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Engineering Geology 67 (2002) 5 – 15
www.elsevier.com/locate/enggeo
Physical properties and textural parameters of calcarenitic rocks:
qualitative and quantitative evaluations
G.F. Andriani, N. Walsh*
Dipartimento di Geologia e Geofisica, Università degli Studi di Bari, Campus Universitario, Via E. Orabona 4, 70100 Bari, Italy
Received 2 October 2001; accepted 15 March 2002
Abstract
Petrophysical and mechanical properties of sedimentary rocks are influenced by size, shape, and packing of grains, porosity,
cement and matrix content, all controlled strongly by depositional fabric and postdepositional processes. This paper presents a
study on the textural characteristics of soft and porous calcarenites and the main methods to determine petrophysical data. The
examined calcarenites, sampled from three quarry districts located in Apulia (southeastern Italy), are fine-grained and coarsegrained grainstones (‘‘A’’ and ‘‘D’’) and medium-grained packstones (‘‘B’’) belonging to a plio-pleistocenic formation
(Calcarenite di Gravina) outcropping in the whole region. The study involved, particularly, textural analysis on thin sections
using optical petrographic microscopy and evaluation of total and effective porosity by means of standard geotechnical
laboratory tests, mercury intrusion porosimetry and image analysis. Grain size frequency distribution was also carried out by
traditional sieve and sedimentation analysis on disaggregated materials and image analysis. Computer analysis of digital images
was performed on photomicrographs applying the methods of quantitative stereology to pore size and grain size distributions. A
comparison between results showed that each technique used has its limitations linked to the textural characteristics, primarily
geometry and topology of the pore network, granulometry, grain shape and packing of calcarenites. D 2002 Elsevier Science
B.V. All rights reserved.
Keywords: Calcarenite; Texture; Porosity; Image analysis
1. Introduction
In recent years, many researchers have focused on
the relationship between textural parameters and physical properties of rocks, and several methods have
been developed for a qualitative and quantitative
evaluation of geometry and topology of pore network
and grain size and shape.
*
Corresponding author. Fax: +39-80-5442625.
E-mail addresses: [email protected] (G.F. Andriani),
[email protected] ( N. Walsh).
Physical properties include, above all, heat and
fluid flows of engineering and geoscientific interest,
indispensable to predicting the movement of hydrocarbons in a reservoir, the transport of contaminants in
an underground aquifer or weathering processes and
stone decay in numerous architectural structures and
historical monuments.
Previous works on textural parameters that affect
physical response have been presented by a great
number of authors (Friedman, 1958; Morrow et al.,
1969; Morgan and Gordon, 1970; Pittman and
Duschatko, 1970; Beard and Weyl, 1973; Berg,
0013-7952/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved.
PII: S 0 0 1 3 - 7 9 5 2 ( 0 2 ) 0 0 1 0 6 - 0
6
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
1975; Wardlaw and Taylor, 1976; Schowalter, 1979;
Swanson, 1979; Schowalter and Hess, 1982; Keith
and Pittman, 1983; Brie et al., 1985). Recently,
Ehrlich et al. (1991) and McCreesh et al. (1991)
describe the relationship between pore type and throat
size in sandstones to characterise the pore geometry
and petrophysical response of the porous medium.
The relationship between depositional fabric and permeability is discussed by Bloch (1991) and Andriani
and Walsh (in press). Mongelli et al. (1993) discuss
the influence of textural parameters on thermal properties and Andriani and Walsh (2000) show the
relationship between the latter and strength and
deformability of carbonate rocks. Caputo et al.
(1996) report the results of a study on the influence
of thermal shock on mechanical properties of different
calcarenite types with respect to grain size, amount of
matrix and cementation degree.
Andriani and Walsh (1998) explain the incidence
of texture on shear strength in calcarenites and Hoffman and Niesel (1996) suggest correlations between
compressive strength and water absorption, saturation
degree and porosity of sedimentary rocks utilised as
building stones.
