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									                            Customer Success Story
        Coeur d’Alene successfully used ISATIS to
     quantify the ROI of drilling on resource estimation

John Sims, Director of Mineral Resources chose GEOVARIANCES for quantifying the Return
On Investment of further drilling and the risk on resource estimation. With GEOVARIANCES
expertise in Advanced Geostatistics, GEOVARIANCES has been providing Coeur with global
solution - software product, consulting and training – which fits perfectly John Sims’

Quick facts                                         and forth from one software package to another
                                                    one.” John Sims, Coeur Director of Mineral
Coeur d’Alene Mines Corporation is one of
                                                    Resources and certified QP explained.
the world’s leading silver companies and
                                                    “I contacted GEOVARIANCES because they
also a significant gold producer. Coeur
                                                    are known as the leader in advanced
operates several mines in the world and is
                                                    geostatistics and offer solutions that you do
presently constructing two of the world’s largest
                                                    not find anywhere else.” he added.
silver mines. The Company also conducts
exploration activities worldwide.
                                                    The Solution
The Challenge                                       GEOVARIANCES offered Coeur d’Alene to
                                                    purchase ISATIS together with a workshop
Several hundred meters of drilling is a costly
                                                    training session.
undertaking and mining companies such as
Coeur d’Alene often hesitates in increasing their   Coeur d’Alene expectations were:
sampling campaigns without knowing whether it       - To gain advanced geostatistical skills;
is worthwhile, in other words, whether they will
                                                    - To build an interactive and customized
gain in the estimated recoverable resources.
                                                      workflow guideline for classic geostatistical
In order to base their decision on tangible           processing (variography, declustering,
figures, Coeur’s objective was to find a new          kriging) in ISATIS;
decision-making tool to:                            - To set an advanced and genuine workflow for
- Carry out accurate resource estimation and          drilling optimization and risk analysis;
  risk analysis;                                    - To practice and validate the workflows on
- Achieve sophisticated workflows as the one          Coeur’s main projects.
  described hereafter.
                                                    ISATIS numerous geostatistical capabilities
“To quantify the Return On Investment of            (kriging and conditional simulations) come up to
further drilling, I needed to run a sophisticated   the first expectation, whereas its modularity
workflow on my dataset. To reach my goal in         enhanced by the journal file system allows to
an efficient way, I was seeking a tool that would   create sophisticated and interactive workflows
allow me to achieve the workflow in its             easily usable by beginners.
entirety in one single software package.
Indeed, I have no time to spend in going back

                                                                            Customer Success Story - 1
This kind of one-to-one mentoring has been
particularly valuable to John Sims. Indeed, it
allowed him not only to become familiar with
ISATIS but it also allowed him to build and run
the workflow he needed in three weeks. And
this, under the guidance of an expert

The Results
                                                      Fig 2. Current Palmajero model with
The workshop was carried out on data coming           the open pit project and the main clavos
from Coeur Palmajero project (Fig.1).
                                                  The main objective was to take advantage of
                                                  these simulations, at the least cost, for drilling
                                                  optimization. The workflow consisted of:
                                                  - Performing N conditional simulations from
                                                    existing data (considered as N different
                                                  - Sampling the N simulations in order to create
       Fig 1. The Palmajero project                 N fictitious drill hole datasets according to
                                                    different drilling strategies (Fig 3.);
Palmajero is located in Mexico, inside the        - Kriging each fictitious dataset and compare it
Sierra Madre Precious Metals Belt.                  to the corresponding simulation;
The deposit consists in two very large vein       - For each drilling strategy (with different
systems, with auxiliary hanging wall and            sampling distance), calculating the optimal,
footwall veins. Each major vein is composed of      estimated and recovered values for tonnage,
different mineralized areas corresponding to        metal, and mean grade recovered after
different clavos (ore shoots). An open pit mine     applying an economic cutoff.
is first scheduled, likely followed by an
                                                  Results obtained on the 76 clavo are displayed
underground mining plan (Fig.2).
                                                  in the table below for a regular 55x55 m
Beyond ordinary kriging block modeling,           sampling compared to a 30x30m one. They are
geostatistical conditional simulations were       expressed in percentage of the real in-situ
used for risk analysis: uncertainty               quantities, considered unknown.
assessment on tonnage and metal predictions,
                                                  The estimated value is derived from the
and also on grade variability.
                                                  ordinary kriged block model, as it would be
                                                  done in classic resource estimation.

                                                                              Fig 3. Representation
                                                                              of the area of interest
                                                                              (76 clavo) with actual
                                                                              drill holes (left) and
                                                                              fictitious drill holes
                                                                              with regular 30x30
                                                                              horizontal drilling
                                                                              (right). A real drilling
                                                                              plan could also be used
                                                                              in the workflow.

                                                                           Customer Success Story - 2
                                                             “ISATIS, with its great flexibility and its unique
The recovered value is derived from the
                                                             ability to build tailored workflows through its
simulated block model and represents the real
                                                             journal file system, provided me with the
value that would in fact be recovered.
                                                             solution I expected.” John Sims added. “Last but
Comparing estimated vs. recovered allows a                   not least, I found no other software package as
quantitative prediction of the error related to the          powerful as ISATIS for in-depth data analysis
smoothing effect of kriging.                                 and quality control.”

                                                             Given these successful results and upon full
                            55x55m       30x30m              validation of the workflow by Coeur’s
                            sampling     sampling            management, John Sims is willing to apply the
              Real           100.0 %       100.0 %           methodology on other Coeur’s main projects.
TONNAGE       Estimated      142.0 %       133.6 %           To achieve this in the most efficient way,
              Recovered      142.0 %       133.6 %           GEOVARIANCES will provide Coeur with
              Real             100 %        100 %            technical support and will give them the expert
 GRADE        Estimated        69.7 %       73.5 %           advice they need.
              Recovered        63.9 %       70.8 %
                                                             Another possible promising development is to
              Real           100.0 %       100.0 %           extend the technique to the multivariate
 METAL        Estimated        99.0 %       98.3 %           framework for Coeur’s combine silver/gold
              Recovered        90.2 %       94.5 %           projects. Indeed, by taking advantage of the
                                                             existing correlation between silver and gold
Comparing both columns gives quantitative                    grades, Coeur will gain confidence in their
results on the gain of prediction when drilling is           resource estimations.
refined: the tonnage overestimation is reduced               “This quantitative approach obtained from
and the mean grade is closer to 100%. Metal                  different drilling plans is valuable to our
quantity does not vary significantly because the             Palmajero project,” John Sims concluded. “I
tonnage overestimation is compensated by                     can now base my decision on proofs. Today,
grade underestimation.                                       given this example, I know that if we multiply
                                                             the drilling density by about 3.5, the tonnage to
Resource estimations improved with
                                                             be sent to the mill will be reduced by 6% for a
further drilling
                                                             mean grade higher by 11%. These results are
GEOVARIANCES succeeded in sharing its                        most important for long-term mine planning and
skills at a high flexibility and expertise level.            avoiding unnecessary mining costs.”
Indeed, GEOVARIANCES workflow allowed
Coeur d’Alene to get a quantitative solution
                                                             September 2008
which represents a distinctive key for risk
management and extra drilling decision.

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