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Wear Prediction of Rock Drill Bits Based on Geomechanical Properties of Rocks

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Abstract

The excavation of rock, whether in mining, petroleum, or civil engineering projects, predominantly relies on traditional drilling techniques. Across these applications, drilling bit wear considered as a primary factor impacting the overall cost of rock excavation projects. This wear of drill bits is directly linked to the properties of the rock being drilled. In this study, an investigated relations between drilling bit wear and geomechanical properties have been investigated. To measure drill bit wear, a laboratory-scale drilling rig was employed, based on 30 selected rock units. A comprehensive laboratory testing plan was executed on these rock units, encompassing various rock characteristics such as uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), Cerchar abrasivity index (CAI), equivalent quartz content (EQC), grain size of minerals (GS), and Schmidt rebound number (SRN). Nonlinear regression techniques were employed to predict bit wear based on geomechanical rock properties. Performance evaluation criteria were used to validate the regression models. The results revealed an exponential increase in bit wear values with rising UCS, BTS, CAI, EQC, GS, and SRN. The statistical analysis indicated a strong correlation between rock characteristics and drill bit wear, with CAI emerging as the most influential parameter, having a correlation coefficient of R2 = 0.954. The regression models developed in this study are primarily intended for rock engineers engaged in rock drilling projects.

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Data Availability

The data that support the findings of this study are available from the corresponding author upon request.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Mining Engineering, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Hamid Kalhori & Raheb Bagherpour

  2. Department of Surface Mining and International Mining, Institute of Mining, Clausthal University of Technology, 38678, Clausthal-Zellerfeld, Germany

    Hossein Tudeshki

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  1. Hamid Kalhori
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by HK and RB. The first draft of the manuscript was written by HT and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Raheb Bagherpour.

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Kalhori, H., Bagherpour, R. & Tudeshki, H. Wear Prediction of Rock Drill Bits Based on Geomechanical Properties of Rocks. Arab J Sci Eng (2023). https://doi.org/10.1007/s13369-023-08598-8

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