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. The method discriminated layers...
- Autores:
-
Castaño, Kelyn Paola
Ojeda, Germán
Montes, Luis
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2011
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/39240
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/39240
http://bdigital.unal.edu.co/29337/
- Palabra clave:
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | 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. 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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