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Modeling of drilling tool vibration in the process of drilling blast wells

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Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

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Authors:

V.S.Morkun, orcid.org/0000-0003-1506-9759, University of Bayreuth, Bayreuth, Federal Republic of Germany, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

N.V.Morkun, orcid.org/0000-0002-1261-1170, University of Bayreuth, Bayreuth, Federal Republic of Germany, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

S.М.Hryshchenko*, orcid.org/0000-0003-4957-0904, State Tax University, Irpin, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Ye.Ye.Bobrov, orcid.org/0000-0002-9275-3768, Kryvyi Rih National University, Kryvyi Rih, Ukraine

A.A.Haponenko, orcid.org/0000-0003-1128-5163, Kryvyi Rih National University, Kryvyi Rih, Ukraine

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 012 - 018

https://doi.org/10.33271/nvngu/2024-5/012

Abstract:

Purpose. To determine the characteristic features and model bit vibration during its interaction with rock in the process of drilling technical (blast) wells in open pit mines.

Methodology. The following methods were used in the work: analysis of scientific and practical solutions; statistical methods for processing the results of experimental studies; methods of analytical synthesis; computer modeling methods for synthesis and analysis of mathematical models.

Findings. The process of interaction between a drill bit and a rock was analyzed. The conditions and causes of vibration of drilling equipment are determined. The spectral analysis of the vibration signal, the formation and analysis of the map of the order of rotation of the rotating parts of the drilling rig during the drilling of technical (blast) wells were performed to identify the bit in the frequency domain of the measured concomitant integrated vibration signal as a source of high-amplitude vibration. The modulated signal measured in the time domain at the specified frequency carries information about the physical and mechanical characteristics of the drilled rock and the state of the bit. The analysis of the experimental studies and modeling of the process of interaction of the bit with the rock allows us to conclude that the obtained statistical indicators of the accompanying vibration signal really adequately characterize the process of well drilling.

Originality. A method for determining the characteristics of the interaction of a drill bit with rock in the process of drilling technical (blast) wells based on measuring the parameters of the accompanying vibration signal is proposed. The method differs from the known ones in the fact that in the process of changing the operating mode of the drive of the rotating parts of the drilling rig, an order map is formed over the entire range of its revolutions, the frequency of high-amplitude vibration of the bit is determined, which corresponds to a certain peak order of revolutions, and at this frequency the statistical parameters of changes are measured.

Practical value. This approach to the process of drilling wells in open pit mines makes it possible to quickly determine the physical and mechanical characteristics of the drilled rock and adjust the process parameters accordingly to increase its productivity and energy saving.

Keywords: mine working, well drilling, chisel, vibration, parameters, modeling

References.

1. Parimal, A. P., & Catalin, T. (2013). Model Development of Torsional Drillstring and Investigating Parametrically the Stick-Slips Influencing Factors. Journal of Energy Resources Technology, 135(1), 01310. https://doi.org/10.1115/1.4007915.

2. Du, K., & Wei, Z. (2022). Research on the optimization of a drilling rock breaking method based on fuzzy cluster analysis. Fluid Dynamics & Materials Processing, 18(3), 751-760. https://doi.org/10.32604/fdmp.2022.019577.

3. Wang, Y., Ni, H., Wang, R., & Liu, S. (2022). An improved model to characterize drill-string vibrations in rotary drilling applications. Fluid Dynamics & Materials Processing, 18(5), 1263-1273. https://doi.org/10.32604/fdmp.2022.020405.

4. Suriani bt Che Kar, S., Esat, I. I., Alkhamees, A. A., & Mohd Farid Woo, M. E. (2016). Drill string dynamic: Improving the drilling performance by study the resonance of the experimental drill string system using 2 contact points of friction force of breaking system. 2016 7^th International Conference on Mechanical and Aerospace Engineering (ICMAE), 175-179. https://doi.org/ 10.1109/ICMAE.2016.7549530.

5. Xu, Y., Zhang, H., & Guan, Z. (2021). Dynamic characteristics of downhole bit load and analysis of conversion efficiency of drill string vibration energy. Energies, 14(1), 229. https://doi.org/10.3390/en14010229.

6. Ghasemloonia, A., Rideout, D. G., & Butt, S. D. (2015). A review of drillstring vibration modeling and suppression methods. Journal of Petroleum Science and Engineering, 131, 150-164. https://doi.org/10.1016/j.petrol.2015.04.030.

7. Oktav, A. (2017). Advances in Noise and Vibration Analysis. In Arapgirlioğlu, H., Elliott, R. L., Turgeon, E., Atik, A. (Eds.). Researches on Science and Art in 21^st Century Turkey. Chapter: 332, (pp. 2988-2998). Gece Kitaplığı. Retrieved from https://www.researchgate.net/publication/321621659_Advances_in_Noise_and_Vibration_Analysis.

