Baraka-Lokmane, S.

Elphick, S. C.

Main, I. G.

Ngwenya, B. T.

Earth-prints Repository

& School of Engineering and Physical Sciences
S. Baraka-Lokmane1,2,3, I.G. Main1, B.T. Ngwenya1, S.C. Elphick1
1 School of GeoSciences, University of Edinburgh, UK
2 Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh, UK
3 School of Environment and Technology, University of Brighton, UK
Prediction of Reservoir Permeability from 
Petrography Characterisation
29th Course of the International School of Geophysiscs
Euro-Conference of “Rock Physics and Geomechanics” on Natural hazards: thermo-hydro-
mechanical processes in rocks
(EMFCSC, Erice, Sicily, 25-30 September, 2007)
Slide 2& School of Engineering and Physical Sciences
Outline
• Introduction
• Description of the rock material
• Fluid-rock interactions, regression results
• Conclusions
Slide 3& School of Engineering and Physical Sciences
Introduction
Reservoir quality, primarily determined by the porosity and 
permeability of the relevant formations, can be a function of many 
controls including: 
- Nature of the constituent minerals and cement; 
- Degree of rock cementation; 
- Degree of sorting or equivalently the particle size of the grains; 
- Pore-size distribution.
Reservoir engineers, petrophysicists and exploration geologists have 
tried to obtain quantitative relationships between 2-D petrographic
properties and 3-D petrophysical properties. 
McCreesh et al., 1991; Ehrlich et al., 1991; Gerard et al., 1992; Passas
et al., 1996; Mowers and Budd, 1996; Anselmetti et al., 1998; Ioannidis 
et al., 1996
Slide 4& School of Engineering and Physical Sciences
1- A detailed characterisation of three sandstone reservoir 
samples
¾ Fife sandstone  
¾ Locharbriggs sandstone 
¾ Slick Rock Aeolian sandstone
2- Evaluation of the effect of mineralogy on permeability 
and prediction of reservoir permeability from 
petrography characterisation
Purpose of this study
Slide 5& School of Engineering and Physical Sciences
Description of Rock Material
• X-ray Computer Tomography (CT-Scanner)
• Particle Size Analysis
• Petrography (thin sections analysis, using a point 
counting technique) 
• Environmental Scanning Electron Microscopy (ESEM) 
• X-Ray Diffraction (XRD) Analyses
• X-Ray Fluorescence (XRF) Analyses 
• Petrophysical description - permeability and porosity 
Slide 6& School of Engineering and Physical Sciences
X-ray Computer Tomography (CT-Scanner)
Method of
measurement
Measured 
parameters
Comments on the 
advantages 
Comments on the 
disadvantages
3-D X-ray 
Computer 
Tomography
• Rock 
heterogeneity
• Presence of 
iron and 
calcite
• Relatively rapid 
method of 
measurement
• Not destructive 
method
• Interpretation of 
the grey scale is 
challenging
• Previous 
petrography 
analysis  is 
necessary
Slide 7& School of Engineering and Physical Sciences
Iron 
banding
Calcite
Kaolinite
Slick Rock Aeolian sandstone Locharbriggs Sandstone
Fife sandstone
X-ray Computer Tomography (CT-Scanner)
Fife sandstone
Iron banding
Calcite patch
Slide 8& School of Engineering and Physical Sciences
Particle Size Analysis
Slide 9& School of Engineering and Physical Sciences
Particle Size Analysis
Method of
measurement
Measured 
parameters
Comments on the 
advantages 
Comments on the 
disadvantages
3-D Particle 
size
• Rock       
heterogeneity
• Mean grain 
size
• useful to supplement 
porosity for empirical 
permeability 
estimation
• Not always 
easy to obtain 
grains from a 
sandstone 
core 
Slide 10& School of Engineering and Physical Sciences
Petrography
Method of
measurement
Measured 
parameters
Comments on the 
advantages 
Comments on the
disadvantages
2-D Point 
counting using 
thin sections
• Percentages of 
the different 
mineral 
constituents and 
porosity
• Identification of 
the dominant 
cement
• Structural analysis
• Identification of rare 
minerals 
• Time consuming
3-D XRD • Mineralogy 
composition
• Quantitative analysis
• Independent method 
from point counting
• Identification of the 
different types of 
clays
• Minerals present 
with less than 1 % 
of the rock are not 
identified
3-D XRF • Chemical 
composition
