Special Core Analysis
Challenges, Pitfalls and Solutions
Colin McPhee
SPE London May 26 2015
The geomodel juggernaut!
=
• Modelling is ‘finished’, but the forecasts do not match observations,
imagine the reaction to a request to go back & check core data inputs.
• Often happens & each time the team’s protestations are loud.
• Very hard to stop the ‘geomodel juggernaut’, usually built on a tight
budget that is almost spent & to a deadline that is getting closer
2
Cultural resistance to change – “I know my place”
• Cultural issues can prevent the
models from being improved.
• Reluctance to change model
inputs as may have to admit
mistakes were made to peers.
• Misplaced respect for elders.
• Fear of management’s response
when told of model rebuild
3
Core data for static and dynamic models
• Core tests provide fundamental input to static (in place) and
dynamic (recovery factor) reservoir models
STOIIP  GRV 
fw 
N
1
   1  Sw 
G
B0
N, , Sw from RCA & SCAL
1
1
k ro  w
.
k rw  o
kro and krw from SCAL
• Core data experiments are….
•The ground truth!
4
The elephant in the room
• SCAL data have uncertainties that
few end users want to discuss or
contemplate (or even want to
know about)
• Misinterpretation and poor
practice impact on static and
dynamic modelling
5
The Ground may be shakier than you think
• Based on review of > 50,000
SCAL experiments……
• 70% of SCAL unfit for purpose
• core damage
• variable data quality
• inadequate program planning and
inappropriate design
• poor reporting standards
• method-sensitivity
• vendors reluctant to share
experience and expertise
6
Core damage
• During coring
• Oil-based mud usually alters
wettability
• Difficult to remove sometimes
• Mud invasion and shear failure in
weak rock
• During core recovery
• POOH too fast results in tensile
fracturing if pore pressure cannot
dissipate
• During wellsite/lab handling
• Liners flexing/bending
• Freezing
• Poor stabilisation
• Poor preservation
7
Formation evaluation – examples of SCAL
• Porosity
• Permeability
• Capillary Pressure
Porosity
Permeability
• Drainage and imbibition
• Relative Permeability
8
Porosity
• Core porosity - Total or Effective?
• Humidity dry for effective porosity?
T > HOD > E
Absolute or Total Porosity Øt
Matrix
Effective Porosity Øe
VClay
Grains
Clay
Layers
Clay surfaces &
Interlayers
Small
Pores
Bound Water
Capillary
Water
Structural Water
Large Pores
Isolated Pores
Volume
available for
storage
Irreducible or
Immobile Water
Usually assumed negligible
in Clastics
Often assumed negligible
in Carbonates
Often significant in Clastics
May be significant in
Carbonates
9
Porosity (RCA)
Vg & VbHg
• Two different methods
Vb  Vg
Vb
Vp
 
Vg  Vp
 
Vp & Vg
• Two different results!
Vp+Vg
Vg+VbHg
10
Porosity compaction at stress
• Sensitive to “insignificant” artefacts
• Two labs – two different results!
• Annulus volume between sleeve & plug
stress/amb
• Check pre- and post-test results
Net confining stress (psi)
Porosity Change
1.00
0.80
0.60
(p.u.)
Porosity Change
Porosity Change Post-Test (p.u.)
0.40
+ 0.25 p.u.
0.20
0.00
-0.20
- 0.25 p.u.
-0.40
-0.60
-0.80
-1.00
0.0
5.0
10.0
15.0
20.0
Pre-Test Porosity (%)
Pre-test porosity (%)
25.0
30.0
35.0
11
Permeability
• What is the permeability in your static 3D model?
10000
Kl (mD)
1000
100
10
y = 0.851x1.020
R2 = 1.000
1
1
10
100
1000
10000
Kg (mD)
Kg @ Swir @ Stress (mD)
Kair after harsh drying (mD)
• Air permeability?
• Klinkenberg? – measured or from a correlation?
• Brine?
• Ambient or stressed?
• What stress?
• How measured – steady or unsteady-state?
• How were plugs prepared?
• Does it matter?
Gas vs. Klinkenberg (measured) permeability (20- 30
bar NCP)
Kair after HOD (mD)
Kair at 400 psi (mD)
12
Capillary pressure (drainage)
Height above FWL (ft)
• Principal application in saturation-height modelling
• Pc (Height) versus Sw by rock type, rock quality and height
J Function
Water Saturation (-)
Carbonate J function by R35 bin
Normalised Sw
13
Capillary pressure (drainage)
• Mercury injection capillary pressure
• NOT a capillary pressure test (just looks like one)
• No Swir: Sw goes to zero at high injection pressure
• Lower Sw at high Pc
• Core damage at high injection pressures?
