Advanced prognostic technique for improving the drilling performance of downhole tools

Modern drilling equipment faces increasingly severe environments, with bottom hole temperatures excessing 200°C and high vibration stresses. Meanwhile, customers continuously demand high reliability to prevent bottom hole failures, which result in one half or two days of nonproductive time (NPT) on drilling rigs costing $100K-$1M per day [1]. However, the current periodic maintenance strategy is insufficient and costly to meet the new challenges. From a cost-effective perspective, developing a conditional-based maintenance (CBM) prognostic model to evaluate the health condition of bottom hole assembly (BHA) tools becomes important and necessary for the oil and gas industry. This paper presents a CBM prognostic model for assessing the life consumption (LC) of BHA tools. Based on the analysis of physics of failure (PoF) [2], there are four major impacts on electronics reliability, i.e., lateral vibration (LV), stick slip (STI), temperature (TEMP), and axial vibration (AX) [1][2]. The CBM prognostic model described in this paper is acumulative damage model with weibull distribution, which is a linear regression model synthesizing the four impacts. To estimate the parameters of the model, the maximum likelihood estimation (MLE) is utilized. The confidence interval and the Fisher information matrix theories are applied to assess the LC intervals of the tools. The developed model will allow service providers to make more efficient decisions to reduce operation cost and increase downholoe tool availability and reliability.