Identifying and Dealing With Outliers in Resource Estimation

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Douglas McLaughlin
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1 Identifying and Dealing With Outliers in Resource Estimation Ninth International Mine Geology Conference 2014 Chris De-Vitry

2 Overview Aim What is an Outlier? What Causes an Outlier? Dealing with outliers Importance of understanding geology of the outliers/high grade tail Conclusions

3 Aim of Talk This talk is aimed at the geologist who logs core, maps, samples etc. The key message: Geological observation, geological understanding and documentation of outliers and high grades is often critical to a project.

4 What is an Outlier An outlying observation appears to deviate markedly from the sample population. An outlier can be An extreme low; or An extreme high.

5 What is an Outlier An outlier can be neither low or high but in some way unusual e.g. Outlier on a scatterplot.

6 What is an Outlier Outliers may be part of an as yet poorly defined heavy tailed distribution. Which is the real unknown distribution?

7 What Causes an Outlier Issue with domaining. The sampling may be clustered or otherwise not representative e.g. Drilled down the axis of a high grade shoot.

8 What Causes an Outlier Chance e.g. Our first 20 samples could contain the highest grade individual sample in the deposit. An outlier may represent a location error, sampling error or measurement error. An outlier may be related to sample support.

9 Why Outliers can Cause Problems Outliers and high-grade tails can result in significant over or underestimation of block model grades. The bias can be local or global.

10 What to do with Outliers? If an outlier is an error, it should be corrected or discarded and if possible resampled. If the outlier relates to domaining then the domain boundaries may need adjusting.

11 What to do with Outliers? If the outlier is considered real, first understand geology then either: Leave the outlier in the database and proceed as normal; Apply a top-cut; Deal with the outlier in estimation; or Assess variability via comparing different approaches or by simulation.

12 Geology of Outliers/High Grade Population Case 1 Case 2 Case 3 Case 4 200m

14 Controls on High Grade Population Key characteristics of high grade population/outliers: Stationarity; Anisotropy; and Diffusivity. These characteristics should define how we deal with the high grade tail/outliers.

15 Controls on High Grade Population Not Stationary Case 1 Case 2 Stationary 200m Restrict high grade during estimation. Spread high grade throughout domain.

16 Controls on High Grade Population Anisotropy Can be managed in estimation via the variogram and the search neighborhood. Case 2 Isotropic 200m Case 3 Anisotropic

17 Controls on High Grade Population Diffusive Case 1 Case 2 Not-Diffusive 200m Linear Estimation Indicators

Controls on High Grade Population When mapping, face sampling, logging core etc think about key characteristics: Stationarity (Structural, lithological and alteration controls

18 Controls on High Grade Population When mapping, face sampling, logging core etc think about key characteristics: Stationarity (Structural, lithological and alteration controls on high grades); Anisotropy (What if any is the preferred direction of continuity of the high grades); and Diffusivity (Are there transitions between low and high grade samples).

19 SCALE 1M LEGEND Scree Felsic Rock Green Serpentinite Amphibole-Chlorite-Biotite Rock Massive Sulphide Vein Shearing SCALE 1M LEGEND Scree Felsic Rock

20 ffff SCALE 1M LEGEND Felsic Rock Amphibole-Chlorite-Biotite Rock Bladed Olivine-Sulphide Roc k Massive Sulphide 165 SCALE 1M LEGEND Felsic Rock Amphibole-Chlorite-Biotite Rock Bladed Olivine-Sulphide Roc k Massive Sulphide Massive Sulphide Vein Quartz Vein

23 Controls on High Grade Population Document your geological understanding of the outliers/high grade tail and discuss it with the resource geologist before estimation. This discussion should guide how estimation occurs and may be of critical importance to the project.

24 Conclusions Lack of understanding of outliers and heavy tailed distributions has destroyed some projects and will continue to do so. People often have a preferred approach to deal with outliers/high grade tails. Approaches should be based on what best matches the geological understanding not a preferred approach of the practitioner.

Tricks to Creating a Resource Block Model. St John s, Newfoundland and Labrador November 4, 2015

Tricks to Creating a Resource Block Model St John s, Newfoundland and Labrador November 4, 2015 Agenda 2 Domain Selection Top Cut (Grade Capping) Compositing Specific Gravity Variograms Block Size Search