Influence of Static and Dynamic Rock Properties on Drillability Prognosis for Mining and Tunnelling Projects

• Published in: Indian Geotechnical Journal Vol. 52; no. 4; pp. 765 - 779
• Main Authors: Siva Prasad, B. N. V., Murthy, V. M. S. R., Naik, Sripad R.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.08.2022; Springer Nature B.V
• Subjects: Developing countries; Dredging; Drilling; Engineering; Excavation; Foundations; Geoengineering; Hydraulics; Hydroelectric power; LDCs; Mechanical properties; Mountains; Multilayer perceptrons; Neural networks; Original Paper; Penetration; Prognosis; Project feasibility; Quartz; Rock masses; Rock properties; Rocks; Tunnels; Underground mines; Bhutan; Multi-layer perceptron neural network; Penetration rate; Physico-mechanical properties; Hard rocks; Multivariate regression
• ISSN: 0971-9555; 2277-3347
• DOI: 10.1007/s40098-022-00608-0

Land scarcity for infrastructure development and mining in developing nations such as India and Bhutan call for the adoption of effective underground space utilization techniques. Excavation rates, in tunnels from hydroelectric projects and development headings of underground mines implementing drill and blast methodology, need to be geared up to keep pace with the developmental requirements. Such excavations demand extensive drilling lengths, and realistic prediction of rock drillability is highly essential for determining the progress vis-à-vis feasibility of such excavation projects. Rock drillability investigations were taken up in this study covering a stretch of about 7 km of Indian Aravalli hills and Bhutan Himalayan mountains covering 15 rock variants. Prior research has indicated that several physico-mechanical properties of the rock play a crucial role in drillability assessment. Multilayer perceptron neural network indicated that quartz content (QC) and rock strength factor (RSF) predominantly influence penetration rates. A drillability prognosis model was developed that could explain the variance in laboratory penetration rate (LPR) up to 82.7% signifying a high level of correlation. Both QC and RSF were found to have negative relationships with LPR. It is inferred that the developed model is applicable for the rocks having quartz content varying from 30.0 to 96.0%, RSF from 35.8 to 74.0 MPa, and alternatively UCS and BTS values ranging from 65 to 142 MPa and 2.6 to 18.8 MPa, respectively. Correlations indicated that LPR could be a potential indicator of expected field penetration rate when there is little information about the rock mass parameters. Graphical Abstract