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MULTI-SCALE SPECTRAL SENSING APPLIED TO
MINERAL AND HYDROCARBON EXPLORATION AND
PRODUCTION – PART II
Carlos Roberto de Souza Filho
Instituto de Geociências - UNICAMP
Rio de Janeiro, 20-24 Agosto 2018
Carlos Roberto de Souza Filho (IG-UNICAMP)
Saeid Asadzadeh (IG-UNICAMP)
Rebecca Scafutto (IG-UNICAMP)
Rosa Pabón (IG-UNICAMP)
Wilson Oliveira (PETROBRAS)
MULTI-SCALE INVESTIGATION OF HYDROCARBON PLAYS: AN ASSESSMENT
BASED ON ORBITAL MULTISPECTRAL, AIRBORNE AND CLOSE-RANGE
HYPERSPECTRAL DATA
Rio de Janeiro, 20-24 Agosto 2018
Rio de Janeiro, 20-24 Agosto 2018
OUTLINE
 General Comments about “multi” approaches
 Background on multiscale petroleum hydrocarbon detection
 experiments with hyperspectral data
 experiments with World-View 3 and ASTER data
 Case study focused on exposed bituminous sandstone (“tar sands”) plays
using hyperspectral and multispectral data
Multi-sensor …
Multi-source …
Multi-platform …
Multi-scale …
Ground & Lab
hyperspectral
Airborne
hyperspectral
We are pretty much
there in the VNIR-
SWIR range !
Orbital
“super”spectral
HISUI
EnMAp
PRISMA
BACKGROUND: OIL SIGNATURES
1700nm 2300nm
• MACRO/FIELD EXPERIMENT
 Conducted at the Rocky Mountain Oilfield Testing Center
(ROMTC), in Casper (Wyoming), US.
BACKGROUND – CONTROLLED EXPERIMENTS
• MACRO/FIELD EXPERIMENT
 4 types of HCs and three mineral substrates (sandy,
clayey and dolomitic soils, with varying particle size)
were selected for the experiment.
 The HCs were mixed to the mineral substrates making a
total of 12 macro-samples.
 The mixtures were prepared in the field, in wooden
boxes (“bins”)
BACKGROUND
• MACRO/FIELD EXPERIMENT
(i)
distribution and
preparation of the
bins in the field
(ii)
addition of the
clayey soil
substrate and light
crude oil to one of
the bins
(iii) measurement
of the substrate
using a FieldSpec
FR instrument.
BACKGROUND
• MACRO/FIELD EXPERIMENT
HC Bin Mixture Plan
Bin Substrate Hydrocarb
on
1 1 A
2 1 B
3 1 C
4 1 D
5 2 A
6 2 B
7 2 C
8 2 D
9 3 A
10 3 B
11 3 C
12 3 D
Legend
Substrates
1 – Sandy Soil (Topsoil)
2 – Dolomite-rich Gravel/Soil Mix
3 - Clayey Soil (Modified Base)
Hydrocarbons
A – 29 API Crude
B – 41 API Crude
C – Diesel
D – Unleaded Gasoline
MIXTURE PROTOCOL
- 18L of HC, 1.0 hour prior to aircraft flyover
- 18L of HC, 30 minutes prior…
- 18L of HC, 15 minutes prior…
BACKGROUND
• MACRO/FIELD EXPERIMENT
 PROSPECTIR VS and SEBASS co-located sensors on a
single Twin Otter on same roll-controlled mount.
