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Conference Papers Year : 2010

Stochastic identification using the maximum likelihood method and a statistical reduction: application to drilling dynamics

Abstract

A drill-string is a slender structure that drills rock to search for oil. The nonlinear interaction between the bit and the rock is of great importance for the drill-string dynamics. The interaction model has uncertainties, which are modeled using the nonparametric probabilistic approach. This paper deals with a procedure to perform the identification of the dispersion parameter of the probabilistic model of uncertainties of a bit-rock interaction model. The bit-rock interaction model is represented by a nonlinear constitutive equation, and the identification of the parameter of this probabilistic model is carried out using the Maximum Likelihood method together with a statistical reduction in the frequency domain using the Principal Component Analysis.
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Dates and versions

hal-00692970 , version 1 (01-05-2012)

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  • HAL Id : hal-00692970 , version 1

Cite

T.G. Ritto, Christian Soize, R. Sampaio. Stochastic identification using the maximum likelihood method and a statistical reduction: application to drilling dynamics. MECOM 2010 (IX Argentinean Congress on Computational Mechanics y II South American Congress on Computational Mechanics) and CILAMCE 2010 (XXXI Iberian-Latin-American Congress on Computational Methods in Engineering), Nov 2010, Buenos Aires, Argentina. pp.ISSN 1666-6070, Pages: 1-11. ⟨hal-00692970⟩
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