U. S. DEPARTMENT OF THE INTERIOR 

U. S. GEOLOGICAL SURVEY

An evaluation of alternative chemical classifications of sandstones

by 

David A. Lindseyi

OPEN-FILE REPORT 99-346 

paper edition

-1 -.5 0 .5 1 

Log (K20/Na20)

Classification of some representative sandstones (Fig. 1A)

This report is preliminary and has not been reviewed for conformity with U. S. Geological Survey editorial standards or 

with the North American Stratigraphic Code. Any use of trade, product, or firm names is for descriptive purposes only 

and does not imply endorsement by the U. S. Government.

1U. S. Geological Survey, Denver, Colo., 80225
CONTENTS 

Summary 1 

Introduction 1 

Principles of classification 2 

Classification of common sandstones 7 

Igneous sources 9 

Composition range of gray wackes 12 

Composition of Rocky Mountain Eocene arkoses 12

Composition of Midcontinent Pennyslvanian lithic arenites and clay-rich sandstones 18 

Conclusions 21 

Acknowledgments 21 

References cited 21
LIST OF FIGURES

Figure 1. Scattergrams showing composition of representative sandstones (data from Pettijohn, 1963; 1975): A) log 

(SiO2/Al2O3) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O), C) SiO2/Al2O3 vs K2O/ 

Na2O, and D) (FeTO3+MgO)/(K2O+Na2O) vs K2O/Na2O.

Figure 2. Alternative classification diagrams showing composition of representative sandstones (data from Pettijohn, 

1963; 1975): A) scattergram of log (FeTO3/K2O) vs log (SiO^A^Os) from Herron (1988), B) triangular scattergram of 

Na2O-K2O-(FeTO3+MgO) from Blatt and others (1972),

Figure 3 Rotated three-dimensional scattergram of log (SiO2/Al2C>3) vs log (K2O/Na2O) vs log ((Fe-rOs+MgO)/ 

(K2O+Na2O)) for representative sandstones (data from Pettijohn, 1963; 1975).

Figure 4. Scattergrams showing composition of common average igneous rocks (data from Le Maitre, 1976): A) log 

(SiOyAl2O3 ) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O), C) log (FeTO3/K2O) vs log 

(SiO2/Al2O3), and D) triangular scattergram Na2O-K20-(FexO3+MgO).

Figure 5. Scattergrams showing composition of tuffaceous and nontuffaceous sandstones in the Harebell Formation 

(data from Lindsey, 1972): A) log (SiO^AfeOs) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/(K2O+Na2O)) vs log (K2O/ 

Na2O), C) log (FeTO3/K2O) vs log (SKVAbOs), D) log pet plagioclase vs log (SiO^A^Os), and E) triangular 

scattergram Na2O-K2O-(FeTO3+MgO).

Figure 6. Scattergrams showing composition of graywackes and modern marine sands, classified according to plate 

boundary setting (data from Bhatia, 1983): A) log (SiO2/Al2O3) vs log (K2O/Na2O), B) log ((Fe-rOs+MgO)/ 

(K2O+Na2O)) vs log (K2O/Na2O), C) log (FeTO3/K2O) vs log (SiO^A^Os), and D) triangular scattergram Na2O-K2O- 

(FeTO3+MgO).

Figure 7. Scattergrams showing average composition of Eocene sandstones at 36 localities in Rocky Mountain foreland 

basins, western United States (data from Vine and Tourtelot, 1973): A) log (SiCtyAbOs) vs log (K2O/Na2O), B) log 

((FeiO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O), C) log (FexO3/K2O) vs log (SiO^AbOs), and D) triangular 

scattergram Na2O-K2O-(FeTO3+MgO).

Figure 8. Scattergrams showing correlations of A) log (SiO;2/Al2O3) vs log Ga ppm and B)

(K2O+Na2O)) vs log Co ppm, average values for Eocene sandstones at 36 localities in Rocky Mountain foreland basins,

western United States.

Figure 9. Scattergram of log cobalt ppm vs log gallium ppm, average values for Eocene sandstones at 36 localities in 

Rocky Mountain foreland basins, western United States (data from Vine and Tourtelot, 1973).

Figure 10. Scattergram of log cobalt ppm vs log gallium ppm for 216 samples of Eocene sandstone in Rocky Mountain 

foreland basins, western United States.

Figure 11. Scattergrams showing composition of 39 analyses of Pennsylvanian sandstones from Kansas, Missouri, and 

Oklahoma (data from Boerngen and others, 1975): A) log (SiO^A^Os) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/ 

(K2O+Na2O)) vs log (K2O/Na2O), C) log (FeTO3/K2O) vs log (SiO^AfcOs), and D) triangular scattergram Na2O-K2O- 

(FeT03+MgO).

Figure 12. Variation scattergrams of 39 analyses of Pennyslvanian sandstones from Kansas, Missouri, and Oklahoma 

(data from Boerngen and others, 1975): A) K2O vs A12O3, B) Na2O vs A12O3, C) K2O+Na2O vs A12O3 , and D) A12O3 vs 

Si02.

TABLE

Tablet. List of analyzed sandstones compiled by Pettijohn (1963; 1975) and plotted in Figs. 1 and 2.
U.S. GEOLOGICAL SURVEY OPEN-FILE REPORT 99-346 

AN EVALUATION OF ALTERNATIVE CHEMICAL CLASSIFICATIONS OF SANDSTONES

by David A. Lindsey

SUMMARY

Chemical classification of sandstone is worth attempting because modern analytical methods are producing 

extensive data sets on rock composition. Previous compilations and statistical studies have demonstrated the application 

of chemical data to problems in sandstone petrology, but classification has been largely ignored. Chemical data has 

value for classification, but the limitations of using chemical data for classification must be identified. Consideration of 

the processes of sandstone formation permits formulation of classification guidelines and systems for classification. 

Alternative systems for chemical classification can be then evaluated for their power to identify major types of 

sandstones and to facilitate genetic interpretation.

The relative concentrations of three major oxide groups silica and alumina, alkali oxides, and iron oxide plus 

magnesia have been used to classify sandstones. The enrichment of SiOi by weathering and transport produces quartz 

arenites (orthoquartzites). Silica enrichment can be represented by SiO^A^Oa. Abundant alkalis (Na2O and K^O) 

characterize immature sandstones such as graywackes and arkoses; the ratio K2O/Na2O is determined by the net effects 

of provenance and diagenesis. The concentration of iron oxide and MgO is the net effect of provenance and the 

hydraulic concentration and diagenesis of detrital ferromagnesian and iron minerals. The relative concentration of iron 

oxide plus magnesia can be represented by (FeiO3+MgO)/(K2O+Na2O). These ratios form the basis for chemical 

classification, and may be represented by two 2-dimensional diagrams or one 3-dimensional (triangular) diagram. 

Variants of these ratios have been used in previous classification systems.

With varying success, the classes quartz arenite, graywacke, and arkose can be defined by chemical composition. 

Guidelines for chemical classification are defined by plotting major oxide ratios for major classes of sandstone, and by 

examining compositional variation within and among the major classes. Thus, quartz arenites are here defined by log 

(SiO2/Al2O3) > 1.5 and graywackes are defined by log (SiO^AhOs) < 1 and log (K20/Na2O) < 0. Arkoses are defined 

by log (SiO2/Al2O3) < 1.5, log (K2O/Na2O) > 0 and log ((FeTO3+MgO)/(K2O+Na2O)) < 0. However, graywackes from 

passive continental margins have log (K2O/Na2O) > 0 and some arkoses have log (K20/Na2O) < 0. A fourth sandstone 

class, lithic arenite, is compositionally diverse; various classifications were tested with modest success, but lithic arenites 

cannot be identified with great confidence by chemical composition alone.

Alternative classification systems proposed previously rely on various oxide combinations, ratios, plotting methods, 

definitions of petrographic terms, and class boundaries. Comparison of these systems with the guidelines offered here 

reveals strengths and weaknesses of each. No system is ideal, and classification is facilitated by using chemical data in 

conjunction with petrographic data, and by exploring relationships among chemical variables that might have genetic 

significance.

Trace elements, notably Ga and Co, show promise for use in chemical classification. In a data set containing trace 

element analyses of quartzose (including lithic) arenites and arkosic sandstones, gallium is highly correlated with SiOi/ 

AhOs and cobalt is correlated with (FeiO3+MgO)/(K2O+Na2O). Log Co vs log Ga was used to distinguish arkosic 

sandstones from quartz arenites, but neither could be distinguished from lithic arenites.

INTRODUCTION studies, or identifying rocks and formations in boreholes.

The purpose of chemical study of sandstones should If rocks could be classified and interpreted from chemical

not be to supplant petrographic examination, but to extend data in the context of only limited petrographic data, then

petrogenetic interpretation. However, with the chemical data acquired in the course of diverse

introduction of modern chemical analytical methods (X- investigations could contribute to petrogenetic studies or to

ray fluorescence, energy dispersive X-ray spectrometry, applications that require genetic information. For

and atomic absorption spectrometry, to mention a few), sandstones, new applications might include investigations

large numbers of high-quality chemical analyses of rocks, of hydrocarbon reservoir porosity, the origin of

including sandstones, are becoming available without metalliferous ore, and the effect of lithology on ground and

corresponding detailed petrographic study. Increasingly, surface water chemistry. In reality, of course,

new down-hole analytical methods are capable of classification and interpretation from chemical data alone

producing large numbers of analyses in a few hours (e.g., have severe limitations. This report is an exploration of

Herron and Herron, 1996). Many chemical data sets were the limits of using chemical data for classification of

acquired for purposes other than petrogenetic studies, such sandstones and an evaluation of the relative power of

as conducting geochemical exploration for minerals, classification systems. For individual sandstones, the use

establishing geochemical baselines for environmental of the classification process for insight to genetic
interpretation is illustrated.

Chemical classification of sandstone has been largely 

ignored by sedimentary petrographers, who preferred to 

classify sandstones using more accessible and definitive 

mineralogical and textural data derived from thin-section 

petrographic studies. Except for the work of Herron 

(1988), and brief explorations of the topic by Blatt and 

others (1972) and Pettijohn and others (1972), chemical 

studies of sandstones have been directed toward goals 

other than classification. Some of the first attempts to 

summarize and interpret chemical analyses of sandstones 

focused on identifying tectonic environments (Middleton, 

1960; Crook, 1974; Schwab, 1975). Chemical analyses 

were also tabulated for representative sandstones, 

including those important to the naming of the common 

sandstone clans (called "classes" in this report) (Pettijohn, 

1963; 1975; Pettijohn and others, 1972). At the time these 

studies were conducted, only a few hundred analyses were 

available in the literature, and most analyses were limited 

to major oxides.