 ONLY PROSPECTIR VS data approached in this session
Spectral resolution of 357 bands (VNIR-SWIR)
Spatial resolution of 60 cm on the ground
BACKGROUND
Physics: Reflective BandsEmissive Bands
Reflected sunlight Direct thermal emission
Complex phenomena Simpler phenomena
Surface reflectivity Surface temperature
Reflectance Emissivity
.4 .6 .8 1 2 4 6 8 10 20
Wavelength (
LWIRMWIRSWIRNIR
EnergyperBand
0
2
4
6
8
10
EnergyperBand
0
2
4
6
8
10
2
4
6
8
10
.4 .6 .8 1 2 4 6 8 10 20
Wavelength (µm)
LWIRMWIRSWIRNIR
REFLECTED SUNLIGHT THERMAL EMISSION
25000 10000 5000 2500 1667 1250 1000 500
Wavenumber (cm -1
)Wavenumber (cm -1
)
VIS
ProSpecTIR VNIR-SWIR
Sensor
BACKGROUND
• MACRO/FIELD EXPERIMENT
Flight line
Aerial view of the contaminated bins
(numbered 1 to 12) and indication of the
flightline along which hyperspectral
imagery was acquired with the ProspecTIR
sensor
BACKGROUND
• MACRO/FIELD EXPERIMENT
MEASUREMENT 1 MEASUREMENT 2 MEASUREMENT 3
SANDYSOILDOLOMITICSOILCLAYEYSOIL
a b c
d e f
g
h i
Bin1 - field spectra
Bin1 - imagery spectra
Lab. Spectral library
Bin1 - field spectra
Bin1 - imagery spectra
Lab. Spectral library
Bin1 - field spectra
Bin1 - imagery spectra
Lab. Spectral library
Bin6 - field spectra
Bin6 - imagery spectra
Lab. Spectral library
Bin6 - field spectra
Bin6 - imagery spectra
Lab. Spectral library
Bin6 - field spectra
Bin6 - imagery spectra
Lab. Spectral library
Bin11 - field spectra
Bin11 - imagery spectra
Lab. Spectral library
Bin11 - field spectra
Bin11 - imagery spectra
Lab. Spectral library
Bin11 - field spectra
Bin11 - imagery spectra
Lab. Spectral library
HC – 18 L (1h) HC – 36 L (30min) HC – 54 L (15 min)
DieselLightOil(API41)HeavyOil(API29)
• MACRO/FIELD EXPERIMENT
• Yellow pixels = mapped HC-bearing targets.
• Scattered yellow pixels distant from the bins in the southern sector of the figures correspond to residues of contaminated soils and HCs
and plastic paints
1h 30min 15min
1
2
3
4
6
5
8
10
12
7
9
flightline
Image 1 – HC 18L
(A)
1
2
3
4
6
5
8
10
12
7
9
Image 2 – HC 36L
11
(B)
1
2
3
4
6
5
8
10
12
7
9
Image 3 – HC 54L
HC
11
(C)
HCHC
flightline
BACKGROUND
SIMULATION EXPERIMENT – WORLDVIEW-3
Same airborne ProspecTIR hyperspectral imagery acquired in Casper over twelve synthetic
oil-shows was resampled to WV-3 spectral resolution.
SIMULATION EXPERIMENT – WORLDVIEW-3
ASTER’s band 8 coincides with 2300 nm feature.
WorldView-3’s band 12 (SWIR-4) coincides with 1700 nm feature.
ASTER
WorldView-3
SIMULATION EXPERIMENT – WORLDVIEW-3
Sensor
# hit pixels per box Total
1 2 3 4 5 6 7 8 9 10 11 12 Pixels Boxes
WV-3 9 20 18 22 13 34 27 36 4 19 16 13 231 12
AST 3 9 10 8 8 16 14 11 0 4 6 2 91 11
2.5x
Resampled WV-3 data (16 bands, 60cm) able to detect all 12 targets with 2.5 times
higher average score relative to ASTER (9 bands, 60 cm).
SIMULATION EXPERIMENT – WORLDVIEW-3
REAL CASE STUDY – TAR SANDS
Characterize bituminous sandstones at multiple scales using
spectral technology.
Evaluate the consistency of HC’s signatures for bitumen content
estimation.
Delineate the alteration mineralogy associated with bitumen
emplacement in sandstone beds.
Evaluate the merits of ground-based imaging data in oil-sand
mining.
Demonstrate the capability of WorldView-3 data to detect oil
signatures in real scenarios.
ANHEMBI STUDY AREA
The area under study is located in the Paraná Basin, southern Brazil.
The sandstone beds of the Pirambóia Formation are widespread in the region.
Pirambóia Formation is a succession of fluvial and aeolian sandstones of the lower
Triassic.
Two facies are recognized: thick aeolian sand sheet facies at the base, overlain by
aeolian dune and interdune strata.
