Gold Exploration Target Prioritization in West African Greenstone Belt
Engineering Case Study
Case Study 2: Gold Exploration Target Prioritization in West African Greenstone Belt
Scenario A junior exploration company is evaluating three drill-defined targets in southern Mali (Birimian Supergroup). Historical government survey data reports gold grades in g/t, while recent contractor assays were mistakenly delivered in % Au — causing confusion during target ranking. With limited field budget, the team must rapidly prioritize one target for Phase II drilling based on grade-thickness (g·m/t) potential. Time pressure and inconsistent units risk misallocating $1.2M in exploration capital.
Given Data
- Ore Grade Input: 0.0032 % Au
- Input Unit: %
- Output Unit: g/t
- Element: Au
Calculation
Conversion uses same mass-based factor: g/t = % × 10,000. Gold is reported as elemental metal in both datasets; no molecular weight correction is applied (unlike Au₂O₃ or tellurides, which would require stoichiometric adjustment — but none were detected in XRF screening).
- Step 1: Validate reporting convention → all assays confirmed as elemental Au (ICP-MS, certified reference materials).
- Step 2: Convert: 0.0032 % × 10,000 = 32.0 g/t.
- Step 3: Apply tool precision: 32.0000 g/t (4 decimals retained for downstream statistical analysis).
Result and Decision The converted grade (32.0000 g/t Au) revealed Target Gamma had a true weighted average grade of 32.0 g/t over 4.2 m — exceeding Targets Alpha (28.7 g/t) and Beta (19.3 g/t) — shifting priority from Alpha to Gamma. Subsequent trenching confirmed continuity, leading to a 22% increase in inferred resource estimate. The tool’s audit trail (including element selection and unit validation) was submitted with the JORC-compliant Technical Report.
Lesson Never assume unit homogeneity across data sources — even within a single jurisdiction; always validate elemental reporting basis (metal vs. compound) before conversion, as incorrect assumptions (e.g., treating % Au as % Au₂O₃) introduce ~23% systematic error.