closing_the_loop_r.pdf
TRANSCRIPT
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Closing the Loop between geo&engineering in building
calibration and history matching carbonate reservoir models?
Patrick Corbett
BG Group Professor
Carbonate Petroleum Geoengineering
AAPG Distinguished Lecture May 2014
3
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Fractured or not?
Reservoir Engineering YES Well test response Negative skin Cross-flow
Geology NO No fractured core No open fractures on image logs No significant losses
4
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Fractured or not?
Reservoir Engineering YES >>> NO Well test response Negative skin >> not fractures >> double matrix Cross-flow >> not fractures >> double matrix
Geology NO No fractured core No open fractures on image logs No significant losses
5
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Fractured or not?
Reservoir Engineering YES Well test response Negative skin >>>> double matrix + fractures Cross-flow >>>> double matrix + fractures
Geology YES Fractured core Open fractures on image logs Significant losses
6
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Closing the loop
Highly heterogeneous carbonate reservoirs Fractured vs non-fractured well tests? Build a model without fractures Care to distribute RTs appropriately Check History Match without fractures Not conclusive but potentially useful Role for PLTs
7
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Dual porosity Horizontal well Closely bounded reservoir Negative skin
Horizontal well Dual porosity Rectangular bounded Negative skin
Horizontal well Dual porosity Infinite boundary Small positive skin
Dual porosity Vertical well Negative skin
A2
0.01 1.0 100Time, hr
1E+6
1E+7
Gas
pot
enti
al, p
sia/
cp
A1
A3 A4
0.1 10 1000
Time, hr
1E+6
1E+7
Gas
pot
enti
al, p
sia/
cp
0.1 10 1000Time, hr
1E+6
1E+7
Gas
pot
enti
al, p
sia/
cp
0.1 10 1000Time, hr
100
1000
Pres
sure
, psi
a
Fracture performance of well test??
Kazemi et al, 20118
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Composite log
Layer 2
Layer 3
Layer 4
Prograding ramp facies with higher frequency cycling
Layer 1
Kazemi et al, 20119
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11020 200 290 370 460 550 640
Wel
l bot
tom
hol
e pr
essu
re, p
sia
A4
A3
A2
A1
Time, day
Figure 10b
Kazemi et al, 201110
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11020 200 290 370 460 550 640
11020 200 290 370 460 550 640
A1
A2
A3
A4
Wel
l gas
pro
duct
ion
rate
, MM
sm3/
day
Wel
l oil
prod
ucti
on r
ate,
sm
3/da
y
Time, day
Time, day
Figure 10a
Kazemi et al, 201111
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Facies Model
Simple depositonal model with dolomite modification>>>PODS
Kazemi et al, 201112
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Well Location in Facies Model
Interdigitation of Mid- to Outer- Ramp facies
From Simpson, 2010
Low PorosityIntragranular Porosity
Foraminiferal Packstone
Higher Inter XL Porosity
Higher Permeability
Un-dolomitised
Strong primary control on property distribution
Dolomitised
Kazemi et al, 201113
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Review of H Field Rock Types
0.001
0.010
0.100
1.000
10.000
100.000
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Perm
eabi
lity
mD
Porosity
L1L2L3L4
0.001
0.010
0.100
1.000
10.000
100.000
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Perm
eabi
lity
mD
Porosity %
H1H2H3H4
0.001
0.010
0.100
1.000
10.000
100.000
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Perm
eabi
lity
Porosity
GB
GN
GPB
GPN
MWB
MWT
By facies?0.01
0.1
1
10
100
0 0.05 0.1 0.15 0.2 0.25
By well?
By layer?
By RRT?By GHE?
Simpson, 2010
How do we distribute properties?
From full field model?
Kazemi et al, 201114
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Composite log
Layer 2
Layer 3
Layer 4
Based on given Log Porosity
H Field Well H2
NB: super-k >16%F >40mD?
