APPLICATION OF 3-D VELOCITY MODELS AND RAY TRACING IN DOUBLE DIFFERENCE EARTHQUAKE LOCATION ALGORITHMS: APPLICATION TO THE MYGDONIA BASIN (NORTHERN GREECE)

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.

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Velocity models for routine earthquake monitoring at volcanoes: from deterministic to Bayesian

10.5194/egusphere-egu21-3310 ◽

2021 ◽

Author(s):

Jeremy Pesicek ◽

Trond Ryberg ◽

Roger Machacca ◽

Jaime Raigosa

Keyword(s):

Velocity Structure ◽

Full Range ◽

Earthquake Location ◽

Monitoring Networks ◽

Unknown Parameters ◽

Widespread Application ◽

Starting Values ◽

Velocity Models ◽

Earthquake Locations ◽

Station Corrections

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.&#160; Ensuring earthquake location accuracy is therefore of critical importance.&#160; However, accurate earthquake locations require accurate velocity models, which are not always available.&#160; 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.&#160; &#160;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.&#160; 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.&#160; 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.&#160; Furthermore, such solutions depend on subjective choices for model regularization and parameterization.In contrast, Bayesian methods promise to avoid all these pitfalls.&#160; 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.&#160; 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.&#160; We compare the results with those from a more traditional deterministic approach and show that the resulting velocity models produce more accurate earthquake locations.&#160; Finally, we chart a path forward for more widespread adoption of the Bayesian approach, which may improve catalogs of volcanic seismicity at observatories worldwide.&#160;

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The effect of velocity structure errors on double-difference earthquake location

Geophysical Research Letters ◽

10.1029/2004gl019682 ◽

2004 ◽

Vol 31 (9) ◽

pp. n/a-n/a ◽

Cited By ~ 17

Author(s):

A. Michelini ◽

A. Lomax

Keyword(s):

Velocity Structure ◽

Earthquake Location ◽

Double Difference

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

Geophysical Research Letters ◽

10.1029/2004gl020650 ◽

2004 ◽

Vol 31 (15) ◽

Cited By ~ 1

Author(s):

Clifford Thurber

Keyword(s):

Velocity Structure ◽

Earthquake Location ◽

Double Difference

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Seismotectonic evidence for subduction beneath the Eastern Greater Caucasus

Geophysical Journal International ◽

10.1093/gji/ggaa522 ◽

2020 ◽

Vol 224 (3) ◽

pp. 1825-1834

Author(s):

Michael Gunnels ◽

Gurban Yetrimishli ◽

Sabina Kazimova ◽

Eric Sandvol

Keyword(s):

Caspian Sea ◽

Velocity Structure ◽

Seismic Velocity ◽

Double Difference ◽

Mountain Range ◽

Seismic Structure ◽

The Caspian Sea ◽

Study Region ◽

Greater Caucasus ◽

Velocity Models

SUMMARY We generated high-resolution 3-D seismic velocity models as well as a relocated earthquake catalogue across the eastern Greater Caucasus and Kura basins. This work was done using data from the recently upgraded Republic Seismological Survey Center's (RSSC) seismic network. We generated our tomographic images of crustal velocity structure in Azerbaijan using double-difference inversions (i.e. tomoDD and hypoDD). Earthquake catalogues from the RSSC between 2011 and 2016 were used; these catalogues include absolute arrival times of 103 288 P- and 120 952 S-wave traveltime picks for 7574 events recorded at 35 stations in Azerbaijan. Beginning with a layered, 1-D velocity model that was estimated using VELEST, we inverted simultaneously for relative location, Vp and Vs on a 3-D grid with dimensions 670 × 445 × 45 km, with a uniform grid spacing of 55 × 55 × 5 km for all of Azerbaijan. We observe that the relocated hypocentres cluster into two depth ranges, at the surface and at depth, that appear to correspond to major fault zones and the top of a subducting plate. Additionally, we note intermediate depth seismicity (∼50–60 km) beneath the Kura Basin, and a northward deepening of earthquake depths. Seismic velocities vary significantly throughout the study region; we observe very slow velocities throughout the Kura Basin between 5 and 15 km, and elevated velocities at 20–35 km. The wholesale velocity structure and seismic structure of Kura Basin strongly mirrors that of the Caspian Sea, which suggests that the geodynamics of the Caspian continue westwards into Azerbaijan. The key results of this study suggest that the northward subduction observed in the Caspian Sea continues beneath the Eastern Greater Caucasus, as well as provides evidence for active faulting along the southern margin of the mountain range.

