scholarly journals Source Rupture Process of the Tecoman, Colima, Mexico Earthquake of 22 January 2003, Determined by Joint Inversion of Teleseismic Body-Wave and Near-Source Data

2004 ◽  
Vol 94 (5) ◽  
pp. 1795-1807 ◽  
Author(s):  
Y. Yagi
Keyword(s):  
Joint Inversion ◽  
Body Wave ◽  
Rupture Process ◽  
Source Rupture Process ◽  
Source Data ◽  
Mexico Earthquake

scholarly journals Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

scholarly journals The waveform inversion of mainshock and aftershock data of the 2006 M6.3 Yogyakarta earthquake

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hijrah Saputra ◽  
Wahyudi Wahyudi ◽  
Iman Suardi ◽  
Ade Anggraini ◽  
Wiwit Suryanto
Keyword(s):  
Joint Inversion ◽  
Body Wave ◽  
Moment Tensor ◽  
Near Field ◽  
Source Parameters ◽  
Waveform Inversion ◽  
Moment Tensor Inversion ◽  
Slip Distribution ◽  
Aftershock Distribution ◽  
Velocity Models

AbstractThis study comprehensively investigates the source mechanisms associated with the mainshock and aftershocks of the Mw = 6.3 Yogyakarta earthquake which occurred on May 27, 2006. The process involved using moment tensor inversion to determine the fault plane parameters and joint inversion which were further applied to understand the spatial and temporal slip distributions during the earthquake. Moreover, coseismal slip distribution was overlaid with the relocated aftershock distribution to determine the stress field variations around the tectonic area. Meanwhile, the moment tensor inversion made use of near-field data and its Green’s function was calculated using the extended reflectivity method while the joint inversion used near-field and teleseismic body wave data which were computed using the Kikuchi and Kanamori methods. These data were filtered through a trial-and-error method using a bandpass filter with frequency pairs and velocity models from several previous studies. Furthermore, the Akaike Bayesian Information Criterion (ABIC) method was applied to obtain more stable inversion results and different fault types were discovered. Strike–slip and dip-normal were recorded for the mainshock and similar types were recorded for the 8th aftershock while the 9th and 16th June were strike slips. However, the fault slip distribution from the joint inversion showed two asperities. The maximum slip was 0.78 m with the first asperity observed at 10 km south/north of the mainshock hypocenter. The source parameters discovered include total seismic moment M0 = 0.4311E + 19 (Nm) or Mw = 6.4 with a depth of 12 km and a duration of 28 s. The slip distribution overlaid with the aftershock distribution showed the tendency of the aftershock to occur around the asperities zone while a normal oblique focus mechanism was found using the joint inversion.

scholarly journals Coseismic Rupture Process of the Large 2019 Ridgecrest Earthquakes From Joint Inversion of Geodetic and Seismological Observations

2019 ◽  
Vol 46 (21) ◽  
pp. 11820-11829 ◽  
Author(s):  
Chengli Liu ◽  
Thorne Lay ◽  
Emily E. Brodsky ◽  
Kelian Dascher‐Cousineau ◽  
Xiong Xiong
Keyword(s):  
Joint Inversion ◽  
Rupture Process
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