2. Characterised Uncertainty
= scientific and economic value
The age of this granite is 107 Ma…………………………………………….Value $5000?
The age of this granite is 107 290 Ma………………………………………..Value $50
The age of this granite is 107 Ma ????? ………………………………..Value $???
3. Uncertainty frameworks & metrics
• Mann, 1993 Uncertainty in geology: International Association for Mathematical
Geosciences, IAMG Studies in Mathematical Geology, v. 20, p. 241–254.
• Kennedy & O’Hagan 2001 Bayesian Calibration of Computer Models Marc C. Kennedy; Anthony O'Hagan
Journal of the Royal Statistical Society. Series B (Statistical Methodology ), Vol. 63, No. 3. (2001), pp. 425-464.
• Bardossy and Fodor, 2001 Traditional and new ways to handle uncertaintyin geology: Natural Resources
Research, v. 10, p. 179−187.
• Thore et al., 2002 Structural uncertainties: Determination, management and applications: Geophysics, v. 67,
p. 840–852.
• Tacher et al., 2006 Geological uncertainties associated with 3-D subsurface models: Computers and
Geosciences, v. 32, p. 212–221.
• Caers, 2011 Modelling uncertainty in the earth sciences: Chichester, Wiley, 239 p.
• Lark et al., 2013 A statistical assessment of the uncertainty in a 3-D geological framework model: Proceedings
of the Geologists’ Association, v. 124, p. 946–958.
• Nearing et al 2016 A philosophical basis for hydrological uncertainty Grey S. Nearing, Yudong Tian, Hoshin V.
Gupta, Martyn P. Clark, Kenneth W. Harrison & Steven V. Weijs (2016) A philosophical basis for hydrological
uncertainty, Hydrological Sciences Journal, 61:9, 1666-1678
4. 1 km
3D geomodelling scenarios
Sedimentary Basins Mines Regional Lithosphere
3D Constraints RICH (3D seismic, deep
boreholes, gravity)
RICH (dense
boreholes, magnetics,
seismic,
electromagnetics)
POOR (rare
boreholes, surface
outcrops, gravity,
magnetics)
RICH (Teleseismic, seismic,
gravity, MT)
Structural Complexity SIMPLE(R) COMPLEX COMPLEX SIMPLE(R)
Dedicated Software Gocad 1989, Geomodeller
1999…
MicroMine 1986,
Leapfrog 2003...
Noddy 1981, Gocad-
Sparse 1995,
Geomodeller 1999 …
Gocad 1989
Starting point 3D seismic reflection Boreholes Maps Seismic tomography, RF
Dimensionality 3D -> 3D 1D -> 3D 2D -> 3D 3D -> 3D
30 km5 km 200 km
Geothermal energy
Hydrogeology
Urban Geology
Natural Hazards
…
5. Haldoresen & Damsleth, 1990
The Hybrid model is a two-stage
model
In Stage 1, a discrete model describes
the large-scale heterogeneities in the
reservoir- e.g., the various
sedimentological building blocks or
the flow units.
In Stage 2, different continuous
models describe the spatial
variations of the petrophysical
parameters within each class.
10. Pakyuz-Charrier et al in prep., 2018
Down-hole Positional Error
Gjerde et al., 2011
Measurement While Drilling
(MWD) technology error at
2200 m depth
60m N-S
100m E-W
15m Z
12. +/- 5% error in positional measurements
+/- 5° error in structural measurements
• Mitigated by stochastic modelling?
Large errors resulting from natural variability
• Mitigated by denser data collection and stochastic
modelling?
