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Sampling 2019 Theory and Practice, Course, Lima, Peru
July 8 @ 8:00 am - July 10 @ 5:00 pm$590
Poor sampling, compounded by poor laboratory subsampling, leads to questionable geostatistics, and generates severe conciliation problems between the geological model, the mine, and the plant estimates. These problems also affect the price of commodities and the validity of environmental assessments. The result is a huge money loss for the company involved, evolving later in likely litigation. It is of key importance for geologists, miners, metallurgists, chemists, and environmental specialists to extract maximum information from the available data, as large investments and crucial decisions depend on it. False evaluations lead to devastating scenarios such as:
Abandonment of viable properties.
Exploitation of unprofitable properties.
Mismanagement of viable properties, and Incompetence in fraud detection.
It is critical to quantify the heterogeneity of important constituents in any new property. Failure to do appropriate testing leads to invalid sampling and subsampling protocols, excess drilling, and a biased database that would later lead to false geostatistics. The following sequence is part of an inescapable practice:
How is the constituent of interest distributed in the material to be sampled?
Conduct Heterogeneity Tests to quantify the sampling characteristics of the constituent of interest.
Optimize sampling protocols and the way they are implemented, according to the results from the Heterogeneity Test.
Implement protocols using valid sampling equipment: 75% of the sampling equipment available on the market will never do the job.
Implement a comprehensive, systematic quality control program to monitor sampling precision and accuracy.
The staggering cost of irrelevant data variability is not easy to detect, quantify, or correct. A strategy for effective management of variability will enable managers to identify and minimize annoying conciliation problems between theoretical models and reality: Your decisions are only as good as your samples !
The course offers simple ways to quantify money losses for a given sampling precision, and it provides a good strategy to prevent sampling inaccuracy for which there is no statistical cure. Unless sampling precision and accuracy are clearly connected to economic issues, it is unlikely that managers would understand the need to improve sampling protocols and the way they are implemented. At the end of the course, attendees will be better equipped to present the economic advantages of good sampling. Thus, the course is a pre-requisite for bank investment: Bankers must listen and trust the Sampling Theory.