• Quantitative analysis 
for most elements 
with concentrations 
as low as 1ppm
• time consuming
Slide 11& School of Engineering and Physical Sciences
FELDESPAR ROCK
FRAGMENT
Quartz arenite
Sub litharenite
Litharenite
Felspathic
litharenite
Lithic
arkoseArkose
Sub arkose
Quartz
Berea
Fife
Locharbriggs
Slick Rock Aeolian
Composition of the three groups of samples shown in the Q-F-RF 
diagram of Folk (1974)
Petrography
Slide 12& School of Engineering and Physical Sciences
Petrography (thin sections analysis using point 
counting technique)
Slick Rock Aeolian sandstone Locharbriggs Sandstone
Fife sandstone
Slide 13& School of Engineering and Physical Sciences
Environmental Scanning Electron Microscopy 
(ESEM) Measurements
Method of
measurement
Measured 
parameters
Comments on the 
advantages 
Comments on the 
disadvantages
3-D ESEM/
EDX
•Wettability of 
the different 
minerals
•Mineral 
identification
•Relatively rapid method 
of measurement
•Qualitative and 
not quantitative 
method of 
measurement
Slide 14& School of Engineering and Physical Sciences
Environmental Scanning Electron Microscopy 
(ESEM) Measurements
Water wet quartz Water wet feldspar
Cement containing kaolinite,                    Very water wet clays
smectite and illite
Slide 15& School of Engineering and Physical Sciences
Strongly oil wet condition
Environmental Scanning Electron Microscopy 
(ESEM) Measurements
Strongly water wet condition
Intermediate in wetness condition
Schematic diagrams of three levels of wettability
Slide 16& School of Engineering and Physical Sciences
Environmental Scanning Electron Microscopy 
(ESEM) Measurements
Water wet quartz Water wet feldspar
Cement containing kaolinite,                    Very water wet clays
smectite and illite
Slide 17& School of Engineering and Physical Sciences
Sandstone Locharbriggs Slick Rock Aeolian Fife
Brine permeability, kl
(mD) 
706 ± 177 285 ± 71 1980 ± 388
Gas permeability, kg
(mD) (200 psi)
1424 ± 35 499 ± 49 1366 ± 63
kg /kl 2.1 ± 0.7 1.9 ± 0.6 0.7 ± 0.2
Porosity, Φ (%) 26.1 ± 0.1 22.3 ± 0.5 23 ± 3
Mean Grain size, 
MGS (μm)
199 ± 5 208 ± 28 348 ± 28
SiO2 content (%) 92.9 ± 0.4 91.5 ± 0.4 97.5 ± 0.1
Cement content (%) 7 ± 2 10 ± 2 5 ± 1
Type of cement illite, kaolinite,
smectite, hematite
Calcite, illite
hematite
kaolinite
Clays content (%) 6 ± 2 5.3 ± 0.9 5 ± 2
Type of clays illite, kaolinite,
smectite
illite kaolinite
Petrographycal and petrophysical parameters of the 3 groups of samples
Slide 18& School of Engineering and Physical Sciences
Fife sandstones
Fife sandstones present systematically different 
petrographical/petrophysical characteristics than Slick Rock 
Aeolian and Lochabriggs sandstones. 
- Most homogeneous rock material; the main detrital
components are represented by quartz; 
- Largest percentage of SiO2 content (97.5 %), 
- Largest mean grain size (348μm);
- Lowest percentage of cement (5 %).
These microstructural characterisations explain the highest 
values of permeability (k ~ 1980 mD) 
- Good agreements between gas and liquid permeability; the 
only clay minerals are kaolinite (5 %).
Slide 19& School of Engineering and Physical Sciences
Slick Rock Aeolian and Locharbriggs sandstones
- Higher values of the ratio between gas and liquid permeability 
(kg/kl ~2). 
- Ilite (5.3%) for Slick Rock Aeolian sandstones
- Smectite, Illite and kaolonite (6 %) for Lochabriggs sandstones.
The swelling clays are responsible for the reduction of the  liquid 
permeability. 
- Smectite tends to swell when exposed to brine. It is very 
hydrophilic due to its “mobile” structure. 
- Illite is a mineral that reacts with brine to a limited extent.
- Kaolinite is not prone to swelling with changes in water content. 
Kaolinite, having a stable, “rigid” structure (due to the strong 
book bonds) reacts with water to a minimum extent
Slide 20& School of Engineering and Physical Sciences
- SiO2, 
- Clay, 
- Cement  
- Porosity 
- Mean grain size (MGS)
Fluid-Rock Interactions
Liquid permeability is correlated to 1 to 5 petrographical / 
petrophysical parameters such as
Slide 21& School of Engineering and Physical Sciences
 
