Method to find the minimum 1D linear gradient model for seismic tomography

Tatyana A. Smaglichenko; Ingi T. Bjarnason; Alexander V. Smaglichenko; Wolfgang R. Jacoby

doi:10.3233/FI-2016-1382

Method to find the minimum 1D linear gradient model for seismic tomography

Tatyana A. Smaglichenko
, Ingi T. Bjarnason
, Alexander V. Smaglichenko
, Wolfgang R. Jacoby

University of Iceland

Research output: Contribution to journal › Article › peer-review

Abstract

The changes in the state of a geophysical medium before a strong earthquake can be found by studying of 3D seismic velocity images constructed for consecutive time windows. A preliminary step is to see changes with time in a minimum 1D model. In this paper we develop a method that finds the parameters of the minimum linear gradient model by applying a twodimensional Taylor series of the observed data for the seismic ray and by performing least-square minimization for all seismic rays. This allows us to obtain the mean value of the discrete observed variable, close to zero value.

Original language	English
Pages (from-to)	211-217
Number of pages	7
Journal	Fundamenta Informaticae
Volume	146
Issue number	2
DOIs	https://doi.org/10.3233/FI-2016-1382
Publication status	Published - 13 Sept 2016

Other keywords

Jarðskjálftamælingar
Jarðskjálftar
Líkön
linear gradient of velocity
local earthquake tomography
minimum 1D model

Access to Document

10.3233/FI-2016-1382

https://hdl.handle.net/20.500.11815/2543

Cite this

@article{ef3df44a88714e9fa815086504cd7773,

title = "Method to find the minimum 1D linear gradient model for seismic tomography",

abstract = "The changes in the state of a geophysical medium before a strong earthquake can be found by studying of 3D seismic velocity images constructed for consecutive time windows. A preliminary step is to see changes with time in a minimum 1D model. In this paper we develop a method that finds the parameters of the minimum linear gradient model by applying a twodimensional Taylor series of the observed data for the seismic ray and by performing least-square minimization for all seismic rays. This allows us to obtain the mean value of the discrete observed variable, close to zero value.",

keywords = "Jar{\dh}skj{\'a}lftam{\ae}lingar, Jar{\dh}skj{\'a}lftar, Linear gradient of velocity, Local earthquake tomography, L{\'i}k{\"o}n, Minimum 1D model, Jar{\dh}skj{\'a}lftam{\ae}lingar, Jar{\dh}skj{\'a}lftar, L{\'i}k{\"o}n, linear gradient of velocity, local earthquake tomography, minimum 1D model",

author = "Smaglichenko, \{Tatyana A.\} and Bjarnason, \{Ingi T.\} and Smaglichenko, \{Alexander V.\} and Jacoby, \{Wolfgang R.\}",

year = "2016",

month = sep,

day = "13",

doi = "10.3233/FI-2016-1382",

language = "English",

volume = "146",

pages = "211--217",

journal = "Fundamenta Informaticae",

issn = "0169-2968",

publisher = "SAGE Publications Ltd",

number = "2",

}

TY - JOUR

T1 - Method to find the minimum 1D linear gradient model for seismic tomography

AU - Smaglichenko, Tatyana A.

AU - Bjarnason, Ingi T.

AU - Smaglichenko, Alexander V.

AU - Jacoby, Wolfgang R.

PY - 2016/9/13

Y1 - 2016/9/13

N2 - The changes in the state of a geophysical medium before a strong earthquake can be found by studying of 3D seismic velocity images constructed for consecutive time windows. A preliminary step is to see changes with time in a minimum 1D model. In this paper we develop a method that finds the parameters of the minimum linear gradient model by applying a twodimensional Taylor series of the observed data for the seismic ray and by performing least-square minimization for all seismic rays. This allows us to obtain the mean value of the discrete observed variable, close to zero value.

AB - The changes in the state of a geophysical medium before a strong earthquake can be found by studying of 3D seismic velocity images constructed for consecutive time windows. A preliminary step is to see changes with time in a minimum 1D model. In this paper we develop a method that finds the parameters of the minimum linear gradient model by applying a twodimensional Taylor series of the observed data for the seismic ray and by performing least-square minimization for all seismic rays. This allows us to obtain the mean value of the discrete observed variable, close to zero value.

KW - Jarðskjálftamælingar

KW - Jarðskjálftar

KW - Linear gradient of velocity

KW - Local earthquake tomography

KW - Líkön

KW - Minimum 1D model

KW - Jarðskjálftamælingar

KW - Jarðskjálftar

KW - Líkön

KW - linear gradient of velocity

KW - local earthquake tomography

KW - minimum 1D model

UR - https://www.scopus.com/pages/publications/84988591889

U2 - 10.3233/FI-2016-1382

DO - 10.3233/FI-2016-1382

M3 - Article

SN - 0169-2968

VL - 146

SP - 211

EP - 217

JO - Fundamenta Informaticae

JF - Fundamenta Informaticae

IS - 2

ER -

Method to find the minimum 1D linear gradient model for seismic tomography

Abstract

Other keywords

Access to Document

Fingerprint

Cite this