Ore Deposits 101: Mineral Resources and Reserves

Presenter

• Andrew Jackson
  • Geologist at Sprout
  • Conducts technical evaluations of mineral companies and properties
  • Series aimed at helping non-technical people understand ore deposits

Lecture Overview

• Focus on mineral resources and reserves at the end of exploration
• Goal: Establish if the discovered ore is economically viable
• Background on resources and reserves from historical examples

Historical Context

• Poseidon Nickel (1969): Fabricated reports led to inflated share prices and eventual collapse
• Bre-X Minerals (1997): Overstated gold resources leading to market scandal
• Both cases highlighted need for standardized reporting

Regulatory Responses

• JORC Code (1989): Standardized reporting of resources and reserves in Australia
• NI 43-101 (2005): Canadian regulation ensuring transparency in resource estimation

Mineral Resource Categories

• Measured: High confidence, supports production planning
• Indicated: Sufficient confidence for mine planning
• Inferred: Low confidence, cannot be used in economic studies
• Based on geological evidence and sampling

Mineral Reserve Categories

• Proven Reserves: Economically minable part of measured resource
• Probable Reserves: Economically minable part of indicated resource

Resource and Reserve Estimation Process

1. Data Collection: Geological mapping, drilling
2. Geological Modeling: Building a 3D model using collected data
3. Grade Modeling: Estimating ore grade using statistical methods
   • Methods: Polygonal, Inverse Distance (ID), Kriging
   • Kriging: Most common, accounts for geological trends
4. Economic Evaluation
   • Estimating cut-off grade for economic viability
   • Dividing resources into measured, indicated, and inferred
5. Feasibility Studies: PEA, PFS, FS
   • Preliminary Economic Assessment (PEA): Rough economic sense (~40-50% accuracy)
   • Preliminary Feasibility Study (PFS): Detailed analysis (~20-30% accuracy)
   • Feasibility Study: Comprehensive study (~15% accuracy), includes environmental, legal, and financial aspects

Pit Optimization (Open Pit Mining)

• Use of algorithms like Lersch-Grossman
• Determines optimal mining strategy by evaluating economic scenarios

Key Takeaways

• Regulatory Frameworks: Ensure transparency but are not foolproof
• Feasibility Studies: Critical for decision-making but require scrutiny
• Investment Decisions: Positive feasibility does not guarantee profitability

Conclusion

• The talk outlined the systematic process of evaluating ore deposits to determine their economic potential.
• Reminder: A positive feasibility study is not the final indicator for construction decisions.

Thank you for attending the lecture.