Various approaches to porosity characterisation
emphasise different aspects of porosity and their
degree of applicability. Stereological methods have
been widely used to determine geometric properties of
three-dimensional structures on the basis of information from two-dimensional sections (Kwiecien et al.,
1990). Dullien and Dhawan (1973) show a combination of quantitative photomicrography and mercury
porosimetry to characterise pore structure of porous
medium. Frykman and Rogon (1993) describe a
system for generating variomaps of binary images
produced from plane sections through porous media
(sandstones) using Fourier transformation to evaluate
the ‘‘mean porel size’’ and anisotropy in the analysed
section. Marfil et al. (1996) quantify the effects of
diagenetic processes such as compaction, cementation
and leaching on reservoir sandstone properties. Image
analysis technique to measure the shape and size of
aggregates and clastic sediments, and comparison
with sieve analysis results are presented by Persson
(1998), Fernlund (1998), Francus (1998) and Kwan et
al. (1999).
In this paper, we discuss procedures for deriving
total and effective porosity, pore types and grain size
distribution of calcarenites using different methods to
evaluate fields of applications and accuracy of the used
techniques. Evaluation of these textural parameters
was carried out by means of standard geotechnical
laboratory tests, mercury intrusion porosimetry and
image analysis. Grain size distribution was also performed by traditional sieve and sedimentation analysis
on completely disaggregated materials obtained by the
separating of grains by hand from saturated samples
subjected to numerous freeze –thaw cycles.
The examined calcarenite types belong to the Calcarenite di Gravina Formation (Azzaroli, 1968) and
consist of whitish biolithoclastic medium-grained
packstones (type ‘‘B’’) or light yellow fine-grained
(type ‘‘A’’) and buff yellow coarse-grained (type ‘‘D’’)
lithobioclastic grainstones. Calcarenite di Gravina Formation, upper Pliocene –lower Pleistocene, onlap Mesozoic – Cenozoic limestone successions (exceeding
6000 m in thickness) of the Apulia Foreland (Azzaroli,
1968; Iannone and Pieri, 1979; Ciaranfi et al., 1988)
and constitutes continuous exposure of intrabasin biocalcarenites and biocalcirudites and/or terrigenous calcarenites with a carbonate content approximately
between 90% and 99%. These transgressive deposits
of limited thickness (of between 5 and 80 m) are
composed of several lithofacies which are conglomeratic at the proximal end (rocky coast) and become
progressively sandier basinward (offshore).
2. Sampling and description of fabric
The examined calcarenites were sampled from
three quarry districts located in Apulia, southeastern
Italy (Fig. 1). They consist of slightly compacted finegrained (‘‘A’’), medium-grained (‘‘B’’) and coarsegrained (‘‘D’’) calcarenites, poorly cemented, whitish
(‘‘B’’), light yellow (‘‘A’’) and buff yellow (‘‘D’’)
coloured. From the chemical point of view, these
calcarenites are composed of normal calcite with a
low magnesium content. Minor constituents commonly are kaolinite, illite, clorite, smectite and halloysite 7 Å, gibbsite and goethite, finely disseminated
through the rock, or quartz and feldspars occurring as
individual grains.
Fabrics were analysed with transmitted light on
standard thin-sections using optical petrographic
microscopy. Thin-sections were taken from specimens
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
7
Fig. 1. Location map.