Recently, trace elements and isotopes as well as major 

oxides have been used to investigate the origin of 

siliciclastic sedimentary rocks (McLennan and others, 

1993). Major oxides and trace elements have been used 

extensively to identify graywacke provenance and 

correlate graywacke composition with plate-tectonic 

setting (Bhatia, 1983; Roser and Korsch, 1986,1988; 

Floyd and others, 1991; McCann, 1991). Other studies 

have used geochemical data to make stratigraphic 

assignments (Connor, 1969; Hickman and Wright, 1983; 

Ehrenberg and Siring, 1992) and to identify the 

provenance and weathering history of sandstones 

(Humphreys and others, 1991; Fedo and others, 1995; 

Young and Nesbitt, 1998). These studies demonstrate the 

application of data on chemical composition to problems 

in sandstone petrology.

In this report, I examine some alternative methods for 

chemical classification of sandstones, with emphasis on 

the major oxide composition of the principal types of 

sandstone (Blatt and others, 1972; Herron, 1988; Pettijohn 

and others, 1972). I begin with a discussion of principles 

of chemical classification and various classification 

systems that have been proposed previously. 

Classification systems are compared first for a data set of 

representative examples of major sandstone classes; 

further comparisons are made though examination of data 

sets for each sandstone class. All of the data sets are 

drawn from the literature and from the work of others at 

the U.S. Geological Survey. Emphasis is given to 

graphical analysis (scattergrams and triangle diagrams) of 

major oxide components and simple combinations of these 

components that can be related to the major classes of 

sandstones and to processes thought to affect sandstone 

composition. Simple graphical methods are not a 

substitute for other statistical techniques, but they enable 

comparison of sandstone classes and depiction of general 

relationships among analyzed samples. Where two or

more populations are to be compared and differentiated, 

and where sufficient data representative of target 

populations are available, multivariate statistical 

techniques such as discriminant analysis (e.g., Connor, 

1969) may be more effective than the classification 

techniques described here.

The approach to chemical classification of sandstones 

used here relies on the assumption that chemical attributes 

can be correlated with names assigned by petrographic 

study. This assumption is not always valid because, as 

discussed by Gilbert (in Williams and others, 1954), 

petrographic criteria for sandstone classification are 

neither consistent nor necessarily related to mineral or 

chemical composition. For example, "graywacke" is 

defined by sorting and grain size, whereas "arkose" is 

defined by mineral composition. "Graywacke" (or 

Gilbert's term, "wacke") is applied to sandstones having 

abundant clay- and silt-sized matrix. The composition of 

the sand-sized fraction varies widely. In contrast, "arkose" 

is applied to sandstones containing abundant feldspar. 

Feldspar grains in arkose include both potassic and sodic 

varieties, and these vary greatly in proportion. Graywacke 

and arkose overlap where both feldspar and matrix are 

abundant, as in arkosic graywacke (Williams and others, 

1954), and chemical compositon may not be indicative of 

petrographic class. A third major sandstone class, "lithic 

arenite," is composed of abundant sand-sized rock 

fragments. Lithic arenite varies in chemical composition 

according to the type of rock fragments. The lack of any 

mineralogical basis for defining graywacke and lithic 

arenite is a major reason for misclassification when only 

chemical composition is considered.

Despite the impediments to chemical classification 

imposed by inconsistent petrographic criteria, each 

sandstone class can be characterized by chemical 

attributes. These attributes are not unique for all classes 

and are best employed when petrographic observations are 

also available. Where chemical data alone are available, 

classification is improved by experimenting with 

alternative classification systems and by examining the 

data for relationships that have genetic significance.

PRINCIPLES OF CLASSIFICATION 

The concentrations of three major oxide groups have 

been used to classify sandstones: silica and alumina, alkali 

oxides, and iron oxide plus magnesia. The significance of 

these variables is discussed by Blatt and others (1972), 

Herron (1988), Pettijohn and others (1972) and, for 

modern river sands, Potter (1978); some important points 

are summarized as follows:

The enrichment of SiO2 over AllOa by mechanical 

and chemical processes produces quartz arenites 

(orthoquartzites). Silica (quartz) enrichment is a measure 

of sandstone maturity, and is a reflection of the duration 

and intensity of weathering and destruction of other 

minerals during transport. Silica enrichment also occurs 

by addition of silica cement, as quartz and opal.
Abundant alkalis (NaiO and KiO) characterize 

immature sandstones such as arkoses and graywackes. 

The ratio K2O/N32O is determined by the sum of 

provenance and diagenesis. The ratio K2O/N32O reflects 

the relative abundance of potassic feldspar and plagioclase 

but is also affected by the compositions of the feldspars 

present. Potassic feldspar commonly contains some 

sodium (Herron and Matteson, 1993), whereas the 

contribution of sodium from plagioclase is decreased by 

calcium substitution. The ratio K2O/N32O has been used 

to discriminate between arkose (K2O>Na2O) and 

graywacke (Na2O>K2O) (Pettijohn, 1963). Arkoses are 

immature sandstones with abundant feldspar (both potassic 

feldspar and plagioclase). Graywackes contain abundant 

plagioclase (Huckenholz, 1963; Middleton, 1972). 

However, as will be discussed in this report, numerous 

exceptions to the relative abundance of K2O and Na2O in 

arkoses and graywackes have been found. Where clays, 

micas, and lithic fragments are present, they may also 

contribute significant amounts of alkalis; in particular, 

illite and mica contribute to the concentration of 

potassium.

The concentration of iron oxide (Fe-rOs, total iron as 

Fe2Os) and MgO is the net result of provenance and 

processes that concentrate and preserve detrital 

ferromagnesian and iron minerals (mainly amphibole, 

mica, illite, ilmenite, and magnetite) and their alteration 

products (chlorite, hematite, and some clays). 

Concentration of detrital ferromagnesian minerals reflects 

their abundance in source rocks and is increased by 

hydraulic sorting and is decreased by chemical destruction 

during weathering and diagenesis under oxidizing 

conditions. Studies of redbeds suggest that iron has been 

oxidized and redistributed locally, but not removed, during 

diagenesis (Walker, 1967). The low content of MgO in 

many arkoses stems from ferromagnesian-poor source 

rocks or possibly, as proposed by Blatt and others (1972, p. 

318), removal during diagenesis. Based on chemical 

analyses of clay minerals in Herron and Matteson (1993), 

sandstones that contain illite or chlorite matrix would be 

expected to contain more iron oxide than matrix-free 

arenites. Abundant chloritic matrix in most graywackes 

accounts for the high iron oxide and MgO content of these 

sandstones (Pettijohn, 1963).

The three major oxide variables proposed for 

sandstone classification are a complex effect of 

provenance, sediment transport, and diagenesis. Study of 

major-oxide content alone cannot suffice to identify the 

separate effects of various processes, but the chemical 

composition of sandstones does bear some relationship to 

the action of one process or another. For example, the 

effects of prolonged weathering and transport are most 

evident in the formation of quartz arenite. Provenance is a 

major factor in the formation of arkose and lithic arenite. 

The effect of diagenesis is probably most evident in 

production of graywacke matrix (Cummins, 1962; 

Kuenen, 1966), but dissolution and cementation may be

major factors in forming quartz arenites, also.

Ratios are commonly selected for classification (e.g., 

Pettijohn and others, 1972, fig. 2-11; Roser and Korsch, 

1986, fig. 13). They provide some distinct advantages 

over percentage compositional data for classifying 

sandstones. Ratios can be selected to represent processes 

believed to have been important in sandstone genesis. 

Thus silica enrichment can be represented by SiO2/Al2Oa, 

the relative concentrations of alkalis can be represented by 

K2O/N32O, and the relative concentration of iron oxide 

plus magnesia can be represented by (Fe-rOa+MgO)/ 

(K2O+Na2O). Ratios largely overcome complex 

computstion problems posed by abundant calcite cement, 

variable content of volatile components (CO2, H2O, Cl, 

and F), or other constituents that may be present in unusual 

amounts. Ratios have also been used to sidestep the effect 

of closure in geochemical data, whereby negative 

correlations among variables are forced by the necessity of 

summing percentage data to 100 (Chayes, 1960; Miesch 

and others, 1966). Finally, use of ratios allows plotting of 

incomplete analyses without recalculation, making 

determination of volatiles and minor constituents such as 

TiO2 and MnO unnecessary.

Adoption of ratios for plotting chemical analyses of 

sandstones does not overcome problems posed by silica, 

carbonate, and other, less common cements, such as albite 

or analcime. However, the presence of silica cement in 

quartz arenites, where it is most common, only enhances 

the value of SiO^AhOs and does not lead to 

misclassifying a sandstone. Carbonate cement is common 

in sandstones, and where the carbonate is dolomite or 

ankerite, the concentrations of MgO and FeO are elevated, 

respectively. Because ratios involving Mg and Fe oxides 

will be affected if these elements are present in carbonate 

cement, analyses should be screened before use in 

chemical classification. Elevated MgO or Pe-pOs will yield 

anomalously high (Fe-rO3+MgO)/(K2O+Na2O), causing 

the sample to plot outside the compositional fields for 

other sandstones. The presence of abundant sodium 

minerals as cements may also be indicated by unusual 

location of the sample on ratio scattergrams. 

Mineralogical study is the only recourse for identifying 

and classifying rocks with unusual cements.

Logarithmic scales were adopted for the twodimensional ratio scattergrams used here. Most frequency 

distributions of major oxide ratios, upon inspection, tend 

to be skewed toward low values. Also, the range of some 

ratios is rather large, making adoption of logarithmic 

scales convenient for plotting. Ratios may be converted to 

logarithms and plotted on linear scales, or plotted directly 

on logarithmic scales. For computational purposes, such 

as fitting lines to data, the former is convenient, but 

logarithmic scales permit direct reading of ratio values 

from scattergrams.

Scattergrams of log (SiO^AhOs) vs log ( K2O/Na2O) 

and log ((FeTO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O) 

were adopted for use in this report (Fig. 1). The
0 .5 1 

Log (K20/Na20)

1 10 

K20/Na20

10

B

0 .5 1 

Log (K20/Na20)

1.5

O f\J 

ro

O f\J

O

O)

CO

O

D

19

20. \, 

21 22X3 btf

1 10 

K20/Na20

TOO

TOO

Figure 1. Scattergrams showing composition of representative sandstones 

(data from Pettijohn, 1963; 1975): A) log (SiO2/Al2O3) vs log (K2O/Na2O), 

B) log ((FerO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O), C) (SiOyAl2O3) 

vs (K2O/Na2O), and D) ((Fe-rO3+MgO)/(K2O+Na2O)) vs (K2O/Na2O). A 

and B show ratios expressed as logarithms on a linear scale; C and D are 

same as A and B except raw ratios are plotted on logarithmic scales. 

