Checking the validity and robustness of any resource estimate is a mandatory step to ensure models remain current and useful. Key avenues for validation and reconciliation are:
– Geostatistical inspection of resource estimates and benchmarking against data inputs; and
– Reconciliation of production outcomes with grade control models and exploration resource estimates (e.g. using past and current production information to improve the predictive performance of your models).
Geostatistics is particularly well-suited to test and check:
1/ The internal consistency of the model (check hypotheses, reproduction of input parameters):
Grade architecture: helps you chose the change of support models adapted to your deposit; and
Compare grade tonnage curves produced by your estimates (OK, UC, CS…) with theoretical curves based on samples and change of support model.
2/ The statistical compatibility of the estimates with input parameters:
Global checks: statistics, histograms, variograms; and
Local checks: scatter plots, q-q plots, swathplots, boxplots.
3/ The validity of the estimation domains used:
Border effect and contact analysis (samples/models):
these two complementary tools are used to qualify how domains should be treated at estimation (i.e. hard/soft boundary, definition of transition domains etc.);
Response of estimates to combination/sub-division of domains; and
Uncertainty on estimation volumes/tonnages.
4/ The use of production dig line to reconcile models at different scales with actual production data and propose mediatory actions;
5/ Time-sampling and reconciliation at the mill; and
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