half of which were cut along and half across the
stratification (Fig. 2a). The general fabric is one of a
relatively loose packing calcarenite, poorly to moderately sorted with a self-supporting framework of
skeletal grains of marine organisms and with subrounded and rarely sub-angular terrigenous lithic fragments of limestones. The micritic matrix is almost
completely absent in ‘‘A’’ and ‘‘D’’ and is present in
small quantities in ‘‘B’’. Lithoclasts usually comprise
40 –50% (‘‘A’’), 25 – 35% (‘‘B’’) and 60 – 70% (‘‘D’’),
while the skeletal component (mainly fragmented)
constitutes between 25– 35% (‘‘A’’), 45 –55% (‘‘B’’)
and 20– 25% (‘‘D’’) and is represented by benthonic
foraminifera, bryozoa, lamellibranchs, gastropods,
echinoderms, calcareous algae and serpulid worm
tubes. Bioclasts in a significant part were dissolved
after deposition leaving empty casts with thin recrystallised micrite envelopes representing only the outer
layers of these shells (‘‘B’’). ‘‘A’’ is moderately sorted
while ‘‘B’’ and ‘‘D’’ are poorly sorted. Type ‘‘D’’ is
characterised by a lesser degree of compactness as a
significant proportion of cementation in this shallow
water coarse-grained calcarenite may have occurred
immediately after deposition. Clastic grains and carbonate skeletal fragments are in direct contact and
form a very loosely packed self-supporting framework
with a high total porosity that, in type ‘‘B’’, reaches
49.4% where bioclasts with internal cavities and
micrite envelopes from dissolved shells are common
(‘‘B’’). Most sand grains touch the others at few points
(from 3 to 5) and this determines the formation of
large open pore spaces, above all in ‘‘D’’.
The amount of calcitic cement, with respect to the
sediment total volume, is low in type ‘‘A’’ (up to 15%)
and ‘‘D’’(up to 10%) and medium –low in type ‘‘B’’
(up to 25%). In this last case, the range estimation also
comprises the recrystallised micritic matrix. The most
common cement form is constituted by a border of
equidimensional carbonate microcrystals on the external surfaces of the grains, better developed on the
skeletal grains. It is a fine encrustation of minute
calcite crystals, an early cement generation, growing
at the contact between grains or on the grain walls in
open pore spaces and inwards where there are internal
cavities of bioclasts. The crystals grow perpendicular
or at high angles to their substrate and exhibit dogtooth sparry habits. Late generation sparry calcite
occurs in both interparticle pore spaces and skeletal
moulds and is characterised by greater sizes and a
lighter colour; this cement, in ‘‘B’’, is so well developed that it completely fills the voids, especially the
intraparticle pores. The micritic matrix is in practice
absent in ‘‘A’’ and ‘‘D’’ while in ‘‘B’’ it is recrystallised and hardly distinguishable from the microcrystalline cement. All the calcarenite types reveal an open
porosity with intercomunicating voids, as the narrow
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G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
Fig. 2. Fine-grained (‘‘A’’), medium-grained (‘‘B’’) and coarse-grained (‘‘D’’) calcarenites. On the left, images of petrographic thin-sections in
plane-polarised light; on the right, images binarized by simple thresholding. The length of the photomicrographs is 4.2 mm (‘‘A’’ and ‘‘B’’) and
8.0 mm (‘‘D’’).
throats at grain contacts are not closed by the irregular
crystalline cementation.
Considering Choquette and Pray’s (1970) classification scheme, the major contribution to the total
porosity is made by intergranular porosity. Intragranular and moldic porosity occur especially in type ‘‘B’’.
On the basis of these observations, we have classified these calcarenites as lithobioclastic grainstone
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
Table 1
Average values of physical parameters of tested calcarenites
Physical parameters
‘‘A’’
‘‘B’’
‘‘D’’
G
cd (KN/m3)
csat (KN/m3)
n (%)
wa (%)
Sr (%)
2.70
14.14
19.00
48.60
34.40
100
2.70
13.64
18.58
49.40
36.20
100
2.70
15.11
19.40
42.90
28.40
100
9
Tool IT Version 2.0, developed at the University of
Texas Health Science Center at San Antonio.
In the first step, photomicrographs were taken in
plane-polarised and cross-polarised light and both
utilised for image analysis. Successively, only photomicrographs of thin-sections in plane-polarised light
were used because they allowed a better evaluation
(‘‘A’’ and ‘‘D’’) and biolithoclastic packstone (‘‘B’’)
of high energy shallow marine environment.
3. Physical properties
Following the standard test procedure outlined in
ISRM (1972), the dry density (cd), the saturated
density (csat), the porosity (n), the water absorption
(wa) and the saturation degree (Sr) were determined.
The evaluation of the physical properties was carried
out on 30 samples of each calcarenite type. As regards
the specific gravity ( G), reference was made to a value
of 2.70 on the basis of the chemical composition of all
the examined calcarenites (Andriani and Walsh, 1998).
