Continuing global population increase and industrialisation provides major new challenges for the maintenance of supply of both energy and essential metals such as copper. Since the 1980s, however, the number of new metal discoveries has fallen substantially and it is almost certain that future copper deposit discoveries will be made at depths beyond the technical and financial limits of even super-pit mining.
Very deep underground super-cave mining at depths of > 2000m from the surface is therefore necessarily becoming the preferred and most capital efficient way forward for metal production from large-scale disseminated and generally low average grade mineral deposits. Such deep development brings with it increasing cost and risk, triggering a consensus amongst major mining companies that deep cave mining practice needs to be rapidly transformed in order to develop productive, safe, low-cost and profitable mass underground mining options and maintenance of supply of strategic metals into the future.
The ability to identify and quantify the huge technical and financial risks inherent in billion dollar mine design decisions ultimately depends on the quality of geoscientific data that have been collected. Geoscientific risks and their related mining uncertainties are the fundamental determinants of how caving will progress over the multi-decade life of a mine and the failure to properly use presently available data, let alone data that can be collected but aren’t, is a major failing of present practice. The challenges that arise for mining engineers and applied scientists include definition of the technologies needed to “accurately” characterise an ore deposit and its critical rock properties. Many of the questions are common to petroleum reservoir development. For example, what techniques are available to confidently characterise the deposit volume between drill holes, how may the viability of deep deposits be fully evaluated faster and what data management and 3D visualisation systems are required to forward model large scale rock mass properties in order to support high risk decision making?