8. Babak, V., Beregun, V., & Krasilnikov, A. (2017). Methods and means of vibrodiagnostics of units of cogeneration installations. 11 International Conference NDT Days 2017, June 12-16, Sozopol, Bulgaria. Special Issue of e-Journal of Nondestructive Testing (eJNDT), 22(11). ISSN 1435-4934.

9. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Simulation of high-energy ultrasound propagation in heterogeneous medium using k-space method. Metallurgical and Mining Industry, 6(3), 23-27.

10. Morkun, V., & Morkun, N. (2018). Estimation of the crushed ore particles density in the pulp flow based on the dynamic effects of high-energy ultrasound. Archives of Acoustics, 43(1), 61-67. https://doi.org/10.24425/118080.

11. Babak, S. V. (2015). Statistical diagnostics of electrical equipment. Kyiv: Institute of Electrodynamics of the National Academy of Sciences of Ukraine. Retrieved from https://previous.ied.org.ua/files/mon5_2015.pdf.

12. Liu, X., Kou, H., Ma, X., & He, M. (2023). Investigation of the Rock-Breaking Mechanism of Drilling under Different Conditions Using Numerical Simulation. Applied Sciences, 13(20), 11389. https://doi.org/10.3390/app132011389.

13. Patil, P. A., & Teodoriu, C. (2013). Analysis of Bit–Rock Interaction During Stick–Slip Vibration Using PDC Cutting Force Model. OIL GAS European Magazine, 3, 124-129.

14. Egamberdiiev, І. P. (2019). Methods for assessing the technical condition of drilling rigs. Navoii: publishing house named after Alisher Navoii. ISBN 978-9943-5884-4-8.

15. Dukkipati, R. V., & Srinivas, J. (2010). Solving Engineering Mechanics Problems with MATLAB. UK: New Academic Science. ISBN: 9781781831731.

16. Dukkipati, R. V. (2014). MATLAB for Control System Engineers. UK: New Academic Science Limited. ISBN: 9781781830062.

17. Franca, L. F. P. (2011). Drilling Action of Roller-Cone Bits: Modeling and Experimental Validation. ASME. Journal of Energy Resources Technology, 132(4), 043101. https://doi.org/10.1115/1.4003168.

18. Flegner, P., Kaˇcur, J., Durdán, M., & Laciak, M. (2022). Evaluation of the Acceleration Vibration Signal for Aggregates of the Horizontal Drilling Stand. Applied Sciences, 12, 3984. https://doi.org/10.3390/app12083984.

19. Kumar, S., Lokesha, M., Kumar, K., & Srinivas, K. (2018). Vibration based Fault Diagnosis Techniques for Rotating Mechanical Components: Review Paper. IOP Conference Series: Materials Science and Engineering, 376, 012109. https://doi.org/10.1088/1757-899X/376/1/012109.

20. Porkuian, O., Morkun, V., Morkun, N., & Serdyuk, O. (2019). Predictive Control of the Iron Ore Beneficiation Process Based on the Hammerstein Hybrid Model. Acta Mechanica et Automatica, 13(4), 262-270. https://doi.org/10.2478/ama-2019-0036.

21. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Simulation of the Lamb waves propagation on the plate which contacts with gas containing iron ore pulp in Waveform Revealer toolbox. Metallurgical and Mining Industry, 6(5), 15-18.

22. Jia, G., Guo, F., Wu, Z., Cui, S., & Yang, J. (2023). A noise reduction method for multiple signals combining computed order tracking based on chirplet path pursuit and distributed compressed sensing. Structural Durability & Health Monitoring, 17(5), 383-405. https://doi.org/10.32604/sdhm.2023.026885.

23. Wang, K. S., & Heyns, P. S. (2011). Application of computed order tracking, Vold-Kalman filtering and EMD in rotating machine vibration. Mechanical Systems and Signal Processing, 25(2), 416-430. https://doi.org/10.1016/j.ymssp.2010.09.003.

24. Wang, T., Zhang, L., Qiao, H., & Wang, P. (2020). Fault diagnosis of rotating machinery under time-varying speed based on order tracking and deep learning. Journal of Vibroengineering, 22(2), 366-382. https://doi.org/10.21595/jve.2019.20784.

25. Borghesani, P., Pennacchi, S., Chatterton, R., & Ricci, R. (2014). The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery. Mechanical Systems and Signal Processing, 44(1-2), 118-133. https://doi.org/10.1016/j.ymssp.2013.03.026.

26. Brandt, A. (2011). Noise and Vibration Analysis: Signal Analysis and Experimental Procedures. Chichester, UK: John Wiley & Sons.

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