INTEGRATION OF GPR AND GEOLOGICAL DATA INTO THE STOCHASTIC DESCRIPTION OF AQUIFER PROPERTIES

A key issue of the research in the domain of hydrogeophysics is the integration of 2D or 3D structure information from Ground penetrating radar (GPR) in combination with geological data in the stochastic description of heterogeneous gravelly aquifers. To solve the difficulties of integration of subsurface heterogeneity and different type and quality of data into stochastic groundwater models would help stochastic modelling to be applied more frequently for the solution of practical problems.

Braided river deposits form important aquifers at many parts of the world. The heterogeneity of these deposits strongly influences groundwater flow and transport. A detailed understanding of fluvial processes in braided river environments, the knowledge of the preservation potential of depositional elements, and the development of techniques, which allow the integration of data of different quality into quantitative models, can aid characterization of gravelly fluvial aquifers. Recent research on facies analysis demonstrates the possibility of fully three-dimensional ground-penetrating radar (GPR or georadar) combined with outcrop analysis. Particular time slices (horizontal image surfaces) are used as a tool for determining the strikes of inclined layers and for depicting the connectivity and spatial relations of the main sedimentary structure types.

The objective oft his paper is:(1) to illustrate a sedimentological model characterizing heterogeneity including information from outcrops and modern river analogues, (2) to present a lithofacies-based interpretation of drill-core and georadar data, and (3) to give an example of a stochastic simulation of a portion of the Rhine / Wiese aquifer. The sedimentological model and the data interpretation method include the essential character of a particular aquifer system. They allow definition of depositional elements consisting of sedimentary structure and texture types, respect differences in data uncertainty, and provide probabilities of drill-core layer descriptions and radarfacies types representing defined sedimentary structure types. The stochastic simulation characterizes the spatial distribution of aquifer properties and can be used for groundwater flow and transport simulations.