Abstract
Simulation studies of geologic phenomena with probabilistic models based on independent-events mechanisms, Markov processes, and Poisson processes, are increasingly common. Arbitrary selection of a given model because its simulation output resembles the system under study may be misleading or, at best, may shed only minimal light on the physical controls that actually determine the behavior of the system.
As in other sciences, stochastic process modeling in geology is a formal procedure that normally requires conceptualization of the process followed by identification and mathematical expression of the elements that control the process. This procedure (in which the conceptualization stage may be mainly qualitative) forces the geologist to be specific in his statements concerning the essential elements in his study and the relations among them. These elements then are combined in a “reasonable” probabilistic setting, which may have one or more deterministic controls.
The advantages of this formal sequence are that they normally lead to an initial model that is highly flexible and lends itself well to sequential modeling procedures. The steps involved are illustrated with examples from paleontology and sedimentation.
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Krumbein, W.C. (1976). Probabilistic Modeling in Geology. In: Merriam, D.F. (eds) Random Processes in Geology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-66146-4_4
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DOI: https://doi.org/10.1007/978-3-642-66146-4_4
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