Estimation of Life Consumption for Advanced Drilling Tools

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Published Mar 26, 2021
Dustin Garvey Martin John Jörg Baumann

Abstract

Prognostics has the potential to be very valuable in many industries. This is especially the case in the petroleum industry where the costs of tool failure are extremely high and continue to increase. Previous attempts have been made to predict the remaining useful life of drilling tools. While the developed methods were shown to be able to accurately predict the remaining useful life, the data requirement was such that they had limited or no viability in "real world" operations. This paper builds on previous work in this area by developing a new life consumption estimation model that has been specifically designed to ensure that it can be viable in the "real world". The developed model was shown to be able to estimate the life consumed of an individual drilling tool to within 4-12% with uncertainties of ±15-35%.

How to Cite

Garvey, D., John, M., & Baumann, J. (2021). Estimation of Life Consumption for Advanced Drilling Tools. Annual Conference of the PHM Society, 1(1). Retrieved from https://papers.phmsociety.org/index.php/phmconf/article/view/1528
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Keywords

health monitoring, applications: industrial

References
(Brehme and Travix, 2008) J. Brehme and J. T. Travis (2008). Total BHA Reliability – An Improved Method to Measure Success, IADC/SPE 112644, Proceedings of the IADC/SPE Drilling Conference, Orlando, Florida.
(Efron and Tibshirani, 1994) B. Efron and R. J. Tibshirani (1994), An Introduction to the Boostrap, Monographs on Statistics and Applied Probability, Chapman & Hall/CRC.
(ExxonMobil, 2007) ExxonMobil (2007). ExxonMobil Announces Drilling of World- Record Well, Press Release: April 24, 2007.
(Fan and Gijbels, 1996) J. Fan and I. Gijbels (1996). Local Polynomial Modeling and Its Applications, Chapman & Hall/CRC, New York, NY.
(Garvey et al., 2009) D. R. Garvey, J. Baumann, J. Lehr, and J. W. Hines (2009). Pattern Recognition Based Remaining Useful Life Estimation of Bottom Hole Assembly T ools, SPE/IADC 118769, Proceedings of the 2009 SPE/IADC Drilling Conference and Exhibition, Amsterdam, The Netherlands.
(Hines et al., 2009) J. W. Hines, D. R. Garvey, R. Seibert, A. Usynin, and S. Arndt (2008), Technical Review of On-line Monitoring Techniques for Performance Assessment: Part II Theoretical Issues, NUREG/CR-6895, V ol. 2, United States Nuclear Regulatory Commission.
(Hines and Garvey, 2008) J. W. Hines and D. R. Garvey (2008). Nonparametric Model-Based Prognostics, Proceedings of the Annual Reliability and Maintainability Symposium, Las Vegas, NV.
(Tamhane and Dunlop, 2000) A. C. Tamhane and D. D. Dunlop (2000), Statistics and Data Analysis from Elementary to Intermediate, Prentice Hall, Upper Saddle River, NJ: 2000.
(Wand et al., 2006) P. Wand, M. Bible, and I. Silvester (2006). Risk-Based Reliability Engineering Enables Improved Rotary- Steerable-System Performance and Defines New Industry Performance Metrics, IADC/SPE 98150, Proceedings of the IADC/SPE Drilling Conference, Miami, Florida.
Section
Technical Research Papers