Moritz Ziegler

Geomechanical-numerical modeling aims to provide a continuous description of the stress tensor within rock volumes by leveraging localized stress magnitude data for model calibration. This calibration process involves optimizing displacement boundary conditions to achieve the best possible alignment with in-situ stress measurements obtained from microhydraulic fracturing (MHF) and sleeve reopening (SR) test in boreholes providing magnitudes of the minimum and maximum horizontal stresses. However, the high cost associated with acquiring stress magnitude data often results in sparse and incomplete datasets, which can potentially hinder a robust model calibration.We investigate the relationship between calibration dataset size and stress field prediction quality by leveraging an exceptionally high-quality set of 45 in-situ stress magnitude data from MHF and SR tests performed in two boreholes in the Zürich Nordost region, a potential deep geological repository location in northern Switzerland. We present a statistical framework that analytically evaluates extensive model ensembles, where each realization uses a distinct subset of the entire stress magnitude dataset for the model calibration. This methodology quantifies the effect of data quantity on modeled stress distributions in lithological units with different elastic properties by efficiently computing stress states for multiple data combinations.By systematically comparing modeled stress magnitudes derived from incrementally larger calibration datasets, we identify the minimum number of stress magnitude data records needed to achieve a modeled stress range narrower than the predicted stress range resulting from rock stiffness variability. For Zürich Nordost, approximately 15 stress magnitude data records are sufficient to reach this threshold, beyond which additional data provides only minimal improvement to model predictions.Examination of the dataset revealed one measurement that deviated from the expected model, due to localized variations in the mechanical properties of the rock. Although this observation is geologically valid, it substantially distorts predictions when there are few calibration points available. However, its distorting effect weakens progressively as the size of the calibration dataset increases. Our analytical framework also enables the systematic detection of such anomalous records, which in turn affects the minimum number of data points required for model calibration.Our findings emphasize the importance of dataset size and composition in reducing uncertainties and help establishing a practical methodology for efficient data acquisition planning. These insights are particularly valuable for subsurface engineering applications that require reliable stress estimates, such as geothermal systems, carbon storage facilities, radioactive waste repositories and underground energy infrastructure.

The use of geothermal energy inevitably causes changes in pore fluid pressure in the subsurface due to the production of fluids at one location and their reinjection at another location. In turn, this local change in pore pressure influences the undisturbed effective stress state. Depending on the stress state and changes in pore pressure, the rock's stability can be compromised. A resulting failure of the rock is perceived as induced seismicity. Since this is undesirable, the thermo-hydro-mechanical response of the rock to operations is often studied with the aim of better understanding the underlying mechanisms that lead to induced seismicity and potentially identifying ways to constrain its impact. However, the availability of direct data on the relevant parameters is usually sparse, if available at all. Thus, it is of interest to understand the magnitude of impact of different parameters on the stability. The ultimate goal is to enhance understanding of the parameters that are most decisive.Here, we present and quantify the influence of various relevant parameters on the stability of the rock mass. Specifically, we examine the effect of different initial stress states, varying hydraulic and mechanical fault properties, and different rock stiffnesses on the stability of the rock mass. For quantification and comparability, we use the slip tendency as a measure of how close a rock mass is to failure. Differences in slip tendency due to different parameter sets enable us to assess the impact of uncertain information for a specific parameter on the eventual uncertainty of stability prediction.We illustrate this approach with a case study from the North Alpine Foreland Basin. The geothermal power plant in Unterhaching has operated for almost two decades. Currently, it is used solely for district heating, but it was previously employed for power generation. During its operation, it has experienced several hundred microseismic events around the reinjection well that are attributed to the operation.We set up a 3D thermo-hydro-mechanical model around the reinjection well to model the response of the stress field to ongoing fluid reinjections. The model geometry is based on a 3D seismic survey that includes six lithological units, each populated with corresponding rock properties. Additionally, pore fluid overpressures, as observed locally in the North Alpine Foreland Basin, are incorporated. Different stress states based on data records and model results are calibrated. Furthermore, the hydraulic properties of the faults are assumed to be either sealing or conducting. Several model scenarios allow us to eventually identify those parameter sets that are in agreement with observations of induced seismicity and reject those that do not align with them. Essentially, this enhances the quality of model predictions and facilitates a more accurate assessment of future operations.

