Two-dimensional frequency-domain visco-elastic full waveform inversion: Parallel algorithms, optimization and performance

Full waveform inversion (FWI) is an appealing seismic data-fitting procedure for the derivation of high-resolution quantitative models of the subsurface at various scales. Full modelling and inversion of visco-elastic waves from multiple seismic sources allow for the recovering of different physical...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computers & geosciences Jg. 37; H. 4; S. 444 - 455
1. Verfasser: Brossier, R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.04.2011
Elsevier
Schlagworte:
Algorithms
Applied geophysics
Computation
computers
Distributed memory
Earth Sciences
Earth, ocean, space
equations
Exact sciences and technology
Finite element discontinuous Galerkin
Forward problem
Geomorphology
image analysis
Imaging
Internal geophysics
Inversions
Massively parallel computing
Mathematical models
Multi-parameter seismic imaging
Quasi-Newton optimization
Sciences of the Universe
Seismic phenomena
Seismic wave modelling
system optimization
Viscoelasticity
Asia
Japan
Nankai Trough
Pacific Ocean
Far East
Northwest Pacific
North Pacific
Finite element discontinuous Galerkin
Quasi-Newton optimization
Multi-parameter seismic imaging
Massively parallel computing
Seismic wave modelling
algorithms
global
elastic waves
frequency
modern
optimization
seismic sources
viscoelasticity
performances
computers
high resolution
seismic waves
models
inverse problem
interfaces
elastic media
data processing
P-waves
finite element analysis
Galerkin method
waveforms
petroleum exploration
discretization
ISSN:0098-3004, 1873-7803
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Full waveform inversion (FWI) is an appealing seismic data-fitting procedure for the derivation of high-resolution quantitative models of the subsurface at various scales. Full modelling and inversion of visco-elastic waves from multiple seismic sources allow for the recovering of different physical parameters, although they remain computationally challenging tasks. An efficient massively parallel, frequency-domain FWI algorithm is implemented here on large-scale distributed-memory platforms for imaging two-dimensional visco-elastic media. The resolution of the elastodynamic equations, as the forward problem of the inversion, is performed in the frequency domain on unstructured triangular meshes, using a low-order finite element discontinuous Galerkin method. The linear system resulting from discretization of the forward problem is solved with a parallel direct solver. The inverse problem, which is presented as a non-linear local optimization problem, is solved in parallel with a quasi-Newton method, and this allows for reliable estimation of multiple classes of visco-elastic parameters. Two levels of parallelism are implemented in the algorithm, based on message passing interfaces and multi-threading, for optimal use of computational time and the core-memory resources available on modern distributed-memory multi-core computational platforms. The algorithm allows for imaging of realistic targets at various scales, ranging from near-surface geotechnic applications to crustal-scale exploration.
Bibliographie:http://dx.doi.org/10.1016/j.cageo.2010.09.013
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:0098-3004
1873-7803
DOI:10.1016/j.cageo.2010.09.013