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A fabric classification of argillaceous rocks, sediments, soils
Applied Clay Science, 5 (1990) 353-360
353
Elsevier Science Publishers B.V., Amsterdam
A fabric classification of argillaceous rocks, sediments, soils V.N. Sokolov and Neal R. O'Brien Faculty of Geology, Department of Engineer Geology, Moscow State University, Moscow 119899, U.S.S.R. Geology Department, Potsdam College of the State University of New York, Potsdam, New York 13676, U.S.A. (Received January 3, 1990; accepted after revision July 6, 1990)
ABSTRACT Sokolov, V.N. and O'Brien, N.R., 1990. A fabric classification of argillaceous rocks, sediments, soils. Appl. Clay Sci., 5: 353-360. A microfabric classification of argillaceous rocks and nonlithified clay sediments and soils is proposed based upon fabric determined from scanning electron micrographs and by using a signal intensity gradient technique. This technique generates a visual image of the actual particles plus a computer-generated rose diagram illustrating their orientation. The latter may be quantified and expressed as a .fabric index If number. Analysis of numerous argillaceous rocks, sediments, soils from various sedimentary environments reveals the following fabric classification: preferred, intermediate and random. The classification quantifies clay fabrics and provides a frame of reference for other clay scientists t o use in describing microfabrics.
INTRODUCTION
This paper presents a method to describe the microfabric (i.e., particle orientation) of argillaceous rocks, sediments, and soils by using scanning electron microscope techniques. A fabric classification scheme is proposed based upon the degree of particle randomness. To date no established microfabric classification system exists that may be used by clay scientists in sedimentology, marine geology, or soil science. The classification system proposed is an attempt to provide a frame of reference common to all describing clay microfabrics. Previous investigators have contributed to the analysis of the fabric of soils but few have been also concerned with rocks. Brewer ( 1964 ) determined the orientation of the c-crystallographic axis of mineral particles in soil using an optical microscope. He measured the azimuth and dip of particles and obtained polar diagrams distinguishing four orientation groups: (1) strongly 0169-1317/90/$03.50
© 1990 - - Elsevier Science Publishers B.V.
354
V.N. S O K O L O V A N D N.R, O ' B R I E N
oriented; (2) moderately oriented; (3) weakly oriented; (4) unoriented. Others (Mitchell, 1956; Smart, 1965; Morgenstern and Tchalenko, 1967; La Feber, 1967 ) also used optical techniques for fabric analysis. Optical methods and X-ray techniques of clay orientation evaluation (Martin, 1962, 1966; O'Brien, 1964; Odom, 1967 ) and a method of magnetic anisotropy (Osipov and Sokolov, 1972) are also well known. Tovey (1971) was one of the early workers using transmission and scanning electron microscope images for orientation analysis. Polar diagrams were drawn manually based upon the ratio of the magnitudes of maximum and minimum vector normals. Fourier analysis of SEM images of Tovey and Sokolov ( 1980, 1981 ) and of Sergeev et al. ( 1985 ) as well as the signal intensity gradient technique (Unitt, 1975; Tovey, 1980; Smart and Tovey, 1982) presented other means for the evaluation of particle orientation. There is a wide range of microfabrics in clay-rich sediments and rocks that is of interest to sedimentologists because particle orientation provides useful clues to the sedimentary conditions of formation (O'Brien, 1980, 1987 ). This range is well illustrated in Fig. 1 which shows typical particle orientation of surfaces of samples broken perpendicularly to bedding planes. The remarkable parallelism in the fissile Sunbury shale (Fig. 1A ) contrasts greatly with the randomness of microfabric of an unconsolidated sediment in a Pleistocene core from the Great Salt Lake of Utah (Fig. 1B). In these examples most interpreters could agree upon a description of the fabrics as "preferred" or "random" because they are so obvious. However, a more detailed description of other fabrics is difficult because many are intermediate between the obvious extremes, thus making it more difficult for fabric observers to report their findings to others. Furthermore, no fabric classification scheme now ex-
Fig. 1. Scanning electron micrographs showing a wide range of microfabric in argillaceous rock and sediment. (A) High degree of preferred particle orientation in the Sunbury shale (Mississippian, Ohio), scale= 10 Ftm. (B) Randomness of particles in a freeze-dried sample of core sediment, Great Salt Lake (Pleistocene, Utah), scale = 1/tm. Surface perpendicular to bedding planes.
