Thin-layer detection using spectral inversion and a genetic algorithm

Spectral inversion using a genetic algorithm (GA) as an optimisation approach was used for increasing the seismic resolution of a particular dataset; by contrast with the conjugate gradient method, a GA does not require a good starting model but rather a search space.<br />The method d...

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Main Authors: Castaño Kelyn Paola, Ojeda Germán, Montes Luis
Format: Article
Language:English
Published: Universidad Nacional de Colombia 2011-12-01
Series:Earth Sciences Research Journal
Online Access:http://www.revistas.unal.edu.co/index.php/esrj/article/view/27716
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author Castaño Kelyn Paola
Ojeda Germán
Montes Luis
author_facet Castaño Kelyn Paola
Ojeda Germán
Montes Luis
author_sort Castaño Kelyn Paola
collection DOAJ
description Spectral inversion using a genetic algorithm (GA) as an optimisation approach was used for increasing the seismic resolution of a particular dataset; by contrast with the conjugate gradient method, a GA does not require a good starting model but rather a search space.<br />The method discriminated layers thinner than λ/8 when tested on synthetic and log data. When applied to a seismic dataset concerning the Barco formation in the Catatumbo basin, Colombia, spectral inversion led to recovering information from seismic data contributing towards the vertical identification of geological features such as thin distributary channels deposited in a deltaic environment having a tidal influence. The results revealed that a GA outperformed traditional minimisation schemes.
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series Earth Sciences Research Journal
spelling doaj-art-af3ee29ab5494a619685b2b5459e8bf92025-08-20T02:28:59ZengUniversidad Nacional de ColombiaEarth Sciences Research Journal1794-61902011-12-01152121128Thin-layer detection using spectral inversion and a genetic algorithmCastaño Kelyn PaolaOjeda GermánMontes LuisSpectral inversion using a genetic algorithm (GA) as an optimisation approach was used for increasing the seismic resolution of a particular dataset; by contrast with the conjugate gradient method, a GA does not require a good starting model but rather a search space.<br />The method discriminated layers thinner than λ/8 when tested on synthetic and log data. When applied to a seismic dataset concerning the Barco formation in the Catatumbo basin, Colombia, spectral inversion led to recovering information from seismic data contributing towards the vertical identification of geological features such as thin distributary channels deposited in a deltaic environment having a tidal influence. The results revealed that a GA outperformed traditional minimisation schemes.http://www.revistas.unal.edu.co/index.php/esrj/article/view/27716
spellingShingle Castaño Kelyn Paola
Ojeda Germán
Montes Luis
Thin-layer detection using spectral inversion and a genetic algorithm
Earth Sciences Research Journal
title Thin-layer detection using spectral inversion and a genetic algorithm
title_full Thin-layer detection using spectral inversion and a genetic algorithm
title_fullStr Thin-layer detection using spectral inversion and a genetic algorithm
title_full_unstemmed Thin-layer detection using spectral inversion and a genetic algorithm
title_short Thin-layer detection using spectral inversion and a genetic algorithm
title_sort thin layer detection using spectral inversion and a genetic algorithm
url http://www.revistas.unal.edu.co/index.php/esrj/article/view/27716
work_keys_str_mv AT castanokelynpaola thinlayerdetectionusingspectralinversionandageneticalgorithm
AT ojedagerman thinlayerdetectionusingspectralinversionandageneticalgorithm
AT montesluis thinlayerdetectionusingspectralinversionandageneticalgorithm