©MBDCI
Sampling, Preserving and Testing Heavy
Oil Sand Cores
Maurice Dusseault
Sampling Viscous Oil Sands
©MBDCI
Sampling Viscous Oil Sands
©MBDCI
Canadian Experience
Heavy oil core samples exhibit expansion of
1% to as much as 12%
 Lab values of  = 34-40% are quite
common
 Porosities in the ground, calculated from
geophysical logs, are consistent – 29-31%
 Reservoir parameters based on expanded
core samples can give serious problems
 The expansion cannot be fully reversed by
using
overburden
pressures
on
specimens
Sampling Viscous Oil Sands

©MBDCI
International Experience
Kazakhstan - Karazhanbas - largest heavy
oil field in the FSU – core damage issues
 Venezuela – Orinoco Extra Heavy Oil
Sands – largest extra heavy oil deposit in
the world – severe core damage issues
 China – Liaohe and Karamay – damaged
heavy oil sands core leads to problems
 Colombia – Magdalena heavy oil fields –
damage leads to poor choice of technology
 Oman, Ecuador, USA, …
Sampling Viscous Oil Sands

©MBDCI
KARAZHANBASMUNAI - KZ
Kashagan Tengiz
Karazhanbasmunai
(i.e. Karazhanbas
Oilfield)
Aktau
Sampling Viscous Oil Sands
©MBDCI
Study Area
Kulsary
Atyrau
Astrakhan
PreCaspian Basin
TENGIZ
CASPIAN
SEA
N. BUZACHI
(Texaco)
KARAZHANBASSHELF
Tengiz
ARMAN
(Kerr-McGee)
KALAMKAS
(MMG)
Karazhanbas
(NECL)
Roads
Oil Pipelines
Sampling Viscous Oil Sands Aktau
©MBDCI
The Problems

Data, based on core analyses only, gave…
 Porosities
of 33-38%
 Permeabilities of 4-8 D
 Gas saturation of 1-8%
 High kw

(~31%)
(~2-3D)
(Sg = 0)
(low kw)
The field was operated on a 50% production
share basis. Issues…
 Service
company problems (core tests…)
 Regulatory agency problems (KZ - CDC)
 Poor predictions of recovery and rates
Sampling Viscous Oil Sands
 Poor choice of technology
©MBDCI
Faja del Orinoco (XH Oil)






Extra-heavy crude
oil deposits
> 1.21012 BOIP
 ~ 0.30, z ~ 450800 m, So ~ 0.88
Unconsolidated
Estimated 25%
recoverable with
current methods
SAGD – CHOPS –
HWCS …
Sampling Viscous Oil Sands
©MBDCI
Faja del Orinoco
-On the order of 200109 m3 OOIP
-1000-6000 cP oil, <10ºAPI
- = 30%, k = 1-15 D
-z = 300-700 m
Sampling Viscous Oil Sands
©MBDCI
Faja Stratigraphy
Seq.
.
Strat
Ma
GR
M1
16.8
M9
17.0
B
MFS
M12 17.1
C1
MFS
Lower delta plain
DELTAIC
MFS
M14 17.3
C2
Top D1 19.1
D1
Top D2
D2
Top D3
Alluvial/Upper delta plain
TS/
MFS
FLUVIAL
level fall
A
Long term base level rise
Long term base
MFS
Architecture
Upper delta plain
Base level
cycles
D3
Top E1
E1
E2
F
Unconformity
Sampling
Viscous Oil Sands
Top E2
Top F
Base F.
23.8
Cambrian/Cretaceous sedimentary rocks
©MBDCI
The Problems

Core damage led to:
 Excessively
high permeabilities
 High lab compressibilities (40-10010-6 psi-1)

This led to a “belief” in compaction drive
 Lake
Maracaibo heavy oil reservoirs benefit
substantially from compaction drive

