assumed geological model. For efficient visualization of seismic wave propagation and interference, peak-to-average power ratio was used. Identification of the importance of variables used in seismic source location was obtained using the Morris elementary effect method, which is a global sensitivity analysis method.

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“…The following were tested as imaging parameters: maximum horizontal and vertical displacement components (Hu and McMechan 1988;Steiner and Saenger 2012;Saenger 2011), maximum particle velocity (Steiner et al 2008), strain components (Blomgren et al 2002), maximum amplitude of pressure value (Gajewski and Tessmer 2005), stress components' energy density (Gajewski and Tessmer 2005; Saenger 2011), maximum P-and S wave energy density, maximum energy density, and maximum stress components (Saenger 2011). With regard to the acoustic wave field modelling, the maximum absolute pressure value (MAPV) applied as an imaging condition appears to be a good indicator of the point source location (Eq.…”

Section: Source Location Reverse Modellingmentioning

confidence: 99%

Time reversal seismic source imaging using peak average power ratio (PAPR) parameter

2017

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The time reversal method has become a standard technique for the location of seismic sources. It has been used both for acoustic and elastic numerical modelling and for 2D and 3D propagation models. Although there are many studies concerning its application to point sources, little so far has been done to generalise the time reversal method to the study of sequences of seismic events. The need to describe such processes better motivates the analysis presented in this paper. The synthetic time reversal imaging experiments presented in this work were conducted for sources with the same origin time as well as for the sources with a slight delay in origin time. For efficient visualisation of the seismic wave propagation and interference, a new coefficient-peak average power ratiowas introduced. The paper also presents a comparison of visualisation based on the proposed coefficient against a commonly used visualisation based on a maximum value.

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Comparison of 2D and 3D time-reverse imaging—A numerical case study

Cited by 7 publications

References 27 publications

The New Algorithm for Fast Probabilistic Hypocenter Locations

The New Algorithm for Fast Probabilistic Hypocenter Locations

Using the Morris sensitivity analysis method to assess the importance of input variables on time-reversal imaging of seismic sources

Time reversal seismic source imaging using peak average power ratio (PAPR) parameter

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