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Lateritic nickel deposits are created by weathering. Their layers can vary sharply over short vertical distances, and nickel grades are closely linked to the material type in which they occur. Even when a resource model looks orderly, it may hide uncertainty around domain boundaries, local grade continuity and the relationships between chemical variables.
For resource teams, this uncertainty can influence confidence in tonnes and grade, resource classification, drillhole spacing and the assumptions passed into mine planning.
The key question is not only, ‘What is our best estimate?’ It is also, ‘How variable could the deposit be, and where would that variance affect a decision?’
What a single model may hide
A conventional resource estimate provides one smooth usable interpretation. It does not show every geological configuration that could reasonably fit the same drilling data.
Two plausible interpretations may have similar global averages but different local proportions, connectivity or grades.
Those differences matter when decisions are made at a local scale.
A probabilistic approach generates multiple realistic versions of the deposit. Comparing them reveals where the interpretation is stable and where it varies. This turns uncertainty from a general warning into information that geologists, resource managers and planners can use.
Four decisions that become better informed
Resource confidence:
Identify areas where the available data consistently support the geological interpretation and areas where results vary.
Drilling priorities:
Focus infill drilling where reducing uncertainty is most likely to improve an important decision.
Recoverable resources:
Test how alternative geological and grade outcomes may affect recoverable tonnes and grade at the relevant support.
Mine planning risk:
Assess whether key planning choices remain robust across more than one plausible deposit scenario.
A practical application to lateritic nickel
A published study by Rolo, Arief and Yuminti applies a unified probabilistic workflow to an Indonesian lateritic nickel deposit. The approach models lithology and multiple grades as a connected system rather than as separate problems. It also accounts for the geometry of the weathering profile and generates conditional scenarios that honour the drilling information.
The authors report that the models reproduce lithological proportions, spatial continuity, grade distributions and relationships between variables.
The resulting range of outcomes provides a basis for uncertainty assessment in recoverable resource estimation, with potential downstream applications in resource classification and drillhole spacing analysis.
The technical workflow combines unfolding, plurigaussian simulation, multivariate data preparation and conditional grade simulation. For a broader audience, the main message is simpler: geology and grades remain connected, while multiple credible outcomes make uncertainty visible.
How Isatis.neo supports the workflow
Isatis.neo provides geostatistical tools for building and analysing this type of uncertainty-aware resource model. Its practical value for lateritic nickel teams is the ability to represent alternative geological-domain configurations, preserve important relationships between grade variables, generate scenarios that honour available data and compare the results in a consistent environment.
- The workflow must still be adapted to the deposit, data quality and business question.
- Software supports the analysis;
it does not replace geological judgement, validation or competent-person review.
The opportunity for lateritic nickel teams
Uncertainty cannot be removed from a lateritic nickel deposit, but it can be measured and communicated before it reaches planning. By testing a range of geologically realistic outcomes, teams can see where confidence is strong, where more information may add value and which conclusions remain robust.
Want to understand where uncertainty could affect your lateritic nickel resource decisions? Speak with the Datamine team about a focused review of your geological domains, multivariate grade model and decision requirements.
Source
Rolo, R., Arief, J. and Yuminti, S. (2026). ‘Probabilistic Modeling of Lateritic Nickel Mineral Resources’. Minerals, 16(5), 551. https://www.mdpi.com/2075-163X/16/5/551
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