GEOLOGY OF THE AREA
Bitumen is derived from the Permian Irati shales, thermally matured by Serra Geral
magmatism, and then migrated along the contacts of diabase dykes to impregnate
the eolian sandstones.
The Anhembi deposit is estimated to contain about 5.7 million barrels of oil in-place
based on average bitumen content of 5.5 wt. %.
The oil is immature, very heavy, and highly viscose.
DATA COLLECTION
HAND SAMPLE analysis using nonimaging (FieldSpec-4) and imaging (sisuCHEMA)
systems (n =15).
WALL/FACE MAPPING using the AisaFENIX hyperspectral imaging system (3 walls).
AIRBORNE MAPPING using the same AisaFENIX system.
WORLDVIEW-3 satellite multispectral data
POINT SPECTROSCOPY
Five individual absorption features were analyzed using the Absorption-based
Mineral Spectral Analyst software (AMISA-UNICAMP).
The wavelength position, depth, and asymmetry of the features were considered
for analysis and comparison.
X-ray diffraction (XRD) was used to verify the alteration mineralogy.
C-H
Al-OH
C-H
IMAGING SECTROSCOPY – HAND SAMPLES
An oil-rich rock sample was scanned by sisuCHEMA hyperspectral imaging
instrument.
Striping and illumination variations were discarded and the image was smoothed
by Sav-Gol filter.
Spectra validated against point measurements.
RGB photo SisuCHEMA color composite
Vertical walls of the oil-sand deposit were scanned on the ground using an
AisaFENIX hyperspectral system.
The 4x2 binning options (corresponding to 450 spectral bands) were used.
For atmospheric compensation, a single calibration panel made of BaSO4 was used.
1
2
Outcrop azimuth
Local time Solar
elevation
Solar
azimuth
Distance
(m)
GSD
(cm)
Illumination
condition
Physical
condition
1 135° 10:30 37.2° 30.4° 10 1.5 Direct sunlight dry
2 75° 11:12 41.3° 19.1° 30 3.0 Direct sunlight dry
IMAGING SECTROSCOPY – FACE MAPPING
11h00 carlos roberto 21 08 botafogo
AisaFENIX hyperspectral scanner on board a twin-engine Seneca II (Piper) airplane
Altitude of 915 m at 02:14 PM local time
The hyperspectral data were acquired in a clear sky condition with a nominal GSD of
35 cm. Data resampled to 1.0 m spatial resolution using a pixel aggregate function.
8x2 binning mode within which 363 co-registered spectral bands are contained
between 380–2500 nm wavelengths
Radiance data converted to apparent surface reflectance using the ATCOR
atmospheric correction software
IMAGING SECTROSCOPY – AIRBORNE MAPPING
DATA PRE-PROCESSING – HYPERSPECTRAL DATA
A workflow was devised for preprocessing of the hyperspectral data.
The depth of Al–OH feature was determined by polynomial fitting.
The total bitumen content (TBC) the samples/pixels were estimated by employing
the two-bands normalization method (Rivard et al. 2010).
WV-3 MULTISPECTRAL IMAGING
VNIR+SWIR imagery over target area was acquired by Digital Globe on February, 2016.
Data delivered as ‘at-surface reflectance’ resampled to 7.5m resolution.
A combination of feature tracking (applied to continuum-removed data) and match
filtering techniques were used to map the distribution of oil-sands
RESULTS – POINT SPECTROSCOPY
The clay mineralogy was identified to be dominated by montmorillonite.
Montmorillonite is present in almost all samples, including the impregnated ones,
implying that the clays are in an intimate mixture with bitumen.
The oil-sands emplacement was associated with the loss of iron (Feox) feature and
an increase in clay content.
unimpregnated
sandstones
Oil-sands
RESULTS – POINT SPECTROSCOPY
The TBC of the oil-sand samples was observed to vary between 6 to 11.5 wt. %.
The TBC showed proportionality to the depth of the absorption features at ~1700
and 2300 nm.
The feature at 2300 nm is very distinct and more pronounced, but the one at 1700
nm is remarkably more correlated to the TBC. R2: 0.98 vs. 0.95.
The TBC was inversely proportional to the clay content of the samples.
