How can we address uncertainty in our characterization activities? And how can we deal with uncertainty in our decision?

• A. Recognize uncertainty
• B. Try and quantify uncertainty by effective probability and statistics
• C. Use geostatistics for mining
• D. All of the above

Answer: (D)

Addressing uncertainty involves three interconnected ideas that together support better characterization and tougher decision-making. First, recognize that uncertainty exists—you’re dealing with data gaps, measurement errors, and natural variability in how properties change across space. This awareness guides better data collection, model framing, and cautious interpretation.

Second, quantify the uncertainty using probabilistic thinking. Rather than settling for a single value, describe unknowns with probability distributions, derive confidence or credible intervals, and update estimates as new information comes in. This makes the level of uncertainty explicit and comparable across scenarios.

Third, apply geostatistics when the data have a spatial component, as in mining. Geostatistics models how property values vary in space, uses variograms to capture spatial correlation, and employs kriging to produce grades at unsampled locations with an explicit estimation variance. Conditional simulation can create multiple plausible realizations of the ore body, helping you propagate uncertainty into resource estimates and mine plans.

In decision-making, use these quantified uncertainties to compare options, assess risk, and run scenario analyses or robust optimization. Because recognizing uncertainty, quantifying it, and using spatial statistics to model and propagate that uncertainty are all important steps, the best approach is all of the above.