Compositional fields for major classes of sandstones are shown in A and B. 

Sample numbers in C and D are identified in Table 1.

EXPLANATION 

O Quartz arenite 

D Graywacke 

A Arkose 

O Lithic arenite 

Solid symbol = average

scattergram, log (SiO2/Al2Os) vs log (K2O/Na2O) is a 

variant of one first proposed by Pettijohn and others (1972, 

fig. 2-11), but without their overlay of compositional fields 

for major sandstone classes. A third possible scattergram, 

log ((FeTO3+MgO)/(K2O+Na2O)) vs log (SiO2/Al2O3), 

was investigated but appears to largely duplicate the first 

two. Three-dimensional Scattergrams, portraying samples 

in terms of all three ratios, can be used to group samples 

and show relationships between a sample and the principal

groups. Three-dimensional scattergrams usually require 

rotation for optimal viewing of sample groups.

A variation of the ratio scattergrams proposed here has 

been used to classify terrigenous sands and shales, with 

application to lithologic classification from borehole 

geochemical logs (Herron, 1988). Herron (1988) used a 

scattergram of log (FeTO3/K2O) vs log (SiO2/Al2O3) to 

distinguish the various classes of sandstone as well as 

shale and other iron-rich clastic sediments (Fig. 2A). The
Table 1 . List of analyzed sandstones compiled by Pettijohn (1963; 1975) and plotted in Figs. 1 

and 2. Geologic ages and stratigraphic nomenclature do not reflect later revisions, if any.

QUARTZ ARENITES (ORTHOQUARTZITES AND PROTOQUARTZITES)

1 Precambrian Mesnard Quartzite, Marquette Co., Michigan

2 Precambrian Lorrain Quartzite, Plummer Township, Ontario*

3 Precambrian Sioux Quartzite, Sioux Falls, South Dakota

4 Cambrian? Lauhavuori Sandstone, Tiiliharju, Finland

5 Ordovician St. Peter Sandstone, Mendota, Minnesota

6 Ordovician Simpson Sand, Cool Creek, Oklahoma*

7 Silurian Tuscarora Quartzite, Hyndman, Pennsylvania*

8 Devonian Oriskany Sandstone, Berkeley Springs quarry, West Virginia

9 Pennsylvanian Mansfield Formation, Crawford County, Indiana

10 Mississippian Berea Sandstone, Berea, Ohio*

LITHIC ARENITES (SUBGRAYWACKES AND PROTOQUARTZITES)

11 Jurassic Salt Wash Formation, composite of 96 samples, Colorado Plateau

12 Oligocene Frio Formation, composite of 10 samples, Jim Wells and Kleberg Counties, Texas

13 Molasse, Aquitanienne, Lausaunne, Switzerland

14 Molasse, Granichen, Burghalde, Canton Aargau, Switzerland 

1 5 Mississippian Berea Sandstone, Berea, Ohio

16 Molasse burdigalienne, Voreppe

17 Carboniferous coal measures, Westphalian coal basin, France and Belgium

18 Carboniferous coal measures, Westphalian coal basin, France and Belgium

GRAYWACKES

19 Archean, Manitou Lake, Ontario

20 Archean, Knife Lake, Ontario

21 Precambrian Tyler Slate, Hurley, Wisconsin

22 Ordovician? Rensselaer Graywacke, Spencertown, New York

23 Upper Devonian and Lower Carboniferous Tanner Graywacke, Scharzfeld, Germany

24 Mississippian Stanley Shale, Mena, Arkansas

25 Lower Mesozoic, composite of 20 graywackes, Wellington, New Zealand

26 Jurassic and Cretaceous Franciscan Formation, Piedmont, California

27 Eocene, Solduc, Washington

28 Carboniferous Kulm, Steinbach, Frankenwald, Germany

ARKOSES AND SUBARKOSES

29 Precambrian Jotnian, Koylio, Muurunmaki, Finland

30 Precambrian Torridonian, Kinlock, Skye

31 Lower Cambrian Sparagmite, Engerdalen, Norway

32 Devonian lower Old Red Sandstone, Foyers, Loch Ness, Scotland

33 Devonian Old Red Sandstone, Red Crags, Fochabers-on-Spey, Scotland

34 Portland Stone (Triassic Newark Group), Portland, Connecticut

35 Devonian Rosebrae Sandstone, Rosebrae, Elgin, Scotland

36 Cambrian or Ordovician sandstone, Bastard Township, Ontario*

37 Permian Whitehorse Group, Kansas

38 Oligocene Molasse, Unterageri, Canton Zug, Switzerland

39 Oligocene, Auvergne, France

* No NazO measurable; not included on two-dimensional ratio plots (Fig. 1)
.5 1 1.5 

Log (SJ02/AI203)

2.5

FeT03+MgO

.17

Ferromagnesian 

Potassic Sandstones

33

EXPLANATION 

O Quartz arenite 

D Graywacke 

A Arkose 

O Lithic arenite 

Solid symbol = average

B Na20 K20

Figure 2. Alternative classification diagrams showing composition of representative sandstones (data from Pettijohn, 

1963; 1975): A) scattergram of log (FeTO3/K2O) vs log (SiO2/Al2O3 ) from Herron (1988), and B) triangular scattergram 

of Na2O-K2O-(Fe-rO3+MgO) from Blatt and others (1972). Sample numbers are identified in Table 1.

ratio log (Fe-rO3/K2O) is the rough equivalent of log 

(FeTO3+MgO)/(K2O+Na2O). The use of Fe-rO3 alone 

emphasizes concentration of iron-bearing heavy minerals 

such as magnetite and ilmenite in sandstone, but the 

omission of MgO makes the ratio less sensitive to effects 

of carbonate cement. Because borehole geochemical logs 

do not report sodium, that element was not included in the 

classification system of Herron (1988). The resulting 

classification does not take into account the ratio of K2O to

Na2O, which may be of value for distinguishing arkoses 

from graywackes. Herron (1988) assigned compositional 

fields to each sandstone class based on a reference set of 

analyzed sandstones from Pettijohn (1963) and Pettijohn 

and others (1972), so that a name could be assigned to a 

sandstone by simply plotting the values of log (FexOa/ 

K2O) vs log (SiO^A^Oa). Herron's classification system 

is designed to distinguish subtle compositional classes 

such as subarkoses from arkoses and sublitharenites from
litharenites, as well as to distinguish the major sandstone 

classes, and it can be used with geochemical log data. 

Herron (1988) showed that his system provides more 

accurate classification of sandstones than the diagram log 

(K2O/Na2O) vs log (SiCVAhOs) with compositional 

fields, proposed by Pettijohn and others (1972). For this 

reason I have used Herron's (1988) system, instead of the 

one by Pettijohn and others (1972), for comparison with 

the two-fold system log (SiO2/Al2O3 ) vs log (K2O/Na2O) 

and log ((FerO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O).

A triangular diagram (Fig. 2B) that incorporates the 

three components Na2O, K2O, and (Fe-rOs+MgO) 

represents two of the variables adopted for ratio plots 

(Blatt and others, 1972, p. 318). In the triangular diagram, 

Blatt and others (1972) do not attempt to correlate 

chemical composition with petrographically defined 

sandstone classes, but instead divide sandstones into three 

chemical groups: sodic sandstones, potassic sandstones, 

and ferromagnesian potassic sandstones. The triangular 

diagram is useful for classification and comparison, but 

relationships among samples are in some cases visually 

obscured by squeezing data points near the corners of the 

triangle. Groups of samples that should plot separately 

tend to merge toward one apex if one component is 

dominant, and mixing trends visible on two-dimensional 

diagrams can be obscured by scatter. On the other hand, 

triangular diagrams portray three components 

simultaneously and allow location of a sample point even 

when values for one or two components are zero. For the 

triangular diagrams of Blatt and others (1972), the three 

components are generally subequal in abundance and do 

not require multiplication or transformation to logarithms. 

The diagrams are employed here to compare with twodimensional scattergrams. The two methods of plotting 

sandstone composition complement one another.

CLASSIFICATION OF COMMON SANDSTONES

Principles of classification were tested first (Figs. 1, 2 

and 3) on a widely published reference set of chemical 

analyses of representative sandstones, tabulated by 

Pettijohn (1963,1975). The set (Table 1) is only slightly 

larger than that used by Herron (1988); four average 

values for quartz arenite, arkose, graywacke, and lithic 

arenite (Pettijohn, 1963) are also plotted. These analyses 

represent classic sandstones, such as the type arkoses and 

graywackes, and typical examples of the major classes of 

sandstones. Most of the analyzed sandstones are from 

formations that have received independent petrographic 

study, and hence have been classified on that basis. For 

convenience, ratio scattergrams are presented both as 

logarithms on linear scales and as raw ratios on 

logarithmic scales in Figure 1.

Quartz arenites (orthoquartzites) are readily separated 

on the scattergram of log (SiO2/Al2O3 ) vs log (K2O/Na2O) 

(Figs. 1A,C), which represents silica enrichment. Most 

representatives have log (SiO2/Al2O3) > 1.5, indicating 

that SiO2 is at least 30X more abundant than Al2Os.

Quartz arenites generally contain more than 95 percent 

(pet) SiO2, or more than 90 pet quartz sand. Log (K2O/ 

Na2O) varies, although most examples are potassic (log > 

0). Four analyses of quartz arenites (Table 1) were not 

plotted because K2O and Na2O contents were so small as 

to be unmeasured. The scattergram of log ((FejOs+MgO)/ 

(K2O+Na2O)) vs log (K2O/Na2O) (Figs. 1B,D) does not 

distinguish quartz arenites because iron oxide and 

magnesia values are small and erratic. As reported by 

Herron (1988), the scattergram of log (FejO3/K2O) vs log 

(SiO2/Al2O3) (Fig. 2A) discriminates quartz arenite well. 

The triangle diagram of Blatt and others (1972) (Fig. 2B) 

excludes sandstones having < 5 pet Al2Os and thus, quartz 

arenites.

