the integra « gold rush challenge »: impacts from hard data management through resulting...
TRANSCRIPT
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Francine Fallara, P.Geo., M.Sc. A.,
Stéphane Faure, P.Geo., Ph.D. and Guilhem Servelle, P.Geo., M.Sc.
Earth Modelling Forum 2016
Montreal, Quebec
October 3rd, 2016 Consultants – Mine - Exploration
The Integra « Gold Rush Challenge »:
Impacts from hard data management through
resulting exploration targets ranking
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2The Integra « Gold Rush Challenge » Case Study
«Gold Rush Challenge» Objectives
Increase rapidly their chance in finding the next
major gold deposit discovery within the Sigma-
Lamaque gold properties in Val-d’Or, Québec by:
1. Implementing one of the largest organized
crowdsourcing analytical challenge ever
created in the mining industry
2. Opening it to worldwide individuals and
organizations
3. Marketing the challenge through financed
sponsoring
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3The Integra « Gold Rush Challenge » Case Study
«Gold Rush Challenge» AOI - Mineralized ZonesSigma-Lamaque Mines
75 years producing > 9 Moz. Au
Sigma-Lamaque Mill and Mine
Complex are located directly east of
the city of Val-d'Or in the Province of
Quebec, Canada
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4The Integra « Gold Rush Challenge » Case Study
InnovExplo Mandate
InnovExplo major roles, before and after the «Gold Rush Challenge»,
are presented in three main phases:
Historical Hard Data Compilation and ManagementPhase 1
Phase 2
Phase 3
Resulting Targets Validation and Classification
Resulting Targets Ranking and Querying
171 302 files of
various types
stored
on external drives
26 080 mine plan
levels and sections
(image format)
2 boxes of various
digital supports
(CD, 3.5 inches
disks and tapes)
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5The Integra « Gold Rush Challenge » Case Study
Hard Data Integration Methodology1. Scan, compile, merge and unify: Several local grids,
scales and elevations within one chosen coordinate
system (UTM nad 83 Z18)
2. Digitalize the 2D polylines of the digital historical geo-
referenced plan levels and sections images
3. Construct the 3D Sigma-Lamaque mines
developments (pit, shafts and drifts)
4. Model the 3D Sigma-Lamaque mines stopes
5. Combine various digital databases from historical
logs (PDF) and spreadsheet files (Excel, Drill-A,
Prolog)
6. Collect all available diamond drill hole (DDH) assays
7. Compile, homogenize and simplify the DDH
lithological markers
Phase 1
InnovExplo
homogenized the
historical data
archived in the
Sigma-Lamaque
mines vaults
InnovExplo
produced a 6-
terabytes hard
drive database
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6The Integra « Gold Rush Challenge » Case Study
Historical 3D Digital Hard Data Integration
Pits, Shafts and Developments
3D Construction3D Stopes
Underground Geology
and Veins Drift Mapping
Phase 1
Developments draped on
surfaces modelled from the 2D
polylines digitalized on the geo-
referenced plans and sections
2D polylines digitalization of the geo-referenced plan levels and sections
3D stopes surfaces from the 2D digitalized polylines
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3D Surfaces from digitalized polylines:
Lamaque Mine: Main mineralized plugs
Sigma Mine: 43 production veins7The Integra « Gold Rush Challenge » Case Study
Historical 3D Digital Hard Data Integration
3D Mineralized Zones DDH Entry: Trace DDH Entry: Assays
3D DDH Trace: 36 830Validate various types of spreadsheet files (Excel, Drill-A, Prolog)
Build the DDH database: Collars position and deviation tests
DDH Assays: 16 055712 339 assays entries and validation
Phase 1
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8The Integra « Gold Rush Challenge » Case Study
Historical 3D Digital Hard Data Integration
Data entry of simplified geological lithologies
along the DDH (110 857 entries)
Phase 1
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9The Integra « Gold Rush Challenge » Case Study
« Top 21 » Exploration Targets Synthesis
InnovExplo Resulting Targets Validation and Classification:Phase 2
• Define ranking methods based on several key criteria for 561 selected gold exploration
targets interpreted by the « Top 21 » Gold Rush participants.