GHE Proportion Curve
GHE Grouping
Layer 2U
Layer 2L
Layer 1
Use GHE grouping approach
Kazemi et al, 201115
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PLT Performance
H2
H A1
H2
16
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H Field Model
17
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Distribution of Rock Types
Kazemi et al, 201118
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Cell dimension (m): 100X100X1Total number of cells: 95760Local grid refinement: 5X5X3
Porosity
Permeability
Simulation Model
Kazemi et al, 201119
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Horizontal correlation length, m
Ver
tica
l cor
rela
tion
leng
th, m
1000500100
13
6
PODS Distribution lengths
Kazemi et al, 201120
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SHORT CORRELATION
LONG CORRELATION
Example Models
Kazemi et al, 201121
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Storage capacity Flow capacity
H100V1
H100V3
H100V6
H500V1
H500V3
H500V6
H1000V1
H1000V3
H1000V6
REALISATIONS
Kazemi et al, 201122
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Kv/Kh0
Kv/Kh= 0
Short correlation length Long correlation length
Bars
Vertical Permeability
Kazemi et al, 201123
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Short correlation lengthLong correlation lengthHomogenous model
Gas
pot
enti
al
Time, hr
Numerical Well Tests
Kazemi et al, 201124
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H100V1 H1000V6
Short correlation length vs. long correlation length
Numerical PLT
Kazemi et al, 201125
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PorosityPermeabilityShort correlation length
Long correlation length
Full Field Model
Kazemi et al, 201126
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PorosityPermeability
Short correlation length
Long correlation length
Full Field Model
Kazemi et al, 201127
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Full fieldSector modelShort correlation
Full Field vs Sector Model
Kazemi et al, 201128
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Sector model
Full field model
Short correlation length Long correlation length
Bars
Full Field vs Sector Model
Kazemi et al, 201129
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Short correlation lengthLong correlation lengthShort correlation length, field
Gas
pot
enti
al
Time, hr
Long correlation length , field
Full Field vs Sector Model
Kazemi et al, 201130
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Short correlation lengthLong correlation length
Gas
pot
enti
al
Time, hr
sector Full field GHElong
GHEShort
Next stage:PLT and WT history matching
Kazemi et al, 201131
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Poroperm data and effective RTs
32
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PC and Saturation Height
0
5
10
15
20
25
30
0.0 0.2 0.4 0.6 0.8 1.0
Hei
ght
(m) a
bove
FW
L
Water Saturation
Capillary Pressure Data
Plug 1 (Por:=18.7%)
Plug 2 (Por: =14.4%)
Plug 3 (Por: 12.4%)
0
5
10
15
20
25
30
0.0 0.2 0.4 0.6 0.8 1.0
Hei
ght
(m) a
bove
FW
L
Water Saturation
Saturation Height Modelling
GHE2
GHE4
GHE5
33
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Well H2
Petrotype Model Calibration
Layer 2
Layer 4
Layer 3
2U
2L
34
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Porosity Permeability
Full Field RT based poroperm scenarios
Kazemi et al, 201135
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Porosity Permeability
Full Field RT based poroperm scenarios
Kazemi et al, 201136
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Days
Gas
pro
duct
ion
rate
Oil
prod
ucti
on r
ate
History
History Match Gross Production
Kazemi et al, 201137
-
300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600
A1
A2
A4A3
Time, hr
Pres
sure
History
Rate
Pres
sure
Rate
6000 8000 10000 12000 14000 3000 4000 6000 8000 10000
