18.2 Geological Modeling, Mine Planning, Scheduling & Valuation Software

Mining software links evidence to design and value. The workflow is only as reliable as its weakest transformation. Each export can change coordinates, units, fields, precision, classification, or naming, so interfaces are controlled and reconciled.

Exploration Database and Geological Model

Load and validate collars, downhole surveys, lithology, alteration, structure, samples, assays, density, recovery, and QA/QC. Checks include duplicate collars, negative depths, interval overlap or gap, assays beyond end of hole, impossible grades, missing density, coordinate bounds, and survey deviation.

Interpret domains using geology rather than grade alone. Build surfaces and wireframes with topological checks for self-intersection, gaps, and invalid solids. Composite samples within domains, evaluate distribution and outliers, model spatial continuity, estimate blocks with an appropriate method, and validate globally, locally, visually, and statistically. Classification reflects confidence, not color preference.

Mine Design

For an open pit, software can generate pit shells, phase designs, benches, berms, ramps, dumps, haul profiles, and quantities. An optimized shell is not an operational design: access, minimum mining width, drainage, geotechnical sectors, blending, equipment, and phase interaction remain.

For underground work, tools design declines, shafts, levels, stopes, pillars, raises, ventilation connections, development and fill. Automated stope shapes must be checked against geotechnical spans, minimum width, dilution, recovery, access, sequence, and neighboring voids.

Scheduling

A schedule assigns activities through time under constraints:

• predecessor and access logic;
• equipment and crew capacity;
• development and production rates;
• plant feed and blending;
• ventilation, backfill and dewatering;
• stockpile reclaim and material destinations;
• maintenance calendars and ramp-up; and
• environmental, permit and community conditions.

A schedule that draws ore before development or exceeds a hoist, crusher, fill plant, or tailings limit is mathematically output but operationally infeasible.

Valuation and Optimization

Valuation attaches prices, recoveries, payabilities, royalties, taxes, operating cost, capital, working capital, closure, and discounting to the physical schedule. Pit optimization may use revenue factors and maximum-closure algorithms; production scheduling may optimize NPV under capacity constraints. Review objective function and constraints. Maximizing undiscounted value, NPV, metal, or utilization produces different schedules.

Validation Ladder

1. Input: reconcile source counts, totals, units, coordinate range, versions.
2. Transformation: inspect domains, coding, compositing, dilution, recovery, and destination logic.
3. Output: reconcile tonnes, grade, metal, waste, development, capacity, and cash.
4. Independent check: reproduce selected volume, block value, stope, or cash-flow calculation outside the model.
5. Sensitivity: vary material assumptions and constraints.
6. Peer review: competent person challenges method and evidence.
7. Reconciliation: compare short-term model and schedule with survey, production, plant, and actual cost.

A model can pass global tonnage reconciliation yet misplace high grade locally. Use swath plots, nearest-neighbor comparison, section inspection, and production reconciliation.

Interoperability and Version Control

Declare coordinate system and units in every exchange. Use controlled field dictionaries and test a small file before bulk transfer. After export/import, compare record counts, bounding coordinates, tonnes, grade, classifications, and identifiers. Store native and exchange files with model version, software version, date, author, change reason, and approval.

Software Selection

Assess:

• surface or underground method and deposit geometry;
• estimation, optimization, scheduling, ventilation or geotechnical needs;
• data volume and performance;
• open interfaces and long-term accessibility;
• audit trail and scripting;
• user competence and local support;
• licensing and total cost;
• cybersecurity and cloud/data location; and
• validation and regulatory expectations.

Training matters. A powerful optimizer in untrained hands can generate a persuasive but invalid solution faster than a spreadsheet.

Exam Scenario

After importing a block model, scheduled tonnes match the source but average grade is lower. Check field mapping, domain and classification filters, percent-versus-fraction units, density, partial blocks, mining depletion, and destination cut-offs. Do not correct the result by multiplying grade until the transformation error is found.

Operational Reconciliation

Compare forecast with reality at the same support and time scale. Reconcile model tonnes and grade to grade-control estimates, surveyed mining, stockpile movement, plant feed, product, and tailings. Separate spatial error, sampling error, classification, dilution, ore loss, moisture, and inventory timing. A monthly total can reconcile while individual stopes fail systematically. Use the findings to improve the geological and operating process; do not adjust future models solely to force historical agreement.

Algorithm Trap

An optimizer returns the best solution to the objective and constraints supplied. If a ventilation limit, community commitment, ramp capacity, or development precedence is omitted, the “optimal” answer may be impossible. Validate the mathematical formulation before celebrating the objective value.