355
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
ists as an established frame of reference for observers. Thus the authors propose a simple fabric classification which is based upon techniques that quantify various clay fabrics into three different classes. In addition, a chart is presented which provides examples of SEM images of a typical fabric of each class. The latter is presented to provide a rapid method of determining fabric by a simple visual comparison and should be especially valuable to those investigators who do not have facilities to use the signal intensity gradient technique described, but who wish to use the SEM in their study and to communicate their results with others. METHOD
The basis for the quantification of the clay fabrics is a signal intensity gradient technique used in quantitative automatic analysis of particle orientation in a scanning electron microscope-microcomputer system. The theoretical background of the technique is described in papers by Unitt ( 1975 ), Tovey
L
B
a
If= 1- ~. = 0.68
D
a
If= 1- 6 =0.003
Fig. 2. Typical fabric index (If) diagrams generated by the signal intensity gradient technique. (A) Signal intensity gradient diagram of preferred orientation. (B) An If is determined by drawing a line around the border of the diagram shown in (A) and by measuring the length of axes. The formula indicates how If is obtained. Notice that preferred orientation If diagram approaches an ellipse. (C) Signal intensity gradient diagram of random orientation. (D) The If of diagram shown in (A) is also determined by measuring the axis length. As fabric becomes more highly random the fabric index diagram approaches a circular shape. Random approaches a perfect circle.
356
V.N. SOKOLOV AND N.R, O'BRIEN
SEH IMAGE
SIGNAL INTENSITY
ORIENTATION DESCRIPTION (If RANGE)
A
PREFERRED (0.21+)
B
Fig. 3. Fabric Classification Chart. (A) Preferred: fissile shale (Cretaceous), Soci, U.S.S.R. ( B ) Preferred: bituminous Shale Fm. (Jurassic), Ravenscar, England. (C) Intermediate: marine clay (Miocene), Stavropol, U.S.S.R. (D) Intermediate: Canton Shale Mbr., Carbondale Fm. (Pennsylvanian), Gallatin County, Illinois, U.S.A. (E) Random: moraine silt (Holocene), Kertch, U.S.S.R. All SEM scales are 10 #m.
(1980), and Smart and Tovey (1982). The interested reader is referred to the paper by Tovey (1980), who describes in detail the method used in the quantitative analysis of clay particle orientation in electron micrographs. Briefly, the technique is based upon the computing of the signal intensity for each point in a SEM image along two mutually orthogonal directions. After computing the gradient intensity vectors of each point in a scan across the image, a rosette diagram can be constructed (see Fig. 2 ). The radial distance from the center of the diagram is proportional to the number of intensity gradient vectors in the appropriate class.
357
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
SEM IMAfiE
SIGNAL INTENSITY
ORIENTATION DESCRIPTION (If RANI3E)
INTERMEDIATE (0.11-0.20)
D
RANDOM (0.00-0.I0)
E
If = 0.003 Fig. 3. Continued.