Vast sums of money and field experiments
 Based

on expanded core properties
Finally, in the 1990’s, the issue disappeared,
but only after much time and money was spent
Sampling Viscous Oil Sands
©MBDCI
Evidence of Core Damage
Porosity
Porosity vs. Permeability - Edam Core
0.43
0.41
0.39
0.37
0.35
0.33
0.31
0.29
0.27
0.25
Typical value, good
heavy oil sands: 31%
0
1000
2000
3000
4000
5000
6000
7000
Permeability - mD
Sampling Viscous Oil Sands
EDAM Field, Well 15-29
©MBDCI
Edam Core, Well 7-30
Porosity
Porosity vs. Permeability - Edam Core: 7-30
0.4
0.38
0.36
0.34
0.32
0.3
0.28
0.26
0.24
0.22
0.2
Typical value, good
heavy oil sands: 31%
0
2000
4000
Permeability - mD
Sampling Viscous Oil Sands
6000
8000
©MBDCI
Well 13-29 – Edam Field
Porosity vs. Permeability - Edam Core: 13-29
0.5
Porosity
0.45
0.4
0.35
0.3
0.25
Typical value, good
heavy oil sands: 31%
0.2
0
2000
4000
6000
Permeability - mD
Sampling Viscous Oil Sands
8000
10000
©MBDCI
Edam Well 6-29
Porosity
Porosity vs. Permeability - Edam Core: 06-29
0.38
0.36
0.34
0.32
0.3
0.28
0.26
0.24
0.22
0.2
Typical value, good
heavy oil sands: 31%
0
1000
2000
3000
4000
Permeability - mD
Sampling Viscous Oil Sands
5000
6000
7000
©MBDCI
Conclusions from Edam Core


Lab porosities are consistently too high
The “correction factor” is not consistent among
different wells
 Different
coring practices and operators
 Different hardware
 Different treatment in transport, storage, lab
The differences are not trivial
 We may expect other properties to be affected,
often to the detriment of the company
 Can these issues be resolved?
Sampling Viscous Oil Sands

©MBDCI
Evidence of Core Expansion
Radially
Axially
Schematic Diagram of Expansion of an 89 mm Core
90-91 mm
Corrugated surface
characteristic of thinlybedded and laminated
fine-grained sands of
variable oil saturation
Oil-poor to oilfree silty sands,
expansion much
less than other
material
95 mm
Oil-rich sample
expands to
completely fill
the liner
Core has expanded from 120.7mm to
127mm diameter and is now acting
like a piston in a cylinder
89 mm
Ironstone
band, no
expansion
PVC
liner
Cores separate readily along cracks which form
between zones of differing expansion potential
127 mm
Oil sand
Gas pressure inside liner
Observed Expansions of 89mm Core:

Ironstone
89 mm

Basal clays, clayey silts
89-91 mm

Oil-poor to oil-free silty sands
90-93 mm

Fine-grained oil-rich sand
91-95 mm

Coarse-grained oil-rich sand
94-95 mm
Sampling Viscous Oil Sands
ref. Dusseault (1980) Fig. 5 & 6
©MBDCI
Reasons for Core Expansion





CH4 present in solution, exsolves during the
Δp in bringing core to surface
The high oil content means a lot of gas
High μ oil means gas cannot drain; no
continuous gas phase is formed without ΔV
The sand is cohesionless (To = 0); it cannot
resist internal expansion
The core barrel liners are 7%-13% oversize,
allowing a lot of expansion
Sampling Viscous Oil Sands
Heavy Oil
Cores, MR
Scans
Sampling Viscous Oil Sands
©MBDCI
Courtesy of Glen
Brook, Nexen and
Apostolos
Kantzas, U of
Calgary
decreasing density
©MBDCI
CT-Scan Evidence of Damage in Heavy Oil Cores
Courtesy
Glen Brook, Nexen and Apostolos Kantzas, U of Calgary
Sampling Viscous
OilofSands
©MBDCI
Core Damage Consequences






Porosity overestimated
Permeability measurements in the lab are too
high by a factor of ~1.5 to 2
Laboratory data for So, Sw, Sg are wrong
Reserve estimation can be out by 5-10%
Predicted productivity index by factor of 2
All rock mechanics data are in error
 Compressibilities
are too high by a factor of >10
 Rock strength predictions far too low
Viscous
Etc…Oil Sands
Sampling
©MBDCI
History…




