HR: 1340h
AN: H13D-1350    [Abstracts]
TI: Subsurface Heterogeneity Characterization using Random Cellular Automata
AU: * Schuttelaars, H M
EM: H.M.Schuttelaars@geo.uu.nl
AF: Environmental Hydrogeology Group, Utrecht University, P.O. Box 80021 , Utrecht, 3508 TA Netherlands
AU: Dekking, F M
EM: F.M.Dekking@EWI.TUDelft.NL
AF: Delft Institute for Applied Mathematics, Delft University of Technology, Mekelweg 4 , Delft, 2628 CD Netherlands
AB: It is well-known that geological formations exhibit significant spatial heterogeneity. This variability manifests itself at various scales. A precise description of the configuration (geometry), behaviour, and properties of various geological patterns in the underground is essential in many engineering fields (for a recent discussion on the importance of subsurface characterization, see de Marsily et al. [2005]). In this presentation, the subsurface heterogeneity is modelled using an extended version of the Coupled Markov Chain model of Elfeki and Dekking (2001). The resulting type of model is known as a Random Cellular Automaton. The rules of these cellular automata are based on the transition probabilities between the various lithographies obtained from boreholes observations. The rules can be adapted to include soft data.information as well The model properties will be discussed in both a one and two-dimensional setting. More specifically, the statistical characteristics such as the relative occurrence of a specific type of lithography will be discussed. As a next step, a comprehensive comparison of the results obtained using this-method, with those obtained from other methods and with field observations will be necessary.
DE: 0515 Cellular automata
DE: 1829 Groundwater hydrology
DE: 1869 Stochastic hydrology
DE: 3260 Inverse theory
SC: Hydrology [H]
MN: Fall Meeting 2005