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© 2016 Mira Geoscience Ltd.
Towards Integrated Interpretation
John McGaughey
CENTRE FOR EXPLORATION
TARGETING
PERTH, OCTOBER 2016
• target (x, y, z) = f (geology, alteration, structure, geochemistry, geophysics, …)
Drillhole targeting
Geohazard
courtesy Glencore
hazard (x, y, z, t) = f (rock quality, geometry, stress, seismicity, geology, …)
Geohazard
November 6, 2003
March 4, 2004
June 3, 2004
August 19, 2004
August 29, 2004
November 30, 2004
July 7, 2005
July 24, 2005
August 16, 2005
October 27, 2005
October 31, 2005
April 3, 2006
May 21, 2006
September 11, 2006
June 22, 2007
December 1, 2007
March 4, 2008
April 19, 2008
December 24, 2008
courtesy Glencore
The petroleum industry experience
• exploration is model-driven, evidence-based
• integrated interpretation: one common earth model consistent with
geological, geophysical, geochemical, petrophysical data
• validation is essential
Integrated interpretation – what we’ve learned
• multi-disciplinary, interpretive at every step, iterative
• geoscientific judgement is more important than computational details
• the right tools are important; the right team is more important
• culture change is required to break sequential workflows
• formal planning is required to connect objectives to interpretation
“The deployment of 3D earth modelling
technology in daily operational work will
require changes in paradigms and work
processes.”
- Garrett et al. (1997)
Where are we going?
• dedicated focus on each key step in the process:
• planning and data management
• integrated interpretation and validation
• communication, collaboration and analysis
• build the skilled, multi-disciplinary team required as leaders to deliver
software, training, workshops, consulting services
• develop a software ecosystem to support this vision through third-party
relationships and internal software development
geophysical data
geological data
inversion model
geological modelwhat is the connection?
Conventional 3D modelling
Integrated interpretation
• model creation, update
• model validation
Flin Flon Mining District, Manitoba and Saskatchewan. NRCAN Open Government licence
observed data
final model
geometry
correction
starting model
Integrated Interpretation - Mutaroo
Regionally extensive magnetite-bearing sedimentary strata within
Minotaur’s Mutooroo project area.
Example of developing a geologically-based model through geophysical
modelling.
Under cover
Inputs
- High resolution aeromagnetic survey data
- 7 Drill holes (depth of cover constraint and magnetic susceptibility).
Integrated Interpretation - Mutaroo
• interpret and model subsurface domains…
Model Validation
54000.0
56000.0
58000.0
60000.0
62000.0
64000.0
66000.0
TMI (nT)
485000 E
485000 E
487500 E
487500 E
490000 E
490000 E
6 405 000 N 6 405 000 N
6 407 500 N 6 407 500 N
6 410 000 N 6 410 000 N
6 412 500 N 6 412 500 N
54000.0
56000.0
58000.0
60000.0
62000.0
64000.0
66000.0
TMI (nT)
485000 E
485000 E
487500 E
487500 E
490000 E
490000 E
6 405 000 N 6 405 000 N
6 407 500 N 6 407 500 N
6 410 000 N 6 410 000 N
6 412 500 N 6 412 500 N
• homogeneous domain forward
modelling
• correspondence with observed
data validates modelled domains
Observed
Calculated
Integrated Interpretation - Mutaroo
Courtesy Minotaur Exploration
The technical team
• exploration project management
• economic geology
• resource evaluation
• structural interpretation
• structural restoration
• geophysics
• geochemistry
• geotechnical engineering
• targeting
• analytics / machine learning
• software design and development
Effective modelling for decision making value
• organizing and documenting the inputs, outputs, and process
• transforming data into a consistent 3D model
• communication, collaboration, analysis
data
management
integrated
interpretation:
the 3D model
communication,
collaboration,
analysis
GOCAD®
3D/4D
Data Sets
Monitoring3rd Party
Databases Project Files
Documents
Reports
3D VisualizationMachine Learning
Web Browser
Access
Geoscience INTEGRATOR
SKUA-GOCAD Mining Suite
• multi-disciplinary modelling
• fully integrated: equal standing of geological, geophysical,
geochemical, petrophysical data
• input can be raw data or basic models from silo platforms
courtesy Glencore
SKUA GOCAD Mining Suite – New Bundles
Mining
Essentials
Mining
Basic
Mining
Integrated
Interpretation
Mining
Advanced
Geophysics
Mining
Stratigraphic
Modelling
3D viewer,GIS,
modelling, utils
3D viewer,GIS,
modelling, utils
3D viewer,GIS,
modelling, utils
3D viewer,GIS,
modelling, utils
3D viewer,GIS,
modelling, utils
maps, sections,
log display
maps, sections,
log display
maps, sections,
log display
maps, sections,
log display
maps, sections,
log display
section analysis,
interp, correlation
section analysis,
interp, correlation
section analysis,
interp, correlation
section analysis,
interp, correlation
volume explorer,
seismic interp
volume explorer,
seismic interp
volume explorer,
seismic interp
SKUA structural
implicit modelling
SKUA structural
implicit modelling
SKUA structural
implicit modelling
3D voxet and sgrid
geostatistics
geophysical 3D
grid construction
SKUA stratigraphic
and fault analysis
potential fields
forward modelling
geophysical
forward modelling
SKUA geologic
grids, geostatistics
Sparse parametric
modelling, ioGas,
targeting workflow
geophysical
inversion
Geoscience ANALYST
3D drillhole and geologic map database of the Flin
Flon Mining District, Manitoba and Saskatchewan.
NRCAN Open Government licence
Integrated Interpretation - strategic R&D investment
• Centre for Excellence in Mining Innovation (CEMI):
• “Mining Observatory Data Control Centre”
• Ultra Deep Mining Network (UDMN):
• “4D Real-Time Geotechnical Hazard Assessment…”
• Canadian Mining Innovation Council (CMIC):
• “Integrated Multi-Parameter Footprints of Ore Systems…”
• National Research Council (NRC-IRAP):
• “MinSim: A Mineral Exploration Simulator”
• INRS / MITACS Accelerate Program:
• “…Statistical Algorithms”
Footprints Project - Research Problems
Test the following hypotheses:
1. Methods of machine learning applied to large, complex mineral exploration
data sets will yield recognition of new multi-variate relationships.
2. Methods of interpreting new multi-variate relationships can characterize
domains of mineral system footprints.
3. Methods of interpreting spatial relationships amongst footprint domains will
result in new methods for vectoring toward the mineral system core.
Data Integration Objectives
Development of data integration methods:
1. methods of managing multi-disciplinary exploration data
2. methods of representing data through 3D models
3. methods of representing 3D models to machine learning
4. methods of machine learning for footprint recognition
5. methods of vectoring based on footprint recognition
Input to Machine Learning
In what form?
• a computer model of wireframe surfaces and points
• wireframe surfaces: faults, contacts, domain boundaries
• points: (x, y, z, property 1, property 2, …. property n)
What information does the CEM
contain?
• lithology, alteration, structure,
geochemistry, mineralization,
physical properties, geometry,
topology
Research Methods
(obs 1, x, y, z, property 1, property 2, … property n)
(obs 2, x, y, z, property 1, property 2, … property n)
(obs 3, x, y, z, property 1, property 2, … property n)
Are there patterns amongst the properties that enable us to group
observations in a meaningful way?
Strategic R&D investment
Towards integrated interpretation
• it will happen—similar drivers exist in today’s mineral industry as
existed in the oil industry when conventional resources became scarce
• technology, methods, and culture will evolve to meet the challenge
• for Mira Geoscience, it means we are growing
• R&D investment
• building the team
