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AIG QLD Technical TalkIdentifying and Quantifying Uncertainty Inherent in Mineral Resource EstimatesPresenter: Andrew Waltho (Independent Consultant) Uncertainty is inherent in all mineral resource estimates. Geoscientists engaged in resource estimation and mineral resource development have a responsibility to:
Uncertainty management begins with ensuring the quality of data used in geological interpretation and resource estimation. This includes both quality assurance of fundamental drilling and assay data. Data inconsistency is a major source of uncertainty that geologists could limit, if not eliminate. Interpretations of sub-surface geological features are the product of limited observations. Maximising the value of data collected by drilling plays an important role in reducing the “degrees of freedom” available when interpreting how points of observation are connected in the uninformed space between points of observation provided by mapping and drilling. Rigorous data analysis is needed to understand relationships between data. A family of stochastic techniques are emerging that help to group data into domains exhibiting comparable characteristics to ensure the quality of the geological framework on which resource estimates must be based. Exploration drilling needs to assess both the scale and continuity of mineralisation at an early stage. Scale and grade are needed to establish economic potential, but continuity is essential to help determine the density of drilling required to provide required confidence in estimates and the amount of drilling required during different stages of project development. Stochastic techniques are receiving renewed attention as a means of understanding potential grade variability. There are also some exciting developments on the geological modelling front with the advent of techniques such as neural networks and radial landing algorithms being applied to geological modelling. These techniques are being marketed as tools for rapid geological model development. What isn’t being promoted is that all of these tools have a stochastic component that could be used to better understand uncertainty which, to date, is a lost opportunity and a situation that will only change when geoscientists engaged in resource evaluation declare a need for these tools. Understanding uncertainty generates large quantities of data that would test any desktop computer. Cloud computing offers access to computing resources able to deal with this situation and, at the same time, improve collaboration between geoscientists and other stakeholders in resource estimation and provide a means of quickly and effectively communicating information within an organisation. Zoom meeting detailsJoin from a PC, Mac, iPad, iPhone or Android device: |
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