358
V.N. SOKOLOV AND N.R. O'BRIEN
On the basis of the obtained rosette diagram one can compute the quantitative characteristics of the fabric: the direction of orientation, i.e. the angle 0 between a horizontal diagram axis and a maximal axis of an ellipse describing the diagram, as well as a fabric index If or a degree of orientation, which shows the number of structural elements (in percents) lying within the plane of orientation. The samples for fabric analysis have been prepared in the following way. To avoid fabric distortion of water-saturated clays and silts while drying up, the samples have been prepared following the method called freeze-drying (Smart and Tovey, 1982). Rock samples (shales) having hard crystallizational or cementational structural bonds have been dried up in air. Then the dried samples have been split perpendicularly to a bedding plane. After that clays and silts have been polished with emery paper or cleaned with a razor blade and treated with adhesive tape (Smart and Tovey, 1982 ). After having been analyzed the rock samples' surface has been treated with adhesive tape for loose particles after splitting. Samples have then been mounted on a SEM stub, gold-coated and observed in the scanning electron microscope at × 1000 magnification. The accurate adherence to the succession of all the mentioned procedures in sample preparation provided the preservation of the natural structure of the samples and correctness of a fabric analysis. Results presented herein were obtained with the SEM-microcomputer system at the Department of Engineering Geology of the Geological Faculty Moscow State University (USSR) using a Hitachi S-800 SEM in combinations with a Iskra-226 microcomputer. The orientation analysis program was written in Basic-02 based upon work by Tovey ( 1980 ). More than 600 samples were analyzed by the signal intensity gradient technique to obtain the classification distribution presented here. Rocks, sediments and soils from various environments, ages and degrees of lithification, were selected. Preliminary SEM-viewing was used to select samples showing a wide range of particle orientation. Characteristic fabrics on which the classification is based, are shown in Fig. 3. MICROFABRIC CLASSIFICATION
Fig. 3 shows the classification chart of argillaceous fabric viewed in SEM and based upon variations of particle orientation using the signal intensity gradient technique to determine the fabric index (If). The range of the fabric index within each class of orientation (Fig. 3, see "orientation description") was not chosen arbitrarily but is based upon the statistical distribution of Ifvalues from more then 600 samples used in the study. Results indicate that fabric index values could be grouped into three distinct classes: 0.00-0.10; 0.11-0.20; 0.21-0.80. These classes have been identified respectively: random, intermediate and preferred.
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
359
The first column (labeled SEM image) in Fig. 3 displays the actual SEM image of typical fabric of each class. Investigators not using the signal intensity gradient technique or those who wish a rapid estimate of fabric may simply compare their SEM photos to those in the chart and pick the appropriate "orientation description". This method is somewhat analogous to the visual estimate technique of particle roundness commonly used in sedimentary petrology. Others who obtain a fabric index (If) for their sample may compare that If number to the range listed on the chart and in turn select the appropriate "orientation description". The actual If for those SEM images shown in Fig. 3 are listed in the second column (Signal intensity gradient diagram). SUMMARY
The fabric classification system proposed for argillaceous rocks, sediment, and soils is based upon the microfabric revealed by scanning electron microscopy. The utility of such a classification is that it provides a useful common frame of reference for investigators when describing their samples. The classification rests upon a quantitative base provided by the generation of a signal intensity gradient diagram; however, it may be used by anyone who evaluates clay microfabric from scanning electron micrographs but who lacks the equipment to generate such a diagram. Simply by making a visual comparison to the type reference fabrics presented in Fig. 3, one is able to put a microfabric into an orientation class. The authors are aware that in the future refinements (e.g. subdivisions ) may be added to this classification by others. However, this classification scheme is presented as an initial attempt to enhance the communication of those studying argillaceous rocks, sediment, and soil microfabric by providing a common fabric terminology to which all may refer. ACKNOWLEDGEMENTS
The authors acknowledge the support (N.R.O.) given by the Donors of the Petroleum Research Fund administered by the American Chemical Society, the help of the National Science Foundation (RUI Grant No. 8611608) and of Clarkson University, Potsdam, N.Y. for use of facilities. We express our gratitude to John Gray, Ohio Geological Survey and Ron Spenser, University of Calgary who provided samples, and to N.A. Rumjantseva, Engineering Geology Department, Moscow State University for the experimental work on SEM sample and fabric analysis. V.N.S. acknowledges the support given by the International Program of the State University of New York.