RESULTS (sisuCHEMA vs FieldSpec-4)
There is a correspondence in the overall spectral shape of the two datasets,
especially >1850 nm.
There are three differences between the two series:
The pixel spectra at around 1650 nm is unusually high.
The image data is noisier between 1500–1800 nm;
The shape of the HC feature at 1700 nm is modified in the image spectra.
RESULTS – IMAGING SPECTROSCOPY
The bitumen content of the rock is unevenly distributed in the scale of a hand
sample and is controlled by lamination and clay content of the sandstone.
The montmorillonitic clay is ubiquitous and occurs virtually in all pixels.
RESULTS – IMAGING SPECTROSCOPY
The data processing workflow was effective in increasing the SNR of the data.
Spectral denoising was crucial in retrieving the overall shape of the HC’s absorption
features.
Calculated over the panel (~450 pixels)
RESULTS – IMAGING SPECTROSCOPY
At outcrop scale, the TBC is controlled by sedimentary facies: interdune: bitumen poor vs.
sand sheet: bitumen rich.
RESULTS – AIRBORNE IMAGING SPECTROSCOPY
The close association of bituminous outcrops with clays is because besides
intimate mixing, the two components are areally mixed in the sub-meter scale.
RESULTS – WV3
The HC feature at WV-3 band SWIR-4 (band 12) was present within a large part of the
oil-sand pixels.
There is a reasonable match between WV-3 and airborne maps.
green
vegetation
SUMMARY & CONCLUSIONS
The HC signature was demonstrated to be consistent among scales
(maintaining a linear relationship with the TBC of samples/pixels)
and capable of estimating the TBC of oil-sands at all imaging scales.
Spectrally-derived TBC estimates of the deposit was determined to
vary between 0–11.5 % with a mean of ~5 wt. % - a good match
with available geochemical data.
The clay minerals (montmorillonite) were ubiquitous and mixed
intimately with bitumen at all studied scales.
WV-3 could resolve HC feature by its band 12 (SWIR band 4)
provided that the target is large enough to cover ~1/4 of a SWIR
pixel. The estimation of TBC was not successful using WV-3 data.
Geosciences Institute
University of Campinas
(UNICAMP)
http://portal.ige.unicamp.br/
beto@ige.unicamp.br
Thank you !

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  • 1. MULTI-SCALE SPECTRAL SENSING APPLIED TO MINERAL AND HYDROCARBON EXPLORATION AND PRODUCTION – PART II Carlos Roberto de Souza Filho Instituto de Geociências - UNICAMP Rio de Janeiro, 20-24 Agosto 2018
  • 2. Carlos Roberto de Souza Filho (IG-UNICAMP) Saeid Asadzadeh (IG-UNICAMP) Rebecca Scafutto (IG-UNICAMP) Rosa Pabón (IG-UNICAMP) Wilson Oliveira (PETROBRAS) MULTI-SCALE INVESTIGATION OF HYDROCARBON PLAYS: AN ASSESSMENT BASED ON ORBITAL MULTISPECTRAL, AIRBORNE AND CLOSE-RANGE HYPERSPECTRAL DATA Rio de Janeiro, 20-24 Agosto 2018
  • 3. Rio de Janeiro, 20-24 Agosto 2018 OUTLINE  General Comments about “multi” approaches  Background on multiscale petroleum hydrocarbon detection  experiments with hyperspectral data  experiments with World-View 3 and ASTER data  Case study focused on exposed bituminous sandstone (“tar sands”) plays using hyperspectral and multispectral data
  • 4. Multi-sensor … Multi-source … Multi-platform … Multi-scale … Ground & Lab hyperspectral Airborne hyperspectral We are pretty much there in the VNIR- SWIR range ! Orbital “super”spectral HISUI EnMAp PRISMA
  • 6. • MACRO/FIELD EXPERIMENT  Conducted at the Rocky Mountain Oilfield Testing Center (ROMTC), in Casper (Wyoming), US. BACKGROUND – CONTROLLED EXPERIMENTS
