📦 Resource excel

Geometallurgical Block Model Template (Excel)

The Geometallurgical Block Model Template (Excel) is a standardized spreadsheet-based framework designed to integrate geological, geotechnical, mineralogical, and metallurgical data at the mining block level. It enables consistent spatial representation of ore variability and its impact on downstream processing performance. The template serves as a bridge between resource estimation and process engineering, supporting data-driven decision-making in mine planning and optimization.

📖 Overview

Geometallurgical block models extend traditional 3D geological resource models by incorporating metallurgically relevant attributes—such as mineral liberation, gangue composition, acid consumption, grindability (e.g., Bond Work Index), and recovery response—to each discrete volumetric block. The Excel-based template provides a structured, auditable, and interoperable format for populating, validating, and exporting these attributes, often derived from drill-core assays, QEMSCAN/MLA mineralogy, batch testing, and pilot plant data. Its design emphasizes traceability (linking blocks to sample IDs and analytical methods), scalability (supporting hierarchical block sizes), and compatibility with mine planning software (e.g., via CSV or ODBC export). Crucially, it facilitates geometallurgical risk assessment by enabling scenario analysis—e.g., simulating how variations in sulfide content or clay mineralogy across blocks affect leach kinetics or flotation recovery—thereby informing selective mining, blending strategies, and processing circuit design. While less spatially sophisticated than full 3D modeling platforms (e.g., Leapfrog Geo or Vulcan), the Excel template offers accessibility, transparency, and rapid iteration for early-stage studies, cross-functional workshops, and SME-led integration efforts.

📑 Key Components

1 Block ID and 3D Coordinates (X,Y,Z)
2 Geological Domain & Lithology Classification
3 Metallurgical Response Parameters (e.g., % Recovery, Residence Time, Acid Consumption)

🎯 Applications

  • Optimizing selective mining and ore-waste delineation based on process performance thresholds
  • Feeding metallurgical simulations (e.g., in JKSimMet or METSIM) with spatially resolved feed characteristics
  • Supporting life-of-mine scheduling with grade-and-recovery-aware constraints

📐 Key Formulas

Weighted Average Recovery per Mining Unit

∑(Recovery_i × Tonnage_i) / ∑Tonnage_i

Calculates blended metallurgical recovery for a group of blocks (e.g., a pushback or bench) based on individual block recoveries and their estimated tonnages.

Acid Consumption Estimate (kg H2SO4/t)

(0.015 × %Carbonates + 0.035 × %Sulfides) × 1000

Empirical approximation of sulfuric acid demand for sulfide-carbonate ores during heap leaching or agglomeration.

Composite Bond Work Index (BWIs)

∑(Wi_i × (ρ_i × V_i)) / ∑(ρ_i × V_i)

Mass-weighted average Bond Work Index across blocks, where Wi_i is the index for block i, ρ_i is density, and V_i is block volume—used for mill power and throughput forecasting.

🔗 Related Concepts

Geometallurgy Block Modeling Ore Characterisation Mine-to-Mill Integration Resource Confidence Classification (e.g., JORC/NI 43-101)

📚 References

#geometallurgy #excel-template #mine-planning #ore-characterisation #process-integration