For the saturation degree (Sr) and the water absorption
(wa), oven dried cylindrical specimens (71 140 mm)
were dipped in water and weighed constantly at
prefixed intervals of time until a constant weight was
attained and then saturated under vacuum. Using this
method for all calcarenite types, the saturation degree
(Sr) was equal to 100% (Andriani and Walsh, in press).
Complete saturation demonstrates that pores in the
rock particle systems are interconnected and continuous. Table 1 summarises the average values of the
experimental data of the physical properties.
During laboratory tests, a greater dispersion of
experimental data for type ‘‘D’’ was observed, principally due to its greater textural heterogeneity.
4. Image analysis
Thin-sections obtained from samples hardened with
epoxy resin were photographed with a high resolution
camera connected to the optical microscope. Photomicrographs were transferred directly and processed
on a PC using the public domain UTHSCSA Image
Fig. 3. Pore size frequency distribution carried out by mercury
intrusion porosimetry technique and image analysis.
10
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
analysis with a lesser influence of the operator.
Grains, matrix and cement, in fact, had rather high
relief and in plane-polarised light were very clearly
distinguishable from the voids, so much so that in the
preparing of the thin-sections epoxy resin was not
coated with a fluorescent dye. After some contrast
enhancement, shading correction and filters application, the images were binarized by simple thresh-
olding (Fig. 2b). The threshold grey-level was
selected after examination of the histogram of the
grey-level values of the image. Through image segmentation (Duda and Hart, 1973), the identification of
the image pixels ‘‘belonging’’ to the textural parameters and their subdivision in different categories,
related to the grey-level values, were not possible
because the procedure did not ensure a good contrast
Fig. 4. Grain size frequency distributions and cumulative curves obtained using sieve and sedimentation analysis and image analysis.
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
Table 2
Porosity evaluated using geotechnical laboratory tests, image
analysis on microphotographs and mercury porosimeter (average
values)
Calcarenite
type
Porosity (%)
Geotechnical
tests
Image
analysis
Mercury
porosimetry
A
B
D
48.6
49.4
42.9
36.2
33.7
37.4
48.8
44.8
15.5
between grains, matrix and cement as they are characterised by the same range of grey-level values.
Using contrasted and filtered images, before
thresholding, pore size and grain size distributions
were determined, while on binarized images ‘‘porosity’’ was evaluated.
In the first case each photomicrograph was calibrated to define a measurement unit and corrected for
magnification for all dimensional analyses.
‘‘Equivalent disk diameter’’ (Francus, 1998), D0,
was used as index to quantify pore size and grain size.
Measurements were performed along a sequence
obtaining the diameter of each ‘‘equivalent disk’’. It
is evident that the void space within a porous medium
can be regarded as a network of pores connected by
smaller void channels and microcracks and that meas-
11
urement of their size is not a simple matter. Voids, in
fact, by image analysis appear as patches that vary in
size and shape. Regarding their morphological complexity in the plane of the image, such patches can
represent single pores or a network consisting of
connected pores and throats. In image analysis, we
divided complex patches into simple ‘‘equivalent
disks’’ (pores and throats) measured by means of
D0. Also, the grains, although subrounded and rarely
sub-angular, are not spherical and necessarily cut
through their centre of gravity in random two-dimensional thin-sections. Therefore, this approximation can
lead to an under-estimation of grain diameters. Stereological methods have been widely used to determine
geometric properties of three-dimensional structures
on the basis of information from two-dimensional
sections (Underwood, 1970). Fig. 3 illustrates a comparison of pore size frequency distribution obtained
by mercury intrusion porosimetry technique and
image analysis. Fig. 4 shows a comparison of grain
size frequency distribution and cumulative curves
obtained using sieve and sedimentation analysis and
image analysis. A suite of 15 thin-sections for the
three calcarenite types were analysed, photographed
and digitised to a 1050 710 pixel format (pixel size
of 4 Am) for ‘‘A’’ and ‘‘B’’ and to 887 591 pixel
format (pixel size of 9 Am) for ‘‘D’’ with 8 bit
resolution (256 grey levels). The minimum size for
Fig. 5. Image analysis process flow chart.
