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Automated Core Imaging:Opportunities for Integrating Hyperspectral
Mineralogy and Structural Orientation Data for More Robust Structural Interpretations
Cassady Harraden, PhD
Laurel Stothers, MSc
Cari Deyell-Wurst, PhD
Corescan
Structural Assessment in Ore Deposits
• Structural complexity of ore
deposits vary → BUT
measurements remain
fundamental to characterizing and
understanding most ore bodies.
• In exploration, data used to:
– map vein distribution/density
– understand fluid pathways
– assess controls on
mineralization/deposit
geometry
• In mining, data used in:
– predicting geotechnical
behavior of an orebody
– mine planning decisions
– economics of ore recovery Example of Acoustic Televiewer (ATV) structural data used to interpret a complex, structurally-controlled uranium deposit in
the Athabasca basin, Canada. The difference in orientation of the mineralized VS non-mineralized structures aided in updating
both the geology model and the regional paragenesis (from Benedicto et al., 2021). ACON0011
Traditional Method: Manual Structural Logging
• Structural data from drill core traditionally collected manually:
– Orientations: alpha/beta angles (planes) and gamma angles
(lines) collected using manual tools → more recent tools help
speed up data collection (e.g. IQ-Logger), but still require
manual measurement
– Mineralogy: Visual determination of mineralogy in and around
measured structures can be challenging
Core
Photo
Montmorillonite
Map
Pyrophyllite
Map
Kaolinite
Map
60mm
Low Match High Match Low Match High Match Low Match High Match
Reflex IQ-LoggerACON0011
Opportunities for Automated Methods
• While successfully applied in exploration and
mining, manual structural data collection
methods are labor intensive, time consuming,
and can lead to incomplete or inconsistent
results.
• Automated core imaging allows for the
collection of high volumes of consistent drill
core information from multiple, co-registered
sensors including visual, geochemical, and/or
mineralogical data.
• Compared to manual data collection,
automated methods increase not only the
speed and efficiency of data collection, but
also the density of structural measurements
that can be collected downhole.
Objective estimation of parameters
Consistent data collection
Improved data coverage
Rapid data collection and calculation
ACON0011
Automated Structural Detection and Measurement
• Structural features can be
automatically detected and oriented
using data derived from an automated
hyperspectral imaging system.
• High-resolution 3D profiler and core
imagery data are used to
automatically identify and orient
structures.
• This is accomplished through
contouring/gradient calculations,
segmentation, morphological filtering,
and adaptive feature thresholding
methods*.
*To learn more, check out Laurel Stothers’ Speed Talk – ST.055 Data inputs Gradient calc/Segmentation Adaptive feature thresholding Calculate result
ACON0011
Speed Talk ST.055
Speed Talk ST.055: Adaptive Feature Detection For Improved Measurement
of Structural Orientations Using Core Imagery
Laurel A. Stothers, Cassady L. Harraden
Integrating Hyperspectral Mineralogy
• While orientations of these features are
important, mineralogy in and around
structures is also a key piece of information.
• For automated core imaging systems where
the hyperspectral mineralogy is co-
registered, the mineralogy of structures can
be integrated with the automatically
measured orientation values.
• Methodology:
1. define the spatial extents of structural
features in the image.
2. apply a series of multiple-distance
buffers (user-defined) within (and
proximal to) the defined structural
feature.
3. query the co-registered hyperspectral
mineralogy image within the buffered
distances.50mm
Core
photo
1. Define
spatial
extents of
feature
2. Apply
multiple-
distance
buffers
Automatically
identified
structure
Automatically
oriented
structure
3. Query
hyperspectral
mineralogy
image
Reported
mineralogy
within
structure
Structure
extent buffer
5mm
distance
buffer
Kaolinite White Mica
Kaolinite + White Mica CarbonateACON0011
Opportunities for Integrated Structural Data
• Structural orientation measurements with integrated hyperspectral mineralogical data can be used to delineate sets
of structures (fractures, veins, etc.) even in deposits with seemingly uniform structural orientations.
• Example of automatically detected and orientated joint orientations colored by primary hyperspectral mineralogy
within the joint from an orogenic gold deposit (rose diagrams):
Undifferentiated
mineralogy
Amphibole-Chlorite
n = 275
Biotite
Quartz
White mica-carbonate
Carbonate-White mica
n = 275
Colored by
primary
mineralogy
within open
joint
ACON0011
Opportunities for Integrated Structural Data
Undifferentiated
mineralogy
Chlorite
n = 710
Featureless Spectrum
Montmorillonite
Carbonate
n = 710
• Reporting the mineralogy for fracture orientations has implications for late-stage alteration fluid
pathways/paragenesis in exploration models and ground support requirements and fragmentation in mine planning.
• Example of automatically detected and orientated fracture orientations colored by primary hyperspectral mineralogy
within the fracture from a porphyry Au-Cu deposit (rose diagrams):
Colored by
primary
mineralogy
within
fracture
ACON0011
Opportunities for Integrated Structural Data
Kaolinite +
white mica
n = 710
Undifferentiated
5mm buffer
mineralogy
White
mica
Gypsum
Carbonate
Other
minerals
n = 118
n = 193 n = 241
n =125
• The mineralogy immediately proximal to the structures can also be integrated with the measured orientations →
implications for paragenesis/fluid pathways + processing response and mine planning.
• Example of automatically detected and oriented fractures colored by primary hyperspectral mineralogy within 5mm
buffer of the fracture (wall rock alteration) from a porphyry Au-Cu deposit (pole to plane density plots, colored by
density):
n = 33
Low density High density
ACON0011
Summary: Applications to Exploration and Mining
• New developments allow for measurements of core morphology and structural features (e.g., fractures, faults, and veins) that can provide vital information for the successful exploration and development of ore deposits.
• Structural data is vital to successful exploration in mapping vein distribution and density as well as understanding fluid pathways, controls on mineralization and deposit geometry.
• Structural data is also fundamental in the accurate characterization of structural features and key to predicting the geotechnical behavior of an orebody → guides mine planning decisions and affects the economics of ore recovery.
• The application of automated core imaging technology to fault, vein, fracture/joint orientation combined with mineralogy assessment provides the opportunity for increased data output and targeted data points to be acquired over shorter time frames, consistently → robust structural assessment at various scales.
• Automated imaging systems provide an opportunity to improve sampling statistics, provide robust datasets for informed decision-making while also maximizing value from recovered drill core → leads to better, informed geological and engineering decisions.
ACON0011
Core
photo
3D Core
Profile
Structure Pixel
Heat Map
Mineral Map and
Structure Traces
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Disclaimer
Cassady Harraden, PhD | [email protected]
Laurel Stothers, MSc | [email protected]
Cari Deyell-Wurst, PhD | [email protected]
