Research Article Open Access

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

Rodolfo Wilvert Reitz1 and Paulo José de Freitas Filho1
  • 1 Universidade Federal de Santa Catarina, Brazil

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.

Journal of Computer Science
Volume 14 No. 2, 2018, 273-285

DOI: https://doi.org/10.3844/jcssp.2018.273.285

Submitted On: 1 September 2017 Published On: 27 February 2018

How to Cite: 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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Keywords

  • Simulation
  • Monte Carlo
  • Risk Analysis
  • Drill Bit Wear
  • Clustering Algorithms