Ore Control Analysis for Mining Geologists
Analyze assay data and grade control metrics to optimize ore extraction and minimize dilution
What You Can Do
You can rapidly process grade control data from face samples, drill core composites, and blast hole patterns to identify ore characteristics, flag anomalies, and quantify dilution losses. Claude helps you reconcile actual extracted grades against your block model predictions, investigate grade bias in active mining areas, and structure sampling strategies for new mining fronts. This skill generates technical recommendations for ore routing decisions (crushing, stockpiling, reprocessing, or waste designation) backed by statistical analysis and trend interpretation.
Features
Parse multi-element assay results, identify high-grade zones, deleterious element distributions, and grade variability patterns
Compare actual ore grades extracted vs. block model predictions to quantify bias, detect sampling errors, or reveal geological surprises
Calculate dilution percentages, classify overbreak sources, and estimate economic impact of waste inclusion in ore
Flag outlier assay values, sudden grade shifts, unexpected element correlations, and sampling consistency issues
Evaluate blast performance against planned block geometry, identify grade bias patterns, and recommend drilling/powder adjustments
Generate data-driven decisions for directing ore to crusher, stockpile, reprocess circuit, or waste based on grade thresholds and deleterious elements
Structure face sample grids, composite intervals, and quality assurance programs for reliable grade control
Produce grade control summaries with trend charts, anomaly logs, and actionable recommendations for mine planning
Example Output
Example 1: Grade Reconciliation Report
Comparing Block Model vs. Actual Extraction (Week 48):
- Predicted average grade: 2.14% Cu | Actual grade: 1.89% Cu (Grade bias: -11.7%)
- Tonnage overbreak: 12,400t vs. 10,800t planned (+14.8% dilution)
- High-grade loss: 340t grading >3.0% Cu misclassified as waste
- Recommendation: Adjust blast design (reduce powder factor by 8%) and tighten face sample grid from 5m × 5m to 3m × 5m in high-variance zones
Example 2: Anomaly Flagging
Sample AS-4521 inconsistencies:
- Cu: 4.32% (expected 2.1–2.8% range) — Statistical outlier (+2.1 SD)
- Mo: 0.087% (vs. 0.012% average in zone) — 7x background
- Recommendation: Resample location, check for Au-Cu stockwork mineralization not mapped in block model
Example 3: Ore Routing Decision
Blast B-287 routing analysis (480t ore):
- 62% grading >2.5% Cu → Primary crusher (target feed)
- 28% grading 1.8–2.5% Cu → Stockpile (blend for mill feed stability)
- 10% grading <1.8% Cu with elevated As (0.14%) → Waste (reprocess queue when feasible)
What's Included
- SKILL.md instruction file: Full ore control analysis framework and usage guidelines
- Assay data analysis template: Multi-element result parsing and grade distribution worksheet
- Grade reconciliation checklist: Block model vs. actual comparison and bias quantification workflow
- Dilution investigation framework: Overbreak classification, source identification, and economic impact calculator
- Ore routing decision matrix: Grade threshold table and routing recommendation logic by ore type
- Blast reconciliation analysis template: Performance vs. plan comparison and grade bias diagnosis
Who It's For
- Mining geologists — Conducting daily grade control analysis, monitoring dilution, and making ore routing decisions
- Grade control technicians — Processing assay data, flagging anomalies, and documenting ore characteristics at the mine face
- Mine planners — Reviewing reconciliation reports and adjusting mining geometry and blast design based on grade control feedback
- Operations managers — Understanding grade control performance, investigating mill feed quality issues, and identifying ore losses
- Mineral resource engineers — Validating block model accuracy and reconciling geological estimates with actual production
Best For
- Multi-element assay interpretation and trend analysis across mining blocks or blast zones
- Grade reconciliation studies comparing predicted vs. actual ore grades and quantifying model bias
- Dilution investigations to identify overbreak sources, waste inclusion, and high-grade ore losses
- Ore routing optimization based on grade thresholds, element constraints, and operational routing rules
- Blast reconciliation and performance evaluation to improve future mining accuracy and grade control
- Sampling strategy design and quality assurance program development for new mining fronts
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