scholarly journals Comment on “The effect of velocity structure errors on double-difference earthquake location” by A. Michelini and A. Lomax

2004 ◽  
Vol 31 (15) ◽  
Author(s):  
Clifford Thurber

2004 ◽  
Vol 36 (3) ◽  
pp. 1396 ◽  
Author(s):  
O. C. Galanis ◽  
C. B. Papazachos ◽  
P. M. Hatzidimitriou ◽  
E. M. Scordilis

In the past years there has been a growing demand for precise earthquake locations for seismotectonic and seismic hazard studies. Recently this has become possible because of the development of sophisticated location algorithms, as well as hardware resources. This is expected to lead to a better insight of seismicity in the near future. A well-known technique, which has been recently used for relocating earthquake data sets is the double difference algorithm. In its original implementation it makes use of a one-dimensional ray tracing routine to calculate seismic wave travel times. We have modified the implementation of the algorithm by incorporating a three-dimensional velocity model and ray tracing in order to relocate a set of earthquakes in the area of the Mygdonia Basin (Northern Greece). This area is covered by a permanent regional network and occasionally by temporary local networks. The velocity structure is very well known, as the Mygdonia Basin has been used as an international test site for seismological studies since 1993, which makes it an appropriate location for evaluating earthquake location algorithms, with the quality of the results depending only on the quality of the data and the algorithm itself. The new earthquake locations reveal details of the area's seismotectonic structure, which are blurred, if not misleading, when resolved by standard (routine) location algorithms.





2021 ◽  
Author(s):  
Jeremy Pesicek ◽  
Trond Ryberg ◽  
Roger Machacca ◽  
Jaime Raigosa

<p>Earthquake location is a primary function of volcano observatories worldwide and the resulting catalogs of seismicity are integral to interpretations and forecasts of volcanic activity.  Ensuring earthquake location accuracy is therefore of critical importance.  However, accurate earthquake locations require accurate velocity models, which are not always available.  In addition, difficulties involved in applying traditional velocity modeling methods often mean that earthquake locations are computed at volcanoes using velocity models not specific to the local volcano.   </p><p>Traditional linearized methods that jointly invert for earthquake locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, which are then iteratively updated to minimize the data misfit.  However, these deterministic methods are susceptible to local minima and divergence, issues exacerbated by sparse seismic networks and/or poor data quality common at volcanoes.  In cases where independent prior constraints on local velocity structure are not available, these methods may result in systematic errors in velocity models and hypocenters, especially if the full range of possible starting values is not explored.  Furthermore, such solutions depend on subjective choices for model regularization and parameterization.</p><p>In contrast, Bayesian methods promise to avoid all these pitfalls.  Although these methods traditionally have been difficult to implement due to additional computational burdens, the increasing use and availability of High-Performance Computing resources mean widespread application of these methods is no longer prohibitively expensive.  In this presentation, we apply a Bayesian, hierarchical, trans-dimensional Markov chain Monte Carlo method to jointly solve for hypocentral parameters, 1D velocity structure, and station corrections using data from monitoring networks of varying quality at several volcanoes in the U.S. and South America.  We compare the results with those from a more traditional deterministic approach and show that the resulting velocity models produce more accurate earthquake locations.  Finally, we chart a path forward for more widespread adoption of the Bayesian approach, which may improve catalogs of volcanic seismicity at observatories worldwide. </p>



2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
I. Bernal ◽  
H. Tavera

In this study, we present a velocity model for the area of the 2007 Pisco-Peru earthquake ( Mw = 8.0 ) obtained using a double-difference tomography algorithm that considers aftershocks acquired for 6 months. The studied area is particularly interesting because it lies on the northern edge of the Nazca Ridge, in which the subduction of a large bathymetric structure is the origin of geomorphological features of the central coast of Peru. Relocated seismicity is used to infer the geometry of the subduction slab on the northern flank of the Nazca Ridge. The results prove that the geometry is continuous but convex because of the subduction of the ridge, thereby explaining the high uplift rates observed in this area. Our inferred distribution of seismicity agrees with both the coseismic and postseismic slip distributions.



2018 ◽  
Vol 90 (1) ◽  
pp. 229-241 ◽  
Author(s):  
Hailiang Xin ◽  
Haijiang Zhang ◽  
Min Kang ◽  
Rizheng He ◽  
Lei Gao ◽  
...  


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