--> --> Geological Modeling Using Cellular Automata, by Tristan Salles, Simon Lopez, Marie-Christine Cacas, Didier Granjeon, and Thierry Mulder; #90052 (2006)

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Geological Modeling Using Cellular Automata

Tristan Salles1, Simon Lopez1, Marie-Christine Cacas1, Didier Granjeon1, and Thierry Mulder2
1 Institut Français du Pétrole, Rueil Malmaison Cedex, France
2 Université Bordeaux, Talence, France

Because of the long time scales involved in geological modeling, operational models can barely take into account detailed physical processes governing sedimentation. Diffusion-based approaches of sediment transport have already proved successful at the basin scale. Yet, they can reach their limits when smaller scales are considered where inertial effects may overcome purely gravitational components. A possible way to average physical processes over time is then to consider geological events as successive quasi steady states for which sediment transport has permanent values.

Nevertheless, finding such steady states from universal physics laws is not a simple matter. In a few situations, simplifying assumptions and tedious mathematical work can produce manageable models. Yet, on average, such efforts fail on instability properties such as shocks. Though they may have important physical meaning, those aspects are rarely important from the points of view of the overall geological succession of deposits or the sedimentary architecture.

The cellular automata paradigm can be an interesting approach to quickly obtain such stationary states at the expense of the mathematical rigor of classical physical models. Moreover, in its very conception, it is perfectly suited for object based programming and code parallelization enhancing model operational aspects. We propose to compare two numerical models of turbidity currents: one resorts to a classical finite volume approach while the other one uses a cellular automata approach. The first one can provide detailed understanding of processes whereas the second one infers geological deposits from a succession of steady states.