‘If it is not grown, it is mined!’
Mining activity is an essential integral component of human civilisation. Since the earliest human settlements technology to discover, uncover and process rocks and minerals has been developing. These developments have been an essential underpinning of the growth, and some may say success of civilisation as we know it. Although mining endeavours have had a chequered history it remains an essential activity that will be part of our future forever. It is essential that we in the industry actively strive to develop and deploy technologies that will allow us to drive towards consistently and abundantly exceeding the triple bottom line targets for social, environmental, and economic outcomes.
The content provided here, is evolving, and will help the interested reader to gain deeper insights into the emergent developments in the mining industry in general, and to the particular areas we are engaged in more specifically.
The content is then summarised with a brief synopsis of the value that our approach can unleash.
The mining industry relies on a vast array of technologies and skills. Overtime the specific expertise has coalesced into different areas, often termed disciplines, which range across diverse fields such as social, natural and engineering sciences. All of these rely on using data of varying degrees of validity and abundance. In data technologies one of the key developments in the early nineteen seventies was the ability to effectively use scarce and spatially space grade data to generate estimates for predicting grades of mined blocks, this field was given the term Geostatistics.
The development and consequences of its implementation are considerable. A link to several seminal papers in this area can be found on the AUSIMM One Mine Portal. A key benefit was that it allowed not only for estimates to be made, but the calculation of the ‘error’ of the estimate was an inherent part of the mathematical technology. A natural consequence was that it became possible to classify the reliability of the estimate. A variety of frameworks now exist globally for the classification of Resources and Reserves.
The value and success of a mining project is however not only dependant on the grade of the deposit. The conception of a mining project as a highly evolved system with feedforward and feedback loops goes some way towards providing a framework to begin to understand how to best use, harness and realise the latent value that is inherent in mineral resources.
A description of the application of this approach to an underground mine showed that is it possible to integrate geostatistical simulation with process simulation to optimise drilling layouts. In building this model it also became apparent that the combination of spatial and temporal constraints in mining would prove to be highly challenging.
There are several alternative approaches to evaluating the risks, opportunities, and value of mining projects. The method selected is often selected based on the phase of the mining proiject development and the time available for investment decision making. To describe the benefits and limitations of these approaches an exercise that generated values for a project using simple to complex evaluation metrics was carried out. The Results are briefly described in the paper below.
An important finding of the comparison of the methodologies suggested that although simple methods may be easier to build, validate and understand, they cannot be used to explore how the interaction of project configuration and ore body characteristics impact on project risk, opportunity and value. There are several ways to generate spatial simulations of a variety of ore body characteristics. These can readily be used, in the right evaluation framework, to explore how high value irreversible project decisions can be enhanced through a betted understanding of ore body /process interactions.
The Primary-Response Framework for Geo-metallurgical Variables was developed as a taxonomy for describing variables used in the field of Geometallurgy. It’s usefulness lies in understanding valid and potentially invalid uses of different variables types.
We have spent several years developing an integrated evaluation approach for complex projects. The approach termed “Scenario based project evaluation” (SBPE) allows evaluation teams to collaborate, explore and quantify a variety of risks and opportunities in rich financial terms. The paper was awarded best paper by the AUSIMM.
A more in-depth coverage of the concepts of dealing with the challenges presented with uncertainty and variability that impacts on mining projects was provided in an APCOM publication – ‘Value Chain Modelling‘ in 2013.