COST-EFFECTIVE USE OF AUTOMATED MINERALOGY TO CALIBRATE GEOMETALLURGICAL CHARACTERIZATION OF A RARE EARTH ELEMENT DEPOSIT

Rare earth element (REE) deposits generally represent extreme examples in the category of polymetallic ores, with up to fifteen different metals of potential interest, not including non-REE byproducts. Though REEs generally co-crystallize within the same minerals, these deposits typically carry multiple significant ore mineral phases. A detailed understanding of ore mineral identities, associations, and physical characteristics is crucial to development of the process flowsheet for the mine.

The Bear Lodge carbonatite complex in northeastern Wyoming has multiple parageneses of REE mineralization related to magmatic, carbohydrothermal, and supergene processes. The result is a deposit that exhibits lateral and vertical zonation of REE mineralogy and distribution. The deposit currently has measured and indicated resources of 18 Mt at 3.05 wt. % total rare earth oxide.

Processing ore minerals that can exhibit variation in grain size, gangue associations, and mineral type (e.g., fluorocarbonate, phosphate, or oxide) is challenging. Quantitative deposit characterization is crucial to maximize recoveries. This also is necessary for more efficient usage of energy and reagents during processing.

The use of automated mineralogical analysis (AMA) in deposit evaluation is becoming the rule, rather than the exception. This study discusses how the challenges of conducting accurate AMA of a partially laterized carbonatite at Bear Lodge were surmounted. Using assay reconciliation, optical mineralogy, core logs, and x-ray diffraction to audit the results of AMA is a necessary and iterative process.

A cost-saving strategy using geochemical indices calibrated from high quality, representative AMA data is also presented. The high per-sample cost of AMA can be offset by careful selection of a representative sample suite. These data are used to calibrate the geochemical indices calculated from assay data. The indices cover criteria that can affect processing: clay alteration, oxidation, gangue carbonate abundance, etc. They are developed using knowledge of the geological processes involved in deposit genesis. Given a well-calibrated set of indices and thorough coverage of assay samples, it is possible to evaluate the deposit for mine planning and processing without having to do hundreds of costly AMA samples.