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V.N. SOKOLOV AND N.R. O'BRIEN
REFERENCES Brewer, R., 1964. Fabric and Mineral Analysis of Soils. Wiley, New York, N.Y., 470 pp. La Feber, D., 1967. The optical determination of spatial (three dimensional) orientation of platy clay minerals in soil thin-sections. Geoderma, 1: 359-369. Martin, R.T., 1962. Research on the Physical Properties of Marine Soils. M1T Soil Eng. Div., No. N-127. Martin, R.T., 1966. Quantitative fabric of wet kaolinite. 14th Nat. Conf. Clays Clay Miner., pp. 271-287. Mitchell, J.K., 1956. The fabric of natural clays and its relation to engineering properties. Proc. Highway Res. Board, 35:693-713. Morgenstern, N.R. and Tchalenko, T.S., 1967. The optical determination of preferred orientation in clays and its application to the study of microstructure in consolidated kaolin, II. Proc., R. Soc. London, Ser. A, 300: 235-250. O'Brien, N.R., 1964. Origin of Pennsylvanian underclays in the Illinois Basin. Bull. Geol. Soc. Am., 75: 832-832. O'Brien, N.R., 1980. Use of clay fabric to distinguish turbiditic and hemipelagic siltstones and silts. Sedimentology, 27:47-61. O'Brien, N.R., 1987. The effects of bioturbation on the fabric of shale. J. Sediment. Petrol., 57: 449-455. Odom, I.E., 1967. Clay fabric and its relation to structural properties in Mid-continent Pennsylvanian sediment. J. Sediment. Petrol., 37:610-623. Osipov, J.B. and Sokolov, B.A., 1972. Quantitative characteristics of clay fabrics using the method of magnetic anisotropy. Bull. Int. Assoc. Eng. Geol., 5: 23-39. Sergeev, J.M., Osipov, V.1. and Sokolov, V.N., 1985. Quantitative analysis of soil structure with the microcomputer system. Bull. Int. Assoc. Eng. Geol., 31: 131-136. Smart, P., 1965. Optical microscopy and soil structure. Nature, 210: 1400. Smart, P. and Tovey, N.K., 1982. Electron Microscopy of Soils and Sediments: Techniques. Clarendon Press, Oxford, 264 pp. Tovey, N.K., 1971. A selection of scanning electron micrographs of clay. CUED/c-Soils/TR5b, U n iv. Cambridge, Dept. Engineering, Cambridge, 10 pp. Tovey, N.K., 1980. A digital computer technique for orientation analysis of micrographs of soil fabric. J. Microsc., 120:303-315. Tovey, N.K. and Sokolov, V.N., 1980. Quantitative methods for measurement of scanning electron micrographs of soil fabric. Int. Soc. Photogrammetry, XIVth Congr., Hamburg, 23: 154163. Tovey, N.K. and Sokolov, V.N., 1981. Quantitative SEM methods for soil fabric analysis. SEM/ 1981, SEM Inc. AMF O'Hare, pp. 537-554. Unitt, B.M., 1975. A digital computer method for revealing directional intbrmation in images. .I. Phys.. E, Sci. Instrum.~ 8: 423-425.
353
Elsevier Science Publishers B.V., Amsterdam
A fabric classification of argillaceous rocks, sediments, soils V.N. Sokolov and Neal R. O'Brien Faculty of Geology, Department of Engineer Geology, Moscow State University, Moscow 119899, U.S.S.R. Geology Department, Potsdam College of the State University of New York, Potsdam, New York 13676, U.S.A. (Received January 3, 1990; accepted after revision July 6, 1990)
ABSTRACT Sokolov, V.N. and O'Brien, N.R., 1990. A fabric classification of argillaceous rocks, sediments, soils. Appl. Clay Sci., 5: 353-360. A microfabric classification of argillaceous rocks and nonlithified clay sediments and soils is proposed based upon fabric determined from scanning electron micrographs and by using a signal intensity gradient technique. This technique generates a visual image of the actual particles plus a computer-generated rose diagram illustrating their orientation. The latter may be quantified and expressed as a .fabric index If number. Analysis of numerous argillaceous rocks, sediments, soils from various sedimentary environments reveals the following fabric classification: preferred, intermediate and random. The classification quantifies clay fabrics and provides a frame of reference for other clay scientists t o use in describing microfabrics.
INTRODUCTION
This paper presents a method to describe the microfabric (i.e., particle orientation) of argillaceous rocks, sediments, and soils by using scanning electron microscope techniques. A fabric classification scheme is proposed based upon the degree of particle randomness. To date no established microfabric classification system exists that may be used by clay scientists in sedimentology, marine geology, or soil science. The classification system proposed is an attempt to provide a frame of reference common to all describing clay microfabrics. Previous investigators have contributed to the analysis of the fabric of soils but few have been also concerned with rocks. Brewer ( 1964 ) determined the orientation of the c-crystallographic axis of mineral particles in soil using an optical microscope. He measured the azimuth and dip of particles and obtained polar diagrams distinguishing four orientation groups: (1) strongly 0169-1317/90/$03.50
© 1990 - - Elsevier Science Publishers B.V.