y = 279.27x - 25259
R2 = 0.95
0
500
1000
1500
2000
2500
90 92 94 96 98 100
SiO2, %
L
i
q
u
i
d
 
p
e
r
m
e
a
b
i
l
i
t
y
,
 
k
l
,
 
m
D
Cross-plots for kl versus percentage of SiO2
Fluid-Rock Interactions
Slide 22& School of Engineering and Physical Sciences
Cross-plots for kl versus mean grain size (MGS)
 
y = 9.15x - 1439.50
R2 = 0.72
0
500
1000
1500
2000
2500
100 150 200 250 300 350 400
Mean grain size, MGS, micrometre
L
i
q
u
i
d
 
p
e
r
m
e
a
b
i
l
i
t
y
,
 
k
l
,
 
m
D
Fluid-Rock Interactions
Slide 23& School of Engineering and Physical Sciences
Cross-plots for kl versus percentage of porosity
 
y = 220.73x - 4194.40
R2 = 0.60
0
500
1000
1500
2000
2500
10 15 20 25 30
Porosity, %
L
i
q
u
i
d
 
p
e
r
m
e
a
b
i
l
i
t
y
,
 
k
l
,
 
m
D
Fluid-Rock Interactions
Slide 24& School of Engineering and Physical Sciences
Cross-plots for kl versus percentage of cement
 
y = -153.84x + 1967.60
R2 = 0.47
-500
0
500
1000
1500
2000
2500
0 5 10 15
Cement, %
L
i
q
u
i
d
 
p
e
r
m
e
a
b
i
l
i
t
y
,
 
k
l
,
 
m
D
Fluid-Rock Interactions
Slide 25& School of Engineering and Physical Sciences
Cross-plots for kl versus percentage of clay
 
y = -804.79x + 1511.20
R2 = 0.56
-500
0
500
1000
1500
2000
2500
0.00 0.50 1.00 1.50 2.00 2.50
Clay, %
L
i
q
u
i
d
 
