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Research Article · Open access · Published 27 February 2018

Real-Time Simulation Method Using Monte Carlo and Clustering Algorithms: A Case Study Covering Drill Bit Wear

Rodolfo Wilvert Reitz1 & Paulo José de Freitas Filho1

Journal of Computer Science, Volume 14, Issue 2, pp. 273–285 · doi.org/10.3844/jcssp.2018.273.285

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Abstract

Minimization of the cost of drilling an oil well is primarily achieved by reducing the operation completion time, which in turn can be achieved by increasing the Rate of Penetration (ROP). The ROP is the result of a combination of factors, such as lithological formation, operational parameters and bit wear. This paper addresses bit wear during drilling, using a method that combines a physical equation, techniques for risk analysis and data mining to estimate the behavior of bit wear per meter drilled. Experiments were conducted with real-world data to test the method’s validity and accuracy and the results demonstrated the relevancy of this approach.

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Reitz, R. W. & Filho, P. J. F. (2018). Real-Time Simulation Method Using Monte Carlo and Clustering Algorithms: A Case Study Covering Drill Bit Wear. Journal of Computer Science, 14(2), 273–285. https://doi.org/10.3844/jcssp.2018.273.285

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Real-Time Simulation Method Using Monte Carlo and Clustering Algorithms: A Case Study Covering Drill Bit WearJournal of Computer Science · Volume 14, Issue 2 · pp. 273–285 · CC BY 3.0Download