12
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
objects is fixed and depends on the resolving power of
the image-digitising equipment (20 Am).
In the successive image processing step, utilising
binarized images, ‘‘porosity’’ measurement was performed. In Fig. 2b, the black pixels represent voids
(pores and throats) and white pixels represent grains,
matrix and cement. The software used counts the
black and white pixels and evaluates porosity as the
ratio between black pixels and total pixels in the
image. ‘‘Porosity’’ so calculated under stereological
assumptions is equal to the pore volume proportion.
Results so obtained for the three calcarenite types
show that the values calculated using image analysis
are lower but comparable to those evaluated using
standard geotechnical laboratory procedure and can
differ much from those evaluated with a mercury
porosimeter (see the next section) (Table 2). To better
explain image processing step by step flow chart is
shown in Fig. 5.
‘‘Total Optical Porosity’’, TOP (Ehrlich et al.,
1991), is usually less than the physically measured
porosity because some patches of porosity are too
small to resolve. Porosity values estimated in this
way and defined by petrographic image analysis in
general are more closely linked to effective porosity
and for these rocks regards effective porosity considering that in the examined samples pores are interconnected and continuous as resulted in the physical tests.
Grain size distribution by image analysis has shown
that in ‘‘A’’ grain diameter varies between 0.04 and
0.54 mm with a modal value of 0.23 mm, in ‘‘B’’
between 0.06 and 1.00 mm with a modal value of 0.40
mm and in ‘‘D’’ between 0.10 and 2.00 mm with a
modal value of 0.80 mm.
5. Mercury intrusion porosimetry
Using the Mercury Intrusion Porosimetry Technique
(MIP), pore size distribution and ‘‘effective’’ porosity
were determined. Considering adopted operative conditions (max pressure: 200 MPa) and the limits of the
applied method, linked to the simplification of textures
and real geometry of pores (Dullien, 1992), the MIP
makes possible the evaluation of pore-size distribution
and porosity relative to the pores with radius between
3.7 10 6 and 0.075 mm, so that for the calcarenite
types ‘‘A’’ and ‘‘B’’, the experimental results can be
Fig. 6. Pore-size distribution obtained from combination of
porosimetry results and image and textural analysis results. The
total pore-size distribution was obtained extending the pore size
distribution curve resulting from MIP to the greater size classes
utilising a parabolic function.
considered reliable (nMIP = 48.8% and 44.8% respectively for ‘‘A’’ and ‘‘B’’), while for ‘‘D’’ (nMIP = 15.5%)
the analysis concerned fewer than 50% of the total
volume of interconnected pores effectively present in
the rock. As in ‘‘D’’ porosity determined by geotechnical laboratory analysis and image analysis is respectively 42.9% and 37.4% (average values), a quantitative
but at the same time approximate estimate of the total
pore-size distribution was obtained extending the pore
size distribution curve resulting from MIP to the greater
size classes obtained by image and textural analysis,
utilising a parabolic function (r = 0.92) acquired from
the interpolation of the MIP data (Fig. 6).
6. Sieve and sedimentation analysis
Saturated calcarenite samples subjected to 10
freeze – thaw cycles were disaggregated by hand,
oven dried and then sieved using sieve sizes ranging
from 2.00 to 0.063 mm. The remaining fine fraction
(passing 230, ASTM Series) were examined through
sedimentation analysis. ‘‘Sedimentation diameter’’,
that in reality is not the actual physical diameter of
the particles, was calculated using Stokes’ law. Statistical parameters, Mean size (Mz), standard deviation (r/) and skewness (SkI) were calculated (Folk
and Ward, 1957). The results, reported in Table 3,
show that ‘‘A’’ is moderately sorted while ‘‘B’’ and
‘‘D’’ are poorly sorted; Skewness values close to zero
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
Table 3
Mean size (Mz), standard deviation (r/) and skewness (SkI)
statistical parameters (phi units) for the calcarenite types
Statistical
parameters
Mz
r/
SkI
‘‘A’’
2.38
0.78
0.01
‘‘B’’
‘‘D’’
1.77
1.34
0.09
1.22
1.20
0.02
indicate symmetric distributions for all the calcarenite
types.