“Evaluation of the
Alberta Tar Sands”
Sah, Chase, & Wells
SPE 5034 (1974)
Old Problems…
These issues are “rediscovered” repeatedly
However, the issue is
relatively welldocumented (SPE,
CJPT, conferences…)
Sampling Viscous Oil Sands
©MBDCI
Empirical Evidence
Zwicky and Eade (Shell) UNITAR, 1977
Table 3. Comparison of results from core analysis
alone and density from logs, Lease 13, average data
Core
Analysis
Density
Log
Difference
Percent
change
35.5
32.0
-3.5
-10
Tar
Saturation
69
81
+12
+17
Water
Saturation
31
19
-12
-39
Porosity
Sampling Viscous Oil Sands
©MBDCI
Log Derived Porosity
Neutron porosity is not a true measure of
porosity (it actually is a measure of H)
 Determine the true density using a gammagamma density log (average over 1 m)
 Calculate  based on this density number
 Heavy oil sands in situ are almost always
liquid saturated (i.e.: Sg = 0)
 Determine saturations from cores
 Some factors (grain size, mineralogy, liquid
Samplingdensities…)
Viscous Oil Sands are not affected by expansion

©MBDCI
Density Relationship
Intact rock
}
(1 - )
Sampling Viscous Oil Sands
rlog = Soro + Swrw + (1 – ) Gm
Where:
So = oil saturation
Sw = water saturation
rlog= density from logs
ro = density of oil
rw = density of water
Gm = matrix density
Calculate Porosity from gg Log
=
©MBDCI
Gm - rlog
Gm - Soro - Swrw

So, Sw, ro, rw from core (Sg = 0)

Gm is measured on a grain sample

Then, do quality control assessments
Sampling Viscous Oil Sands
©MBDCI
Quality Control Assessments

Obtain So and Sw from log analyses, compare
to lab data to decide if saturations are correct
 Perhaps
some water invasion occurred
 Always assume Sg = 0, but check on logs


Decide which to use
When you have lab-derived porosities and
geophysical-derived porosities:
 Cross
plot of the two
 Examine the data to see what is happening
 Make decisions…
Sampling Viscous Oil Sands
©MBDCI
Porosity Cross Plot
0.40
Log-derived porosity
“Typical” heavy oil case
0.38
Porosity in serious error
0.36
Is it valid to apply an
“average” correction
factor to core data??
0.34
Probably not…
Reasonable data,
acceptable scatter
0.32
Best is to use individual
values of log-derived
porosity information
0.30
Adjust your core data as
required
0.28
0.28 0.30
“average”
error in 
0.32
0.34
0.36
0.38
Core-derived porosity
Sampling Viscous Oil Sands
0.40
©MBDCI
Quality Control



X-plots are useful
Careful with “average” corrections
You can even check using neutron porosity,
but you must be careful!
 CNL
log numbers may be wrong in heavy oils,
which tend to be deficient in hydrogen, as
compared to conventional oil correlations
 If there is a lot of clay, the CNL data may also be
off the mark somewhat (1-2 porosity units)
 Get your logging company to help calibrate your
field case
Sampling Viscous Oil Sands
©MBDCI
More Methods



Needle penetrometer for core consistency
Use of sonic travel time transducers in the
laboratory as a QC method
Visual examination
 Extrusion
when core is cut and boxed?
 Extrusion from cut ends in the lab?
 Core recoveries of 100% always reported?
 Gas bubbling from core surface, fluids extruding?

And so on…
Sampling Viscous Oil Sands
©MBDCI
“Correcting” the Data - A



Clearly, permeability overestimated as well
This is considerably harder to correct
If you have some oil-free, undamaged core
with similar characteristics in your field
 Do
lab tests on undisturbed specimens (check)
 Use these to determine   k equation

Compare log k values with core values
 Is
there a useful “correction factor”?
 Can log data be considered reliable enough?

Find some other way to correct
E.g. Kozeny-Carman correlation, Archie plot…
Sampling 
Viscous Oil Sands
©MBDCI
“Correcting” the Data - B