  • 7. • MACRO/FIELD EXPERIMENT  4 types of HCs and three mineral substrates (sandy, clayey and dolomitic soils, with varying particle size) were selected for the experiment.  The HCs were mixed to the mineral substrates making a total of 12 macro-samples.  The mixtures were prepared in the field, in wooden boxes (“bins”) BACKGROUND
  • 8. • MACRO/FIELD EXPERIMENT (i) distribution and preparation of the bins in the field (ii) addition of the clayey soil substrate and light crude oil to one of the bins (iii) measurement of the substrate using a FieldSpec FR instrument. BACKGROUND
  • 9. • MACRO/FIELD EXPERIMENT HC Bin Mixture Plan Bin Substrate Hydrocarb on 1 1 A 2 1 B 3 1 C 4 1 D 5 2 A 6 2 B 7 2 C 8 2 D 9 3 A 10 3 B 11 3 C 12 3 D Legend Substrates 1 – Sandy Soil (Topsoil) 2 – Dolomite-rich Gravel/Soil Mix 3 - Clayey Soil (Modified Base) Hydrocarbons A – 29 API Crude B – 41 API Crude C – Diesel D – Unleaded Gasoline MIXTURE PROTOCOL - 18L of HC, 1.0 hour prior to aircraft flyover - 18L of HC, 30 minutes prior… - 18L of HC, 15 minutes prior… BACKGROUND
  • 10. • MACRO/FIELD EXPERIMENT  PROSPECTIR VS and SEBASS co-located sensors on a single Twin Otter on same roll-controlled mount.  ONLY PROSPECTIR VS data approached in this session Spectral resolution of 357 bands (VNIR-SWIR) Spatial resolution of 60 cm on the ground BACKGROUND
  • 11. Physics: Reflective BandsEmissive Bands Reflected sunlight Direct thermal emission Complex phenomena Simpler phenomena Surface reflectivity Surface temperature Reflectance Emissivity .4 .6 .8 1 2 4 6 8 10 20 Wavelength ( LWIRMWIRSWIRNIR EnergyperBand 0 2 4 6 8 10 EnergyperBand 0 2 4 6 8 10 2 4 6 8 10 .4 .6 .8 1 2 4 6 8 10 20 Wavelength (µm) LWIRMWIRSWIRNIR REFLECTED SUNLIGHT THERMAL EMISSION 25000 10000 5000 2500 1667 1250 1000 500 Wavenumber (cm -1 )Wavenumber (cm -1 ) VIS ProSpecTIR VNIR-SWIR Sensor BACKGROUND
  • 12. • MACRO/FIELD EXPERIMENT Flight line Aerial view of the contaminated bins (numbered 1 to 12) and indication of the flightline along which hyperspectral imagery was acquired with the ProspecTIR sensor BACKGROUND
  • 13. • MACRO/FIELD EXPERIMENT MEASUREMENT 1 MEASUREMENT 2 MEASUREMENT 3 SANDYSOILDOLOMITICSOILCLAYEYSOIL a b c d e f g h i Bin1 - field spectra Bin1 - imagery spectra Lab. Spectral library Bin1 - field spectra Bin1 - imagery spectra Lab. Spectral library Bin1 - field spectra Bin1 - imagery spectra Lab. Spectral library Bin6 - field spectra Bin6 - imagery spectra Lab. Spectral library Bin6 - field spectra Bin6 - imagery spectra Lab. Spectral library Bin6 - field spectra Bin6 - imagery spectra Lab. Spectral library Bin11 - field spectra Bin11 - imagery spectra Lab. Spectral library Bin11 - field spectra Bin11 - imagery spectra Lab. Spectral library Bin11 - field spectra Bin11 - imagery spectra Lab. Spectral library HC – 18 L (1h) HC – 36 L (30min) HC – 54 L (15 min) DieselLightOil(API41)HeavyOil(API29)
  • 14. • MACRO/FIELD EXPERIMENT • Yellow pixels = mapped HC-bearing targets. • Scattered yellow pixels distant from the bins in the southern sector of the figures correspond to residues of contaminated soils and HCs and plastic paints 1h 30min 15min 1 2 3 4 6 5 8 10 12 7 9 flightline Image 1 – HC 18L (A) 1 2 3 4 6 5 8 10 12 7 9 Image 2 – HC 36L 11 (B) 1 2 3 4 6 5 8 10 12 7 9 Image 3 – HC 54L HC 11 (C) HCHC flightline BACKGROUND
  • 15. SIMULATION EXPERIMENT – WORLDVIEW-3 Same airborne ProspecTIR hyperspectral imagery acquired in Casper over twelve synthetic oil-shows was resampled to WV-3 spectral resolution.