400 600 8000 1000 12001000 3000 5000 7000 9000 1400 1600
12000 14000 16000
History
History
History
History Match - Pressure
Kazemi et al, 2011
38
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1E-4 1E-3 0.01 0.1 1 10 100 10001E-4 1E-3 0.01 0.1 1 10 100 1000
A1
A2
1E+6
1E+7
Gas
pot
enti
al, p
sia/
cp 1E+8
1E+6
1E+7
Gas
pot
enti
al, p
sia/
cp 1E+8
1E-3 0.1 10 1000
1E-3 0.1 10 1000
Time, hr
History Match well rate
Kazemi et al, 201139
-
1E-5 1E-4 1E-3 0.01 0.1 1 10 100 10000.1
1
10
1E-5 1E-4 1E-3 0.01 0.1 1 10 100 10000.1
1
10
A3
A4
1E+7
Gas
pot
enti
al, p
sia/
cp1E
+81
10
Pres
sure
, psi
a
1E-3 0.1 10 1000
1E-3 0.1 10 1000
1E-3 0.1 10 1000
Time, hr
History Match Well rate
Kazemi et al, 201140
-
1E-5 1E-4 1E-3 0.01 0.1 1 10 100 1000
A2
A11E
+71E
+8
Gas
pot
enti
al, p
sia/
cp1E
+61E
+7
Gas
pot
enti
al, p
sia/
cp
1E-3 0.1 10 1000
1E-3 0.1 10 1000
Time, hr
Model WT match
Kazemi et al, 201141
-
A3
A4
1E+7
Gas
pot
enti
al, p
sia/
cp1E
+81
10
Pres
sure
, psi
a
1E-3 0.1 10 1000
1E-3 0.1 10 1000
1E-3 0.1 10 1000Time, hr
Model WT Match
Kazemi et al, 201142
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PLT Predictions
Kazemi et al, 201143
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Aternative match option
Kazemi et al, 201144
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Applied a new modelling strategy based on PODS Porosity Defined System for a carbonate reservoir.
The effect of horizontal and vertical correlation length of PODS observed on WT response.
Matching WT and PLT data in sector before going to full field modelling
Sector model and full field model compare well
WT and PLT Calibration of full field model
Reasonable match achieved without incorporating any fractures
H Field study conclusions
45
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SPE 166033: Using Near Wellbore Upscaling to Improve Reservoir Characterization and
Simulation in Highly Heterogeneous Carbonate Reservoirs
V. Chandra1,2, S. Geiger1,2 , P.W.M. Corbett1,2,4,R. Steele3, P. Milroy3 , A. Barnett3 , P. Wright3 , P. Jain3
1Institute of Petroleum Engineering, Heriot-Watt University2International Centre for Carbonate Reservoirs
3BG Group, Reading, U.K.4 Universidade Federal do Rio de Janeiro
Acknowledgements:46
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Key points of this research
47
Overall aim Using novel near wellbore upscaling (NWU) workflow to obtain
improved permeability model of Field G
Main conclusions Improved characterisation of key small-scale geological
heterogeneities
Revised permeability model eliminated the K-multipliersScientific impact Improved reservoir characterisation and simulation of
carbonates using NWU workflow
Chandra et al, 2012
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Low relief anticline trap Thin oil rim, gas cap, deep seated aquifer Main HC bearing layers: Zone A, Zone B
Field G Background
E-W section: see gas over oil over water. See the two main reservoir layers (Image courtesy: Zoe Watt)
48
A/B Unconformity
Chandra et al, 2012
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Field G Simulation Model
49Chandra et al, 2012
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Field G Production Profiles: Oil, Gas and Water
50Chandra et al, 2012
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Re-evaluating Field G Permeability
- DST K-transform >> core K-transform
- Average K in geomodel ~ 20 mD and Ke in simulation model ~ 200 mD
What was undersampled?How should it be modelled?
Kh-multiplier required for history match : x20 in Zone A, x10 in Zone BPlus local well K and well PI multipliers
Around 90% of the permeability missing !?
Correct the K = Better Simulation Model = Better Production Forecast51
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Removing the K-multiplier
Can
be r
esol
ved
usin
g re
vise
d K-
mod
el?
