Glossary term
Georesource Model
Engineering representation of a resource deposit, including geometry, grade, material domains, uncertainty, and operational constraints.
Definition
modelA georesource model is an engineering representation of a deposit or subsurface resource used for planning, design, and risk decisions.
A georesource model may include geometry, grade, density, lithology, alteration, hardness, groundwater, geotechnical domains, contaminants, uncertainty, sampling basis, and economic or operational classifications. It connects geological interpretation with mine planning, processing, slope design, dewatering, closure, and reconciliation.
A georesource model is an engineering representation of a deposit or subsurface resource. It may describe ore, waste, aggregate, industrial minerals, groundwater, geothermal resources, hydrocarbons, or other geological materials relevant to design and production.
In mining, the model often includes geometry, grade, density, lithology, alteration, structures, hardness, deleterious elements, weathering, groundwater, geotechnical domains, and uncertainty. It may be stored as a block model, wireframe, domain model, resource estimate, or planning model.
Engineering use
Georesource models support mine planning, production scheduling, grade control, processing tests, slope design, dewatering, ventilation, waste classification, stockpiles, tailings estimates, closure planning, and economic evaluation. They connect geological data with operational decisions.
No model is the deposit. It is an interpreted approximation based on drilling, mapping, sampling, assays, geophysics, test work, and operational feedback. Reconciliation between model predictions and production data is essential.
Common mistakes
A common mistake is treating the model as deterministic. Grade, density, boundaries, structures, and processing response can be uncertain, especially between data points. Another is using a model built for resource reporting as if it were automatically suitable for short-term production control. A strong review states data basis, domains, estimation method, uncertainty, validation, reconciliation, and the decisions the model is allowed to support.