Graywackes plot in well-defined fields on all major 

oxide ratio diagrams (Figs. 1, 2 and 3). Generally, 

graywackes in the reference set plot on the Na2O>K2O 

side of the diagrams; they are characterized by fairly low 

log (SiO^A^Os) values of 0.5 to 1.0 (Fig. 1A); and they 

have log ((Fe-rO3+MgO)/(K2O+Na2O)) values between 

-0.2 and 0.5 (Fig. IB). These values are close to, but not 

quite, in the range of average igneous rocks (Le Maitre, 

1976) (Fig. 4). This near coincidence of values is not 

surprising, considering that many of the graywackes 

tabulated by Pettijohn (1963) were deposited in platemargin environments where igneous provenance was 

dominant (for examples, see Roser and Korsch, 1986; 

Floyd and others, 1991). The slightly higher log (SiOV 

Al2Os) values of graywackes compared to average igneous 

rocks indicate the effects of limited exposure already to the 

sedimentary processes of weathering and transport. The 

field of graywackes (labeled "wacke" in Fig. 2A) is small 

relative to other classes of sandstone on the scattergram of 

log (Fe-rO3/K2O) vs log (SiO2/Al2O3); most graywackes, 

except two iron-rich Archean examples, are properly 

classified (Fig. 2A). Most graywackes plot to the left of 

the Na2O=K2O line in the triangle diagram of Blatt and 

others (1972) (Fig. 2B).

Arkoses are readily distinguished on all major oxide 

ratio diagrams (Figs. 1, 2 and 3). Arkoses (including 

subarkose) are distinguished on Fig. 1A by their generally 

low log (SiO2/Al2O3 ) of < 1.5. Log (SiO^AhOs) values 

of < 1.3 are common for subarkose and values <1.0 are 

common for arkose. A log (SiO2/Al2O3) value of 1.3 

corresponds to a mixture of 75 pet quartz and 25 pet alkali 

(sodic or potassic) feldspar; a log value of 0.95 

corresponds to a mixture of 50 pet quartz and 50 pet alkali 

feldspar. Generally, any rock containing 25 pet or more 

feldspar is considered an arkose, and rocks with 25 pet 

total feldspar and rock fragments (of which half is 

feldspar) have been called subarkose (Pettijohn, 1975). 

All arkoses in the reference set except one have more K2O 

than Na2O, and thus plot to the right of the line log (K2O/ 

Na2O) = 0. Values of log ((FeTO3+MgO)/(K2O+Na2O)) 

are generally about 0 or negative (Fig. IB), reflecting the 

general paucity of ferromagnesian minerals in arkose. 

Arkoses are discriminated well on the scattergram log
\

EXPLANATION 

Quartz arenite 

Graywacke 

Arkose 

Lithic arenite 

Protoquartzite 

Class average

^

\

Figure 3 Rotated three-dimensional 

scattergram of log (SiCVAhOa) vs log 

(K2O/Na2O) vs log ((FeTO3+MgO)/ 

(K2O+Na2O)) for representative sandstones 

(data from Pettijohn, 1963; 1975); individual 

samples are connected to the centroid of 

sample distribution to show sample clusters. 

Sample numbers are identified in Table 1.

(FeTO3/K2O) vs log (SiO2/Al2O3) of Herron (1988). 

Subarkoses (nos. 35, 36, and 37 on Fig. 2A) are wellseparated from arkoses. Most arkoses plot to the right of 

the Na2O=K2O line and below the field of ferromagnesian 

potassic sandstone in the triangle diagram of Blatt and 

others (1972) (Fig. 2B).

One sample, of "Portland Stone" from the Hartford 

basin of Connecticut, plots outside the usual arkose field 

(no. 34, Figs. 1 A,C and 2B) because it has more Na2O 

than K2O. Recent research has shown that arkoses of the 

Hartford basin, including the Jurassic Portland Formation, 

have more detrital plagioclase (mostly oligoclase) than 

potassium feldspar, and they also have an average 6 pet by 

volume albite cement (Hubert and others, 1992). The 

sample is properly classified in Herron's (1988) diagram 

(Fig. 2A), but its sodic composition is not evident.

The class of sandstones called "lithic arenites" or 

"subgraywackes," which contains more rock fragments 

than feldspar detritus, is not readily isolated in any of the 

diagrams compared here. The lithic arenites are a diverse 

and poorly defined class (Pettijohn, 1963). In addition to 

abundant rock fragments of widely varying composition, 

many of these sandstones contain clay matrix, and the 

composition of clay varies. In the scattergram of log 

(SiCVAhOs) vs log (K2O/Na2O), the field of lithic 

arenites tends to overlap that of graywackes and arkoses, 

although in general the log of (SiCVA^Os) is slightly 

greater for lithic arenites than for graywackes and arkoses 

(Fig. 1A). Log ((FeT03+MgO)/(K20+Na20)) vs log 

(K2O/Na2O) (Fig. IB) discriminates between lithic 

arenites and arkoses but not graywackes. Herron's (1988) 

diagram of log (Pe-rOs/E^O) vs log (SiCVAhOs) provides 

slightly better discrimination than Figs. 1A and IB; five of 

eight lithic arenites plot within the fields for litharenite and

sublitharenite (Fig. 2A). However, the average litharenite 

of Pettijohn (1963) falls slightly outside the field of lithic 

arenites, and not near the center of the distribution of other 

lithic arenites (Fig. 2A). On the triangle diagram of Blatt 

and others (1972), lithic arenites tend to plot in or near the 

potassic ferromagesian sandstone field, but discrimination 

is poor (Fig. 2B). Probably, lithic arenites cannot be 

identified reliably by chemical classification, even in the 

diagram of Herron (1988). This situation is not surprising, 

given that many rock fragments of lithic sandstones would 

be expected to vary greatly in composition.

The reference set of lithic arenites contains one 

sample (no. 17) with high CO2 and MgO, indicative of 

dolomite cement. High MgO causes sample 17 to plot in 

an outlying position in the scattergram log ((FejOs+MgO)/ 

(K2O+Na2O)) vs log (K2O/Na2O) (Fig. IB) and in the 

trinagular diagram Na2O-K2O-(FeTO3+MgO) (Fig. 2B). 

The position of this sample is not affected by high MgO in 

the scatterplots log (SiO^AhOa) vs log (K2O/Na2O) (Fig. 

1A) and log (Fe-iO3/K2O) vs log (SiO2/Al2O3) (Fig. 2A). 

Such sandstones can be readily identified and, if desired, 

removed from a sample set by searching for high CO2 (or 

LOI, loss on ignition) and MgO values.

Arenites intermediate in composition between quartz 

arenites and lithic arenites (or arkoses) are sometimes 

called "protoquartzites." Protoquartzites are tabulated with 

both orthoquartzites and lithic arenites by Pettijohn (1963). 

They have less quartz than quartz arenites and generally 

about 90 pet SiO2, with log (SiO^AhOa) < 1.5. Two 

examples of protoquartzites are the Jurassic Salt Wash 

Formation and the Mississippian Berea Sandstone (nos. 11 

and 15, respectively, in Figs. 1C,D and 2). Herron (1988) 

reclassified the sample of Berea as subarkose, but both the 

mineral and chemical composition are so close to quartz

8
arenite that classification as subarkose vs sublitharenite is 

problematic. The protoquartzites are here grouped with 

lithic arenites. It seems likely that no chemical 

classification system would be capable of separating 

protoquartzites from other sandstone classes.

Based on study of the reference set, the following 

guidelines are proposed for chemical classification of 

sandstones:

1) quartz arenite: log (SiO2/Al2O3) > 1.5

2) graywacke: log (SiO2/Al2O3 ) < 1 and log (K2O/Na2O) 

<0

3) arkose (includes subarkose): log (SiO2/Al2Os) < 1.5 

and log (K2O/Na2O) > 0 and log ((Fe-rO3+MgO)/ 

(K2O+Na2O)) < 0

4) lithic arenite (subgraywacke, includes protoquartzite): 

log (SiO^A^Os) < 1.5 and either log (K2O/Na20) < 0 

21 log ((Fe-r03+MgO)/(K20+Na20)) > 0. If log 

(K20/Na2O) < 0, lithic arenite can be confused with 

graywacke.

Guidelines for chemical classification may also be 

expressed as fields drawn around the distribution of 

representative sandstones on the various diagrams (Figs. 

1A,B and 2). However, these fields are more restrictive 

than the general guidelines offered here, and are based on 

the very limited number of samples in the reference set. 

Alternatively, sandstones can be classified using the 

systems of Herron (1988) or Blatt and others (1972). 

None of the chemical criteria or chemical classification 

systems employed here can be used to identify 

petrographic class with certainty; their use in tandem 

offers the best hope of assigning a rock name to an 

analyzed sample.

A final experiment was conducted to see if all three 

axes, log (SiCVAhOs), log (K2O/Na2O), and log 

((FeTO3+MgO)/(K2O+Na2O)), could be used together to 

represent the major sandstone classes in three-dimensional 

space (Fig. 3). The three-dimensional scattergram was 

rotated for optimum separation of the four classes of 

sandstones, and rays were constructed from the centroid of 

all sample positions to the individual sample points. 

Although sample clusters in three-dimensional 

scattergrams are best visualized by spinning the axes to 

view a variety of perspectives, the clustering of samples is 

reasonably evident on certain projections in twodimensional space (Fig. 3). Quartz arenites, arkoses, and 

graywackes plot in coherant clusters; lithic arenites cluster 

weakly, adjacent to graywackes, but some samples are 

indistinguishable from graywacke. The two 

protoquartzites of Pettijohn (1963), numbers 11 and 15, do 

not plot with other lithic arenites. Number 11 (Salt Wash 

Formation), plots between the cluster of quartz arenites 

and arkoses; number 15 (Berea Sandstone) most resembles 

the quartz arenites. The sodic arkose, number 34 

("Portland Stone"), plots between the other arkoses and the 

graywacke cluster. The three-dimensional method does

not successfully isolate lithic arenites, but it does isolate 

the other major classes of sandstones, and it is useful in 

establishing relationships of aberrant compositions, such 

as individual protoquartzites and sodic arkoses, to the 

major classes.

IGNEOUS SOURCES

The presence of igneous detritus in sandstones can 

sometimes be identified from major oxide composition. 

Scattergrams of average igneous rocks (Fig. 4) define the 

expected compositional range of unrecycled igneous 

material in sandstones. In scattergrams of major oxide 

ratios in igneous rocks, the well-known covariation among 

SiO2, alkali oxides, iron oxides, and magnesia that is 

generally accepted to represent magma differentiation is 

evident. In tuffaceous sandstones, the sedimentary 

processes of reworking, weathering, and mixing with nonigneous detritus are reflected by departure from the 

compositional range of igneous rocks. As will be 

illustrated, the diagrams (Fig. 4) can be used to locate the 

probable composition and identity of the igneous endmember in a mixing series involving an igneous source.

