Geology Reference
In-Depth Information
6.1.1 Grain-Size Analysis: Methods and
Aims
Phi
Carbonates
Grades
mm
very large
This chapter focuses primarily on some of the meth-
ods used in grain-size analysis and discusses possibili-
ties and problems related to evaluating of grain-size
patterns in the context of interpreting modern and an-
cient sedimentary environments.
2048
11
large
1024
10
Boulders
medium
512
9
small
256
8
large
128
7
Cobbles
small
64
6
6.1.1.1 Measuring Grain Sizes and Describing
Size Distributions
very coarse
32
5
coarse
16
4
Pebbles
medium
The size of siliciclastic grains is determined by sev-
eral techniques. Unconsolidated sediments and disin-
tegrated rocks of clay-, silt-, and sand-size ranges are
commonly measured by sieving or sedimentation meth-
ods (Coakley and Syvitski 1991; Matthews 1991). Mod-
ern carbonate sands have usually been measured by
sieving. Lithified sandstones and limestones require
thin-section measurements for silt- and sand-sized rocks
and electron microscopy for clay-sized samples. Im-
age analysis is a highly promising method for rapid
and accurate measuring of grain sizes, both of loose
grains and indurated sediments (Schäfer 1982; Kennedy
and Mazzullo 1991).
8
3
fine
4
2
Granules
Calcirudite
2
1
very coarse
1
0
m
coarse
500
1
medium
Sand
Calcarenite
250
2
fine
125
3
very fine
63
4
coarse
32
3
medium
16
6
Silt
Calcisiltite
fine
8
7
very fine
The interpretation of grain-size patterns requires graphi-
cal and mathematical treatment of the data. Common
graphic methods
for presenting grain-size data are his-
tograms, frequency curves and cumulative curves.
His-
tograms
are bar diagrams in which grain size is plotted
along the abscissa of the graph and individual weight
percent along the ordinate.
Frequency curves
result
from connecting the midpoints of each size class in the
histogram with a smooth curve.
Cumulative curves
are
grain-size curves generated by plotting grain size
against cumulative weight percent frequency. The
curves can be plotted on an arithmetic scale or on a log
probability scale in which the arithmetic ordinate is re-
placed by a log probability ordinate. The latter method
allows the important grain-size statistical parameters
to be calculated using the φ values read from the cu-
mulative curve for various percentiles (Tab. 6.1). Breaks
and discontinuities in cumulative curves produced by
plotting of grain sizes on a log probability scale are
interpreted as results of mixing of sediment popula-
tions related to different transport processes (Visher
1969).
4
8
coarse
2
9
medium
1
10
Clay
Micrite
fine
1/2
11
very fine
Fig. 6.1.
Wentworth-Udden grain-size scale and grain-size-
based terms used for differentiating of carbonate rocks.
Note
that the upper limit of micrite is often expanded and the size
range of calcisiltite is a matter of discussion (Sect. 4.1.1 and
4.1.4).
advisable to restrict the term to the millimeter- to cen-
timeter-sized range, and to call limestones consisting
of larger and large clasts breccia or conglomerate.
The term calcirudite and the term rudstone used in
limestone classifications are not identical (Sect. 8.3.2).
Both terms refer to carbonate rocks containing particles
> 2 mm, but calcirudite considers only grain size
whereas rudstone is defined by grain size and the num-
ber of grains larger than 2 mm. Note that calciruditic
limestones embrace rudstones as well as floatstones,
and that the term calcarenite covers grain sizes repre-
sented in grainstones and wackestones of the Dunham
classification.
Grain-size data can be plotted statistically, deriving
parameters
that allow average size and sorting of sedi-
mentary populations to be expressed mathematically:
