Bayesian approach to identify the bit-rock interaction parameters of a drill-string dynamical model

A drill string is a slender structure used to search for oil and gas. Many works have tackled the problem of modeling the drill-string dynamics in a vertical well. One important aspect in this dynamics is the bit-rock interaction, and, therefore, an identification of the parameters of the bit-rock interaction model becomes crucial. Few works related to this identification problem have been published. The present paper applies the Bayesian approach to identify the parameters of the bit-rock interaction model considering a simplified drill-string dynamical model which takes into account only torsional vibrations. It is assumed an additive Gaussian noise model, and the Metropolis-Hasting algorithm is used to approximate the posterior distribution of the variables analyzed.