Abstract:

The energy required to excavate or breakdown a unit volume of rock (‘specific energy’) can be estimated from instrumented rotary blast hole drills. Specific energy data have traditionally been used as part of mine-to-mill optimization programs to estimate rock ‘hardness’ for:

Optimization of blast hole loading to reflect rock hardness within a blast pattern.
Optimize energy consumption during ore milling/crushing by blending ore of a range of hardness.

Since 2016, BGC Engineering Inc. has be re-purposing available specific energy measurements in open pit mines to support ongoing geotechnical assessments, specifically:

Mapping and projection of significant faults intersected by the pit excavations. These faults represent key controls on pit slope stability. Faults and fault damage zones of certain scales can be readily identified from specific energy data.
Indifitication of weak rock mass zones that may have poor bench scale performance or contribute to inter-ramp scale slope instability. These zones may be identified as blast holes are advanced bench-by-bench or through targeted prob hole drilling.
Interpreting boundaries between displaced or disturbed rock masses and undisturbed rock masses. The identification of these displaced rock mass zones, often through previous slope instability, permit mine plans to be updated to excavate out these poor-quality zones and reduce the likelihood of leaving unstable material in the excavation face.

In this paper we provide three case studies from operating mines illustrating the application of specific energy data to geotechnical assessments in open pit mines. Through the case studies we outline important considerations with data reliability, data resolution, data processing, and software tools that permit the maximum value to be extracted from these data. Examples of combining the specific energy data with other datasets, such as: photogrammetric mapping, core logging, and traditional bench mapping, are highlighted in each case study. Limitations of the data and common issues with the data that require detailed review as part of quality assurance are discussed.

Menu

Ian Stilwell