MINERAL RESOURCE ESTIMATION (IN-SITU AND RECOVERABLE)
Estimating mineral resources is performed at all stages of the mine life cycle. Geostatistics will ensure you get the maximum value out of the available information: investigate data quality, focus on the reliable data, discount unreliable, erroneous data and produce accurate resource estimates. Maximise the return on your data investment and then use the results to optimise future data collection.
Statistical and Geostatistical skills can be used in all aspects of resource estimation:
The relevance of any resource estimate is directly dependent upon the quality of your input data. Statistical and Geostatistical analyses provide quantitative inputs for:
Assessing the validity of your different data sources
Rejecting imprecise or biased information
Combining different data sources
GEOLOGICAL DOMAIN VALIDATION
The definition of robust geological envelopes is paramount for ensuring the quality of your mineral resource estimation. The envelopes must be relevant (i.e. as detailed as the data allows them to be) and robust (to changes in the local geological rationales). Geostatistics can help assuring they are fit for the purpose of producing a MRE you can trust by focusing on:
Boundary Analysis and Boundary Treatment
Domain Combination or Sub-division
CHARACTERIZATION OF SPATIAL VARIABILITY
This is the only way you can ensure the estimation methodology you use will be completely adapted to the deposit you are modeling:
Exploratory Data Analysis
IN SITU ESTIMATION AT ALL STAGES
RECOVERABLE RESOURCE ESTIMATION
A sound evaluation of Recoverable Resources is a pre-requisite for Reserve Calculation. They help determine the portion of the deposit that is technically recoverable when one applies a cut-off to selective mining units (SMU’s) to be mined at production stage. They are usually much smaller than the Panels that can safely be estimated from exploration data. Linear Interpolation is thus no longer applicable and one needs to resort to non-linear geostatistics to estimate these recoverable resources.
Testing grade architecture to inform the choice of an adapted Change of Support Model
Global or Local recoverable resource estimation
Characterization of uncertainty of the recovery functions (link with simulation)
Localization of models to facilitate communication to mine planning engineers
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