354
V.N. S O K O L O V A N D N.R, O ' B R I E N
oriented; (2) moderately oriented; (3) weakly oriented; (4) unoriented. Others (Mitchell, 1956; Smart, 1965; Morgenstern and Tchalenko, 1967; La Feber, 1967 ) also used optical techniques for fabric analysis. Optical methods and X-ray techniques of clay orientation evaluation (Martin, 1962, 1966; O'Brien, 1964; Odom, 1967 ) and a method of magnetic anisotropy (Osipov and Sokolov, 1972) are also well known. Tovey (1971) was one of the early workers using transmission and scanning electron microscope images for orientation analysis. Polar diagrams were drawn manually based upon the ratio of the magnitudes of maximum and minimum vector normals. Fourier analysis of SEM images of Tovey and Sokolov ( 1980, 1981 ) and of Sergeev et al. ( 1985 ) as well as the signal intensity gradient technique (Unitt, 1975; Tovey, 1980; Smart and Tovey, 1982) presented other means for the evaluation of particle orientation. There is a wide range of microfabrics in clay-rich sediments and rocks that is of interest to sedimentologists because particle orientation provides useful clues to the sedimentary conditions of formation (O'Brien, 1980, 1987 ). This range is well illustrated in Fig. 1 which shows typical particle orientation of surfaces of samples broken perpendicularly to bedding planes. The remarkable parallelism in the fissile Sunbury shale (Fig. 1A ) contrasts greatly with the randomness of microfabric of an unconsolidated sediment in a Pleistocene core from the Great Salt Lake of Utah (Fig. 1B). In these examples most interpreters could agree upon a description of the fabrics as "preferred" or "random" because they are so obvious. However, a more detailed description of other fabrics is difficult because many are intermediate between the obvious extremes, thus making it more difficult for fabric observers to report their findings to others. Furthermore, no fabric classification scheme now ex-
Fig. 1. Scanning electron micrographs showing a wide range of microfabric in argillaceous rock and sediment. (A) High degree of preferred particle orientation in the Sunbury shale (Mississippian, Ohio), scale= 10 Ftm. (B) Randomness of particles in a freeze-dried sample of core sediment, Great Salt Lake (Pleistocene, Utah), scale = 1/tm. Surface perpendicular to bedding planes.
355
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
ists as an established frame of reference for observers. Thus the authors propose a simple fabric classification which is based upon techniques that quantify various clay fabrics into three different classes. In addition, a chart is presented which provides examples of SEM images of a typical fabric of each class. The latter is presented to provide a rapid method of determining fabric by a simple visual comparison and should be especially valuable to those investigators who do not have facilities to use the signal intensity gradient technique described, but who wish to use the SEM in their study and to communicate their results with others. METHOD
The basis for the quantification of the clay fabrics is a signal intensity gradient technique used in quantitative automatic analysis of particle orientation in a scanning electron microscope-microcomputer system. The theoretical background of the technique is described in papers by Unitt ( 1975 ), Tovey
L
B
a
If= 1- ~. = 0.68
D
a
If= 1- 6 =0.003
Fig. 2. Typical fabric index (If) diagrams generated by the signal intensity gradient technique. (A) Signal intensity gradient diagram of preferred orientation. (B) An If is determined by drawing a line around the border of the diagram shown in (A) and by measuring the length of axes. The formula indicates how If is obtained. Notice that preferred orientation If diagram approaches an ellipse. (C) Signal intensity gradient diagram of random orientation. (D) The If of diagram shown in (A) is also determined by measuring the axis length. As fabric becomes more highly random the fabric index diagram approaches a circular shape. Random approaches a perfect circle.
356
V.N. SOKOLOV AND N.R, O'BRIEN
SEH IMAGE
SIGNAL INTENSITY
ORIENTATION DESCRIPTION (If RANGE)
A
PREFERRED (0.21+)
B
Fig. 3. Fabric Classification Chart. (A) Preferred: fissile shale (Cretaceous), Soci, U.S.S.R. ( B ) Preferred: bituminous Shale Fm. (Jurassic), Ravenscar, England. (C) Intermediate: marine clay (Miocene), Stavropol, U.S.S.R. (D) Intermediate: Canton Shale Mbr., Carbondale Fm. (Pennsylvanian), Gallatin County, Illinois, U.S.A. (E) Random: moraine silt (Holocene), Kertch, U.S.S.R. All SEM scales are 10 #m.