200
Air-Brine Lab Capillary Pressure (psi)
67B K=4563.84 mD phi=0.4 RQI=3.572
175
67B K=4563.84 phi=0.36 RQI=3.58
150
251A K=582.62 mD phi=0.4 RQI=1.373
125
251A K=582.61 phi=0.31 RQI=1.38
100
264B K=2441.96 mD phi=0.3 RQI=3.084
75
264B K=2441.96 phi=0.26 RQI=3.09
50
411B K=183.06 mD phi=0.3 RQI=0.791
25
411B K=183.06 phi=0.29 RQI=0.8
0
0.0
0.2
0.4
0.6
0.8
1.0
Sw (frac)
14
Capillary pressure (drainage)
• Centrifuge
• Pc maximum at inlet face of plug


Pci ~ 1.6 x10 7  w   h  re2  ri 2 RPM 2
• Calculation of inlet face saturation



Si  d d ( Pc).S .Pci  S  Pci .
dS
d ( Pci )
Sample No. 136S
Depth (m): 2825.760
Porosity (%): 21.2
Gas Perm (mD):
52.4
130
120
Hassler Brunner
Average
Dean-Stark Sw
110
Inlet face Pc (psi)
Capillary Pressure (psi)
100
90
80
70
60
50
40
30
20
10
0
Water Saturation
0
10
20
30
40
50
60
Brine Saturation(%)
70
80
90
100
15
Capillary pressure (drainage)
• Centrifuge vs MICP vs porous plate (PP)
• MICP
• no wetting phase – no Swir – Sw always lower at higher Pc
• Centrifuge
• No entry pressure (compared to MICP & PP) - Abrupt transition to Swir
MICP
Scaled Lab Pc (psi)
PP Pc
Centrifuge
16
Water Saturation
Capillary pressure (drainage)
• Porous plate
• Good but slow
• Potential loss of capillary contact
• Potentially slow drainage
1.00
Pc=2.900 psi
Pc=5.075 psi
Pc=20.01 psi
0.80
Pc=36.250 psi
Pc=72.500 psi
Water saturation, Sw
Pc=101.500 psi
Water Saturation
Air-Water Capillary Pressure (psi)
0.60
0.40
0.20
0.00
0
50
100days
Time,
150
200
Time (days)
1000
Water Saturation
x, RI
100
17
Imbibition Pc (water-oil)
4
• errors later corrected
• Plugs found to be fractured
0.0
0.2
0.4
0.6
0.8
1.0
0.8
1.0
(psi)
Capillary Pressure
Pc (psi)
-20
-40
Senergy Average
(Forbes-1 Press.)
Senergy Average
(Forbes-2 Press.)
Senergy Endface
(Forbes-1 Pc)
Senergy Endface
(Forbes-2 Pc)
Rep. Lab Average
(Forbes-2 Pc)
Rep. Lab Endface
(Forbes-2)
Rep. Lab DS Sw
-60
-80
-100
-120
Water Saturation
Sw (frac.)
10
0
0.0
0.2
0.4
0.6
-20
-40
Pc (psi)
Capillary Pressure (psi)
• Example results oil-brine
imbibition Pc
• Lab average Sw does not
agree with Dean-Stark
• If average Sw wrong then end
face Sw and Pc-Sw wrong
• Did lab not think Sro = 40%50% strange?
• 3 iterations (and about 3
months) before lab’s
calculated Pc-Sw curves
matched our calculations
• Lab upper-management were
initially unaware of the issues
0
-60
-80
-100
Senergy Average
(Forbes-1 Press.)
Senergy Average
(Forbes-2 Press.)
Senergy Endface
(Forbes-1 Pc)
Senergy Endface
(Forbes-2 Pc)
Rep. Lab Average
(Forbes-2 Pc)
Rep. Lab Endface
(Forbes-2)
Rep. Lab DS Sw
-120
18
Water Saturation
Sw (frac.)
Relative permeability
•“Most relative permeability data are rubbish – the
rest are wrong!” Jules Reed, LR Senergy, 2013
1
Clean
State
0.9
>200 samples – 6 usable
Fresh
State
Residual Oil Saturation (v/v)
0.8
0.7
Restored
State
0.6
C = 0.6
0.5
0.4
C = 1.5
0.3
C = 2.5
0.2
0.1
C = 10
0
0
0.2
0.4
0.6
Initial Oil Saturation (v/v)
0.8
1
19
Why are they rubbish?
