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Mineralogy of Egyptian Bentonitic Clays I: Discriminant Function Analysis

Published online by Cambridge University Press:  01 January 2024

Mohamed Agha*
Affiliation:
Department of Geology, Faculty of Science, Fayoum University, Egypt
Ray E. Ferrell
Affiliation:
Department of Geology & Geophysics, Louisiana State University, Baton Rouge, LA, 70803, USA
George F. Hart
Affiliation:
Department of Geology & Geophysics, Louisiana State University, Baton Rouge, LA, 70803, USA
*
*E-mail address of corresponding author: [email protected]
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Abstract

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The purpose of the present investigation was to apply a discriminant function analysis (DFA) to quantitative mineralogical data from 124 Paleogene and Neogene bentonitic clays from the northern Western Desert of Egypt in order to establish an objective procedure for grouping the samples at three distinctly recognizable, but partially overlapping, levels of classification. These levels were province or geographic region, geologic age, and quarry. Quantitative mineralogical data were obtained by means of X-ray diffraction procedures employing least-squares fitting of simulated and standard mineral patterns with those from the laboratory. All data were transformed by a log-ratio procedure prior to the DFA. Fe-rich smectite (Feoct-1.4 a.p.f.u.), coarsely crystalline kaolinite, Fe-poor I-S (random with 60% S layers), quartz, and illite were the most important discriminator minerals. S-moderate I-S (random with 70% S), S-rich I-S (random with 80% S), two varieties of finely crystalline kaolinite, feldspar, and amorphous matter were also present. Calcite and gypsum were present in some samples. The median wt.% values for Fe-rich smectite, coarsely crystalline kaolinite, Fe-poor I-S, quartz, and illite in all samples were 16.6, 16.0, 15.2, 4.2, and 3.7, respectively. Abundances of quartz and feldspar have a good positive correlation, and finely crystalline kaolinite and Fe-rich smectite are negatively correlated. Other specific mineral associations are difficult to interpret visually because of the numbers of classes and variables employed in the investigation; however, DFA was successful in identifying statistically significant differences amongst the groups.

At the province level, the back-classification of the samples was successful 92% of the time at the highest probability level, or 100% if the first plus second probability results were utilized. For samples of the same age, 80% of the first-choice assignments were correct and >90% were correct when the second choice was included. At the quarry level, the predictability rate ranged from 76 to >90%. Using both probability results, only seven of the samples were misclassified. In a blind test of quarry samples, the DFA assignment was 80% correct. These tests confirm the objective reliability of class assignments based on DFA. Results based on this data set can be used to classify new samples in future geologic interpretations and economic exploitation of the deposits in the region.

