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Grade, tonnage & uncertainty

Kriging, conditional simulation, and grade–tonnage you can defend

Estimate a block model with an anisotropic variogram and a declared search neighbourhood, run conditional simulation to see the spread a single estimate hides, and report tonnage above cut-off with a real uncertainty band.

A kriged block model in the 3D viewer — banded grade classes with block counts, merged block edges, a scale bar, and an axis triad.

Target audience

Resource geologists, mining geostatisticians, mine planning engineers, Competent Persons, technical reviewers, and due-diligence teams.

Platform capabilities

Ordinary kriging producing an estimate and its kriging variance per block
Anisotropic variogram models with nugget and nested structures
Declared search neighbourhoods — a block with no sample in range is refused, not estimated
Sequential Gaussian simulation with stacks of equally probable realizations
Exceedance probability models against a stated cut-off
Grade–tonnage curves with P10 / P50 / P90 bands across realizations
Contained metal computed per realization rather than multiplied from two means
Assumption parameters required and never silently defaulted

Business benefits

Report a tonnage figure with the uncertainty attached to it
Show which samples informed a block, and which blocks were left uninformed
Give reviewers the parameters behind a number, not just the number
Separate the quantity from the classification judgement

Screenshot gallery

The screens that support this workflow, shown in the working application.

An exceedance model — the probability that each node exceeds a stated cut-off, computed across a stack of conditional simulations.
A grade–tonnage report with a P10–P90 uncertainty band across realizations — a stated quantity, explicitly not a resource classification.
The job builder for ordinary kriging — assumption parameters are required, have no pre-filled default, and say why: a silent default is a decision nobody made.
The kernel catalog — every governed compute kernel rendered from its own manifest, with determinism class, execution class, schemas, and the assumption parameters it will not default for you.

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