Failures associated with drillstring vibration continue to occur, despite the use of risk quantification techniques based on vibration intensities and root mean square (RMS) accelerations. This paper introduces the concept of modified vibration stability plot as a practical tool to minimize and predict vibration. It integrates the modified vibration stability plot with a feature modeling data analysis tool to predict drillstring failures caused by torsional and lateral vibration.

The modified stability plot provides optimum operating parameters, including weight on bit (WOB), revolutions per minute (RPM), and rate of penetration (ROP), to minimize vibration. However, actual real-time drilling parameters are not always optimum. Consequently, the deviation of real-time parameters from the optimum values are used to calculate "deviation vectors" using statistical tools. These are then used to generate operating stability clusters to detect outliers in the drilling data that signify potential vibration events. Safe operating limits and operating times have been proposed by integrating the clustering technique with vibration risk index and cumulative vibration intensity plots to mitigate failures. The workflow has been applied to cases in which severe and moderate vibrations were encountered downhole and at the surface, respectively. Extensive simulations were performed to compare the data from downhole vibration sensors. The results show that the workflow closely predicts the occurrence of sustained vibrations before an actual downhole string failure event. Prolonged operations outside of the stability circle can cause failures, depending on the fatigue strength of the material. The occurrence of outliers outside of the stability clusters are calibrated with actual drillstring failures to correlate cumulative vibration intensity plots with the time duration of a vibration event. This calculation helps to define a vibration risk index that can trigger decisions to stop drilling or to change operating parameters before a failure occurs. The workflow also simultaneously predicts the dominant type of vibration in the system and in causing failures. The study concludes by providing guidelines to integrate the vibration stability chart with data analytics and explicates the significance of a statistics-based risk index to initiate real-time procedures to prevent drillstring integrity failure.

The workflow proposed and validated with case histories strives toward cost-effectiveness and increased productivity. This paper also implements data-driven techniques for risk quantification. The results and the method for determining a risk index and operational limits are robust, and can be applied as a starting point for other string configurations in similar downhole environments.

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