  • 17. ASTER’s band 8 coincides with 2300 nm feature. WorldView-3’s band 12 (SWIR-4) coincides with 1700 nm feature. ASTER WorldView-3 SIMULATION EXPERIMENT – WORLDVIEW-3
  • 18. Sensor # hit pixels per box Total 1 2 3 4 5 6 7 8 9 10 11 12 Pixels Boxes WV-3 9 20 18 22 13 34 27 36 4 19 16 13 231 12 AST 3 9 10 8 8 16 14 11 0 4 6 2 91 11 2.5x Resampled WV-3 data (16 bands, 60cm) able to detect all 12 targets with 2.5 times higher average score relative to ASTER (9 bands, 60 cm). SIMULATION EXPERIMENT – WORLDVIEW-3
  • 19. REAL CASE STUDY – TAR SANDS Characterize bituminous sandstones at multiple scales using spectral technology. Evaluate the consistency of HC’s signatures for bitumen content estimation. Delineate the alteration mineralogy associated with bitumen emplacement in sandstone beds. Evaluate the merits of ground-based imaging data in oil-sand mining. Demonstrate the capability of WorldView-3 data to detect oil signatures in real scenarios.
  • 20. ANHEMBI STUDY AREA The area under study is located in the Paraná Basin, southern Brazil. The sandstone beds of the Pirambóia Formation are widespread in the region. Pirambóia Formation is a succession of fluvial and aeolian sandstones of the lower Triassic. Two facies are recognized: thick aeolian sand sheet facies at the base, overlain by aeolian dune and interdune strata.
  • 21. GEOLOGY OF THE AREA Bitumen is derived from the Permian Irati shales, thermally matured by Serra Geral magmatism, and then migrated along the contacts of diabase dykes to impregnate the eolian sandstones. The Anhembi deposit is estimated to contain about 5.7 million barrels of oil in-place based on average bitumen content of 5.5 wt. %. The oil is immature, very heavy, and highly viscose.
  • 22. DATA COLLECTION HAND SAMPLE analysis using nonimaging (FieldSpec-4) and imaging (sisuCHEMA) systems (n =15). WALL/FACE MAPPING using the AisaFENIX hyperspectral imaging system (3 walls). AIRBORNE MAPPING using the same AisaFENIX system. WORLDVIEW-3 satellite multispectral data
  • 23. POINT SPECTROSCOPY Five individual absorption features were analyzed using the Absorption-based Mineral Spectral Analyst software (AMISA-UNICAMP). The wavelength position, depth, and asymmetry of the features were considered for analysis and comparison. X-ray diffraction (XRD) was used to verify the alteration mineralogy. C-H Al-OH C-H
  • 24. IMAGING SECTROSCOPY – HAND SAMPLES An oil-rich rock sample was scanned by sisuCHEMA hyperspectral imaging instrument. Striping and illumination variations were discarded and the image was smoothed by Sav-Gol filter. Spectra validated against point measurements. RGB photo SisuCHEMA color composite
  • 25. Vertical walls of the oil-sand deposit were scanned on the ground using an AisaFENIX hyperspectral system. The 4x2 binning options (corresponding to 450 spectral bands) were used. For atmospheric compensation, a single calibration panel made of BaSO4 was used. 1 2 Outcrop azimuth Local time Solar elevation Solar azimuth Distance (m) GSD (cm) Illumination condition Physical condition 1 135° 10:30 37.2° 30.4° 10 1.5 Direct sunlight dry 2 75° 11:12 41.3° 19.1° 30 3.0 Direct sunlight dry IMAGING SECTROSCOPY – FACE MAPPING
  • 27. AisaFENIX hyperspectral scanner on board a twin-engine Seneca II (Piper) airplane Altitude of 915 m at 02:14 PM local time The hyperspectral data were acquired in a clear sky condition with a nominal GSD of 35 cm. Data resampled to 1.0 m spatial resolution using a pixel aggregate function. 8x2 binning mode within which 363 co-registered spectral bands are contained between 380–2500 nm wavelengths Radiance data converted to apparent surface reflectance using the ATCOR atmospheric correction software IMAGING SECTROSCOPY – AIRBORNE MAPPING
  • 28. DATA PRE-PROCESSING – HYPERSPECTRAL DATA A workflow was devised for preprocessing of the hyperspectral data. The depth of Al–OH feature was determined by polynomial fitting. The total bitumen content (TBC) the samples/pixels were estimated by employing the two-bands normalization method (Rivard et al. 2010).
