Estimation of mechanical properties of rock using artificial intelligence
This article presents the way two artificial intelligence techniques, neural networks and genetic algorithms were combined, for the development of a computational tool used to estimate mechanical properties such as tensile strength, uniaxial compression resistance and resistance to triaxial compress...
- Autores:
-
Galvis, Laura Viviana
Augusto Ochoa, César
Arguello Fuentes, Henry
Carvajal Jiménez, Jenny Mabel
Calderón Carrillo, Zuly Himelda
- Tipo de recurso:
- Fecha de publicación:
- 2011
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- spa
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/14465
- Acceso en línea:
- http://hdl.handle.net/10784/14465
- Palabra clave:
- Artificial Intelligence
Artificial Neural Network
Genetic Algorithm
Petrophysical Properties
Mechanical Properties
Inteligencia Artificial
Red Neuronal Artificial
Algoritmo Genético
Propiedades Petrofísicas
Propiedades Mecánicas
- Rights
- License
- Acceso abierto
| Summary: | This article presents the way two artificial intelligence techniques, neural networks and genetic algorithms were combined, for the development of a computational tool used to estimate mechanical properties such as tensile strength, uniaxial compression resistance and resistance to triaxial compression in sandstones, from petrophysical properties using test data from the Rock Mechanics Laboratory of the Colombian Petroleum Institute - Ecopetrol SA as training data facilitating the design of non-destructive tests with a certain degree of confidence and leading to cost reduction. |
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