Abstract
Timely and accurate anomaly detection is of great importance for the safe operation of the drilling process. To detect bit bounce during the drilling process, this paper proposes a method based on interval augmentation Mahalanobis distance. The method first selects process variables that are closely related to bit bounce through mechanism analysis; secondly, data augmentation is performed on the selected data; then, the Mahalanobis distance statistic of normal data is calculated and its distribution threshold is designed using the Kernel Density Estimation method; finally, the Mahalanobis distance is calculated for the augmented online data and compared to the threshold to determine if a bit bounce is present.
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Acknowledgements
This work was supported by the Knowledge Innovation Program of Wuhan-Shuguang Project under Grant No. 2022010801020208, the Natural Science Foundation of Hubei Province, China, under Grant 2020CFA031.
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Hu, B., Hu, W., Zhang, P., Cao, W. (2023). Anomaly Detection and Alarm Limit Design for In-Hole Bit Bounce Based on Interval Augmented Mahalanobis Distance. In: Zhang, H., et al. International Conference on Neural Computing for Advanced Applications. NCAA 2023. Communications in Computer and Information Science, vol 1870. Springer, Singapore. https://doi.org/10.1007/978-981-99-5847-4_39
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DOI: https://doi.org/10.1007/978-981-99-5847-4_39
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