(1980), and Smart and Tovey (1982). The interested reader is referred to the paper by Tovey (1980), who describes in detail the method used in the quantitative analysis of clay particle orientation in electron micrographs. Briefly, the technique is based upon the computing of the signal intensity for each point in a SEM image along two mutually orthogonal directions. After computing the gradient intensity vectors of each point in a scan across the image, a rosette diagram can be constructed (see Fig. 2 ). The radial distance from the center of the diagram is proportional to the number of intensity gradient vectors in the appropriate class.
357
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
SEM IMAfiE
SIGNAL INTENSITY
ORIENTATION DESCRIPTION (If RANI3E)
INTERMEDIATE (0.11-0.20)
D
RANDOM (0.00-0.I0)
E
If = 0.003 Fig. 3. Continued.
358
V.N. SOKOLOV AND N.R. O'BRIEN
On the basis of the obtained rosette diagram one can compute the quantitative characteristics of the fabric: the direction of orientation, i.e. the angle 0 between a horizontal diagram axis and a maximal axis of an ellipse describing the diagram, as well as a fabric index If or a degree of orientation, which shows the number of structural elements (in percents) lying within the plane of orientation. The samples for fabric analysis have been prepared in the following way. To avoid fabric distortion of water-saturated clays and silts while drying up, the samples have been prepared following the method called freeze-drying (Smart and Tovey, 1982). Rock samples (shales) having hard crystallizational or cementational structural bonds have been dried up in air. Then the dried samples have been split perpendicularly to a bedding plane. After that clays and silts have been polished with emery paper or cleaned with a razor blade and treated with adhesive tape (Smart and Tovey, 1982 ). After having been analyzed the rock samples' surface has been treated with adhesive tape for loose particles after splitting. Samples have then been mounted on a SEM stub, gold-coated and observed in the scanning electron microscope at × 1000 magnification. The accurate adherence to the succession of all the mentioned procedures in sample preparation provided the preservation of the natural structure of the samples and correctness of a fabric analysis. Results presented herein were obtained with the SEM-microcomputer system at the Department of Engineering Geology of the Geological Faculty Moscow State University (USSR) using a Hitachi S-800 SEM in combinations with a Iskra-226 microcomputer. The orientation analysis program was written in Basic-02 based upon work by Tovey ( 1980 ). More than 600 samples were analyzed by the signal intensity gradient technique to obtain the classification distribution presented here. Rocks, sediments and soils from various environments, ages and degrees of lithification, were selected. Preliminary SEM-viewing was used to select samples showing a wide range of particle orientation. Characteristic fabrics on which the classification is based, are shown in Fig. 3. MICROFABRIC CLASSIFICATION
Fig. 3 shows the classification chart of argillaceous fabric viewed in SEM and based upon variations of particle orientation using the signal intensity gradient technique to determine the fabric index (If). The range of the fabric index within each class of orientation (Fig. 3, see "orientation description") was not chosen arbitrarily but is based upon the statistical distribution of Ifvalues from more then 600 samples used in the study. Results indicate that fabric index values could be grouped into three distinct classes: 0.00-0.10; 0.11-0.20; 0.21-0.80. These classes have been identified respectively: random, intermediate and preferred.
