Automated Hierarchical 3D Modeling of Quaternary Aquifers: The ArchPy Approach - Schorpp, Ludovic; Straubhaar, Julien; Renard , Philippe (Frontiers in Earth Science, 2022)
When modeling groundwater systems in Quaternary formations, one of the first steps is to construct a geological and petrophysical model. This is often cumbersome because it requires multiple manual steps which include geophysical interpretation, construction of a structural model, identification of geostatistical model parameters, facies and property simulations. Those steps are often carried out in different software, which makes the automation intractable or very difficult. A non automated approach is time consuming and makes the model updating difficult when new data is available or when some geological interpretations are modified. Furthermore, conducting a cross-validation procedure to assess the overall quality of the models and quantifying the joint structural and parametric uncertainty is tedious. To address these issues, we propose a new approach and a Python module, ArchPy, to automatically generate realistic geological and parameter models. One of its main features is that the modeling operates in a hierarchical manner. The input data consists of a set of borehole data and a stratigraphic pile. The stratigraphic pile describes formally and in a compact manner how the model should be constructed. It contains the list of the different stratigraphic units and their order in the pile, their conformability (eroded or onlap), the surface interpolation method (e.g. kriging, sequential Gaussian simulation (SGS), multiple-point statistics (MPS), etc.), the filling method for the lithologies (e.g. MPS, sequential indicator simulation (SIS), etc.) and the petrophysical properties (e.g. MPS, SGS, etc.). Then, the procedure is automatic. In a first step, the stratigraphic unit boundaries are simulated. Secondly, they are filled with lithologies and finally the petrophysical properties are simulated inside the lithologies. All these steps are straightforward and automated once the stratigraphic pile and its related parameters have been defined. Hence, this approach is extremely flexible. The automation provides a framework to generate end-to-end stochastic models and then the proposed method allows for uncertainty quantification at any level and may be used for fully inversion. In this work, ArchPy is illustrated using data from an alpine Quaternary aquifer in the Upper Aare plain (south-east of Bern, Switzerland).