Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications

Research output: Contribution to journalArticleResearchpeer-review

Authors

  • Juan Navarro
  • José A. Sanchidrián
  • Pablo Segarra
  • Paulo Couceiro
  • Peter Schimek
  • Clara Godoy

External Organisational units

  • Maxam
  • Universidad Politécnica de Madrid
  • VA Erzberg GmbH

Abstract

Blasting performance is influenced by mechanical and structural properties of the rock, on one side, and blast design parameters
on the other. This paper describes a new methodology to assess rock mass quality from drill-monitoring data to guide
blasting in open pit operations. Principal component analysis has been used to combine measurement while drilling (MWD)
information from two drill rigs; corrections of the MWD parameters to minimize external influences other than the rock
mass have been applied. First, a Structural factor has been developed to classify the rock condition in three classes (massive,
fractured and heavily fractured). From it, a structural block model has been developed to simplify the recognition of
rock classes. Video recording of the inner wall of 256 blastholes has been used to calibrate the results obtained. Secondly, a
combined strength-grade factor has been obtained based on the analysis of the rock type description and strength properties
from geology reports, assaying of drilling chips (ore/waste identification) and 3D unmanned aerial vehicle reconstructions
of the post-blast bench face. Data from 302 blastholes, comprised of 26 blasts, have been used for this analysis. From the
results, four categories have been identified: soft-waste, hard-waste, transition zone and hard-ore. The model determines
zones of soft and hard waste rock (schisted sandstone and limestone, respectively), and hard ore zones (siderite rock type).
Finally, the structural block model has been combined with the strength-grade factor in an overall rock factor. This factor,
exclusively obtained from drill monitoring data, can provide an automatic assessment of rock structure, strength, and waste/
ore identification.

Details

Original languageEnglish
Pages (from-to)3209-3228
Number of pages20
JournalRock mechanics and rock engineering
Volume54.2021
Issue numberJune
DOIs
Publication statusPublished - 17 Apr 2021