Type
Article
Copyright
Copyright © Clay Minerals Society 2012

References

Abdel-Motelib, A. Kader, Z.A. Ragab, Y.A. and Mosalamy, M., 2011 Suitability of a Miocene bentonite from North Western Desert of Egypt for pharmaceutical use Applied Clay Science 52 140144.CrossRefGoogle Scholar
Abu El Ezz, A.R. Kholeif, M.M. and Abdo, A.A., 1993 Contribution to mineralogy and geochemistry of some bentonite deposits in Egypt El-Minia Science Bulletin 6 7988.Google Scholar
Agha, M.A., Ferrell, R.E., Hart, G.F., Abu El Ghar, M.S., and Abdel-Motelib, A. (in revision) Mineralogy of Egyptian bentonitic clays II: Geologic origin.Google Scholar
Aitchison, J., 1986 The Statistical Analysis of Compositional Data London, UK Chapman & Hall.CrossRefGoogle Scholar
Alberti, A. and Brigatti, M.F., 1985 Crystal chemical differences in Al-rich smectites as shown by multivariate analysis of variance and discriminant analysis Clays and Clay Minerals 33 546548.CrossRefGoogle Scholar
Aparicio, P. and Ferrell, R.E., 2001 An application of profile fitting and CLAY++ for the quantitative representation (QR) of mixed-layer clay minerals Clay Minerals 36 501514.CrossRefGoogle Scholar
Bailey, S.W., 1982 Nomenclature for regular inter-stratifications American Mineralogist 67 394398.Google Scholar
Barbera, G. Lo Guidice, A. Mazzoleni, P. and Pappalardo, A., 2009 Combined statistical and petrological analysis of provenance and diagenetic history of mudrocks: Application to Alpine Tethydea shales (Sicily, Italy) Sedimentary Geology 213 2740.CrossRefGoogle Scholar
Bertog, J. Huff, W. and Martin, J.E., 2007 Geochemical and mineralogical recognition of the bentonites in the lower Pierre Shale Group and their use in regional stratigraphic correlation The Geology and Paleontology of the Late Cretaceous Marine Deposits of the Dakotas 427 2350.Google Scholar
Bolle, M.P. Pardo, A. Adatte, T. Von Salis, K. and Burns, S., 2000 Climatic evolution on the southeastern margin of the Tethys (Negev, Israel) from the Paleocene to the early Eocene: focus on the late Paleocene thermal maximum Journal of the Geological Society of London 157 929941.CrossRefGoogle Scholar
Chang, L.L.Y., 2002 Industrial Mineralogy: Materials, Processes, and Uses New Jersey, USA Prentice Hall.Google Scholar
Chayes, F., 1960 On correlation between variables of constant sum Journal of Geophysical Research 65 41854193.CrossRefGoogle Scholar
Christidis, G.E., 2001 Geochemical correlation of bentonites from Milos Island, Aegean, Greece Clay Minerals 36 295306.CrossRefGoogle Scholar
Clauer, N. O–Neil, J.R. Bonnot-Courtois, C. and Holtzappfel, T., 1990 Morphological, chemical and isotopic evidence for an early diagenetic evolution of detrital smectite in marine sediments Clays and Clay Minerals 38 3346.CrossRefGoogle Scholar
Cuadros, J. Caballero, E. Huertas, F.J. De Cisneros, C.J. Huertas, F. and Linares, J., 1999 Experimental alteration of volcanic tuff: smectite formation and effect on 18O isotope composition Clays and Clay Minerals 47 769776.CrossRefGoogle Scholar
Cook, H.E. Johnson, P.D. Matti, J.C. and Zemmels, I., 1975 Methods of sample preparation and X-ray diffraction data analysis Initial reports of the Deep Sea drilling project, Riverside, California, University of California 28 9991007.Google Scholar
Cravero, F. Marfil, S.A. and Maiza, P.J., 2010 Statistical analysis of geochemical data: a tool for discriminating between kaolin deposits of hypogene and supergene origin, Patagonia, Argentina Clay Minerals 45 183196.CrossRefGoogle Scholar
Daunis-I-Estadella, J. Barcelo-Vidal, C. and Buccianti, A., 2006 Exploratory compositional data analysis Compositional Data Analysis in the Geosciences: From Theory to Practice 264 161174.Google Scholar