Recalculate your reserves, volumes, etc.
You can eventually develop a better
empirical log equation to determine
porosity, volume factors, etc. directly
Always test out relationships on specimens
that are undisturbed (if this is possible)
I used outcrop samples to do this
High quality coring may help, but…
 Can’t
avoid expansion in heavy oil sands
 Even core plugging at room temp is damaging
 Nevertheless, do the best possible…
Sampling Viscous Oil Sands
©MBDCI
A Few More Slides…
Sampling Viscous Oil Sands
©MBDCI
Index of Disturbance
core  densitylog
ID 
densitylog
A quantitative measure of core disturbance.
e.g.: Dusseault, 1980, used by others, e.g.
Settari, et al. (1993) ID = [10.2%, 18.4%]
Sampling Viscous Oil Sands
©MBDCI
Index of Disturbance
POROSITY (%) - Laboratory
40
35
30
ID < 10%
10% < ID < 20%
20% < ID < 40%
40% < ID
25
Intact or slightly disturbed
Intermediate disturbance
Highly disturbed
Disrupted generally
Dusseault & van Domselaar (1982) Fig. 2
20
35
25
30
POROSITY (%) - Geophysical Density Log
Sampling Viscous Oil Sands
40
©MBDCI
ID - Oldakowski Table 4.3
POROSITY - Laboratory (%)
40
35
30
25
Oldakowski (1994)
POROSITY - Geophysical Density Log (%)
20
Sampling Viscous Oil Sands
25
30
35
40
©MBDCI
Heavy Oil Core Data

Weight percent bitumen
 Mining

application
Summation of fluids
 Grain
weight and Total weight
 Dean-Stark water
 (sometimes) Dean-Stark bitumen – corrections

Do not correlate with well logs because of
the core dilation problem…
Sampling Viscous Oil Sands
©MBDCI
!!
Core Porosity
v.
Log Porosity
“Evaluation of the Alberta Tar Sands”
Sah, Chase, & Wells
SPE 5034 (1974)
Sampling Viscous Oil Sands
©MBDCI
Low Disturbance Samples




Dr. Amin Touhidi-Baghini, PhD thesis
(1998)
McMurray sample from river valley outcrop
Minimal disturbance: no gas ex-solution
Absolute Permeability measured:



at low confining stress
during shear failure
Best laboratory data available (to the
present time)
Sampling Viscous Oil Sands
©MBDCI
Ka Multiplier K2 / K1
Absolute Permeability Increase
6
5
4
Vertical
6x
3
2.5x
2
Experimental
Kozeny-Carmen
Chardabellas B=2
Chardabellas B=5
Horizontal 1.6x
5%
1
5%
Vertical core
specimens with an
average porosity of 33.9%
-4 -2
0
2
4
Volumetric Strain
6
8
ev (%)
10
Horizontal core
specimens with an
average porosity of 33.7%
-2
0
2
Volumetric Strain
Sampling Viscous Oil Sands
ref. Touhidi-Baghini (1998) Fig.8.21 & 8.22
4
6
ev (%)
©MBDCI
What Has Been Tried?








Pressure core barrels
Non-invasive fluids
Special core catchers
Special freezing during transport
Re-stressing before testing
And so on and so forth
None of these methods has been satisfactory.
The best results have been obtained by…
Sampling Viscous Oil Sands
©MBDCI
Best Results
Sampling in a tunnel through an outcrop
where gas pressure was depleted
 In other outcrops (but Sw is incorrect)
 In very shallow boreholes where pgas is low
 Core barrels of short L, small potential for
radial expansion, + axial restraint
 Use of analogue materials from outcrops
(e.g. the oil-free outcrops along riverbanks)
 Intact samples of deep heavy oil UCS sands
highly
problematic. Is it worth doing??
Samplingis
Viscous
Oil Sands

©MBDCI
Then What?

If “successful” core has been brought to
surface…
 Freeze
to dry ice T for transport
 Keep fully sealed

Prepare test specimens in cold room (-25°C)
 Do
not plug with a fluid (heat–expansion–etc)
 Slow lathes for trimming to diameter OK
 Trim ends flat in the lathe as well

Mount specimens while cold, thaw only when
under pressure…
Sampling Viscous Oil Sands
©MBDCI
Coring







Only very shallow cores (<100 m) have
achieved any reasonable ID values
A specialized, short length core barrel is
advised
Internal flush (no radial expansion)
Protruding cutting edge (avoid fluid contact)
Some method for axial restraint
“Rigid” core sleeve
Etc.
Sampling Viscous Oil Sands
©MBDCI
Sampling Viscous Oil Sands
©MBDCI
Conclusions

Core damage can be a very serious issue
 Mis-estimation
of reserves by 10-15%
 Over-estimate permeabilities by factor of 2 to 4
 And so on…

Geophysical log-derived  is best
 Use
lab or log So, Sw?
Calibrated neutron porosity is “OK”
 Put into place quality control measures on
coring, testing, lab procedures, log analysis
 Then, just do the best you can…
Sampling Viscous Oil Sands
