Inversion and Experimental Methods for Tomographic Investigations in Hydrogeology

Abstract:

The spatial variability of hydraulic conductivity K highly influences flow and solute transport in the subsurface. The estimation of the spatial distribution of K in heterogeneous aquifers with an adequate resolution and support scale is therefore one of the major challenges in hydrogeology and still seems to be unsolved. Even though direct measurements of K with modern methods reveal the distribution with typically high vertical resolutions, they still are scarce and local. Therefore, K is mostly inferred from measurements of quantities depending on K, such as hydraulic heads monitored during hydraulic tests and tracer test data. Conventional approaches, such as the type-curve approach for pumping tests, fail in estimating the spatial distribution of K, since they are based on the assumption of homogeneity. Even if data from multi-well pumping tests are analyzed, they always will yield different effective parameters. In contrast, tomographic techniques originally derived for geophysical surveying can be transferred to hydraulic applications and are much better suitable to derive K distributions. In this presentation, we will show results of the project “Tomographic Methods in Hydrogeology” in which we focused on the development of geostatistical methods for the inversion of tomographic data sets of different types (hydraulic testing, heat and ERT-monitoring of salt tracer tests) and the development and improvement of such experimental techniques. Based on selected examples we will present our developments related to the joint geostatistical inversion of tomographic data sets, its efficient parallelization, and its application to a 3D-inversion of tomographic thermal tracer tests. Related to the acquisition of tomographic data sets, we discuss different aspects of the field application of hydraulic tomography, the development of tracer-tomographic methods using heat as tracer, and efficient salt-tracer techniques with a ERT-based salt-tracer monitoring.