Abstract
AbstractVibro-impact drilling has shown huge potential of delivering better rate of penetration, improved tools lifespan and better borehole stability. However, being resonantly instigated, the technique requires a continuous and quantitative characterisation of drill-bit encountered rock materials in order to maintain optimal drilling performance. The present paper introduces a non-conventional method for downhole rock characterisation using measurable impact dynamics and machine learning algorithms. An impacting system that mimics bit-rock impact actions is employed in this present study, and various multistable responses of the system have been simulated and investigated. Features from measurable drill-bit acceleration signals were integrated with operated system parameters and machine learning methods to develop intelligent models capable of quantitatively characterising downhole rock strength. Multilayer perceptron, support vector regression and Gaussian process regression networks have been explored. Based on the performance analysis, the multilayer perceptron networks showed the highest potential for the real-time quantitative rock characterisation using considered acceleration features.
Funder
Petroleum Technology Development Fund
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Applied Mathematics,Mechanical Engineering,Ocean Engineering,Aerospace Engineering,Control and Systems Engineering
Reference75 articles.
1. Conglin, X.: Growth of US upstream spending to decelerate in 2019. https://www.ogj.com/home/article/17222793/growth-of-us-upstream-spending-to-decelerate-in-2019, 2019. Accessed: 2021-04-19
2. Franca, L.F.P.: A bit-rock interaction model for rotary-percussive drilling. Int. J. Rock Mech. Min. Sci. 48(5), 827–835 (2011)
3. Powell, S., Garcia, A., Barocio, H., Alonso, A.: Percussion drilling system combined with hybrid pdc bit increases rop and interval drilled on taoudenni basin well in mauritania. In: SPE/IADC Drilling Conference and Exhibition. OnePetro (2015)
4. Melamed, Y., Kiselev, A., Gelfgat, M., Dreesen, D., Blacic, J.: Hydraulic hammer drilling technology: developments and capabilities. J. Energy Resour. Technol. 122(1), 1–7 (2000)
5. Pyles, H.G., Albright, C.D., Haun, R.E.: Universal drilling machine, September 16 1969. US Patent 3,467,207
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