Measurement Error & Natural Variability
14. Same geology, different mappers, different datasets (mag survey was 1976)
BRGM 1992 BGR 2004
south-east Côte d’Ivoire
Geology “House styles”
15. Texture Grainsize Lithology Colour Shade Oxidation Texture Grainsize
VA FG
VA FG
SH FG
VA FG
VA FG
BX FG
SP FG
SP FG
MA FG
MA FG
FR VC
FR VC
FR VC
FR VC
FR VC
FL VC
FR VC
FL FG
CL VC
CL VC
CL VC
CL VC
FL VC
CL VC
CL VC
CL CG
CL CG
BD FG
CL VC
MA FV
MA FV
MA FC
MA FC
BX FC
MA FC
BX CG
MA FC
MA FC
MA FV
MA FV
BX CG
MA FC
FL FG
MA FG
MA FG
BD VF
MA CG
MA FC
MA CG
MA FC
BD FG
BD VC
MA CG
MA CG
MA FV
MA VC
BD FV
MA VC
MA VC
MA FG
MA VC
FL VF
BD FV
BX FV
BD VF
BD VF
BX FG
BD VF
BD VF
MA VF
BD FC
PW FG
BX VC
MA FG
BD FV
MA FG
BD FV
MA VF
BD FV
MA FG
BD FV
MA FG
MA FG
MA FG
BX FM
MA MG
BX FM
MA MG
MA MG
BD FV
BD VF
BD FG
BD VF
FL VF
BD FG
BX CG
BD FM
MA FG
SH VF
MA VF
BD FV
MA VF
BD FV
BD FC
SH VF
MA VC
MA FG
BD FV
FL FG
FL FG
BD VF
MA FG
BD FV
MA VC
MA VC
MA VC
MA VC
MA FG
MA MG
BX FV
MA MG
BX MG
GP CG
BX FV
GP CG
GP CG
SH FG
GP MG
GP MC
GP MC
MA FC
SH FG
MA FM
MA FG
MA MG
MA FM
SH FG
MA FM
MA MG
MA MG
MA FG
BD VF
PW FG
PW FG
FL VF
FL VF
FL FG
MA MG
BD FM
PW FG
BX CG
PW FG
PW FG
FL FG
PW VF
SH FG
SH FG
BD VF
BX FV
PW VF
PW FG
FL VF
PW VF
PW VF
PW VF
BX FM
MA VF
MA VF
FL VF
FL VF
FL FG
FL FG
FL FG
FL FG
FL FG
Lithology Colour Shade Oxidation Texture Grainsize Lithology Colour Shade Oxidation Texture Grainsize
MB GN P FR VA FG
MB GN P FR VA FG
SZ GY D FR SH FG
MB GN D FR VA FG
MB GN D FR VA FG
UM GN D FR BX FG
UM GN D FR SP FG
UM GN D FR SP FG
RTS RD D OX MA FG
RTSC WH L OX MA FG
FDC GNRD M PO FR VC
FDC GNRD M FR FR VC
FDC GN M FR FR VC
FDC GNRD M FR FR VC
FDC GN M FR FR VC
F KH M FR FL VC
FDC KH M FR FR VC
VN WH M FR FL FG
SCF KH M FR CL VC
SCF KH M FR CL VC
SCF KH M FR CL VC
AN GNRD D FR CL VC
F KH M FR FL VC
AN GNRD D FR CL VC
NSR
SCF GN D FR CL VC
NSR
SCX BE L FR CL CG
NSR
SCX GN D FR CL CG
IZS GY D FR BD FG
SCX GNRD D FR CL VC
AN M L FR MA FV
AN M L FR MA FV
SZ TN L FR MA FC
AN TN L FR MA FC
F TN L FR BX FC
AN TN L FR MA FC
F GY D FR BX CG
AN TN L FR MA FC
AN TN L FR MA FC
AN KH D FR MA FV
AN KH D FR MA FV
F GY D FR BX CG
AN TN D FR MA FC
F GY D FR FL FG
AN BK D FR MA FG
AN BK D FR MA FG
SL BK D FR BD VF
NSR
SGW GY D FR MA CG
AN BK D FR MA FC
NSR
SGW BK D FR MA CG
AN BK P FR MA FC
SL GY D FR BD FG
SCX GY D FR BD VC
AN GY D FR MA CG
NSR
SCX GY D FR MA CG
AN GY D FR MA FV
SCX GY D FR MA VC
SSP GY D FR BD FV
SCX GY L FR MA VC
SCX GY L FR MA VC
MB BE L FR MA FG
SCX GY L FR MA VC
F BK D FR FL VF
SBS GY D FR BD FV
BXR BN D FR BX FV
SBS BK D FR BD VF
SBS BK D FR BD VF
BXR BK D FR BX FG
SL GY D FR BD VF
SL GY D FR BD VF
MB GY D FR MA VF
ISV GY D FR BD FC
MB GY D FR PW FG
BXR GY D FR BX VC
MB GY D FR MA FG
ISV GY D FR BD FV
MB GY D FR MA FG
ISV GY D FR BD FV
MB GY L FR MA VF
ISV GY D FR BD FV
MB GY D FR MA FG
ISV GY D FR BD FV
MB GY D FR MA FG
MB GY D FR MA FG
MB GY D FR MA FG
VN GN L FR BX FM
MD GY L FR MA MG
BX GY D FR BX FM