• Plugs unrepresentative or plugged incorrectly
• Swir too high and/or non-uniform
• Wettability contaminated or unrepresentative
WW
SWW
MW
SOW
OW
1
0.9
Relative Permeability
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
0.2
0.4
0.6
Saturation
0.8
201
Why are they wrong?
• Coreflood testing invalidates analytical theory
Water Saturation (-)
Water Saturation
• Flow is linear and uni-directional
• Capillary effects are negligible
Ncres x100
Ncres x10
Ncres
Sample Length
Length along core (slice)
21
Capillary end effects
Nc_res x100
Nc_res x10
Nc_res
1
0
Capllary Pressure
Differential Pressure
Ncres x100
Ncres x10
Ncres
Sample Length
-1
-2
-3
-4
-5
-6
-8
0
0.2
0.4
0.6
0.8
1
Water Saturation
Saturation is controlled by capillary number (Nc)
Nc = k DP
s Dx
Ncres x100
Ncres x10
Ncres
1
Sample Length
Pressure
0
1-
2-
3-
4-
lary
ser_cN 01x ser_cN 001x ser_cN
Water Saturation
-7
What are the solutions?
• Carefully review legacy data
• Identify uncertainties and impact on:
Drilling &
Completions
• In place calculations
• Recovery factor
• What is the value of information?
• Is it worth doing the experiments at all?
Petrophysics &
Geology
Reservoir
Engineering
Focal point
Laboratory
• Or is it because we have a table to fill in in Eclipse
• New core data
• learn from legacy data review
• integrated program design
• focal point
• improved test and reporting documentation
23
What are the solutions?
• Lab audit
• Assess resources, equipment,
experience and expertise of
management and technicians
• Check plugs
• Test data set interpretation
• Design programme with
stakeholders and lab
• Do not “cut and paste” from
previous jobs
• Do not pick from a “menu”
• Draw up flowchart
• Look where value added at little
incremental cost
• Iterate, iterate, iterate
24
What are the solutions?
• Relative permeability
• Ensure wettability is representative
• Test design
• In situ saturation monitoring
• Coreflood simulation
25
0
%
Sw(NaI)
100
%
Water Saturation
• Reveals what is going on in the core plug
X-ray adsorption
Relative permeability - ISSM
26
Length along core (slice)
Relative permeability - coreflood simulation
• Recommended practice for ALL relative permeability tests
• Several non-unique solutions are possible so need to sense check
27
Test specifications/data reporting
• Detailed test and reporting specifications
• define test procedures and methods
• Define what, when and how reported
• experimental data essential
• use to verify and check lab calculations
• allows alternative interpretation
• most labs retain experimental data only for short time
• Tedious and time consuming … but
• essential in data audit trail
• invaluable in unitisation
• can save money as you may not have to repeat tests
28
Test specification example – centrifuge Pc
29
Plugbook
Core Plug History Chart
• Plug data
• Base properties
• porosity and permeability
• History
• when/how cut, cleaned & dried
• SCAL test history
• Plug CT scans
Plug Parameters
Digital Images: Side and End Face
Sample No.:
Depth (m) :
Length (cm) :
Diameter (cm) :
116
3906.20
5.02
3.88
Plug Base Data
Ambient
Air Permeability (md) :
Porosity (%) :
Grain Density (g/cc) :
0.340
10.6
2.648
Overburden 3035 psi
Air Permeability (md) :
Porosity (%) :
0.182
10.1
Pre-test photographs & CT images:
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Study Flow Chart
Sample preparation
Drilled with Brine : 23-May-07
Hot solvent cleaned & oven dried @ 95°C
In 14-Jul; out 21-Jul
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CT scan & pre-test plug photography
Permeability, porosity and grain density
Pressure saturate & Archimede's porosity
• Heterogeneity
• Damage?
• Plug photographs
Formation factor & resistivity index @ NOBP
Dean-Stark
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Hot solvent cleaned; oven dried @ 95°C; and Kphi
Pressure saturate & Archimede's porosity
Centrifuge air-brine capillary pressure
Dean-Stark
• pre-and post-test
Hg injection and CEC on offcuts
Post-test photographs:
Post-test photography
• Can be easily customised
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Report
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30
Summary
• Lab test pitfalls have a huge
impact on core analysis modelling
data input
• But....
• uncertainties are recognisable
and manageable
• best practice, real-time QC, and
robust workflows ensure that core
data are fit for purpose prior to
petrophysical analysis.
• a forensic data quality
assessment can minimise data
redundancy and reduce
uncertainty in reservoir models
Price is what you pay. Value is what you get - Warren Buffet
31
Questions?
32