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

Abstract

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.