MD GY L FR MA MG
MD GY L FR MA MG
SGW BK D FR BD FV
ISV BK D FR BD VF
SS GY D FR BD FG
ISV BK D FR BD VF
F BK D FR FL VF
ISV GY D FR BD FG
F GY D FR BX CG
ISV GY D FR BD FM
MB GY D FR MA FG
SBS BK D FR SH VF
MB GY L FR MA VF
ISV GY D FR BD FV
MB BN D FR MA VF
ISV BK D FR BD FV
ISV GY D FR BD FC
F GY D FR SH VF
BX GY D FR MA VC
MB BN D FR MA FG
ISV BK D FR BD FV
F BK D FR FL FG
F BK D FR FL FG
SBS BK D FR BD VF
MB GY D FR MA FG
ISV GY D FR BD FV
SCM GY D FR MA VC
SCM GY D FR MA VC
SCM GY D FR MA VC
SCM GY D FR MA VC
MD GN D FR MA FG
MD GN D FR MA MG
F GN D FR BX FV
MD GN D FR MA MG
F GN D FR BX MG
MDG GN D FR GP CG
F BN D FR BX FV
MD GN L FR GP CG
MD GN L FR GP CG
SZ GN L FR SH FG
MD GY L FR GP MG
MD GN L FR GP MC
MD GN L FR GP MC
MD GN D FR MA FC
SZ GN L FR SH FG
MD GY L FR MA FM
MD GN D FR MA FG
MD GN D FR MA MG
MD GN D FR MA FM
SZ GN D FR SH FG
MD GN D FR MA FM
MD GN D FR MA MG
MD GN D FR MA MG
MB GN D FR MA FG
ISV GY L BD VF
MB GN D FR PW FG
MB GN D FR PW FG
MB GN L FR FL VF
ISV GY L FR FL VF
MD GN L FR FL FG
MD GN D FR MA MG
ISV GY L FR BD FM
MB GN D FR PW FG
VN WH L FR BX CG
MB GN D FR PW FG
MB GN D FR PW FG
MB GN P FR FL FG
MB GY D FR PW VF
LO GY D FR SH FG
LO GY D FR SH FG
ISV BK D FR BD VF
MB GY L FR BX FV
MB GY L FR PW VF
MB GN D FR PW FG
F GY L FR FL VF
MB GN D FR PW VF
MB GN D FR PW VF
MB GN D FR PW VF
F GN D FR BX FM
MB GN D FR MA VF
MB GN D FR MA VF
MB GY D FR FL VF
ISV GY D FR FL VF
MB KH L FR FL FG
MB KH L FR FL FG
MB KH L FR FL FG
MB GY D FR FL FG
MB GY D FR FL FG
e Grainsize Lithology Colour Shade Oxidation Texture Grainsize
FG
FG
FG
FG
FG
FG
FG
FG
FG
FG
VC
VC
VC
VC
VC
VC
VC
FG
VC
VC
VC
Lithology Colour Shade Oxidation Texture Grainsize Lithology Colour Shade Oxidation
MB GN P FR VA FG
MB GN P FR VA FG
SZ GY D FR SH FG
MB GN D FR VA FG
MB GN D FR VA FG
UM GN D FR BX FG
UM GN D FR SP FG
UM GN D FR SP FG
RTS RD D OX MA FG
RTSC WH L OX MA FG
FDC GNRD M PO FR VC
FDC GNRD M FR FR VC
FDC GN M FR FR VC
FDC GNRD M FR FR VC
FDC GN M FR FR VC
F KH M FR FL VC
FDC KH M FR FR VC
VN WH M FR FL FG
SCF KH M FR CL VC
SCF KH M FR CL VC
SCF KH M FR CL VC
Archival logging uncertainty
19. Lark et al, 2014
Base of London Clay
One geologist’s interpretation of the base of the
London Clay (red) with 95% confidence intervals
(blue) based on 28 geologists interpretations
20. 3D Seismic Case History of the Darlot – Centenary Gold Mine
Foley et al., AEGC Extended Abstract 2018
22. Ridge strength map
(+ve Phase Symmetry)
Magnetic data
Feature Evidence Tools in the Integrated Exploration Platform
Valley strength map
(-ve Phase Symmetry)
Edge strength map
(Phase Congruency)
David Nathan, Jason Wong
CET/UWA
24. Polson & Curtis 2010 in Curtis 2012
The science of subjectivity
“Scientists should therefore not be ashamed of subjectivity, but we should
strive to develop methods to quantify and sometimes to reduce its effects”
25. Major personal biases during interpretation
• Mitigated by collective analysis?