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Reply to comment by Clifford Thurber and Haijiang Zhang on “The effect of velocity structure errors on double-difference earthquake location”

Geophysical Research Letters ◽

10.1029/2004gl020731 ◽

2004 ◽

Vol 31 (15) ◽

Author(s):

A. Michelini

Keyword(s):

Velocity Structure ◽

Earthquake Location ◽

Double Difference

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Loma Prieta aftershock relocation with S-P travel times: Effects of 3-D structure and true error estimates

Bulletin of the Seismological Society of America ◽

10.1785/bssa0810051705 ◽

1991 ◽

Vol 81 (5) ◽

pp. 1705-1725

Author(s):

Susan Y. Schwartz ◽

Glenn D. Nelson

Keyword(s):

Arrival Time ◽

Velocity Structure ◽

P Wave ◽

S Wave ◽

Time Data ◽

Arrival Times ◽

Velocity Models ◽

Earthquake Locations ◽

Phase Data ◽

Loma Prieta

Abstract Aftershocks of the 18 October 1989 Loma Prieta, California, earthquake are located using S-P arrival-time measurements from stations of the PASSCAL aftershock deployment. We demonstrate the effectiveness of using S-P arrival-time data in locating earthquakes recorded by a sparse three-component network. Events are located using the program QUAKE3D (Nelson and Vidale, 1990) with both 2-D and 3-D velocity models that have been developed independently for this region. The dense coverage of the area around the Loma Prieta rupture zone by instruments of the California Network (CALNET) has allowed the U.S. Geological Survey (USGS) to find P-wave earthquake locations for both velocity models, which we compare with our solutions. We also perform synthetic calculations to estimate realistic location errors resulting from uncertainties in both the 3-D velocity structure and the timing of arrivals. These calculations provide a comparison of location accuracies obtained using S-P arrival times, S and P arrival times, and P times alone. We estimate average absolute errors in epicentral location and in depth for the Loma Prieta aftershocks to be just under 2 km and 1 km, respectively, using S-P phase data and the sparse PASSCAL instrument coverage. The synthetic tests show that these errors are much smaller than those predicted using P-wave data alone and are nearly the same as those predicted using S- and P-phase data separately. This suggests that future aftershock recording deployments with sparse networks of three-component data can retrieve accurate event locations even if absolute timing is problematic. We find moderate differences between our locations and those determined by the USGS from a larger network of stations; however, common characteristics in both seismicity patterns are apparent. Neither set of locations yields earthquake patterns that can be easily interpreted in terms of simple faulting geometries. The absence of a simple pattern in both sets of earthquake locations indicates that this complexity is not the result of earthquake mislocation but is a genuine feature of the seismicity. A deep southwesterly dipping plane and a near-vertical fault extending from the surface to at least 7-km depth beneath the surface trace of the San Andreas Fault are imaged by both sets of earthquake locations. Although earthquake locations indicate the existence of many more fault segments, the complexity of this region requires that a definitive picture of the faulting geometry will have to await improvement in our knowledge of the P- and S-wave velocity structures.

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Velocity structure of Silent Canyon Caldera, Nevada Test Site

Bulletin of the Seismological Society of America ◽

10.1785/bssa0770020597 ◽

1987 ◽

Vol 77 (2) ◽

pp. 597-613

Author(s):

Michael A. Leonard ◽

Lane R. Johnson

Keyword(s):

Travel Time ◽

Velocity Structure ◽

Test Site ◽

Heterogeneous Structure ◽

Time Inversion ◽

Nevada Test Site ◽

S Wave ◽

Waveform Data ◽

One Dimensional ◽

Velocity Models

Abstract A laterally averaged, one-dimensional P- and S-wave velocity structure is obtained for Silent Canyon Caldera, located beneath Pahute Mesa at the Nevada Test Site. The velocity models are derived from a linearized damped least-squares travel-time inversion for slowness gradient perturbations. A total of 72 P- and 20 S-wave travel times generated from 13 different explosions, obtained at locations above the caldera, are used in the inversion. The structure is modeled using linear velocity gradients in a series of horizontal layers. The inversion produces a model in which velocity for P waves increases from 1.5 km/sec at the surface to 4.5 km/sec at 2.3 km depth and from 1.0 km/sec at the surface to 2.3 km/sec at 2.0 km depth for S waves. The P- and S-wave models produce travel-time residuals which are typically less than 0.1 and 0.2 sec, respectively, which is within observational error. In an attempt to estimate the degree of lateral velocity variations over which the one-dimensional model averages, waveform data collected above the caldera are examined for indications of a laterally heterogeneous structure.

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