Grain Size Interpretation

Grain size is a fundamental physical property of sedimentary rocks, and as such it carries practical importance beyond mere description. Because the size and sorting of grains may reflect the sedimentation mechanisms and depositional conditions under which a deposit formed, grain-size data are widely assumed to be useful for inferring what ancient environments looked like. ^[1] The grain size of potential reservoir rocks is also of direct economic interest: coarse-grained, well-sorted sandstones make better oil reservoirs and groundwater aquifers than fine-grained, poorly sorted ones, because sorting and grain size together control porosity and permeability. ^[1]

The Environmental Interpretation Problem

The assumption that grain-size statistics reliably reveal depositional environments has driven an enormous body of research - hundreds of publications over more than a century, with particularly intense effort since the 1950s focused on statistical treatment of grain-size data. ^[1] The reasonable expectation was that this sustained effort would by now have firmly established the relationship between grain-size characteristics and depositional environments. That expectation has not been met. ^[1] Many methods have been proposed and tested, but little agreement has emerged about the reliability of any of them. ^[1]

Methods Attempted

Bivariate Statistical Plots

One approach plots one grain-size statistical parameter against another - for instance, skewness versus standard deviation, or mean size versus standard deviation - and attempts to show that sediments from different environments cluster into distinct, separable fields on the diagram. ^[1] The goal is to define fields on such plots that reliably correspond to specific environments - beach versus river, for example - so that an ancient sandstone could be assigned to an environment by where its statistical values plot. ^[1]

C-M and L-M Diagrams

A graphical approach uses what are called C-M and L-M diagrams, in which the coarsest grain diameter in a deposit (C) is plotted against either the median grain diameter (M) or the proportion finer than 0.031 mm (L). ^[1] The claim is that samples from a given depositional environment tend to cluster into a specific region of these diagrams, allowing environmental assignment from the diagram position of a sample. ^[1]

Log-Probability Curve Analysis

A third approach exploits the shape of grain-size cumulative curves plotted on log-probability paper. When plotted this way, many natural grain populations show two or three straight-line segments rather than a single straight line, and each segment is interpreted to represent a distinct subpopulation of grains that was transported simultaneously but by a different mode - suspension, saltation, or bedload. ^[1] Different environments - dune, fluvial, beach, tidal, nearshore, turbidite - are claimed to be distinguishable from each other based on the general shapes of the curves, the slopes of the individual segments, and the positions of the breaks in slope where one segment meets the next. ^[1]

Reliability and Limitations

Despite the volume of work behind these methods, all of them have been criticised for producing incorrect results in an unacceptably high proportion of cases, with this criticism applied to the bivariate plots, C-M diagrams, and log-probability curve analyses alike. ^[1] More sophisticated multivariate statistical approaches - including factor analysis, discriminant function analysis, and log-hyperbolic distribution fitting - have also been applied, though without fully resolving the fundamental difficulties. ^[1]

The underlying difficulty is not a failure of statistical technique but a genuine physical reality: the same grain-size distribution can be produced by more than one depositional process, and the same process operating under different conditions can produce different grain-size distributions. Grain size is an integrator of many variables - source material, transport distance, flow energy, grain shape - and unpicking the individual contributions of each from the final distribution alone is, in most cases, not possible with the certainty that practical geological application requires. Grain-size data remain useful for description and for broad qualitative guidance, but environmental interpretation based on grain-size statistics alone should be treated with considerable caution.

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