Eden, D.N. Palmer, A.S. and Cronin, S.J., 2001 Dating the culmination of river aggradation at the end of the last glaciation using distal tephra compositions, eastern North Island, New Zealand Geomorphology 38 133151.CrossRefGoogle Scholar
Eggleton, R.A., 1977 Nontronite: chemistry and X-ray diffraction Clay Minerals 12 181194.CrossRefGoogle Scholar
Eisenhour, D.D. and Brown, R.K., 2009 Bentonite and its impact on modern life Elements 5 8388.CrossRefGoogle Scholar
Ekosse, G-IE and Mwitondi, K.S., 2009 Multiple data clustering algorithms applied in search of patterns of clay minerals in soils close to an abandoned manganese oxide mine Applied Clay Science 46 16.CrossRefGoogle Scholar
Ferrell, R.E. (2006) Clay Mineralogy: Introductory Course Material on a CD. E-Series 1, The Clay Minerals Society, Chantilly, Virginia, USA.Google Scholar
Ferrell, R.E. and Dypvik, H., 2009 The mineralogy of the Exmore beds — Chickahominy Formation boundary section of the Chesapeake Bay impact structure revealed in the Eyreville core Geological Society of America Special Paper 458 723746.Google Scholar
Ferrell, R.E. Hart, G.F. Swamy, S. and Murthy, B., 1998 Xray mineralogy discrimination of depositional environments of the Krishna Delta, Peninsular India Journal of Sedimentary Research 68 148154.CrossRefGoogle Scholar
Galán, E., Bergaya, F. Theng, B.K.G. and Lagaly, G., 2006 Genesis of clay minerals Handbook of Clay Science Oxford, UK Elsevier 11291162.CrossRefGoogle Scholar
Galán, E. Aparicio, P. Gonzalez, I. and Miras, A., 1998 Contribution of multivariate analysis to the correlation of some properties of kaolin with its mineralogical and chemical composition Clay Minerals 33 6575.CrossRefGoogle Scholar
Gibbs, R.J., 1977 Clay mineral segregation in the marine environment Journal of Sedimentary Petrology 47 243273.Google Scholar
Grim, R.E. and Guven, N. (1978) Bentonites: Geology, Mineralogy, Properties and Uses. Developments in Sedimentology, 24, Elsevier North-Holland, Amsterdam, 256 pp.Google Scholar
Hadi, A.S., 1992 Identifying multiple outliers in multivariate data Journal of the Royal Statistical Society, Series B 54 761771.Google Scholar
Hart, G.F., Traverse, A., 1994 Maceral palynofacies of the Louisiana deltaic plain in terms of organic constituents and hydrocarbon potential Sedimentation of Organic Particles Cambridge, UK Cambridge University Press 141176.CrossRefGoogle Scholar
Hart, G.F., 2011a.eNote00. Transformation of variables for compositional data-analysisGoogle Scholar
Hart, G.F., 2011b.eNote01. Error checking of the mineralogical data-frame: Bentonite Quarry study of EgyptGoogle Scholar
Hart, G.F. Ferrell, R.E. Lowe, D.R. Lenoir, A.E., Morton, R.A. and Nummedal, D., 1989 Shelf sandstones of the Robulus L zone, offshore Louisiana Shelf Sedimentation, Shelf Sequences and Related Hydrocarbon Accumulation 117141.Google Scholar
Hassan, M.S. and Abdel-Khalek, N.A., 1998 Beneficiation and applications of an Egyptian Bentonite Applied Clay Science 13 99115.CrossRefGoogle Scholar
Huff, W.D. Kolata, D.R., Cross, T.A., 1990 Correlation of K-bentonite beds by chemical fingerprinting using multivariate statistics Quantitative Dynamic Stratigraphy New Jersey, USA Prentice Hall 567577.Google Scholar
Huff, W.D. Bergstrom, S.M. and Kolata, D.R., 2010 Ordovician explosive volcanism In: The Ordovician Earth System. Geological Society of America Special Paper 466 1328.Google Scholar
Ingelthorpe, S.D.J. Morgan, D.J. Hegley, D.E. and Bloodworth, A.J., 1993 Industrial Minerals Laboratory Manual “Bentonite” UK Mineralogy and Petrology Group, British Geological Survey.Google Scholar
Johnson, R.A. and Winchern, D.W., 2007 Applied Multivariate Statistical Analysis 6 New Jersey, USA Prentice Hall.Google Scholar