A simple example of mixing igneous detritus in lithic 

sandstones illustrates the effect on the chemical 

composition of sandstone, and the relative utility of the 

various diagrams in portraying the effects of mixing (Fig. 

5). The fluvial Upper Cretaceous Harebell Formation of 

northwestern Wyoming contains sandstones ranging from 

reworked, nearly pure crystal tuff to lithic arenite and 

wacke with only minor amounts of volcanic detritus 

(Lindsey, 1972). Tuffaceous sandstones in the Harebell 

contain abundant volcanic quartz, a few pet potassium 

feldspar, abundant plagioclase (> 10 pet, typically > 20 

pet), volcanic rock fragments, and biotite. Nontuffaceous 

sandstones contain abundant quartz with undulose 

extinction, only a few (< 10) pet feldspar, and both 

muscovite and biotite. Even in nontuffaceous sandstone, 

plagioclase is typically more abundant than potassium 

feldspar, suggesting minor mixing of tuffaceous detritus. 

Both sandstone classes contain as much as 28 pet 

nonvolcanic lithic fragments (mostly altered grains, 

quartzite, and chert) and both classes contain abundant 

clay matrix (20 pet is common). Chemical analyses of the 

most tuffaceous sandstones compare closely to andesite 

and diorite (compare Figs. 4 and 5). Chemically, 

nonruffaceous sandstones vary widely, but most plot in or 

near the litharenite field of Herron (1988) (Fig. 5C).

Alumina and soda contents are highest in tuffaceous 

Harebell sandstones. For tuffaceous sandstones, log (K20/ 

Na2O) is < 0; for nontuffaceous sandstones, > 0. For log 

(SiO^AhOa) vs log (K2O/Na2O), both tuffaceous and 

nontuffaceous sandstones plot on a mixing line (Fig. 5A) 

that reflects varying amounts of plagioclase. In contrast, 

scattergrams of log ((FeTO3+MgO)/(Na2O+K2O)) vs log 

(K2O/Na2O) (Fig. 5B) and log (FeTO3/K2O) vs log (SiCty 

Al2Oa) (Fig. 5C) do not show the mixing line. Probably, 

any linear mixing trend has been disturbed by reworking
-.5 0 .5 1 

Log (K20/Na20)

CO

O

C\J IC\J

O

CO

CO

o

.5

4X enlargment of A

* A

 x

A - 

T^ ^ o> ^°*

o

n *

«D 

BT

O c\j

6 -5

C\J

% 0

CO

o

B

-1

-1 -.5 0 .5 

Log (K20/Na20)

Log (K20/Na20)

EXPLANATION

O

D

O

*

Syenite

Trachyte

Granite

Rhyolite

Adamellite

A

O

D

El

Tonalite

Diorite

Andesite

Monzonite

Latite

X Granodiorite V Gabbro

A Rhyodacite 

 Dacite

Diabase 

Basalt

o

C\J

CO

O

CD 

O

-1

.5 1 

Log (SJ02/AAI203)

FeTOS + MgO

K20

Figure 4. Scattergrams showing composition of common average igneous rocks (data from Le Maitre, 1976): A) log 

(SiO2/Al2O3) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/(K2O+Na2O)) vs log (K2O/Na2O), C) log (FeTO3/K2O) vs log 

), and D) triangular scattergram Na2O-K2O-(FeTO3+MgO).

10
CO

O r\j

1.5

LU 

CO

8

X

o

CO

D)

o

DbQ_

- 5

-1 -.5 0 .5 

Log (K20/Na20)

-1

B

.5 0 .5 

Log (K20/Na20)

D

-1 -.5 0 .5 

Log (K20/Na20)

FeT03+MgO

EXPLANATION 

O Non-tuffaceous 

X Tuffaceous

Ferromagnesi an 

Potassic Sandstones

Na20 K20

Log SI02/AI203

Figure 5. Scattergrams showing composition of tuffaceous and nontuffaceous sandstones in the Harebell Formation 

(data from Lindsey, 1972): A) log (SiO2/Al2O3) vs log (K2O/Na2O), B) log ((Fe-rO3+MgO)/(K2O+Na2O)) vs log (K2O/ 

Na2O), C) log (FeTO3/K2O) vs log (SiO^AhOs), D) log pet plagioclase vs log (SiO^AhOs), and E) triangular 

scattergram Na2O-K2O-(Fe-rO3+MgO). Classification systems in (C) and (E) from Herron (1988) and Blatt and others 

(1972), respectively.

11
and local concentration of iron oxide minerals. A 

scattergram of log pet plagioclase vs log (KiO/NaiO) 

confirms the relationship between this mineral and major 

oxide ratios (Fig. 5D). On the triangular diagram of Blatt 

and others (1972), tuffaceous sandstones are discriminated 

from nontuffaceous sandstones of the Harebell Formation, 

but the mixing trend is not evident (Fig. 5E).

COMPOSITION RANGE OF GRAYWACKES

Gray wackes represent some of the most 

compositionally and texturally immature sandstones, in 

that many of them were deposited in tectonically active 

plate boundary settings where erosion and sedimentation is 

relatively rapid. Extensive data on average graywacke 

compositions have been compiled and classified according 

to plate margin setting and compared with average modern 

marine sands and average composition of the major classes 

of sandstone (Bhatia, 1983, tabs. 5-8). These data reveal a 

compositional range that reflects chemical variation in 

provenance, ranging from igneous to sedimentary source 

rocks and mixtures of the two. The compositional range is 

correlated with four plate boundary settings: 1) oceanic 

island arc (= modern fore arc), 2) continental island arc (= 

modern back arc), 3) active continental margin (= modern 

leading edge), and 4) passive margin (= modern trailing 

edge).

Bhatia's (1983) average compositions for graywackes 

in various plate boundary settings are plotted here to 

portray the compositional range of graywackes compared 

to other sandstones (Figs. 6A,B). The field of Bhatia's 

graywackes compares well with the working definition of 

graywacke composition established from Pettijohn's 

(1963) reference data set, except that graywackes from 

passive continental margin settings may chemically 

resemble arkose and lithic arenite. Among graywackes 

and modern sands, log (SiO2/Al2O3) and log (K2O/Na2O) 

increase and log ((Fe-rO3+MgO)/(Na2O+K2O)) decreases 

slightly from oceanic island arc to passive margin tectonic 

settings.

When the compositional fields of Herron (1988) are 

overlaid on the scattergram log (FeyOyK^O) vs log (SiO2/ 

A12O3) (Fig. 6C), they fall far short of classifying 

graywackes correctly. Only six of 22 graywackes are 

correctly assigned to the wacke (graywacke) field of 

Herron (1988). Graywackes from continental island arc 

and active continental margin environments overlap the 

wacke field, but graywackes from oceanic island arc and 

passive margin environments fall mostly outside the wacke 

field. Misclassification may result not only from the 

choice of oxide ratios, which excludes Na2O, but from the 

choice of field boundaries and rock names. In contrast, the 

triangular diagram Na2O-K2O-(FeTO3+MgO) (Fig. 6D) 

discriminates most graywackes, except those from passive 

margins, from other sandstone classes. Comparison of 

Figs. 6A,B and D with C illustrates the utility of K2O/ 

Na2O for distinguishing graywackes from other classes of 

sandstone.

The scattergram log (FeTO3/K2O) vs log (SiO2/Al2O3 ) 

(Fig. 6C) discriminates graywackes in some tectonic 

environments, particularly oceanic island arc, which is 

located in the field labeled "Fe-shale." Although "Feshale" is a misnomer for oceanic island arc graywackes, 

the clear separation from other tectonic environments 

suggests that scattergrams of log (Fe-rOa/K^O) vs log 

(SiO2/Al2O3 ) may be useful in identifying oceanic island 

arc graywackes. For example, the two Archean 

graywackes of Pettijohn (1963; 1975) may represent 

oceanic island arc deposits (compare samples 19 and 20 in 

Fig. 2A with the field of OIA in Fig. 6C).

Log values of SiO2/Al2O3 and K^O/Na^O for island 

arc and active continental margin graywackes are 

comparable to those for common igneous rocks in the 

series basalt-rhyolite (Fig. 4A, averages from Le Maitre, 

1976), but variation in the log of (Fe-rOs+MgO)/ 

(K2O+Na2O) is less pronounced in graywackes, falling 

only within the range of intermediate igneous rocks 

(andesite - adamellite) (Fig. 4B). Thus the chemical 

composition of most graywackes deposited in active 

tectonic environments resembles that of their source rocks. 

In the passive margin (modern trailing edge) environment, 

high log (SiO2/Al2O3 ) and log (K2O/Na2O) values for 

graywackes reflect prolonged or multiple cycles of 

weathering and transport in the sedimentary mill as well as 

continental sedimentary and granitic sources. The 

composition of graywackes deposited in passive margin 

environments is comparable to that of arkose and lithic 

arenite, suggesting that these graywackes cannot be 

discriminated from other classes of sandstone by chemical 

means.

Soda metasomatism during diagenesis may have 

affected the composition of some graywackes. The fields 

for passive margin graywackes would be restricted to the 

K2O>Na2O side of scattergrams were it not for the 

Ordovician Charny Sandstone of Quebec (Fig. 6A,B). 

Soda equals or exceeds K2O in the Charny because detrital 

potassium feldspar has been replaced by albite (Middleton, 

1972). Albitization of feldspar has also been reported for 

Devonian graywackes in Europe, but chemical changes are 

thought to have been minimal (Floyd and others, 1991). 

Overall, the ratio of K^O to Na2O for most graywackes 

compared to their probable source rocks (compare Figs. 6 

and 4) does not reveal the enrichment of Na2O that might 

be expected if diagenetic replacement of potassium 

feldspar by sodium feldspar was widespread.