For a deep geological repository (DGR) for radioactive waste, the stress field is a key parameter for the assessment of potential siting regions, the DGR design, and the evaluation of its long-term safety. Therefore, a 3-D description of the stress state (orientation and magnitudes) is required not only for the repository host rock, but also for the under- and overlying formations that act as additional geological barriers. The main objectives of the project SpannEnD are to predict the spatial variability of the present-day stress state in Germany and to develop the tools that are required to set up and calibrate 3-D geomechanical models. Furthermore, we also developed a statistical framework that uses such models to investigate the number of stress magnitude data that are needed for a robust model calibration, and to test at which depth and in which lithologies microhydraulic fracturing and sleeve re-opening tests should be conducted that is used to derive the magnitudes of the minimum and maximum horizontal stress magnitudes Shmin and SHmax, respectively.Another objective is to investigate all relevant aspects of the stress state for Germany on a supra-regional scale. To describe the 3-D stress state with geomechanical-numerical models, stress data for the model calibration are required in combination with the knowledge of the geological structures of the subsurface and the rock properties. The orientation of SHmax has been compiled for decades in the World Stress Map database using a wide range of stress indicator. As part of the SpannEnD project, we updated the dataset for Germany and its surroundings to 1573 data records. For the compilation of stress magnitude data we developed for the first time a quality-ranking for the stress magnitude data applied it to the new open access German database with 1330 stress magnitude data records. These datasets are used to calibrate a large-scale 3-D geomechanical model covering the entirety of Germany. The numerical model is based on a comprehensive geological model that integrates all the structural information from the federal geological surveys and other publicly available sources. This model is populated with the rock properties of the individual lithological units and calibrated using the compiled stress data. The resulting geomechanical model for Germany enables an initial assessment of the crustal stress state for the entire country and can be used to investigate the impact of supra-regional structures. Furthermore, the first-order stress predictions are used to define initial conditions for regional-scale models.In addition to stress data compilation and geomechanical modelling, the project also compiled a fault geometry database for Germany which, in combination with the model results, allows the prediction the slip tendency for these faults and a distribution function for all potential fault orientations. Furthermore, the usage of sub-modelling techniques, the impact of faults on the stress state and uncertainties in the predicted stress state due to the material properties and the calibration data has been investigated. The presentation will provide an overview of the main achievements of the SpannEnD project over the past eight years.

Geomechanical modeling aims to predict the 3D in-situ stress state of the Earth’s crust and to assess the stability of subsurface rock volumes for applications such as radioactive waste disposal, energy storage, or CO₂ geo-sequestration. However, model calibration typically relies on sparse in-situ stress magnitude data which are expensive to acquire, limited in spatial coverage, and may not represent stress conditions over larger rock volumes, away from the measurement sites. Here we present a probabilistic forward-calibration framework that uses the borehole failure interpreted from routinely acquired borehole-image logs as indirect stress data and formation integrity tests (FIT) to calibrate 3D geomechanical models.Our approach integrates four types of indirect stress observations: the occurrence of borehole breakouts (BO), drilling-induced tensile fractures (DITF), formation integrity tests (FIT), and the documented absence of both BO and DITF at micro-hydraulic fracturing (MHF) stations. Although these indirect data provide only upper and lower limits on the stress state, they offer the critical advantage of scanning the entire borehole trajectory with high resolution, yielding far more extensive spatial coverage than point measurements. The absence of borehole failure provides simultaneous upper and lower bounds on horizontal stress magnitudes, addressing a key limitation in previous approaches that struggled to constrain the maximum horizontal stress magnitude. We developed a forward uncertainty quantification framework that explores hundreds of thousands of model scenarios at each observation point using linear elastic principles and compares the agreement between predicted and observed stress indicators through a probabilistic assessment.In the Zürich Nordost siting region for a potential deep geological repository for radioactive waste in northern Switzerland, we leverage an exceptional stress magnitude dataset from two deep boreholes. This dataset comprises 30 high-quality microhydraulic fracturing tests and 15 dry sleeve reopening tests, accompanied by comprehensive borehole image logs and detailed laboratory measurements of Young's modulus and rock strength. Using the stress magnitude data alone to calibrate the geomechanical model yields accurate stress predictions with well-constrained uncertainties, providing a rigorous benchmark against which to evaluate models calibrated solely with indirect stress indicators.Our results demonstrate that stress predictions based solely on indirect observations achieve comparable accuracy to those calibrated with an exceptionally large and robust dataset of in-situ stress magnitude data. For the magnitude of the minimum horizontal stress Shmin, high-agreement scenarios reproduce the reference stress predictions throughout most of the stratigraphic section, with uncertainties dominated by natural rock property variability rather than stress magnitude uncertainty. For the magnitude of the maximum horizontal stress SHmax, the approach successfully delivers constrains within physically realistic ranges, though systematic overestimation of 2–3 MPa in some formations suggests remaining model limitations. This work demonstrates that indirect stress data, readily available during routine drilling operations, can provide reliable, uncertainty-quantified stress predictions without requiring expensive in-situ stress measurement campaigns, opening new possibilities for stress field characterization in subsurface projects worldwide.