p
e
r
m
e
a
b
i
l
i
t
y
,
 
k
l
,
 
m
D
Fluid-Rock Interactions
Slide 26& School of Engineering and Physical Sciences
Multi-variate regressions were performed using 2 to 5 variables of 
petrographic elements
Calculated parameters:
- Correlation coefficient (R2), 
- Standard deviations (S.D.) 
- Akaike’s Information Criterion (AIC) 
Akaike information criterion (AIC) H. Akaike (1973)
Regression results
pLnMLnAIC −∗⎥⎦
⎤⎢⎣
⎡−= )
2
(3
∑ −= 2)( predobsML
where 
n is the number of data points in the regression
p is the number of independently adjusted 
parameters within the model
ML is the maximum likelihood method 
Ln is the natural log
Slide 27& School of Engineering and Physical Sciences
Variables: 
petrographic elements
Least squares fit R2 S.D. AIC
SiO2 a.  kl = 279.27% SiO2 – 25259.20 0.95 132.44 -100.30
MGS b.  kl = 9.15μm MGS – 1439.50 0.72 319.35 -114.38
Φ c.  kl = 220.73% Φ – 4194.40 0.60 392.63 -117.68
Cement d.  kl = – 153.84% Cement + 1967.60 0.47 439.83 -119.49
Clay e.  kl = – 804.79% Clay + 1511.20 0.56 402.37 -118.07
SiO2, MGS f.  kl = 254.11% SiO2 + 1.13 μm MGS – 23181.2 0.95 132.68 -99.74
SiO2, Clay g.  kl = 283.78% SiO2 + 21.88% Clay – 25701 0.94 137.20 -101.68
SiO2, Φ h.  kl = 285.41% SiO2 – 7.86% Φ – 25656.60 0.94 137.04 -100.25
SiO2, Cement i.  kl = 265.82% SiO2 – 15.84% Cement – 23872.60 0.95 133.35 -99.81
MGS, Φ j. kl = 6.61μm MGS + 113.16% Φ – 3331.46 0.79 267.65 -110.96
MGS, Cement k. kl = 7.27μm MGS – 77.39% Cement – 331.71 0.78 273.31 -111.29
SiO2, MGS, Clay l. kl = 259.75% SiO2 + 2.20μm MGS + 142.96% Clay – 24102.9 0.95 131.51 -98.96
SiO2, MGS, Cement m. kl = 235.27% SiO2 + 1.28μm MGS – 18.25% Cement – 21308.2 0.95 132.31 -99.05
SiO2, Cement, Clay n . kl = 266.92% SiO2 – 15.68% Cement + 4.70% Clay – 23981.40 0.94 138.78 -99.81
SiO2, Clay, Φ o. kl = 294.77% SiO2 + 34.14% Clay – 10.85% Φ – 26496.90 0.94 142.09 -100.19
SiO2, MGS, Φ p. kl = 257.14% SiO2 + 1.10 μm MGS – 3.20% Φ – 23386.4 0.94 138.03 -99.73
MGS, Cement, Φ q. kl = 5.69μm MGS – 59.35% Cement + 89.68% Φ – 2089.31 0.83 238.75 -108.49
MGS, Clays, Φ r. kl = 5.73μm MGS – 97.57% Clay + 114.65% Φ – 3056.58 0.78 277.06 -110.88
SiO2, MGS, 
Clay, Φ
s. kl = 272.01% SiO2 + 2.22μm MGS + 158.13% Clay – 12.34% Φ –24992.4 0.95 136.31 -98.83
SiO2, MGS, 
Cement, Φ
t. kl = 236.19% SiO2 + 1.27μm MGS – 18.20% Cement – 0.92% Φ – 21371.8 0.94 138.18 -99.05
SiO2, MGS,
Cement, Clay
u. kl = 242.86% SiO2 + 2.20μm MGS – 15.71% Cement +125.82% Clay –
22379.9
0.95 132.77 -124.63
SiO2, Cement, 
Clay, Φ
v. kl = 275.45% SiO2 – 15.09% Cement + 14.15% Clay – 7.79% Φ – 24617.7 0.94 144.56 -99.77
SiO2, MGS , 
Cement, Clay, Φ
w. kl = 252.86% SiO2 +2.21μm MGS -– 15.00% Cement +138.02% Clay –
9.30% Φ – 23127.4
0.94 138.61 -98.34
Regression results
Slide 28& School of Engineering and Physical Sciences
kl = 272.01% SiO2 + 2.22μm MGS +
158.13% Clay – 12.34% Φ –24992.4
Best Model
R2 = 0.95
S.D.= 136.31
AIC = -98.83 
Results
Slide 29& School of Engineering and Physical Sciences
Conclusions
This study shows that the permeability of sandstone 
cores can be predicted from the measurement of the 
percentages of silica (SiO2), which can be performed with 
the help of XRF analyses using only 50 g of material from 
rock sample. 
The results obtained in this study have useful application 
in the estimation of reservoir permeability where samples 
are not available for experimental testing.
Slide 30& School of Engineering and Physical Sciences
Conclusions
The results of the different methods used were found to 
be consistent with each other, but the combination of a 
variety of methods has allowed a more complete 
characterisation of the rock samples than each method 
used on its own.
This study has shown that rock heterogeneity at the sub-
cm scale may have a significant effect on reservoir 
petrophysical characterisation.
Slide 31& School of Engineering and Physical Sciences
The total radiological density depends on both the mineralogical and chemical composition of 
the rock  and the porosity. The radiological density is expressed in Hounsfield modified units (H.M.U.).
• Very dark grey: quartz and feldspar, they have a physical density varying between 2.55 and 2.76 g/cm3. 
The quartz and feldspar have a low radiological density varying between –120 H.M.U. and –160 H.M.U.
• Dark grey: kaolinite, it has a low physical density () (2.60 g/cm3).
• Light grey: muscovite and illite, they have a medium physical density (2.80 g/cm3) and therefore a 
medium radiological density due to the presence in their chemical formula of potassium.
• Light grey:  potassium feldspars (microcline) have a medium radiological density (-50 H.M.U.) and a 
physical density () (2.59 g/cm3). 
• White: calcite is a very attenuating mineral; it has a physical density of 2.71 g/cm3 and a high radiological
density (241 H.M.U.). Calcite, though only slightly denser (2.71 g/cm3) than quartz and potassium 
feldspar, is substantially more attenuating, owing to the presence of calcium. 
• White: hematite has a physical density higher than the other minerals (5.26 g/cm3) and therefore a high
radiological density due to the presence in its chemical formula of iron.
In sandstone cores, calcite and ferromagnesian minerals would likely be registered as an anomaly in 
X-ray scan.
X-ray Computer Tomography (CT-Scanner)


Prediction of reservoir permeability from petrography characterization

http://www.earth-prints.org/bitstream/2122/2698/1/Baraka-Lokmane.pdf

Prediction of reservoir permeability from petrography characterization

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