ABC for model selection and parameter estimation of drill-string bit-rock interaction models and stochastic stability. (17th March 2023)

• Record Type: Journal Article
• Authors: Castello, D.A.; Ritto, T.G.
• Is Part Of: Journal of sound and vibration. Volume 547(2023)
• Publication Date: 2023-03-17
• Subjects: Drill-string nonlinear dynamics -- Bit-rock interaction -- Stochastic inverse problem -- Experimental data -- Friction -- Finite element model; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2022.117537
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: The bit-rock interaction considerably affects the dynamics of a drill string, thus choosing a suitable model and identifying its parameters considering uncertainties is crucial. This paper proposes a procedure to estimate the parameters of four bit-rock interaction models, one of which is new, and at the same time select the most suitable model, given the available field data. The approximate Bayesian computation (ABC) is used for this purpose. An approximate posterior probability density function is obtained for the parameters of each model, which allows uncertainty to be analyzed. Furthermore, the impact of the uncertainties of the selected models on the torsional stability map (varying the nominal top drive angular speed and the weight on bit) of the system is evaluated. Highlights: Model calibration and selection are performed based on ABC. Stochastic stability maps are analyzed. The shift in the stability boundary represents a safety factor. Four bit-rock interaction models are analyzed. A new bit-rock interaction model is proposed.