Kiipli, T. Kallaste, T. Nestor, V. and Loydell, D.K., 2010 Integrated Telychian (Silurian) K-bentonite chemostratigraphy and biostratigraphy in Estonia and Latvia Lethaia 43 3244.CrossRefGoogle Scholar
Kolata, D.R., Huff, W.D., and Bergstrom, S.M. (1996) Ordovician K-bentonites of Eastern North America. Geological Society of America Special Paper, 313, 84 pp.Google Scholar
Martin-Fernandez, J.A. and Thio-Henestrosa, S., 2006 Rounded zeros: some practical aspects for compositional data Compositional Data Analysis in the Geosciences: From Theory to Practice 264 191201.Google Scholar
Moebis, A. Cronin, S.J. Neall, V.E. and Smith, I.E., 2011 Unravelling a complex volcanic history from fine-grained, intricate Holocene ash sequences at the Tongariro Volcanic Centre, New Zealand Quaternary International 246 352363.CrossRefGoogle Scholar
Montero-Serrano, J.C. Pararea-Albaladejo, J. Martin-Fernandez, J.A. Martinez-Santana, M. and Gutierrez-Martin, J.V., 2010 Sedimentary chemofacies characterization by means of multivariate analysis Sedimentary Geology 228 218228.CrossRefGoogle Scholar
Moore, D.M. and Reynolds, R.C., 1989 X-ray Diffraction and the Identification and Analysis of Clay Minerals Oxford, UK Oxford University Press.Google Scholar
Murray, H.H. (2007) Applied Clay Mineralogy: Occurrences, Processing and Applications of Kaolins, Bentonites, Palygorskite-Sepiolite, and Common Clays. Developments in Clay Science, 2, Elsevier, Amsterdam,188 pp.Google Scholar
Odom, I.E., 1984 Smectite clay minerals: properties and uses Philosophical Transactions of the Royal Society of London 311 391–332.Google Scholar
Petschick, R. (2004) MacDiff 4.2.5. Power Diffraction Software: (/staff/Homepages/Petschick/MacDiff/MacDiffInfoE.html, accessed 23 June 2012).Google Scholar
Prudencia, M.I. Sequeira Braga, M.A. Oliviera, F. Dias, M.I. Delgado, M. and Martins, M., 2006 Raw material sources for the Roman Bracarense ceramics (NW Iberian Peninsula) Clays and Clay Minerals 54 638649.CrossRefGoogle Scholar
R statistical package version 2.10.1 (2009) The R Foundation for Statistical Computing. ISBN 3-900051-07-0.Google Scholar
Sanchez, C. and Galán, E., 1995 An approach to the genesis of palygorskite in a Neogene-Quaternary continental basin using principal factor analysis Clay Minerals 30 225238.CrossRefGoogle Scholar
Shane, P.A.R. and Froggatt, P.C., 1994 Discriminant function analysis of glass chemistry of New Zealand and North American tephra deposits Quaternary Research 41 7081.CrossRefGoogle Scholar
Shapiro, S.S. and Wilk, M.B., 1965 An analysis of variance test for normality (complete samples) Biometrika 52 591611.CrossRefGoogle Scholar
Shoval, S., 2004 Deposition of volcanogenic smectite along the southeastern Neo-Tethys margin during the oceanic convergence stage Applied Clay Science 24 299311.CrossRefGoogle Scholar
Środoń, J., 2006 Identification and quantitative analysis of clay minerals Handbook of Clay Science 1 765787.CrossRefGoogle Scholar
Varadachari, C. and Mukherjee, G., 2004 Discriminant analysis of clay mineral compositions Clays and Clay Minerals 52 311320.CrossRefGoogle Scholar
von Eynatten, H. Barcelo-Vidal, C. and Pawlowsky-Glahn, V., 2003 Sandstone composition and discrimination: a statistical evaluation of different analytical methods Journal of Sedimentary Research 73 4757.CrossRefGoogle Scholar
Weltje, G.J., 2002 Quantitative analysis of detrital modes: statistically rigorous confidence regions in ternary diagrams and their use in sedimentary petrology Earth-Science Reviews 57 211253.CrossRefGoogle Scholar
Zhang, L. Sun, M. Wang, S. and Yu, X., 1998 The composition of shales from the Ordos basin, China: effects of source weathering and diagenesis Sedimentary Geology 116 129141.CrossRefGoogle Scholar