John C. Tipper, 2011. "The Geometric Interrelationships of Outcrops and Rock Bodies: Setting Up and Testing Quantitative Hypotheses", Outcrops Revitalized: Tools, Techniques and Applications, Ole J. Martinsen, Andrew J. Pulham, Peter D.W. Haughton, Morgan D. Sullivan
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An outcrop’s geometry will always have an effect on how data from that outcrop are interpreted; therefore those data should be used only when the implications of that geometry have been taken fully into account. Problems inevitably arise whenever the geologist attempts to do this, the greatest of which stems from the uncertainty that necessarily exists in the position and orientation of the outcrop relative to the underlying rock body. This problem is best handled by means of a hypothesis-based approach for outcrop interpretation, for instance by using one of the three techniques outlined in this paper. The first of these techniques—the use of geometric probability arguments—is illustrated here in the context of recognizing clinoforms in outcrop. It is shown that clinoforms will rarely be seen as sigmoid-shaped curves on randomly positioned and randomly oriented outcrop faces; they are more likely to be seen as simple convex-up or concave-up curves. The second technique—the use of Monte Carlo methods—is illustrated in the context of interpreting dog-legged outcrops in flat-lying sedimentary successions. It is shown that the probability of failing to recognize simple features on the face of dog-legged outcrops can be high, and that this failure probability is highest for relatively long and sinuous outcrops with relatively many segments. This result conflicts totally with conventional geological wisdom. The third technique—the use of standard statistical tests—is illustrated by showing how isolated outcrops can be used to test correlation hypotheses in areas of broken exposure. The paper warns of the danger of conflating rock body and outcrop, then finally offers guidance on hypothesis selection.
Key words: stratigraphy, correlation, model, hypothesis, Monte Carlo