COMPOSITION OF ROCKY MOUNTAIN EOCENE 

ARKOSES

Arkose is well-represented in Laramide foreland 

basins of the Rocky Mountains. Sand and gravel, 

deposited by alluvial fans and braided to meandering 

streams, accumulated around basin margins (e.g., Roehler, 

1993). The western sides of foreland basins immediately 

adjacent to the Rocky Mountain Cordilleran thrustbelt 

were filled with quartz and lithic detritus eroded from

12
-.5 0 .5 

Log (K20/Na20)

O

CM

on 

O

O)

o

-1 -.5 0 .5 1 

B Log (K20/Na20)

	EXPLANATION

 Oceanic Island Arc (OIA) Graywacke

 Continental Island Arc (CIA) Graywacke

a Active Continental Margin (ACM) Graywacke

^ Passive Margin (PM) Graywacke

* Modern Fore-arc Sand

« Modern Back-arc Sand

a Modern Leading Edge Sand

* Modern Trailing Edge Sand

a Average Graywacke

^ Average Arkose

o Average Lithic Arenite

O Average Quartz Arenite

D

.5 1 

Log (SJ02/AI203)

1.5

FeT03+MgO

Ferromagnesian 

Potassic Sandstone

Charny 

Sandstone

Na20 K20

Figure 6. Scattergrams showing composition of 

graywackes and modern marine sands, classified according 

to plate boundary setting (data from Bhatia, 1983): A) log 

(SiO2/Al2O3) vs log (K2O/Na2O), B) log ((FeTO3+MgO)/ 

(K2O+Na2O)) vs log (K2O/Na2O), C) log (Fe-rO3/K2O) vs 

log (SiO2/Al2O3), and D) triangular scattergram Na2OK2O-(FeTO3+MgO). Classification systems in (C) and (D) 

from Herron (1988) and Blatt and others (1972), 

respectively.

13
thrusted sedimentary rocks, but inland from the thrustbelt, 

foreland basins on the craton were filled with arkosic 

detritus from adjacent basement-cored uplifts. The 

foreland basins on the craton were yoked to adjacent 

uplifts along thrust and reverse faults that penetrated the 

basement. These basins subsided from Late Cretaceous to 

middle Eocene time, concurrently with development of the 

thrustbelt (Dickinson and others, 1988).

The mineral and chemical composition of 216 

samples of lower Eocene fluvial sandstone from 36 

localities in the foreland basins was reported by Vine and 

Tourtelot (1973). These samples represent sandstones 

derived from sedimentary rocks of the thrustbelt (west 

sides of the Green River and Uinta basins) and igneous 

and metamorphic rocks of basement-cored uplifts (all 

other basins). Their composition was examined here to 

test chemical criteria for distinguishing arkose and to 

explore the compositional range of arkose.

Each locality is represented by six samples, which 

were analyzed for mineralogy, major oxides, and trace 

elements. Average (geometric mean) values were 

calculated to summarize the data for each locality (Vine 

and Tourtelot, 1973, tab. 7). The mineral content of 

sandstone at each locality, determined by X-ray 

diffraction, was plotted on a quartz-carbonate-feldspar 

triangular diagram (Vine and Tourtelot, 1973, fig. 3), 

permitting sandstones at each locality to be classified as 

quartzose (<10 pet feldspar), subarkose (10-25 pet 

feldspar), and arkose (>25 pet feldspar). Absent modal 

analyses of thin sections, lithic arenite cannot be 

distinguished with confidence. Reliance on X-ray 

diffraction instead of microscopic modal analysis prevents 

further resolution of quartzose sandstones into 

petrographic classes, but the X-ray data are excellent for 

identifying arkosic sandstones.

Major oxide ratios for the Eocene sandstone localities 

show good agreement with the X-ray mineralogical 

classification of locality averages (Fig. 7A,B). Most 

arkose (>25 pet feldspar) and subarkose (10-25 pet 

feldspar) localities plot near the arkose field defined from 

Pettijohn's (1963,1975) tabulated analyses (compare Figs. 

1A,B with 7A,B). However, Eocene arkoses have a 

broader compositional range than the arkoses tabulated by 

Pettijohn, especially for log ((FeTO3+MgO)/(Na2O+K2O)) 

vs log (K2O/Na2O) (Fig. 7B). Probably, the compositional 

range of Pettijohn's tabulated arkoses is too small; his list 

includes only nine examples, plus one sodic arkose (Fig. 1, 

Table 1). The guidelines proposed at the end of the section 

on classification extend the compositional range of arkose. 

An experiment using all three axes log (SiCVA^Os), log 

(K2O/Na2O), and log ((FeTO3+MgO)/(Na2O+K2O)) to 

examine sample clusters in three-dimensional space, 

yielded little information beyond that gleaned from Fig. 7.

Major oxide ratios show that sandstone at several 

localities (1 and 18), classified as quartzose using X-ray 

diffraction data, appears to be clay- or feldspar-rich; thinsection descriptions and X-ray data indicate that samples

at both localities contain kaolinite and mica in addition to 

potassium feldspar. Locality 2, identified as having the 

most quartz by Vine and Tourtelot (1973), appears 

properly classified by major oxide ratios, but the ratios 

show that the most mature (silica-rich) sandstones occur at 

localities 29 and 31, both located near the thrustbelt in the 

Green River and Uinta basins, respectively. Average log 

(SiCVA^Os) values for these two localities are the only 

ones that fall within the quartz arenite range defined from 

Pettijohn's (1963, 1975) reference data set (compare Figs. 

1A and 7A). Sandstones near the overthrust belt are likely 

to contain abundant recycled quartz and chert from 

thrusted sedimentary rock instead of first-cycle feldspar 

from uplifts of Precambrian igneous and metamorphic 

rock.

Sandstones at five localities near the Granite 

Mountains of Wyoming are among the most feldspathic in 

the Rocky Mountain Eocene, in that they tend to have the 

lowest values of log (SiCVAhOs) and log ((Fe-rOs+MgO)/ 

(NazO+KzO)) (Fig. 7A,B). These localities are among 

those identified by Vine and Tourtelot (1973) as containing 

abundant arkose. The Granite Mountains uplift consists 

mainly of Precambrian granitic rock and is the likely 

source of arkose at localities nearby (Love, 1970).

Two localities (20 and 24) having sodic arkose are 

identified (Figs. 7A,B). Locality 20, at West Spanish Peak 

in the Raton Basin, represents metamorphosed sandstone 

enriched in secondary prehnite, laumontite, and 

plagioclase (Utada and Vine, 1984). Before 

metamorphism by heat and fluids from the Spanish Peaks 

intrusions, the arkose at locality 20 was probably similar in 

composition to the potassic arkose of Huerfano Park 

(locality 19). The origin of the sodic arkose at locality 24, 

in the San Juan Basin, is unknown to me; arkose at locality 

24 contains a large amount of plagioclase as well as 

potassium feldspar (Vine and Tourtelot, 1973, tab. 7).

In the classification system of Herron (1988), relying 

on log (Fe-rOa/KzO) vs log (SiCVAlzOs), all but one of the 

arkose localities falls in the field for arkose (Fig. 1C). 

However, thirteen localities characterized as subarkose by 

X-ray mineralogy are variously classified as litharenite (5), 

arkose (5), subarkose (2), and sublitharenite (1). None of 

the quartzose sandstones plot in the quartz arenite field of 

Herron (1988). The ten localities having quartzose 

sandstone defined by X-ray mineralogy are classified as 

sublitharenite (5), subarkose (3), litharenite (1) and wacke 

(1). The most quartz-rich sandstones noted by Vine and 

Tourtelot (1973) (nos. 1 and 2) are classified as litharenite 

and sublitharenite, respectively. The most quartzose 

sandstones defined by log (SiO^A^Os) (nos. 29 and 31) 

are classified as sublitharenite and subarkose. Sodic 

arkoses (nos. 20 and 24) are not separately distinguished. 

The sodic arkose of West Spanish Peak (no. 20) is 

misclassified as litharenite, albeit it is the only arkose 

misclassified by the system of Herron (1988).

On the triangle diagram of Blatt and others (1972) 

(Fig. 7D), the potassic arkoses at localities surrounding the

14
1.5

CO

O

CM

CM 

O 

CO

B

0

FeT03+MgO

Ferromagnesian 

Potassic sandstones

-1 -.5 0 .5 1 1.5 

A Log (K20/Na20)

Na20 

D

o 

A

K20

EXPLANATION

Quartzose sandstone (< 10 pet feldspar) 

Subarkose (10-25 pet feldspar) 

Arkose (> 25 pet feldspar)

Arkose (> 25 pet feldspar) 

near Granite Mountains

-.5 0 .5 1 

Log (K20/Na20)

1.5

Figure 7. Scattergrams showing 

average composition of Eocene 

sandstones at 36 localities in Rocky 

Mountain foreland basins, western 

United States (data from Vine and 

Tourtelot, 1973): A) log (SiO2/ 

A12O3) vs log (K2O/Na2O), B) log 

((FeTO3+MgO)/(K2O+Na2O)) vs 

log (K2O/Na2O), C) log (FeTO3/ 

K2O) vs log (SiO2/Al2O3 ), and D) 

triangular scattergram Na2O-K2O- 

(FexO3+MgO). Classification 

systems in (C) and (D) from Herron 

(1988) and Blatt and others (1972), 

respectively. Localities are 

classified using mineral 

composition data of Vine and 

Tourtelot (1973, fig. 3). Numbered

localities are from Vine and Tourtelot (1973, tab. 1) and located therein: 1, Enos Creek, Bighorn Basin, Wyoming; 2, 

Hillberry Rim, Bighorn Basin, Wyoming; 14, Hoback Basin, Wyoming; 18, Horse Creek-Crazy Woman Creek, Powder 

River Basin, Wyoming; 19, Huerfano Park, Raton Basin, Colorado; 20, West Spanish Peak, Raton Basin, Colorado; 24, 

Gobernador, San Juan Basin, New Mexico; 29, Salina, Wasatch Plateau, Utah; 31, Woodruff, Wasatch Range, Utah.

Log (SJ02/AI203)

15
Granite Mountains are plotted in a compact field closest to 

the KiO apex. The sodic arkoses of localities 20 and 24 

are readily separated from potassic arkose, and the 

difference in composition of the sodic arkose of West 

Spanish Peak (locality 20) and its probable potassic 

protolith (approximated by locality 19) is evident. The ten 

localities having quartzose sandstone were plotted on the 

triangle diagram for comparison even though eight of them 

contain average A^Oa values of < 5 pet. However, eight 

of ten quartzose sandstone localities have log (SiCV 

A^Oa) < 1.5, indicating that most quartzose sandstone is 

not chemical quartz arenite. The quartzose sandstone 

localities plot together in the field of ferromagnesian 

potassic sandstones. The tendency of quartzose sandstones 

to plot near the FejOa+MgO apex evidently reflects 

winnowing and concentration of heavy minerals as well as 

destruction of feldspar.

