1. Integration of multiple data
sources into a resource
estimate – analysis of the
options
Geovariances Geostats Rendezvous
Perth February 26-27, 2013
Presented by Alastair Cornah
Quantitative Group, Fremantle
ac@qgroup.net.au

2. Presented by :
Alastair Cornah
Introduction
Multiple overlapping sources of ‘hard’ data in
brownfields projects.
For example diamond, sonic, reverse circulation,
and percussion drilling.
Channel samples, blasthole samples
How should these various data sources be
handled in resource estimation?
Support?
Precision?
Bias?

3. Presented by :
Alastair Cornah
Treatment of lower precision or
biased data in resource estimation
Does including the lower precision (or biased) data help to
minimise estimation error?
Additional data reduces the information effect, but is this
outweighed by increased estimation error as a result of
that data’s poor precision (or bias)?
The answer is partly dependent upon the choice of
estimation method.
Various geostatistical approaches exist which can be
used to maximise the value of low precision (or biased)
data in a resource estimate.

4. Presented by :
Alastair Cornah
Testwork
Generation of a ‘ground truth’ within a two dimensional test area
using conditional simulation of diamond drillhole data.
Extraction of seven channel sample datasets
Uniform error distributions applied to channel locations to
iregularise the sampling pattern, avoid colocation of channels and
drillholes.
Gaussian error distributions (unbiassed) with increasing variance
applied to extracted grades.
Various estimation methods trailed using the drillholes and the
various channel sample datasets (including and excluding channel
samples).
Estimations compared against the ground truth.

5. Presented by :
Alastair Cornah
Estimation options evaluated
Estimation of drillholes only (ignoring channels) using Ordinary
Kriging
Integration of drillholes and channels estimation using Ordinary
Kriging
Integration of drillholes and channels, estimation using Cokriging
Integration of drillholes and channels, estimation using Colocated
Cokriging
Integration of drillholes and channels, estimation using Ordinary
Kriging with Variance of Measurement Error

6. Presented by :
Alastair Cornah
Conditional Simulation of Ground
Truth

7. Presented by :
Alastair Cornah
Extraction of ‘virtual’ channel
samples

8. Presented by :
Alastair Cornah
Estimated Fe (baseline) vs Ground
Truth

9. Presented by :
Alastair Cornah
OK – drillholes only (baseline)

10. Presented by :
Alastair Cornah
OK – drillholes only (baseline)

11. Presented by :
Alastair Cornah
OK – drillholes and channels

12. Presented by :
Alastair Cornah
OK – drillholes and channels

13. Presented by :
Alastair Cornah
Cokriging – drillholes and channels

14. Presented by :
Alastair Cornah
Cokriging – drillholes and channels

15. Presented by :
Alastair Cornah
Colocated cokriging – drillholes and
channels

16. Presented by :
Alastair Cornah
Colocated cokriging – drillholes and
channels

17. Presented by :
Alastair Cornah
Ordinary Kriging with Variance of
Measurement Error
Ordinary Kriging with Variance of
Ordinary Kriging (channels & drillholes)
Measurement Error (channels & drillholes)
Drillhole Drillhole
Channel Channel

18. Presented by :
Alastair Cornah
Ordinary Kriging with Variance of
Measurement Error – drillholes and
channels

19. Presented by :
Alastair Cornah
Ordinary Kriging with Variance of
Measurement Error – drillholes and
channels

20. Presented by :
Alastair Cornah
OKVME – analysis of weights

21. Presented by :
Alastair Cornah
Conclusions under the testwork
assumptions
If OK estimation is used, channel samples influence the estimation
significantly more than drillholes.
In spite of this, benefit is gained by including the channels, as long
as less than 2SD of sampling / measurement errors associated
with the channels; beyond this using drillholes only is preferable.
If CK, CCK, OKVME estimation is used, benefit is gained by
incorporating the channels regardless of the level of sampling and
measurement error (upto 3SD which was tested)
OKVME rebalances kriging weights from channels to drillholes,
depending upon the sampling / measurement error variance
associated with the channels. Where channels contain any
(unbiassed) error distribution it outperforms CK, CCK and OK.