All K-multipliers removed
History matched case with K-multipliers
52Chandra et al, 2012
-
Evaluating the Role of Meteoric Karst vs Burial Corrosion in an Offshore Indian Carbonate Field
Michael OatesViswa Santhi Chandra
Patrick Corbett
-
Outline
Field G overview Evidence of late burial corrosion Impact on poro-perm Key conclusions
Oates et al, 201254
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Ramp foraminifera facies
Depositional Facies
Coskinolina
1000 m
Miliolids
1000 mCoskinolinids and
Alveolinids
1000 m
Platy corals
1000 m
Fine bioclastic Hash with Rotalid forams
1000 m
Fine bioclastic Hash with Echinoderm debris
1000 m
Nummulitids
1000 m
Discocyclinids
1000 m
Oates et al, 201255
-
Cold Karst ?Meteoric karstic porosity development caused the
conduits?
Diagenesis vs Permeability concepts
Indication of dissolution porosity
Solution enhanced stylolitesand associated fractures in well cores
Evident high perm network, pervasive and stratiform
Long producing data and tracer data indicating good lateral and vertical communication in reservoir
The dissolution porosity +stylolites+associated fractures are the pervasive permeability network ?
Hot Karst ?Late stage (hydro)thermal karstification could have
formed the conduits?
Oates et al, 201256
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Proposed Paragenetic Sequence
Transpressional tectonics at the end of Miocene
Early stage extensive microporosityLate stage macroporosity along fractures, unconformities, vertical pipes
Corrosive fluids penetrated the unloaded dissolution seams and stylolites predating the HC charge
Unloading event
Depositional setting:Ramp settingTransgressive stacking patterns
Cementation+Compaction+Pressure dissolution=
Very tight carbonate units
Very common Associated with late
carbonate cementscalcitedolomiteankeritesiderite
Dissolution seamsStylolitesTension gashes
Oates et al, 201257
-
Burial Corrosion- Field Scale
(Modified from Esteban)Oates et al, 2012
58
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Burial Corrosion- Field Scale
(Modified from Barnett et al . 2010)
Oates et al, 2012
59
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Back to Basics: Key Observations from Core
Stylolites and associated tension gashesCorrosion enhanced micro- and macro-porosity
Corroded zone
Matrix adjacent to corroded zone
60
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Post Stylolite Dissolution
Fine vuggy porosity
1 cm
0.5 mm0.5 mm
Extensive porosity along stylolites and microstylolites
61
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Corrosion along Stylolites and SAF
Corrosion vs Stylolite CorrelationDensity of distribution of corroded zones is proportional to that of stylolites.
2 cm
Oates et al, 201262
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Corrosion fluid front
Corrosion fluid front
Invasion of Corrosive Fluids
Corrosion enhanced porosity
Corrosion enhanced porosity
Corrosion enhanced porosity
Burial Corrosion Mechanism at Core Scale
Oates et al, 201263
-
Post-Saddle Dolomite Dissolution
Fractures with leached bladed calcite cement, saddle dolomite and dickite
Saddle dolomite
Bladed calcite cement
Dickite
Saddle dolomite in a fracture has undergone corrosion followed by dickite precipitation
Dickite
Corroded saddle dolomite
0.5 mm 0.5 mm
Oates et al, 201264
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Dissolution of Tectonic Vein-filling Calcite
Corroded calcite cement in a fracture
0.5 mm
Oates et al, 201265
-
Dickite and Pyrite
Dickite is not common in carbonate reservoirs in general
BUT it is a very common mineral phase in Field G
Deeply etched stylolites and associated fractures
pyrite nodules this size (up to 10mm across) are rare
Dickite is a kaolin mineral thought to indicate the former activity of organic-rich acidic fluids
Oates et al, 201266
-
Highlights: Diagenetic Features
2 cm
(Courtesy Paul Wright )
Oates et al, 201267
-
Key Observations from Core
Key Characteristics of Corroded Zones:
- Higher porosity
- Higher mini-perm
- Dark patches of highly conductive zones on image logs
- High Uranium signature
R1= unmodified limestone matrixR2= corroded matrix
Oates et al, 201268
-
Corrosion Enhanced Porosity
Collapse breccia porosityVuggy/Moldic porosityCorrosion along Stylolites and SAF
BSEM images of typical corroded matrix with microporosity
2 cm
Oates et al, 201269
-
Reservoir Permeability Issues
- DST K- transform >> core K- transform
- Average K in geomodel ~ 20 mD and Ke in simulation model ~ 200 mD
What was undersampled?How should it be modelled?
