Estimation of mechanical properties of rock using artificial intelligence

Authors

  • Laura Viviana Galvis Universidad Industrial de Santander (UIS)
  • César Augusto Ochoa
  • Henry Arguello Fuentes
  • Jenny Mabel Carvajal Jiménez
  • Zuly Himelda Calderón Carrillo

Keywords:

artificial intelligence, artificial neural network, genetic algorithm, petrophysical properties, mechanical properties.

Abstract

This paper discusses how two artificial intelligence techniques were combined, neural networks and genetic algorithms for the development of a computational tool used for the estimation of mechanical properties such as tensile strength, uniaxial compressive strength and triaxial compressive strength in sandstones, from petrophysical properties using data from tests of Rock Mechanics Laboratory of the Colombian Petroleum Institute - Ecopetrol SA as training data, to improve the design of non-destructive testing with some degree of confidence and resulting in cost reduction.

PACS: 91.60.Ba, 91.60.Dc

MSC: 82C32

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Author Biography

  • Laura Viviana Galvis, Universidad Industrial de Santander (UIS)
    Ingeniera de Sistemas e Informática, estudiante de Maestría en Ingeniera de Sistemas e Informatica.

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How to Cite

Galvis, L. V., Ochoa, C. A., Arguello Fuentes, H., Carvajal Jiménez, J. M., & Calderón Carrillo, Z. H. (2011). Estimation of mechanical properties of rock using artificial intelligence. Ingeniería Y Ciencia, 7(14), 83-103. https://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/430