FABRIC CLASSIFICATION OF ARGILLACEOUS ROCKS
359
The first column (labeled SEM image) in Fig. 3 displays the actual SEM image of typical fabric of each class. Investigators not using the signal intensity gradient technique or those who wish a rapid estimate of fabric may simply compare their SEM photos to those in the chart and pick the appropriate "orientation description". This method is somewhat analogous to the visual estimate technique of particle roundness commonly used in sedimentary petrology. Others who obtain a fabric index (If) for their sample may compare that If number to the range listed on the chart and in turn select the appropriate "orientation description". The actual If for those SEM images shown in Fig. 3 are listed in the second column (Signal intensity gradient diagram). SUMMARY
The fabric classification system proposed for argillaceous rocks, sediment, and soils is based upon the microfabric revealed by scanning electron microscopy. The utility of such a classification is that it provides a useful common frame of reference for investigators when describing their samples. The classification rests upon a quantitative base provided by the generation of a signal intensity gradient diagram; however, it may be used by anyone who evaluates clay microfabric from scanning electron micrographs but who lacks the equipment to generate such a diagram. Simply by making a visual comparison to the type reference fabrics presented in Fig. 3, one is able to put a microfabric into an orientation class. The authors are aware that in the future refinements (e.g. subdivisions ) may be added to this classification by others. However, this classification scheme is presented as an initial attempt to enhance the communication of those studying argillaceous rocks, sediment, and soil microfabric by providing a common fabric terminology to which all may refer. ACKNOWLEDGEMENTS
The authors acknowledge the support (N.R.O.) given by the Donors of the Petroleum Research Fund administered by the American Chemical Society, the help of the National Science Foundation (RUI Grant No. 8611608) and of Clarkson University, Potsdam, N.Y. for use of facilities. We express our gratitude to John Gray, Ohio Geological Survey and Ron Spenser, University of Calgary who provided samples, and to N.A. Rumjantseva, Engineering Geology Department, Moscow State University for the experimental work on SEM sample and fabric analysis. V.N.S. acknowledges the support given by the International Program of the State University of New York.
360
V.N. SOKOLOV AND N.R. O'BRIEN
REFERENCES Brewer, R., 1964. Fabric and Mineral Analysis of Soils. Wiley, New York, N.Y., 470 pp. La Feber, D., 1967. The optical determination of spatial (three dimensional) orientation of platy clay minerals in soil thin-sections. Geoderma, 1: 359-369. Martin, R.T., 1962. Research on the Physical Properties of Marine Soils. M1T Soil Eng. Div., No. N-127. Martin, R.T., 1966. Quantitative fabric of wet kaolinite. 14th Nat. Conf. Clays Clay Miner., pp. 271-287. Mitchell, J.K., 1956. The fabric of natural clays and its relation to engineering properties. Proc. Highway Res. Board, 35:693-713. Morgenstern, N.R. and Tchalenko, T.S., 1967. The optical determination of preferred orientation in clays and its application to the study of microstructure in consolidated kaolin, II. Proc., R. Soc. London, Ser. A, 300: 235-250. O'Brien, N.R., 1964. Origin of Pennsylvanian underclays in the Illinois Basin. Bull. Geol. Soc. Am., 75: 832-832. O'Brien, N.R., 1980. Use of clay fabric to distinguish turbiditic and hemipelagic siltstones and silts. Sedimentology, 27:47-61. O'Brien, N.R., 1987. The effects of bioturbation on the fabric of shale. J. Sediment. Petrol., 57: 449-455. Odom, I.E., 1967. Clay fabric and its relation to structural properties in Mid-continent Pennsylvanian sediment. J. Sediment. Petrol., 37:610-623. Osipov, J.B. and Sokolov, B.A., 1972. Quantitative characteristics of clay fabrics using the method of magnetic anisotropy. Bull. Int. Assoc. Eng. Geol., 5: 23-39. Sergeev, J.M., Osipov, V.1. and Sokolov, V.N., 1985. Quantitative analysis of soil structure with the microcomputer system. Bull. Int. Assoc. Eng. Geol., 31: 131-136. Smart, P., 1965. Optical microscopy and soil structure. Nature, 210: 1400. Smart, P. and Tovey, N.K., 1982. Electron Microscopy of Soils and Sediments: Techniques. Clarendon Press, Oxford, 264 pp. Tovey, N.K., 1971. A selection of scanning electron micrographs of clay. CUED/c-Soils/TR5b, U n iv. Cambridge, Dept. Engineering, Cambridge, 10 pp. Tovey, N.K., 1980. A digital computer technique for orientation analysis of micrographs of soil fabric. J. Microsc., 120:303-315. Tovey, N.K. and Sokolov, V.N., 1980. Quantitative methods for measurement of scanning electron micrographs of soil fabric. Int. Soc. Photogrammetry, XIVth Congr., Hamburg, 23: 154163. Tovey, N.K. and Sokolov, V.N., 1981. Quantitative SEM methods for soil fabric analysis. SEM/ 1981, SEM Inc. AMF O'Hare, pp. 537-554. Unitt, B.M., 1975. A digital computer method for revealing directional intbrmation in images. .I. Phys.. E, Sci. Instrum.~ 8: 423-425.