VALIDATION
Review
participants’
reports using
an unbiased
approach
CREATION
Build 2D and
3D objects for
each resulting
targets (x, y, z)
in a common
3D model
INTEGRATION
Integrate
participant’s
interpretations
(if available) in a
common 3D
model
CHARACTERIZATION
Generate a 2D and
3D potential
ranking map based
on the targets
characterization
synthesis
classifications
Step 1
Step 2
Step 3
Step 6
CLASSIFICATION
Produce an
exhaustive
exploration
targets synthesis
classification
table
Step 4
QUERYING
Recommend
the “best” of the
“best” resulting
« Top 21 »
exploration
targets
Step 5Phases
2-3
Phase
3
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10The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
Participants’ approaches can be summarized in 5 categories:
2D and pseudo-3D structural interpretations and regional corridors
2D and 3D geophysical and structural models
Pseudo-3D targets based on geological/metallogenical models
3D estimated resources zones (mine vicinities)
Data-driven and Knowledge-driven approaches
Phase 2 InnovExplo Targets Validation and Classification
• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Step 1
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11The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
InnovExplo Targets Validation and Classification• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Participants’ Approaches:
1. 2D and pseudo-3D structural interpretations and regional corridors
Team 64: Riedels model: Pseudo-3D
C-Shears Triangle Deeps and South
Triangle. 2D geophysical lineaments
interpretations in terms of Riedel
(very focused on one type of
structure). They state in their report: «
Many of these features are very
subtle to identify and may take a
trained eye ore even a touch of
imagination ».
Step 1
Phase 2
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12The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
InnovExplo Targets Validation and Classification• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Participants’ Approaches:
2. 2D and 3D geophysical and structural models
Team 86: 3D mineralized vein clusters
containing several individual auriferous veins
including a detailed analysis and 3D modelling
of multiple feeder faults in the well-drilled #4
Plug. A 3D model of the Main Lamaque diorite
to compare it with the mineralized clusters
distribution at Sigma, Lamaque, #5 Plug and
Parallel Zone. 3D model for the folded Main
Lamaque diorite and gold shoots. Interesting
and plausible model: Dextral compressional
flower structure; Folds (synclines and
anticlines), back-thrust faults and shear zones,
tilting. Size of individual deposits correlates
with the size of the hosting intrusions. The
dextral Manitou Fault could be the main
fault/fluid conduit?Step 1
Phase 2
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13The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
InnovExplo Targets Validation and Classification• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Participants’ Approaches:
3. Pseudo-3D targets based on geological/metallogenical models
Team 35: Simple depth and opening and ore shoot trend testing theories.
Deep target zones contours. New model: Trans-tensional tectonic regime with
eroded Timiskaming type sedimentary basin and intrusion emplacement
(plugs) followed by compression and mineralized veins (Flower structure).
Step 1
Phase 2
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14The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
InnovExplo Targets Validation and Classification• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Participants’ Approaches:
4. 3D estimated resources zones (mine vicinities)
Team 84: Resource estimation exercise: Assay
data validation, creation of solids, statistics
and block modelling completed with GEMs.
Includes: 1) 102 mineralized zones (capped at
25 g/t Au) modeled relative to Sigma-Lamaque
developments; 2) Composited assays at 3 g/t
Au and dataset used as a guide to capture
broader high grade core of the granodiorite (i.e.
two main plugs visually stood out and were
modeled: Bulk1 and Bulk2); 3) Existing
potential corridors modeled to extend up
plunge to surface linking with surface deeper
mine Sigma #45 zone with surface known
deposits; 4) Future prospect: Outline sub-
horizontal high grade veins and 3D plane of
one of the main sub-horizontal high grade vein
with granodiorite outlines projected on the
plane to show areas of higher favorability of
finding new high grade material.
Step 1
Phase 2
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15The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Reports Reviews
InnovExplo Targets Validation and Classification
• The evaluation was unbiased without knowing the authors, judging and/or discriminating any new
geoscientific interpretations and approach used for the resulting targets.
Participants’ Approaches:
5. Data-driven and Knowledge-driven approaches
Team 38: 3D surfaces for first order
intrusions (I2J + I1C). 3D surfaces for
faults model (1st, 2nd and 3rd order).