Interpretation Ambiguity
27. “…our non-geophysical colleagues might be tempted to
think that geophysicists have eliminated uncertainty from
our subsurface images. Nothing could be further from the
truth. Most (if not all) of the time, geophysical
characterization of the subsurface involves estimating
solutions to ill-posed inverse problems.”
Amaru et al. (2017)
Introduction to special section on velocity-model uncertainty
28. North West Shelf 3D Velocity Modeling
Laureline Monteignies* Cédric Magneron Natalia Gritsajuk ASEG Abstract 2016
34. Grose et al., 2017
Structural data constraints for
implicit modelling of folds
35. Chilés et al. 2004
Uncertainties in surface
generation
36. de Kemp et al 2016
2010 2015
Model evolution with time
Data availability
+ =
37. De Kemp et al 2016
Uncertainty derived from model evolution Uncertainty derived from input data density
38. Major personal biases during domain construction
• Mitigated by stochastic simulation?
• Mitigated by incorporation of additional data types?
Domain Construction
43. Complexity of physics and chemistry of natural systems
• Mitigated by stochastic simulation?
• Mitigated by incorporation of prior knowledge?
Property Infill
51. National Drilling Initiative
Mt Isa Geophysical Province
0 100 200
kilometres
What is the best drilling
strategy to optimize cover
AND bedrock sampling?
Not a regular grid if we have
any prior knowledge?
54. NC
P
P
GP
GP
Giraud et al. Geophysics, 2017
Geologically: bestGeologically: best
T
R
U
E
2D Geophysical Inversion results
Single domain:
unconstrained
inversion
Single domain:
petrophysics only
Joint inversion:
Petrophysics only
Single domain:
Geology and
Petrophysics
Joint inversion:
Geology and
Petrophysics
True model
Geoph
y
Petro
Geoph
y
Petro
Geoph
y
GeolPetro
Geoph
y
GeolPetro
Geoph
y
Density Magnetic Susceptibility
Geol
55. Topology as a 3D model classifier
Post-processing
1 2 3 4 5 6
1
2
3
4
5
6
1 2 3 4 5 6
1
2
3
4
5
6
1 2 3 4 5 6
1
2
3
4
5
6
1 2 3 4 5 6
1
2
3
4
5
6
1 2 3 4 5 6
1
2
3
4
5
6
Archetype candidates
Normal
Faulted
Both
None
NA
Topology
Pakyuz-Charrier, in
prep 2018
Lindsay et al, 2012
57. How to carry uncertainty forward?
1. Brute force propagation (e.g. Monte Carlo)
2. Homogenisation via PDF representation of variability
3. Identification of important classes
density
Mag sus
Step 1 Step 2 Step 3
58. Use of uncertainty in decision making is very compartmentalized
• Mitigated by propagation strategies?
Current systems typically do not allow uncertainty as an input
• Mitigated by propagation strategies?
Multistage Uncertainty Propagation
60. Scenario
Stage
Mine Basin Regional
Direct acquisition Drill hole logging Borehole position Surface Geology
Interpretation
Indirect acquisition Geophysical
inversions
Velocity Model Geophysical
inversions
Model Construction Topology of surfaces
& property infill
Interpretational
Ambiguity
Physics-based
construction &
property infill
Downstream
Uncertainty
Petrophysics to
“useful” properties
Rock physics
uncertainty (leaky or
tight faults…)
Rock physics
uncertainty
Biggest sources of uncertainty?
61. What is stopping us?
• Current software is poorly adapted to using probabilistic information as
inputs and/or storing probabilistic information (particularly multiple domain
models) as outputs
• Current software does not use physics-based prior knowledge to populate
domains or define the domains themselves
• Spatial and temporal topology only partially accounted for during modelling
• Geophysical inversions are too-often reduced to fixed support for domain
boundary interpretations
62. l∞p = New Open Source 3D geological modelling platform
= GemPy + foldinv + map2model + pyNoddy + CURE + TOMOFASTx…
+
+ +
+ +
Implicit modeller
Structural inversion
algorithms
Geological Event Manager
Topological Analysis of
source data 3D Uncertainty Analysis
Integrated Geophysical Inversion
l∞p consortium+ +
64. Conclusion
Although there is much to learn from O&G and other geoscience
fields in terms of improving uncertainty analysis in individual
tasks in the 3D modelling workflow, probably the most important
lesson is the need to move towards a coherent workflow (though
not necessarily a single piece of software) where uncertainties
are retained and propagate from data acquisition to model
predictions.