scholarly journals Contiguous rupture areas of two Nankai Trough earthquakes revealed by high-resolution tsunami waveform inversion

2005 ◽  
Vol 32 (8) ◽  
Author(s):  
Toshitaka Baba
Keyword(s):  
High Resolution ◽  
Nankai Trough ◽  
Waveform Inversion ◽  
Tsunami Waveform Inversion ◽  
Tsunami Waveform

Bayesian tsunami-waveform inversion with trans-dimensional tsunami-source models

2014 ◽  
Vol 136 (4) ◽  
pp. 2085-2085
Author(s):  
Jan Dettmer ◽  
Jakir Hossen ◽  
Phil R. Cummins ◽  
Stan E. Dosso
Keyword(s):  
Waveform Inversion ◽  
Tsunami Source ◽  
Tsunami Waveform Inversion ◽  
Source Models ◽  
Tsunami Waveform

scholarly journals GO_3D_OBS – The Nankai Trough-inspired benchmark geomodel for seismic imaging methods assessment and next generation 3D surveys design (version 1.0)

2020 ◽  
Author(s):  
Andrzej Górszczyk ◽  
Stéphane Operto
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Nankai Trough ◽  
Regional Scale ◽  
Waveform Inversion ◽  
Leading Edge ◽  
High Resolution Imaging ◽  
Ocean Bottom ◽  
Next Generation ◽  
Resolution Imaging

Abstract. Detailed reconstruction of deep crustal targets by seismic methods remains a long-standing challenge. One key to address this challenge is the joint development of new seismic acquisition systems and leading-edge processing techniques. In marine environments, controlled-source seismic surveys at regional scale are typically carried out with sparse arrays of ocean bottom seismometers (OBSs), which provide incomplete and down-sampled subsurface illumination. To assess and minimize the acquisition footprint in high-resolution imaging process such as full waveform inversion, realistic crustal-scale benchmark models are clearly required.The deficiency of such models prompts us to build one and release it freely to the geophysical community. Here we introduce GO_3D_OBS – a 3D high-resolution geomodel representing a subduction zone, inspired by the geology of the Nankai Trough. The 175 km x 100 km x 30 km model integrates complex geological structures with a visco-elastic isotropic parametrization. It is defined in form of a uniform Cartesian grid containing 33.6e9 degrees of freedom for a grid interval of 25 m. The size of the model raises significant high-performance computing challenges to tackle large-scale forward propagation simulations and related inverse problems. We describe the workflow designed to implement all the model ingredients including 2D structural segments, their projection into the third dimension, stochastic components and physical parametrisation. Various wavefield simulations we present clearly reflect in the seismograms the structural complexity of the model and the footprint of different physical approximations. This benchmark model shall help to optimize the design of next generation 3D academic surveys – in particular but not only long-offset OBS experiments – to mitigate the acquisition footprint during high-resolution imaging of the deep crust.

scholarly journals Randomly distributed unit sources to enhance optimization in tsunami waveform inversion

2014 ◽  
Vol 2 (5) ◽  
pp. 3659-3682
Author(s):  
I. E. Mulia ◽  
T. Asano
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Surface Deformation ◽  
Waveform Inversion ◽  
Sea Surface ◽  
Tsunami Source ◽  
Unknown Parameters ◽  
Tsunami Waveform Inversion ◽  
Tsunami Waveform

Abstract. Determination of sea surface deformation generated by earthquakes is crucial to the success of tsunami modeling. Using waveforms recorded at measurement stations and assuming that the rupture velocity is much faster than the tsunami wave celerity, sea surface deformation caused by a tsunamigenic earthquake can be inferred through an inversion operation using the Green's function technique. However, this inversion method for tsunami waveforms possesses a limitation, in that the inverse matrix does not always exist because of the non-uniqueness of the solution. In addition to the large number of unknown parameters, which might produce many local optima on the misfit function measure, the search towards optimality is confined by the uniform distance of unit sources used in the regular Green's function. This study proposes a new method to both optimize the determination of the unknown parameters and introduce a global optimization method for tsunami waveform inversion. The method has been tested using an artificial tsunami source with real bathymetry data. A significant improvement is achieved by stochastically searching for an optimal distribution of unit source locations prior to the inversion.

Tsunami Waveform Inversion of the 2007 Peru (Mw8.1) Earthquake

2014 ◽  
Vol 9 (6) ◽  
pp. 954-960 ◽  
Author(s):  
Cesar Jimenez ◽  
◽  
Nabilt Moggiano ◽  
Erick Mas ◽  
Bruno Adriano ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Seismic Source ◽  
Least Square Method ◽  
Source Model ◽  
Least Square ◽  
Coseismic Deformation ◽  
Tsunami Propagation ◽  
Tsunami Waveform Inversion ◽  
Seismic Source Model ◽  
Tsunami Waveform

An earthquake shook the central-southern coast of Peru on August 15, 2007, as a coseismic effect a tsunami was generated, which flooded some villages and beach resorts and killed 3 people. From the analysis and signal processing of 10 tidal records, we obtained the parameters of the seismic source and the initial coseismic deformation through an inversion modeling, in which the synthetic signals are compared with the observed signals by a non-negative least square method. The maximum slip located on the southern part of the rupture geometry is 7.0 m. The calculated scalar seismic moment isM0= 1.99 × 1021Nm, equivalent to a magnitude ofMw8.1. We used these parameters to obtain a heterogeneous seismic source model, which was used as initial condition to simulate the tsunami propagation and inundation. We used the field survey observations to validate our source model.

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