The set of Eocene sandstone analyses offers an 

opportunity to explore an alternative means of chemical 

classification, using trace elements instead of major 

oxides. Trace element values are commonly subject to 

cutoff at the lower limit of analytical detection so that, for 

computational purposes, values for samples falling below 

the limit must be arbitrarily set at a fraction of the limiting 

value. For the trace elements Co and Ga, discussed below, 

the lower limits of detection were 8 and 10 ppm, 

respectively. For averaging values at localities, 2 ppm was 

substituted for <8 ppm Co and 5 ppm was substituted for 

<10 ppm Ga (Vine and Tourtelot, 1973, tab. 6).

Among locality averages for Eocene sandstones, trace 

elements showing a high correlation with log (SiCVA^Oa) 

are Ba and Ga, with log Ga having the highest (negative) 

correlation of -0.86 (Fig. 8A). Gallium may be expected 

to substitute for Al in feldspar, and thus reflects feldspar 

content. Trace elements showing a high correlation with 

log ((FeTO3+MgO)/(K2O+Na2O)) are Co, Cr, and Ni, with 

log Co showing the highest (0.61) correlation (Fig. 8B). 

Cobalt (as well as other heavy metals) occurs in magnetite 

and ilmenite, as can be verified by spectrographic analysis 

of magnetic concentrates (Levering and Hedal, 1987). 

Absent grains of mineralized or mafic rock, Co reflects the 

abundance of magnetite and ilmenite. No trace elements 

are highly correlated with log (K2O/Na2O). Log Ga and 

log Co were selected as proxies for log (SiCVA^Oa) and 

log ((FeTO3+MgO)/(K2O+Na2O)), respectively, to test 

classification by trace element content.

A scattergram of log Co vs log Ga identifies arkosic 

Eocene sandstone localities effectively (Fig. 9). As with 

diagrams of major oxide ratios, arkose localities plot 

slightly below and to the right of subarkose localities. 

Subarkose tends to plot close to the line separating arkosic 

sandstone from quartzose sandstone.

Both major-oxide and trace element scattergrams of 

Eocene sandstones reflect the high feldspar (especially 

potassium feldspar) and low iron oxide (probably, 

magnetite and ilmenite) content of arkose relative to 

quartzose sandstone. This relationship, seen also in major

ro 

O

B

1.5

§? 1

.5

.5

O .5 <\j

V

+ 

O

<\j

TO

-1

Log (SJ02/AI203) = 

2.T52- 1.164*LogGa

R = - 0.86

O

O

1 

Log Ga ppm

1.5

Log ((FeT03+MgO)/(Na20+K20)) 

-.683 + 1.011 * Log Co

R-0.61

.5 1 

Log Co ppm

1.5

Figure 8. Scattergrams showing correlations of A) log 

(SiO2/Al2O3) vs log Ga ppm and B) log ((Fe-rO3+MgO)/ 

(K2O+Na2O)) vs log Co ppm, average values for Eocene 

sandstones at 36 localities in Rocky Mountain foreland 

basins, western United States.

16
1.5

E

Q.

a 

o

en 

o

.5

P 36 LOCALITIES

Quartzose 

sandstone

Subarkose 

and arkose

.5 1 

Log Ga ppm

1.5

EXPLANATION

O Quartzose sandstone (< 10 pet feldspar) 

A Subarkose (10-25 pet feldspar) 

A Arkose (> 25 pet feldspar)

A Arkose (> 25 pet feldspar) 

near Granite Mountains

Figure 9. Scattergram of log Co ppm vs log Ga ppm, 

average values for Eocene sandstones at 36 localities in 

Rocky Mountain foreland basins, western United States 

(data from Vine and Tourtelot, 1973). Localities are 

classified as in fig. 7, using mineral composition data of 

Vine and Tourtelot (1973).

oxide ratios of Pettijohn's (1963; 1975) tabulated analyses 

of sandstones, can probably be applied in other cases to 

separate feldspathic sandstone from quartzose sandstone.

As a follow-up experiment, all 216 individual 

chemically analyzed samples of Rocky Mountain Eocene 

sandstones were sorted into three classes using the majoroxide guidelines proposed at the end of the section on 

classification. These guidelines were used because 

mineralogic classification of individual samples was not 

available. Eighteen Eocene sandstones have log (SiO2/ 

Al2Os) > 1.5 and are considered to be quartz arenites. 

Ninety sandstones have log (SiO2/Al2O3) < 1.5 and log 

(K2O/Na2O) > 0 and log ((FeTO3+MgO)/(K2O+Na2O)) < 

0; these are almost surely arkoses or subarkoses. The 

remaining 108 sandstones most resemble lithic arenites, 

having log (SiO2/Al2O3) < 1.5 and either log (K2O/Na20) 

< 0 or log ((FeTO3+MgO)/(K2O+Na2O)) > 0. Thirty-one 

of the samples classed as lithic arenites have log (K2O/ 

Na2O) < 0 and thus could be confused with graywackes.

16 lithic arenites 

2 arkoses and 

subarkoses

33 lithic arenites 

12 arkoses and 

subarkoses

1.5

E

Q.

a

o 

u 

en 

o

216 INDIVIDUAL 

SAMPLES

7 quartz 

arenites 

25 lithic 

arenites 

2 arkoses 

and

subarkoses

Limit of detection

.5 1 

Log Ga ppm

1.5

11 quartz arenites 

24 lithic arenites 

29 arkoses and 

subarkoses

10 lithic arenites 

45 arkoses and 

subarkoses

EXPLANATION 

O Quartz arenite 

A Arkose or subarkose 

O Lithic arenite

Figure 10. Scattergram of log Co ppm vs log Ga ppm 

for 216 samples of Eocene sandstone in Rocky Mountain 

foreland basins, western United States. Samples are 

classified using major oxide guidelines (see text). Samples 

plotted in lower left of diagram are below limit of 

analytical detection for both Co and Ga.

However, their continental fluvial depositional setting 

virtually rules out classification as true graywackes. Some 

of these sandstones may contain abundant clay matrix, 

however, and warrant the application of Gilbert's 

(Williams and others, 1954) term "wacke."

Finally, classification using only trace elements Co 

and Ga yielded a division of chemically defined quartz 

arenites from arkoses and subarkoses (Fig. 10), but no 

reliable identification of chemically defined lithic arenite. 

Only four arkoses and subarkoses defined by major oxide 

ratios were classified incorrectly as quartz arenite by log 

Co vs log Ga; 57 arkoses and subarkoses were classified 

correctly. No quartz arenites were misclassified. Lithic 

arenites defined by major oxide ratios were classified on 

both sides of the log Co vs log Ga line separating quartz 

arenites from arkoses and subarkoses. Thus, Co and Ga 

cannot be used to identify lithic arenites. Also, a large 

number (64) of samples have values below the limit of 

analytical detection for both Co and Ga, thus prohibiting

17
any classification. The failure to classify almost 30 pet of 

the samples emphasizes the importance of precision and 

low detection limits for classification by trace elements.

COMPOSITION OF MIDCONTINENT

PENNYSLVANIAN 

LITHIC ARENITES AND CLAY-RICH SANDSTONES

Quartz-clay sandstones that chemically resemble lithic 

arenites dominate Pennsylvanian sandstones of eastern 

Kansas, Missouri, and northeastern Oklahoma. They are 

discussed here to explore the chemical similarity of quartzclay mixtures and petrographically-defmed lithic arenites.

The Pennsylvanian Midcontinent sandstones were 

deposited in fluvial and coastal marine environments that 

developed during low sea level stands. During high sea 

level much of middle North America, north of the 

Ouachita orogenic belt, and from the Ancestral Rocky 

Mountains to the Appalachian orogenic belt, was covered 

by a vast epicontinental sea (McKee and Crosby, 1975). 

Most of the sandstones fill incised alluvial channels at the 

base of cyclic marine sequences of limestone and shale 

(Elias, 1964). The well-studied Bluejacket Sandstone 

Member of the Desmoinesian Boggy Formation records a 

southward-flowing incised stream in eastern Kansas that 

ends in a coastal delta in northeastern Oklahoma (Visher, 

in Shelton, 1973). Channels of the Tonganoxie Sandstone 

Member of the Virgilian Stranger Formation (not 

represented among the samples) likewise flowed 

southward into a delta in southeastern Kansas (Walton and 

Griffith, 1985). Although paleogeographic reconstructions 

for many of the sandstones are incomplete, most were 

probably derived from low-lying sources north of the 

Midcontinent Pennsylvanian sea or, like the channel 

sandstones of the Missourian Pleasanton Group (Elias, 

1964), from the locally emergent Ozark uplift.

A total of 32 sandstone samples were collected from 

four complete sections of the Pennsylvanian System in 

northwestern Missouri and northeastern Kansas (hereafter 

referenced as the "northern area") and in northeastern 

Oklahoma (hereafter referenced as the "southern area") 

(Connor and Ebens, 1980). The northern area is 

interpreted to represent mostly fluvial channel sandstones 

located nearest to their source; the southern area is 

interpreted to represent mostly fluvial deltaic sandstones, 

some of which have been reworked by marine currents. 

Each sample was analyzed for major and trace elements 

(Boerngen and others, 1975). Splits of seven samples 

were analyzed at the same time, so that the data set 

contains a total of 39 analyses. All 39 analyses were 

retained for the present investigation.

No modal analyses of the samples are available, but 

the normative mineralogy has been described as a mixture 

of quartz and clay (Connor and Ebens, 1980). Among the 

sandstones represented in this data set, those of the 

Virgilian Wabaunsee Group in Kansas (Mudge and 

Yochelson, 1962), the Virgilian Lawrence Shale in Kansas 

(Sanders, 1959), the Pleasanton Group (Singler, 1965), and

the Bluejacket Sandstone Member in northeastern 

Oklahoma (Shelton, 1973) are most commonly described 

as quartz-rich, silty or clayey, micaceous, and containing 

clasts of shale and limestone. Desmoinsian sandstones of 

northeastern Oklahoma (including the Bluejacket 

Sandstone Member, Senora Formation, and sandstones 

associated with the Labette Shale, all represented in the 

data set) are mostly quartz and lithic arenites (Dyman, 

1989). In the classification system of Blatt and others 

(1972), all analyses plot in or near the field of 

ferromagnesian potassic sandstones (Fig. 11D), 

comparable to lithic arenites (compare with Fig. 2B).

Major oxide ratios of the Pennsylvanian sandstones 

are consistent with classification as lithic arenite (Figs. 