Subsurface exploration for geoenergy resources within the seismically-active Lower Rhine Graben (LRG) in the cross-boarder region of Belgium, Germany and the Netherlands (NW Europe) needs to consider the tendency for induced seismic events as well as the effect of subsurface operations to the present-day crustal stresses. Regionally, geomechanical investigations are challenged by inconsistent coverage of reliable geologic and stress data below the Tertiary Rhineish lignite deposits. As deep geothermal exploration is currently focused entirely below these formations within marine sediments from Lower Carboniferous to the Devonian period, a first order 3D regional stress model to seismogenic depths up to 10 km is developed using a newly compiled 3D structural geological model combining data from three national datasets of the cross-boarder region. The structural geological model is distilled to a parameterized FEM mesh and used as input for numerical simulations of crustal stresses based on linear elasticity theory using the open-source MOOSE framework. Calibration of the resulting geomechanical model is completed using focal mechanisms from seismic catalogues, borehole failure observations, and hydraulic fracturing tests in boreholes within the LRG. 3D geomechanical model results of the LRG region provide a quantitative footing to support deep geothermal development through a spatially-continuous characterization of in situ stresses, even in greenfield prospects with little to no stress information, and an improved assessment of the reactivation potential of major faults in the region targeted for future geothermal development.

The spatial influence of faults on the crustal stress field is a topic of ongoing debate. While faults are often known to perturb the stress field at a meter scale, their lateral influence over a few hundred meters to several kilometers remains poorly understood. To address this knowledge gap, we use a 3D geomechanical numerical model based on 3D seismic data from northern Switzerland. The model is calibrated with 45 horizontal stress magnitude data obtained from micro-hydraulic fracturing (MHF) and sleeve re-opening (SR) tests conducted in two boreholes in the Zürich Nordost (ZNO) siting region, northern Switzerland. This model with seven faults implemented as contact surfaces serves as the reference model in our study. The reference model is systematically compared to three fault-agnostic models, which share identical rock properties, model dimensions, and calibration data with the reference model, but differ in their element resolution and mechanical properties' assignment procedure. Results show that at distances <1 km from faults, differences in maximum horizontal stress orientation between models range from 3–6°, and horizontal stress magnitude differences are approximately 1–2 MPa. Beyond 1 km, these differences reduce to <1.5° and <0.5 MPa, respectively. These differences are significantly smaller than the calibration data uncertainties at ZNO, which average to ±0.7 MPa and ±3.5 MPa for the minimum horizontal and maximum horizontal stress magnitude, respectively, and ±11° for the maximum horizontal stress orientation. An important implication of our results is that, under the specific geological, mechanical, and stress conditions observed at the ZNO siting region, explicit representation of faults may not be necessary in geomechanical models predicting the stress state of rock volumes located 1 km or more from active faults. This simplification substantially reduced our model setup time from 2 months to 2 days, without compromising the reliability of stress field predictions.

The spatial influence of faults on the crustal stress field remains a topic of active debate. While it is well documented that faults often cause perturbations in the stress field at a meter scale, their lateral influence over greater distances, from a few hundred meters to several kilometers, remains poorly understood. This knowledge gap largely results from the lateral resolution limit of stress data. To address this, we use a 3D geomechanical numerical model based on 3D seismic data from northern Switzerland. The model is calibrated with 45 high-quality horizontal stress magnitude data obtained from micro-hydraulic fracturing (MHF) and sleeve re-opening (SR) tests conducted in two boreholes in the Zürich Nordost (ZNO) siting region. The 3D seismic and stress data were collected as a part of site characterization for a potential Deep Geological Repository (DGR) for radioactive waste. This 3D geomechanical numerical model serves as the reference model in our study and includes seven faults, implemented as contact surfaces with Coulomb friction. It is then systematically compared to three fault agnostic models i.e., models without any implemented faults. These fault agnostic models use identical rock properties and model input parameters, are calibrated with the same 45 horizontal stress magnitude dataset and have the same model extent, but differ in their discretization and mechanical properties’ assignment procedure. The results show that at distances of < 1 km from faults, differences in maximum horizontal stress orientation between models range from 3°–6°, and horizontal stress magnitude differences are about 1–2 MPa. Beyond 1 km distance, the differences reduce to < 1.5° and < 0.5 MPa, respectively. These stress differences are far smaller than the uncertainties associated with the horizontal stress magnitude measurements at the ZNO siting region, which average to ±0.7 MPa for the minimum horizontal stress magnitude and ±3.5 MPa for the maximum horizontal stress magnitude. An important implication of this lateral quantification of fault influence on stress state is that explicit representation of faults may not be necessary in geomechanical models predicting the stress state of rock volumes located a kilometer or more from major active faults, an important prerequisite for any DGR campaign. This structural simplification allows for faster model set-up and discretization, leading to a significant reduction in the set-up phase and computational time by more than one order, without compromising the reliability of stress field predictions.

