Predictive DFN modelling for the Upper Muschelkalk aquifer in the northernmost Swiss Molasse Basin based on vertical and horizontal borehole records

<p>The exploration of the underground is a complex, but common task. Structural characterisation of a given sub-surface volume is of interest, for many purposes including deep geological repositories for radioactive waste, exploitation of mineral resources and geothermal energy production. One major challenge in this regard relates to the identification of sub-seismic scale faults and fractures. Discrete fracture network modelling is one possible technique for this purpose. Ideally, it is supported by borehole data. Even so, the results of stochastic models require critical verification to determine resulting uncertainties and model robustness.</p><p>We present a case-study from the village of Schlattingen, located the northernmost Molasse Basin in Switzerland, that is devoted to such a verification aimed at improvement of the DFN modelling workflows. Two boreholes were drilled at this location, a vertical cored borehole reaching into the crystalline basement and a deviated borehole running sub-horizontally for 464 m in the Schinznach Formation (Upper Muschelkalk), a potential geothermal reservoir (Frieg et al. 2015). This borehole layout allows testing the workflow for discrete fracture network modelling from a single borehole and assessment of the the added value of a deviated borehole (and vice versa).</p><p>The modelling workflow used borehole data and outcrop descriptions from a range of locations as input data. The spatial distribution of features was simulated using a Poisson distribution. The aims of the study were to investigate the workflow’s ability to account for the different orientation biases in the two boreholes and develop understanding of spatial variability in fracture orientation and frequency.</p><p>It was found that reasonable consistency in orientation and overall frequency could be achieved using the borehole orientation distributions but that the spatial variability in fracture frequency and clustering of fractures were significant. It was also necessary to critically evaluate the borehole imagery from the deviated borehole.</p><p>Current efforts are focused on better constrain the spatial fracture distribution along the deviated borehole using correlation analysis (Marett et al. 2018, Gale at al. 2018) and assess its influence on the discrete fracture network model. In addition, it is anticipated to integrate observation from nearby outcrops into the modelling strategy.</p><p>References:</p><p>Frieg, B., Grob, H., Hertrich, M., Madritsch, H., Müller, H., Vietor, T., Vogt, T., and Weber, H.P. (2015). Novel Approach for the Extrapolation of the Muschelkalk Aquifer in Switzerland for the CO<sub>2</sub>-free production of vegetables. Proceedings World Geothermal Congress, Melbourne, Australia</p><p>Gale, J. F. W., Ukar, E., & Laubach, S. E. (2018). Gaps in DFN models and how to fill them. 2nd International Discrete Fracture Network Engineering Conference, DFNE 2018.</p><p>Marrett, R., Gale, J. F. W., Gómez, L. A., & Laubach, S. E. (2018). Correlation analysis of fracture arrangement in space. Journal of Structural Geology, 108, 16–33. https://doi.org/10.1016/j.jsg.2017.06.012</p>