11A,B). Although twelve analyses have < 5 pet AlzOi, 

most do not chemically resemble quartz arenite. Based on 

proposed guidelines for use of major oxide ratios to 

classify sandstones, five analyses are consistent with 

quartz arenites [log (SiO^A^Oa) > 1.5], four analyses are 

consistent with arkoses or subarkoses [log (SiOyA^Oa) < 

1.5 and log (K2O/Na2O) > 0 and log ((FeTO3+MgO)/ 

(K2O+Na2O)) < 0], and the remaining 30 analyses most 

resemble lithic arenites [log (SiOi/AhOa) < 1.5 and either 

log (K2O/Na20) < 0 or log ((FeTO3+MgO)/(K2O+Na2O)) 

> 0]. The lithic arenite classification probably results not 

so much from contained lithic grains as the effect of clay 

matrix and intraclasts on chemical composition.

Indications of major amounts of cement are limited to 

three analyses with abundant carbonate and three more 

with moderate carbonate; none are high in MgO 

(dolomitic). Thus inclusion of MgO in ratios should not 

present problems in classification or interpretation. One 

sample contains 11 pet Fe-rOa, probably as hematite 

cement.

The distribution of analyses in the classification 

system of Herron (1988) is noteworthy (Fig. 11C). Only 

18 of 39 analyses fall in the lithic arenite (litharenite and 

sublitharenite) field; most of the other analyses are in the 

fields of wackes and iron-rich sediments. While such 

classification may be explained by the chemical 

composition of these sandstones (for example, high FexOa 

vs K2O of some), it does not correspond to any plausible 

petrographic classification (e.g., Dyman, 1989).

All of the analyses of samples from the northern area 

(Kansas and Missouri) closely resemble one another 

chemically (Fig. 11A,B); they are best classified as 

chemical lithic arenites, or simply clay-rich sandstone. 

The origin of the clay is unknown; it may be detrital, 

diagenetic, or both. In contrast to sandstones of the 

northern area, sandstones from the southern area are 

chemically diverse; many have lower K2O/Na2O, others 

have higher K2O/Na2O, and still others are silica-rich 

quartz arenites. Chemical diversity is also apparent among 

southern sandstones of the Wabaunsee Group, which is 

present in both areas. The chemical diversity of 

Pennsylvanian sandstones in the southern area may reflect 

reworking and sorting by marine currents, variable

18
CO

O

£0 

< 

<\l

g

00

O)

3

1.5 -

1 -

.5 -

FeT03+MgO

-.5 0 .5 1 

Log (K20/Na20)

1.5

Sodic sandstones

Ferromagnesian 

Potassic sandstones

Potassic sandstones

O

^

 >

o .5

CO

o 0

O)

CO

H -.5

0)

u_

O) o _! 

; /

: s £(

: ss|P

TS <ji

: H

; Lithic arenite

"

/- y~

^ a 7^

S3 Sj

S^y

LS_yi(jL

^^

^, x s

H x s %s

/

X c o

Northern area

from Pettijohn

-1 _ 5 0

Na20 K20

D

EXPLANATION

o Bluejacket Sandstone

 Cabaniss Group

A Labette Shale

i:j Lansing Group

O Lawrence Shale

x Nellie Ely Formation

1 ' ' ' ' ' ' ' ' ' ' ' ' ' ' -f Oolagah Formation

.5 1 1.5 2

5 ' Log (K20/Na20) " " Canton Group

2 

S

V

CO

O

*

u_

O)

5 o

,

Fe-shale

'. w SB

/

/: /

Shale /

: ^/

i

A Senora Formation

* Silver Lake Shale

Litharenite / S^ I

Fe-sand s^ /

* AS ^JD S / Sx

\ BH 'fc /

-+ T <5>SS«fx^ ms S /

* / O + / S X S /

'sii^ s / Sublitharenite / w !

/ ^''^? / / -t1

/ / I Q}

Arkose / Subarkose / 

/ Is 1 .1°

& Wabaunsee Group

S Southern area

Figure 11. Scattergrams showing

composition of 39 analyses of

Pennsylvanian sandstones from

Kansas, Missouri, and Oklahoma (data

from Boerngen and others, 1975): A)

log (SiO2/Al2O3) vs log (K2O/Na2O),

B) log ((FeTO3+MgO)/(K20+Na20))

vs log (K2O/Na2O), C) log (FejOs/

K2O) vs log (SiO2/Al2O3 ), and D) 

triangular scattergram Na2O-K2O-

(Fe-rOs+MgO). Classification systems

in (C) and (D) from Herron (1988) and

Blatt and others (1972), respectively.

.5 1 1.5 

Log (SJ02/AI203)

Branson (1962). Northern and 

southern sampling areas are those of 

Connor and Ebens (1980).

19
B

EXPLANATION 

O Northern area

5 10 15 20 

PERCENT AI203

10 15 20 

PERCENT AI203

30

D

30

25

20

15

10

5

10 15 20 

PERCENT AI203

40 50 60 70 80 90 

PERCENT Si02

TOO

Figure 12. Variation scattergrams of 39 analyses of Pennyslvanian sandstones from Kansas, Missouri, and Oklahoma 

(data from Boerngen and others, 1975): A) K2O vs A12O3 , B) Na2O vs A12O3 , C) K2O+Na2O vs A12O3 , and D) A12O3 vs 

SiO2 . All values in weight percent, uncorrected for volatile components. Three samples with abundant calcite cement 

not plotted in (D). I, average illite (Weaver and Pollard, 1973, tab. I), M, mixed layer illite- smectite (68 pet illite, 

Newman and Brown, 1987, tab. 1-31, analysis 5). Solid lines show best fit by linear regression; two lines, separate fit 

for northern and southern areas; one line, areas combined. Dashed line in (D) is possible mixing line.

provenance (Dyman, 1989), or both. Redistribution of 

sand by marine currents has been inferred from 

reconstruction of the delta of the Bluejacket Sandstone 

Member (Shelton, 1973).

An experiment was conducted to see if the 

composition of the Midcontinent Pennsylvanian 

sandstones could be explained by quartz-clay mixing (Fig. 

12), following the method described by Argast and 

Donnelly (1987). Potash, Na2O, and K2O+Na2O are all 

highly correlated with A12O3 (Figs. 12A,B,C); fitted lines 

extend to the origin, suggesting that the content of these 

oxides could be explained by mixing two components. 

Alumina and SiO2 are also correlated (negatively), but less 

so (Fig. 12D). The composition of average illite is well 

above the line for K2O vs A12O3 (Fig. 12A), indicating that 

K2O content is too small to account for the observed 

covariation by mixing quartz and illite. The composition 

of mixed layer illite-smectite varies widely (e.g., Newman 

and Brown, 1987), but mixing with quartz allows Na2O as 

well as K2O to covary with A12O3 (Fig. 12B). If

K2O+Na2O is plotted against A12O3 , an illite-smectite clay 

composition can be found that will plot close to the mixing 

line (Fig. 12C). Mixing of feldspar, with K2O and Na2O 

that plot well above the mixing lines and off the diagrams 

in Figs. 12A,B, and C, cannot explain the observed welldefined correlations. Most of the Pennsylvanian 

sandstones of northeastern Oklahoma are feldspar-poor 

(Dyman, 1989). Thus, the chemical composition of 

Midcontinent Pennsylvanian sandstones is consistent with 

that obtained from mixing variable amounts of quartz and 

illite-smectite clay. Noncarbonate lithic fragments in the 

sandstones are likewise quartz (chert) and clay (shale), or 

mixtures of the two.

Normative mineral calculations (method of Cohen and 

Ward, 1991) suggest that mixtures composed principally of 

quartz, illite, and smectite (equivalent to quartz and illitesmectite) make up the mineral composition of 

Midcontinent Pennsylvanian sandstones. An analysis of 

sandstone from the Pleasanton Group, which is among 

those having low log (SiO^A^Os), and therefore most

20
likely to contain clay or feldspar (Fig. 11 A), was selected 

for normative mineral calculations. Using varying 

assumptions to allocate potassium to feldspar and illite, 

and Ca, Na, Fe, and Mg to smectite, the sandstone has a 

normative mineral content of about 50 weight pet quartz, 

0-8 pet potassium feldspar (8 pet is probably 

unrealistically high), 10-20 pet illite, possibly as much as 

two pet kaolinite, 20-30 pet smectite, and < 4 pet cement 

and accessory minerals.

CONCLUSIONS

The major classes of sandstones can be defined by 

their chemical composition, albeit with varying degrees of 

certainty ranging from high (for quartz arenite), moderate 

(for graywacke and arkose) to low (for lithic arenite). 

Scattergrams of major oxide ratios transformed to 

logarithms appear to be the most useful for separating 

sandstone classes. The ratios SiO^AhOs, K^O/NaiO, and 

(FeiO3+MgO)/(Na2O+K2O) reflect processes of sandstone 

formation and are amenable to process interpretation. 

Compositional fields can be defined on scattergrams, but 

are known with varying degrees of certainty for each class. 

General guidelines for classification, proposed in this 

report, offer a point of departure for classification and 

further study. Understanding how a population of 

sandstones acquired its chemical attributes can be 

enhanced by identifying mixing lines, formed when 

varying amounts of two or more minerals cause welldefined correlations among minerals and major oxides. 

Trace elements, notably gallium and cobalt, may also be 

used to classify sandstones, but considerable work remains 

to establish their reliability.

The various chemical classification systems compared 

here yield somewhat disparate results, but their use 

together can enhance the liklihood of correctly classifying 

individual sandstones. Disparate classification of 

individual sandstones is an indicator that further study is 

required to understand their true identity and origin. All 

classification systems and guidelines should be used with 

caution because of the complex effects of mineral content 

on bulk chemical composition.

Acknowledgements

This work relies heavily on the efforts of others, who 

painstakingly acquired and compiled chemical analyses of 

sandstones. Although they are cited in the text and 

references, I here acknowledge a special debt to J. D. Vine 

and E. B. Tourtelot, whose data set on Rocky Mountain 

Eocene sandstones was particularly useful in testing 

various approaches to the classification of arkosic 

sandstones, and J. J. Connor and R. J. Ebens, whose data 

set on Midcontinent Pennsylvanian sandstones provided an 

insightful example of the challenges posed in 

understanding the chemical composition of lithic arenites. 

Equally worthy of mention is the contribution of the many 

chemists of the U. S. Geological Survey who generated the 

above-mentioned data sets; they are listed in the

referenced data sources. I thank T. S. Dyman, U. S. 

Geological Survey, and M. M. Herron, Schlumberger-Doll 

Research, for comments on earlier versions of the 

manuscript. Finally, I make special mention of the late F. 

J. Pettijohn, who long ago encouraged my interest in 

sedimentary rocks, and whose work laid some of the 

foundation for chemical investigation of sandstones.

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