  • 29. WV-3 MULTISPECTRAL IMAGING VNIR+SWIR imagery over target area was acquired by Digital Globe on February, 2016. Data delivered as ‘at-surface reflectance’ resampled to 7.5m resolution. A combination of feature tracking (applied to continuum-removed data) and match filtering techniques were used to map the distribution of oil-sands
  • 30. RESULTS – POINT SPECTROSCOPY The clay mineralogy was identified to be dominated by montmorillonite. Montmorillonite is present in almost all samples, including the impregnated ones, implying that the clays are in an intimate mixture with bitumen. The oil-sands emplacement was associated with the loss of iron (Feox) feature and an increase in clay content. unimpregnated sandstones Oil-sands
  • 31. RESULTS – POINT SPECTROSCOPY The TBC of the oil-sand samples was observed to vary between 6 to 11.5 wt. %. The TBC showed proportionality to the depth of the absorption features at ~1700 and 2300 nm. The feature at 2300 nm is very distinct and more pronounced, but the one at 1700 nm is remarkably more correlated to the TBC. R2: 0.98 vs. 0.95. The TBC was inversely proportional to the clay content of the samples.
  • 32. RESULTS (sisuCHEMA vs FieldSpec-4) There is a correspondence in the overall spectral shape of the two datasets, especially >1850 nm. There are three differences between the two series: The pixel spectra at around 1650 nm is unusually high. The image data is noisier between 1500–1800 nm; The shape of the HC feature at 1700 nm is modified in the image spectra.
  • 33. RESULTS – IMAGING SPECTROSCOPY The bitumen content of the rock is unevenly distributed in the scale of a hand sample and is controlled by lamination and clay content of the sandstone. The montmorillonitic clay is ubiquitous and occurs virtually in all pixels.
  • 34. RESULTS – IMAGING SPECTROSCOPY The data processing workflow was effective in increasing the SNR of the data. Spectral denoising was crucial in retrieving the overall shape of the HC’s absorption features. Calculated over the panel (~450 pixels)
  • 35. RESULTS – IMAGING SPECTROSCOPY At outcrop scale, the TBC is controlled by sedimentary facies: interdune: bitumen poor vs. sand sheet: bitumen rich.
  • 36. RESULTS – AIRBORNE IMAGING SPECTROSCOPY The close association of bituminous outcrops with clays is because besides intimate mixing, the two components are areally mixed in the sub-meter scale.
  • 37. RESULTS – WV3 The HC feature at WV-3 band SWIR-4 (band 12) was present within a large part of the oil-sand pixels. There is a reasonable match between WV-3 and airborne maps. green vegetation
  • 38. SUMMARY & CONCLUSIONS The HC signature was demonstrated to be consistent among scales (maintaining a linear relationship with the TBC of samples/pixels) and capable of estimating the TBC of oil-sands at all imaging scales. Spectrally-derived TBC estimates of the deposit was determined to vary between 0–11.5 % with a mean of ~5 wt. % - a good match with available geochemical data. The clay minerals (montmorillonite) were ubiquitous and mixed intimately with bitumen at all studied scales. WV-3 could resolve HC feature by its band 12 (SWIR band 4) provided that the target is large enough to cover ~1/4 of a SWIR pixel. The estimation of TBC was not successful using WV-3 data.
  • 39. Geosciences Institute University of Campinas (UNICAMP) http://portal.ige.unicamp.br/ beto@ige.unicamp.br Thank you !