Predictability and controlling factors of overpressure in the North Alpine Foreland Basin, SE Germany: an interdisciplinary post-drill analysis of the Geretsried GEN-1 deep geothermal well

The North Alpine Foreland Basin in SE Germany is Germany’s most active deep geothermal province. However, in its southern and eastern part the basin is considerably overpressured, which is a significant challenge for drilling deep geothermal wells. In this study, we combine drilling data and velocity-based pore pressure analyses with 3D basin modeling to assess the predictability and controlling factors of overpressure in the sub-regional context (area of 80 km × 50 km) around the Geretsried GEN-1 well, a deep geothermal exploration well in the southern part of the North Alpine Foreland Basin in SE Germany. Drilling data and velocity-based pore pressure analyses indicate overpressure maxima in the Lower Oligocene (Rupelian and Schoeneck Formation) and up to mild overpressure in the Upper Oligocene (Chattian) and Upper Cretaceous, except for the hydrostatically pressured northwestern part of the study area. 3D basin modeling calibrated to four hydrocarbon wells surrounding the Geretsried GEN-1 well demonstrates the dominating role of disequilibrium compaction and low permeability units related to overpressure generation in the North Alpine Foreland Basin. However, secondary overpressure generation mechanisms are likely contributing. Also, the impact of Upper Cretaceous shales, which are eroded in the northwestern part of the study area, on overpressure maintenance is investigated. The calibrated basin model is tested against the drilling history and velocity (VSP) data-based pore pressure estimate of the Geretsried GEN-1 well and reveals that pore pressure prediction is generally possible using 3D basin modeling in the North Alpine Foreland Basin, but should be improved with more detailed analysis of lateral drainage systems and facies variations in the future. The results of the study are of relevance to future well planning and drilling as well as to geomechanical modeling of subsurface stresses and deep geothermal production in the North Alpine Foreland Basin. © 2020, The Author(s)

Assessment of human immediate response capability related to tsunami threats in Indonesia at a sub-national scale

Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach. Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunami-safe area. Most endangered areas feature longer estimated-evacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a sub-national scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%. The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support

The Di models method: geological 3-D modeling of detrital systems consisting of varying grain fractions to predict the relative lithological variability for a multipurpose usability

The coexistence of a wide variety of subsurface uses in urban areas requires increasingly demanding geological prediction capacities for characterizing the geological heterogeneities at a small-scale. In particular, detrital systems are characterized by the presence of highly varying sediment mixtures which control the non-constant spatial distribution of properties, therefore presenting a crucial aspect for understanding the small-scale spatial variability of physical properties. The proposed methodology uses the lithological descriptions from drilled boreholes and implements sequential indicator simulation to simulate the cumulative frequencies of each lithological class in the whole sediment mixture. The resulting distributions are expressed by a set of voxel models, referred to as Di models. This solution is able to predict the relative amounts of each grain fraction on a cell-by-cell basis and therefore also derive a virtual grain size distribution. Its implementation allows the modeler to flexibly choose both the grain fractions to be modeled and the precision in the relative quantification. The concept of information entropy is adapted as a measure of the disorder state of the clasts mixture, resulting in the concept of “Model Lithological Uniformity,” proposed as a measure of the degree of detrital homogeneity. Moreover, the “Most Uniform Lithological Model” is presented as a distribution of the most prevailing lithologies. This method was tested in the city of Munich (Germany) using a dataset of over 20,000 boreholes, providing a significant step forward in capturing the spatial heterogeneity of detrital systems and addressing model scenarios for applications requiring variable relative amounts of grain fractions.Bayerisches Staatsministerium für Umwelt und Verbraucherschutz http://dx.doi.org/10.13039/501100010219Technische Universität München (1025

Assessment of the heterogeneity of hydraulic properties in gravelly outwash plains: a regionally scaled sedimentological analysis in the Munich gravel plain, Germany

