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PSGeological Modeling Using Cellular Automata*

By

Tristan Salles1,2, Simon Lopez1, Marie-Christine Cacas1, Didier Granjeon1, and Thierry Mulder2

 

Search and Discovery Article #40202 (2006)

Posted July 1, 2006

 

*Poster presentation at AAPG Annual Convention, Houston, Texas, April 9-12, 2006

 

Click to view posters in PDF format.

Poster 1 (0.4 mb)      Poster (0.5 mb)      Poster (0.6 mb)

  

1Institut Français du Pétrole, Rueil Malmaison Cedex, France ([email protected])

2Université Bordeaux, Talence, France

 

Abstract 

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.

 

Selected Figures

The upper Maastrichtian Pab turbidite system outcrop in the Kirthar fold belt in Western Pakistan (upper) and  its reconstruction (lower).

Upper Pab Dionisos simulation. Dionisos is a stratigraphic model developed by IFP and a consortium of companies.

Lower Pab Dionisos simulation.

Dionosis descriptions (mesh size 5 km), proximal to distal.

Interpreted deposits, with downstream evolution.

CA model results, with downstream evolution.