Estimation of Bourgoyne and Young Model coefficients using Markov Chain Monte Carlo simulation

The Bourgoyne and Young Model (BYM) is used to determine the rate of penetration in oil well drilling processes. To achieve this the model must be parameterized with coefficients that are estimated on the basis of prior experience. Since drilling is a physical process, measurement data may include noise and the model may naturally fail to represent it correctly. In this study the BYM coefficients are determined in the form of probability distributions, rather than fixed values, propagating the uncertainties present in the data and the model itself. This paper therefore describes a probabilistic model and Bayesian inference conducted using Markov Chain Monte Carlo. The results were satisfactory and the probability distributions obtained offer improved insight into the influence of different coefficients on the simulation results.

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