Core and miniperm data
Sample insufficiencySample bias towards tighter zones
K-multiplier required for History match :
x20 in A Zone x10 in B Zone Plus local well K and well PI multipliers
Around 90% of the permeability missing !?
Correct K = Better Simulation Model = Better Production Forecast
Oates et al, 201270
-
Permeability Model Before and After Considering Corrosion Enhanced Porosity
Geomodel using core K-transform After incorporating solution enhanced porosity features in the geomodel
711000
AFTER K-multiplier
Geomodel permeability Modified permeability scenario
100050
-
Simulation results
72
Cumulative oil production curves
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Key Conclusions
Distribution of high permeable corroded zones correlated with stylolites+fractures
Evidence supports the occurrence of thermal karstification causing stratiform pervasive high permeable network
The reservoir permeability model should be improved with considerations to late burial corrosion
Oates et al, 201273
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Near wellbore rock-typing and upscaling
Chandra et al, 201474
m-mm cm-dm m-km
-
75
Core vs upscaled permeability
Corroded matrix porosity
Leached stylolites and tension gashes in highly Corroded matrix
Chandra et al, 2014
-
Poro-perm trends used for GeoPoDS
Chandra et al, 201476
-
GeoPoDS saturation-height curves
77
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Near-wellbore upscaled permeability
GeoPoDS J functions
Improved RQI
-
GeoPoDS water-oil relative permeability
-
GeoPoDS gas-oil relative permeability
-
GeoPoDS summary
GeoPoDS NWRT PHIE K-Transform Kv/Kh Sw-H function
Kr curve
Shale Shale 0.15 K = 663749*(PHIE)5.5071 y = 8E-07*(Kh)2 + 0.0016*(Kh)+ 0.878
G2 G2
-
Now History match
Chandra et al, 201482
-
Triple Porosity Systems
Indian FieldN African Field
No Fractures Needed in the Models for Reasonable History Matching
Chandra et al, 2014Kazemi et al, 2011
83
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Field G Conclusions
Mismatch between geological model and reservoir simulation modelled resolved
Finer detail petrophysics Very high resolution NWB model Upscaled Rock Types ( GeoPODS) Improved History Match (without tuning) No significant fractures
apart from the stylolite-related fractures that are incorporated in stylolite GeoPOD.
