Understanding of sampling distributions and their statistical properties is essential in translating models based on widely spaced data to a scale suitable for decision making. In the mining context, exploration and feasibility study data is often widely spaced and does not have the detail to derive accurate models of ore and waste for use in economic evaluation, Go/No-Go decision making and budgeting for the next stage of project development.
Initial decisions to proceed and budget for the next stage of evaluation are taken at the geological model or Inferred Mineral Resource stage which may have very wide sample spacing (boreholes). Where data of acceptable quality are available for early-stage projects, statistical methods exist to estimate the global characteristics of the mineral distribution. One of these characteristics is the quantity or proportion of material above specified economic cut-offs. These techniques cannot locate the exact positions of “ore” and “waste” but only give an indication of expected quantities within the specified limits. The methods presented in this course are all used to assess both geological properties and risk in mining projects.
This course is part of a series of technical training and professional development courses for Mineral Resource specialists in a mining environment. Although much of the content is general to the mineral resource industry, it provides delegates who are already competent in Resource Estimation with the opportunity to enhance their estimation techniques.
Although several advanced techniques and case studies are presented during the course, it is not possible to present all advanced estimation methods adequately in a one-week course. This course is designed for global exposure and will have variable content depending on the local mining environment. Normally Statistical Sampling, Advanced Linear Regression with either UC or IK and Conditional Simulation using one variable.
NOTE: The concepts presented in this course are complex, not intuitive and generally take many years, a lot of repetition and a lot of interaction with colleagues in the same field to gain competence. Participants should not expect to demonstrate competence at the end of the course rather they should be able to demonstrate an awareness of vocabulary, concepts, basic workflows, software help manuals and how to ask for help/guidance/information or be able to do a literature search for information on concepts and methods by using the correct terminology.
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