A comparison between sieve and sedimentation
analysis results and image analysis results was made
and presented as frequency distribution and cumulative curves based on the weight percentage and the
number percentage within specific size limits (Fig. 4).
Fig. 4a shows a wider range of grain sizes using sieve
and sedimentation analysis. Fig 4b illustrates a steeper
inclination of the image analysis cumulative curves
and a lateral displacement between the curves owing
to the smallest and the biggest grains that cannot
always be evaluated on photomicrographs. In short,
with image analysis, sediments result more well sorted
and devoid of coarse and fine tails.
7. Concluding remarks
Petrophysical properties of three calcarenite types
were analysed and evaluated using different methodologies. Comparison of results was made and discussed to evaluate accuracy of the techniques used.
Porosity evaluated using mercury porosimetry,
image analysis and geotechnical tests assumes similar
values for moderately sorted fine-grained or at most for
poorly sorted medium-grained calcarenites. It is an
effective porosity that, in this particular case, is equal
in value to the total porosity because the analysed
calcarenite types shown complete saturation so that all
pores in the rock particle system are interconnected
and continuous. In the coarser and poorly sorted
calcarenite type, mercury porosimetry measures only
the narrowest pores that constitute fewer than 50% of
all pores. Besides, the narrowest pores are not necessarily all throats in the rocks, in that pores and throats
differ from one another also for shape and distribution
related to depositional fabric and postdepositional
processes. Coarser throats and pores can be evaluated
13
using image analysis under stereological assumption.
In this case, however, complex voids are reduced to a
network of simple connected voids (in two dimensional representation) and frequency distribution is
based on the number percentage of pores within
specific size limits and not on the volume percentage
as for mercury porosimetry. Total pore size distribution
can be approximately estimated extending the pore size
distribution curve resulting from MIP to the greater
size classes obtained by image and textural analysis
supposing that these latter classes have the same
distribution trend (‘‘D’’).
Likewise, grain size distribution from sieve and
sedimentation analysis is based upon the weight percentage, whereas grain size distributions by image
analysis are based upon the number percentage of
particles within specific size limits. Therefore, theorically the distribution curves are incomparable but the
analysed calcarenite types have a high CaCO3 content
( > 95%) so that they can be considered monomineralic
rocks. In general, the two curves are similar but with
image analysis only coarse silt and sand grains are well
measurable. Furthermore, sieve and sedimentation
analysis is representative of a sample of about
1.43 105 mm3 while in image analysis each photomicrograph concerns 20– 40 mm2 so that for a significant analysis at least 20 photomicrographs are required.
Indeed, magnification directly influences the size of the
objects that are perceptible: fine grains become better
visible on images digitised at high magnification but
the coarsest grains have less chance to appear on them.
Two images of the same area taken at different magnifications provide different size frequency populations.
Therefore, magnification must be carefully chosen and
maintained constant for correct analysis and comparative measurements. So the petrographer must decide,
prior to digitization, the magnification to be used after
examination of texture. At the same time, sieve analysis
results are highly dependent on the geometrical form of
the particles. The data shown and the discussion
presented suggest that for any given analysis a combination of methods are dictated by textural parameters
(size, shape, and packing of grains, the topology of the
pore network) and the needs of the specific application
for which analysis is intended.
The combination of both image analysis and traditional laboratory tests gives a rather good presentation
of grain size and pore size distribution of calcarenites
14
G.F. Andriani, N. Walsh / Engineering Geology 67 (2002) 5–15
and provides qualitative and quantitative evaluations
of porosity. Image analysis, even though it produces
rapid measurements and quantified observation in less
time than conventional methods, is nevertheless insufficient to identify and evaluate textural parameters in
percentages and depends largely on the interpretative
skills of the operator. The segmentation of the image
as well as the sample preparation techniques, in fact,
are the main sources of error.
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