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 8 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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