Predictive bloc model (50x50x50m; 2500
m deep). Virtual reality (Oculus Rift) used
to extract new data trends. Team 38
stated « This approach is very similar to
that described in Fallara et al. (2006) in
which the data is integrated into a
GOCAD® “voxet” and a decision tree is
defined to reduce the target areas to a
manageable size ». Fallara et al. (2006)
had chosen for their examples a binary
logic (Yes/No) approach to illustrate the
queries strengths of the gOcad®
software. SGS Geostat chose the Wofe
(weights of evidence) approach to define
classes and ranking scores.
Step 1
Phase 2
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16The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Integration
Roughly 800 digital files were sent with the « Top 21 » reports
Step 2
The majority of the « Top 21 »
resulting targets did not exist
as 3D digital objects and were
manually traced by participants
on their report’s figures
Phase 2
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17The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Build Targets
Step 3
InnovExplo 3D Target Modelling Methodology
Build 2D and 3D objects for each resulting targets (x, y, z) in a common 3D model
Phase 2
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18The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: Classification
InnovExplo produced an exhaustive characterization systematically
based on thematic attributes excerpted from the « Top 21 » reports
Step 4
InnovExplo used this characterization
as a final ranking multiplication criteria
Phase 2
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1:50 000 map of the 561 targets projected at the surface
The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: 2D Potential MapInnovExplo generated a 2D potential ranking map established on the
characterization of the targets based on their interpretation approach
Step 5
19
Targets characterization by their interpretation
method:
1. Knowledge-driven
2. Data-driven
3. Conceptual (areas and geological corridors)
4. Geophysical
Phase 2
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The Integra « Gold Rush Challenge » Case Study
Exploration Targets Synthesis: 3D Potential Cells
Perspective view looking East
Step 5
20
InnovExplo interpolated the targets 3D potential ranking characterization
based on their interpretation approach in a voxet regions cells
Au > 10 g/t (Sigma-Lamaque Assays )
« Top 21 » Gold Rush participants’ 530 targets
centroids
Targets characterization by their interpretation method:
1. Knowledge-driven
2. Data-driven
3. Conceptual (areas and geological corridors)
4. Geophysical
Geophysical
Data-DrivenConceptual
Knowledge-Driven
Phase 2
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Perspective view looking EastPerspective view looking NE
Method - M1Step 5
21The Integra « Gold Rush Challenge » Case Study
« Top 21 » Targets Rankings: Regional-Scale Results
InnovExplo (IE) Mean Class Ranking (Method 1 – M1):
Phase 3
Method – M1
Au > 10 g/t (Sigma-Lamaque Assays )
« Top 21 » Gold Rush
participants’ targets
centroids, scaled with the
Mean Class Ranking
Targets regions painted with
the Mean Class ranking
(ranking_mean_class_IE)
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Perspective view looking EastPerspective view looking NE
Method – M2
Step 5
22The Integra « Gold Rush Challenge » Case Study
« Top 21 » Targets Rankings: Regional-Scale Results
Method Approach Ranking (Method 2 – M2)
Method – M2Au > 10 g/t (Sigma-Lamaque Assays )
« Top 21 » Gold Rush
participants’ targets
centroids, scaled with the
Method Approach RankingTargets regions painted with
the Method Approach Ranking
(ranking_method_reg)
Phase 3
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Perspective view looking EastPerspective view looking NE
Method – M3
23The Integra « Gold Rush Challenge » Case Study
Step 5
« Top 21 » Targets Rankings: Regional-Scale Results
Exploration Ranking (Method 3 – M3)
« Top 21 » Gold Rush
participants’ targets
centroids, scaled with an
Exploration Ranking
multiplied by the
InnovExplo Factor
Targets regions painted with
the regional Exploration
Ranking (ranking_GG_reg)
Method – M3Au > 10 g/t (Sigma-Lamaque Assays )
Phase 3
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Perspective view looking NE