84
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Triple Matrix Porosity Systems
Indian Field GNorth African Field H
Three RTs only needed in the Models for Reasonable History Matching without need for fracture modelling 85
-
Conclusions
Missing permeability in carbonates due to biased sampling and missing scale modelling
Simulation model can show large corrections to geomodels to get history match
Identifying key (3?) RT variations and upscalingthese can lead to improved history matching
Use of upscaled RTs enabled through NWB modelling
Consider Triple Matrix Porosity (GeoPODS) for heterogeneous reservoir models
86
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Acknowledgements Total Professorship (1994-2011) BG Group Professorship (2012-2017) Colleagues
Sebastian Geiger, Alireza Kazemi Students
Viswasanthi Chandra International Centre for Carbonate Reservoirs
DynaCARB Project Schlumberger (Ecplise), Geomodelling (SBED),
CMG (CMOST, IMEX )
87
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Fractured Reservoir Myths
Majority of fractures have a high angle origin but only to bedding (Lewis, HWU) Is use of curvature good OK for thinly bedded systems (Couples, HWU) Is fracture porosity always low (1-2%) yes generally but not always (Quenes,
Sigma3) is the fractal model a good one there are length scales, layering and the
mechanical stratigraphy is important (Couples, HWU; Riva GE Plan), Mechanical fractures follow existing fracture patterns (Alverellos, Repsol) Thermal Fracturing in low permeability rocks also high permeability sandstones
(Tovar, IES) Continuum fracture models vs Discrete Fracture models upscaling DFN is very
challenging (Geiger, HWU) There is no REV in fractured reservoirs except possibly at the seismic bin scale
(Quenes, Sigma3) and at the bed scale (Couples, HWU; Riva GEPlan) Basement provide seals and migration barriers but not if fractured (Hartz, Det
Norske Oljeselskap) Ruger equation can give fracture orientation and density simple laboratory
models show this equation sometimes holds (Chapman, Edinburgh University)
Source: EAGE-SBGf Fracture workshop Rio Nov 201388
-
Fracture Reservoir Agreement
Fractures are difficult to locate but easy to predict with the correct structural model (Lewis, HWU)
Fracture Models should be driven by data and concepts (Riva, GE Plan)
Fractures develop though complex history of burial and many stress episodes(Bezerra, UFRN; Betotti (TUDelft)
Lithology and facies have an impact on fracture distributions (Cazarin, Petrobras)
Need to model fractures in 3D (Hartz, Det Norske Oljeselskap; Moos, Baker-Hugues)
A multidisciplinary approach to tackle fractures is necessary
Source: EAGE-SBGf Fracture workshop Rio Nov 201389
-
All reservoirs are fractured!
What Gary Couples and I can agree on: We think all carbonates are fractured, but the
fractures MAY not be playing a major role in flow
So All reservoirs are fractured and some fractures are useful for flow
And Sometimes reservoirs that appear fractured may actually have very high matrix contrasts
90
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ReferencesChandra, Corbett, Hamdi and Geiger, 2011, Improving Reservoir Characterisation and Simulation with Near Well boremodelling, SPE 148104, SPE Reservoir Characterisation and Simulation Conference, 9-11 October, Abu Dhabi.
Kazemi, Corbett, and Wood, 2012, New approach for geomodeling and dynamic calibration of carbonate reservoirs usingporosity determined system (PODS). Presented at 74th EAGE conference and Exhibition, Copenhagen, Denmark, 4-7 June2012.
Chandra, Geiger, Corbett, Steele, Milroy, Barnett, Wright, Jain, 2012, Using Near Well Bore Upscaling to improve reservoircharacterisation and simulation in highly heterogeneous carbonate reservoirs, SPE 166033, SPE Reservoir SimulationConference
Oates, Chandra, and Corbett, 2013, Evaluating the role of meteoric karst vs burial corrosion in an offshore IndianCarbonate Field, AAPG
Chandra, Corbett, Hamdi, and Geiger. 2013. Improving Reservoir Characterisation and Simulation with Near-WellboreModeling. SPE Res Eval & Eng 16 (2): 183-193. SPE-148104-PA. May.
Chandra, V., Steele, R., Milroy, P., Corbett, P.W.M. and Geiger, S. 2013b. Using near-wellbore modelling and dynamiccalibration to improve permeability modelling in a giant carbonate field. Oral presentation at 75th EAGE Conference &Exhibition incorporating SPE EUROPEC 2013, TU 14 15
Chandra, Wright, Barnett, Steele, Milroy, Corbett, Geiger and Mangione, 2014, Evaluating the Impact of a Late BurialCorrosion Model on Reservoir Permeability and Performance in a Mature Carbonate Field Using Near Wellbore Upscaling,Geol Soc Spec Publication Fundamental Controls on Fluid Flow in Carbonates: Current Workflows to EmergingTechnologies (Paper accepted for publication)
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