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Method for the Interpretation of RMR Variability Using Gaussian Simulation to Reduce the Uncertainty in Estimations of Geomechanical Models of Underground Mines

  • Juliet Rodriguez-Vilca
  • Jose Paucar-Vilcañaupa
  • Humberto Pehovaz-Alvarez
  • Carlos RaymundoEmail author
  • Nestor Mamani-Macedo
  • Javier M. Moguerza
Conference paper
  • 7 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1209)

Abstract

The application of conventional techniques, such as kriging, to model rock mass is limited because rock mass spatial variability and heterogeneity are not considered in such techniques. In this context, as an alternative solution, the application of the Gaussian simulation technique to simulate rock mass spatial heterogeneity based on the rock mass rating (RMR) classification is proposed. This research proposes a methodology that includes a variographic analysis of the RMR in different directions to determine its anisotropic behavior. In the case study of an underground deposit in Peru, the geomechanical record data compiled in the field were used. A total of 10 simulations were conducted, with approximately 6 million values for each simulation. These were calculated, verified, and an absolute mean error of only 3.82% was estimated. It is acceptable when compared with the value of 22.15% obtained with kriging.

Keywords

Gaussian simulation Uncertainty analysis Geostatistics Geomechanical uncertainty RMR 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Juliet Rodriguez-Vilca
    • 1
  • Jose Paucar-Vilcañaupa
    • 1
  • Humberto Pehovaz-Alvarez
    • 1
  • Carlos Raymundo
    • 2
    Email author
  • Nestor Mamani-Macedo
    • 2
  • Javier M. Moguerza
    • 3
  1. 1.Ingeniería de Gestión Minera, Universidad Peruana de Ciencias AplicadasLimaPeru
  2. 2.Dirección de Investigación, Universidad Peruana de Ciencias AplicadasLimaPeru
  3. 3.Escuela Superior de Ingeniería Informática, Universidad Rey Juan CarlosMadridSpain

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