Method – M4
24The Integra « Gold Rush Challenge » Case Study
Step 5
« Top 21 » Targets Rankings: Regional-Scale Results
Total Number of Target Intersections Ranking (Method 4 – M4)
Maximum possible number of
intersecting targets within a
cell is 10 for both the regional-
scale and mine-scale voxets
Phase 3
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Perspective view looking NE Perspective view looking NE
Method – M4
25The Integra « Gold Rush Challenge » Case Study
« Top 21 » Targets Rankings: Regional-Scale Results
Total Number of Target Intersections Ranking (Method 4 – M4)
Step 5
Method – M4
« Top 21 » Gold Rush participants’
targets total number of intersections,
from two to 10 possible intersections,
illustrated on the plan and sections of
the regional-scale voxetTargets regions painted with
the Total Number of Target
Intersections Ranking
(target_int_Number_reg)
Phase 3
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26The Integra « Gold Rush Challenge » Case Study
« Top 21 » Exploration Targets Synthesis: Querying
Summary of 3D Queries based on Best Rankings PercentilesPhase 3
• 3D queries were defined using simple Boolean queries (Q) to identify the best theoretical targets of
the area based on:
Step 6Examples of 3D queries (Q) for the regional-scale and mine-scale voxets
Method
M3-
M3a-
M1-
M2-
Method
M3-
M3a-
M1-
M2-
Thresholds set systematically above the 75th percentile with the resulting total
remaining cells applied to both the regional-scale and mine-scale voxets
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Targets 3D Queries: Regional-Scale Results
Summary of 3D Queries (Q): Q01 through Q05
Q01 = M3 cells Q02 = M3a cells Q03 = M1 cells Q04 = M2 cells
Results
Intersections
∩
Union
U
Q01’ = ∩ (Q02 -Q03-Q04) Q02’ = ∩ (Q02-Q03) Q03’ = ∩ Q04
Q05 = U (Q01-Q02-Q03-Q04) 27The Integra « Gold Rush Challenge » Case Study
Step 6
User-defined 3D queries to extract the
best of the best « Top 21 » Gold Rush
exploration targets
Phase 3
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Distance to drill holes < 100 m
Mine-Scale Sections illustrating Rankings and Attributes
28The Integra « Gold Rush Challenge » Case Study
Step 6
North-South 1:10 000 cross-section (looking West) spaced at 100 ± 50 m
S N
S294 350 m.E.
Attribute 1
SigmaLamaque
MainPlugs
looking West
La
ma
qu
e S
ou
th
Sig
ma
-La
ma
qu
e a
nd
/o
rF
ou
rnie
r
0 m
100 m
Targets Intersections Ranking
S N
S294 350 m.E.
Method 4
Production Veins
SigmaLamaque
MainPlugs
Sig
ma
-La
ma
qu
e a
nd
/o
rF
ou
rnie
r
La
ma
qu
e S
ou
th
Production Veins
Phase 3
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The Integra « Gold Rush Challenge » Case Study 29
Worldwide Brainstorming
Session
Multi-disciplinary
Ideas
Low-risk high return investment
tag
Motivated over 1,000 hours
of brainpower data crunching
Created a mega-database
interpretation
Rendered over 3,000 pages
reports + video submissions
Generated new and
outside the box
innovative approaches
and ideas for future
exploration programs
Donated generous cash
prizes
Received in exchange
(hopefully) their next big
gold discovery
« G
old
Ru
sh
Ch
alle
ng
e »
Imp
act
for
Inte
gra
Go
ldSession: Data ManagementQ1: Why does InnovExplo see value and/or impact in data management?
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1 year investment return ?? Qualified as Au Moz ++ / ++ Production Years ??The Integra « Gold Rush Challenge » Case Study
Session: Data ManagementQ2: What business value or concerns are addressed?
30
TimeImpactAu Ounces
10 Moz
+ 0 Moz
+ ?? Moz
Technologies and
techniques
implementations
Production
> 500 highly
prioritized
quality
exploration
targets
75 yrs.
+ ? yrs.?
« Gold Rush Challenge »
+75 Years1932
ExplorationProduction 2010
Closure
InnovExplo produced 6 terabytes
historical hard database compilation
Future Exploration Program
? Future Production ?
20??
InnovExplo validated, ranked and
queried Top-21 targets
1 y
ea
r sp
an
Investing 1
year focused
on adding
the historical
hard data
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31The Integra « Gold Rush Challenge » Case Study
Integra Gold Corporate,
workers and technical
team
« Gold Rush Challenge »
Participants
InnovExplo Team
Acknowledgements
Top
21
1
SGS Geostat
2
Data Miners