The favorable overall conditions for the utilization of groundwater in fluvioglacial aquifers are impacted by significant heterogeneity in the hydraulic conductivity, which is related to small-scale facies changes. Knowledge of the spatial distribution of hydraulically relevant hydrofacies types (HF-types), derived by sedimentological analysis, helps to determine the hydraulic conductivity distribution and thus contribute to understanding the hydraulic dynamics in fluvioglacial aquifers. In particular, the HF-type “open framework gravel (OW)”, which occurs with the HF-type “bimodal gravel (BM)” in BM/OW couplings, has an intrinsically high hydraulic conductivity and significantly impacts hydrogeological challenges such as planning excavation-pit drainage or the prognosis of plumes. The present study investigates the properties and spatial occurrence of HF-types in fluvioglacial deposits at regional scale to derive spatial distribution trends of HF-types, by analyzing 12 gravel pits in the Munich gravel plain (southern Germany) as analogues for outwash plains. The results are compared to the reevaluation of 542 pumping tests. Analysis of the HF-types and the pumping test data shows similar small-scale heterogeneities of the hydraulic conductivity, superimposing large-scale trends. High-permeability BM/OW couples and their dependence on recognizable discharge types in the sedimentary deposits explain sharp-bounded small-scale heterogeneities in the hydraulic conductivity distribution from 9.1 × 10−3 to 2.2 × 10−4 m/s. It is also shown that high values of hydraulic conductivity can be interpolated on shorter distance compared to lower values. While the results of the HF-analysis can be transferred to other fluvioglacial settings (e.g. braided rivers), regional trends must be examined with respect to the surrounding topography.Bayerisches Staatsministerium für Umwelt und Verbraucherschutz http://dx.doi.org/10.13039/50110001021

Uncertainties in 3-D stochastic geological modeling of fictive grain size distributions in detrital systems

Geological 3-D models are very useful tools to predict subsurface properties. However, they are always subject to uncertainties, starting from the primary data. To ensure the reliability of the model outputs and, thus, to support the decision-making process, the incorporation and quantification of uncertainties have to be integrated into the geo-modeling strategies. Among all modeling approaches, the novel Di models method was conceived as a stochastic approach to make predictions of the 3-D lithological composition of detrital systems, based on estimating the fictive grain size distribution of the sediment mixture by using soil observations from drilled materials. Within the present study, we aim to adapt the geo-modeling framework of this method in order to incorporate uncertainties linked to systematic imprecisions in the soil observations used as input data. Following this, uncertainty quantification measures are proposed, based on entropy and joint entropy for the main outcomes of the method, i.e., the partial percentile lithological models, and for the whole sediment mixture. Both the ability of the uncertainty quantification measures and the uncertainty propagation derived from the extension of the method are investigated in the model outcomes in a simulation experiment with real data conducted in a small-scale domain located in Munich (Germany). The results show that this adaptation of the Di models method overcomes potential bias caused by ignoring imprecise input data, thus providing a more realistic assessment of uncertainty. The uncertainty measures provide very useful insight for quantifying local uncertainties, comparing between average uncertainties and for better understanding how the implementation parameters of the geo-modeling process influence the property estimation and the underlying uncertainties. The main findings of the present study have great potential for providing robust uncertainty information about model outputs, which ultimately strengthens the decision-making process for practical applications based on the implementation of the Di models method

The Di models method: geological 3-D modeling of detrital systems consisting of varying grain fractions to predict the relative lithological variability for a multipurpose usability

<jats:title>Abstract</jats:title><jats:p>The coexistence of a wide variety of subsurface uses in urban areas requires increasingly demanding geological prediction capacities for characterizing the geological heterogeneities at a small-scale. In particular, detrital systems are characterized by the presence of highly varying sediment mixtures which control the non-constant spatial distribution of properties, therefore presenting a crucial aspect for understanding the small-scale spatial variability of physical properties. The proposed methodology uses the lithological descriptions from drilled boreholes and implements sequential indicator simulation to simulate the cumulative frequencies of each lithological class in the whole sediment mixture. The resulting distributions are expressed by a set of voxel models, referred to as <jats:italic>D</jats:italic><jats:sub><jats:italic>i</jats:italic></jats:sub> models. This solution is able to predict the relative amounts of each grain fraction on a cell-by-cell basis and therefore also derive a virtual grain size distribution. Its implementation allows the modeler to flexibly choose both the grain fractions to be modeled and the precision in the relative quantification. The concept of information entropy is adapted as a measure of the disorder state of the clasts mixture, resulting in the concept of “Model Lithological Uniformity,” proposed as a measure of the degree of detrital homogeneity. Moreover, the “Most Uniform Lithological Model” is presented as a distribution of the most prevailing lithologies. This method was tested in the city of Munich (Germany) using a dataset of over 20,000 boreholes, providing a significant step forward in capturing the spatial heterogeneity of detrital systems and addressing model scenarios for applications requiring variable relative amounts of grain fractions.</jats:p&gt