Customer Story

Using geochemical vectoring to identify proximity to mineralisation at Costerfield

Alkane Resources, operator of the Costerfield gold–antimony mine in Victoria, needed a reliable method to use routine drill-hole geochemistry to prioritise exploration drilling.

Datarock developed a geochemical vectoring workflow that analyses multivariate assay data to predict whether samples fall within 15 m or 30 m of ore.

Alkane Resources | Costerfield Gold Mine

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Challenge
  • Incomplete element coverage made data suitability for modelling uncertain.
  • No clear geochemical controls; teams relied on assumption over evidence.
  • No scalable way to flag near-ore samples without subjective interpretation.
Solution
  • Assay data cleaned, standardised, and filtered for spatial coverage.
  • Geochemical ratios engineered as inputs: Sb/As, Mn/Zn, Fe/Mg, As/Fe, Ba/K.
  • Two gradient-boosted models predict proximity within 15 m and 30 m of ore.
  • Validated via leave-one-hole-out testing with a 40 m exclusion buffer.
Result
  • 15 m model: 69% accuracy. 30 m model: 60% accuracy.
  • Arsenic drives the near-ore signal; barium defines the 15–30 m halo.
  • Spatial outputs flag where predictions diverge from geological interpretation.
  • Alkane can screen new assay batches and identify targets earlier.

“Multi-element geochemistry contains strong signals about proximity to mineralization, but those signals can be difficult to interpret consistently across large datasets. This approach helped translate complex assay data into a clear and practical tool for identifying samples that may be close to ore.”

Braden VerityGeology Manager, Alkane Resources