Sedimentary formations that compose most aquifers are difficult to model as a result of the nature of their deposition. Their formation generally involves multiple processes (alluvial, glacial, lacustrine, etc.) that contribute to the complex organization of these deposits. Representative models can be obtained using process-based or rule-based methods. However, such methods have several drawbacks: complicated parametrization, large computing time, and challenging, if not impossible, conditioning. To address these problems, we propose a new hierarchical surface-based algorithm, named EROSim. First, a predefined number of stochastic surfaces are simulated in a given order (from older to younger). These surfaces are simulated independently but interact with each other through erosion rules. Each surface is either an erosive or a deposition surface. The deposition surfaces represent the boundaries of depositional events, whereas the erosive surfaces can remove parts of the previously simulated deposits. Finally, these surfaces delimit sedimentary regions that are filled with facies. The approach is quite simple, general, flexible, and can be conditioned to borehole data. The applicability of the method is illustrated using data from fluvio-glacial sedimentary deposits observed in the Bümberg quarry in Switzerland.

Nowadays, the centralization of subsurface-related observation is more and more common. Databases constituted of an ensemble of geophysical, hydrological, or borehole measurement forms a unique source of information for subsurface hydro-geological modeling. However, the increasing amount of data and the importance of being able to update the model when new data becomes available creates a huge need for automatic workflow for such data integration, hopefully reeling on open-source technology. Quaternary deposits are complex to model due to the high heterogeneity they present. Over the last 2.5 Ma, multiple cycles of glacial and inter-glacial phases deposited complex intertwining of sedimentary pattern, with high contrast in parameters (e.g. : permeability, porosity, nature of sediment) and space. Nevertheless, these deposits are some of the most extensively used for water resources, shallow geothermal exploitation, or construction material exploitation. In this study, we propose a new method based on a flipped stochastic joint inversion, and applied it on complex Quaternary deposits. Geophysical, boreholes and hydrological observations are inverted together. Boreholes are used to generate stochastic geological models, populated with parameters. The inversion tune the geological model in order to fit the field data. Our method allows not only to integrate boreholes, geophysical and hydrological data, but also conceptual models, with a robust uncertainty estimation. The method was applied on some areas of the Upper Aare Valley (Switzerland), a valley covered by more than 58’000 geophysical measurement points, 1’500 boreholes and 100 of hydrological observations. Our method showed promising results in combining these data. Comparison with existing geological models proves that our automated method not only show realistic underground structures, but also significantly improved the regional knowledge of the underground by combining all the existing data, and will therefore lead to better decision making while being based on open-source technology.