The spatial influence of faults on the crustal stress field remains a topic of active debate. While it is well documented that faults often cause perturbations in the stress field at a meter scale, their lateral influence over greater distances, from a few hundred meters to several kilometers, remains poorly understood. This knowledge gap largely results from the lateral resolution limit of stress data. To address this, we use a 3D geomechanical numerical model based on 3D seismic data from northern Switzerland. The model is calibrated with 45 high-quality horizontal stress magnitude data obtained from micro-hydraulic fracturing (MHF) and sleeve re-opening (SR) tests conducted in two boreholes in the Zürich Nordost (ZNO) siting region. The 3D seismic and stress data were collected as a part of site characterization for a potential Deep Geological Repository (DGR) for radioactive waste. This 3D geomechanical numerical model serves as the reference model in our study and includes seven faults, implemented as contact surfaces with Coulomb friction. It is then systematically compared to three fault agnostic models i.e., models without any implemented faults. These fault agnostic models use identical rock properties and model input parameters, are calibrated with the same 45 horizontal stress magnitude dataset and have the same model extent, but differ in their discretization and mechanical properties’ assignment procedure. The results show that at distances of < 1 km from faults, differences in maximum horizontal stress orientation between models range from 3°–6°, and horizontal stress magnitude differences are about 1–2 MPa. Beyond 1 km distance, the differences reduce to < 1.5° and < 0.5 MPa, respectively. These stress differences are far smaller than the uncertainties associated with the horizontal stress magnitude measurements at the ZNO siting region, which average to ±0.7 MPa for the minimum horizontal stress magnitude and ±3.5 MPa for the maximum horizontal stress magnitude. An important implication of this lateral quantification of fault influence on stress state is that explicit representation of faults may not be necessary in geomechanical models predicting the stress state of rock volumes located a kilometer or more from major active faults, an important prerequisite for any DGR campaign. This structural simplification allows for faster model set-up and discretization, leading to a significant reduction in the set-up phase and computational time by more than one order, without compromising the reliability of stress field predictions.

The spatial influence of faults on the crustal stress field remains a topic of active debate. While it is well documented that faults often cause perturbations in the stress field at a meter scale, their lateral influence over greater distances, from a few hundred meters to several kilometers, remains poorly understood. This knowledge gap largely results from the lateral resolution limit of stress data. To address this, we use a 3D geomechanical numerical model based on 3D seismic data from northern Switzerland. The model is calibrated with 45 high-quality horizontal stress magnitude data obtained from micro-hydraulic fracturing (MHF) and sleeve re-opening (SR) tests conducted in two boreholes in the Zürich Nordost (ZNO) siting region. The 3D seismic and stress data were collected as a part of site characterization for a potential Deep Geological Repository (DGR) for radioactive waste. This 3D geomechanical numerical model serves as the reference model in our study and includes seven faults, implemented as contact surfaces with Coulomb friction. It is then systematically compared to three fault agnostic models i.e., models without any implemented faults. These fault agnostic models use identical rock properties and model input parameters, are calibrated with the same 45 horizontal stress magnitude dataset and have the same model extent, but differ in their discretization and mechanical properties’ assignment procedure. The results show that at distances of < 1 km from faults, differences in maximum horizontal stress orientation between models range from 3°–6°, and horizontal stress magnitude differences are about 1–2 MPa. Beyond 1 km distance, the differences reduce to < 1.5° and < 0.5 MPa, respectively. These stress differences are far smaller than the uncertainties associated with the horizontal stress magnitude measurements at the ZNO siting region, which average to ±0.7 MPa for the minimum horizontal stress magnitude and ±3.5 MPa for the maximum horizontal stress magnitude. An important implication of this lateral quantification of fault influence on stress state is that explicit representation of faults may not be necessary in geomechanical models predicting the stress state of rock volumes located a kilometer or more from major active faults, an important prerequisite for any DGR campaign. This structural simplification allows for faster model set-up and discretization, leading to a significant reduction in the set-up phase and computational time by more than one order, without compromising the reliability of stress field predictions.

The spatial influence of faults on the crustal stress field remains a topic of active debate. While it is well documented that faults often cause perturbations in the stress field at a meter scale, their lateral influence over greater distances, from a few hundred meters to several kilometers, remains poorly understood. This knowledge gap largely results from the lateral resolution limit of stress data. To address this, we use a 3D geomechanical numerical model based on 3D seismic data from northern Switzerland. The model is calibrated with 45 high-quality horizontal stress magnitude data obtained from micro-hydraulic fracturing (MHF) and sleeve re-opening (SR) tests conducted in two boreholes in the Zürich Nordost (ZNO) siting region. The 3D seismic and stress data were collected as a part of site characterization for a potential Deep Geological Repository (DGR) for radioactive waste. This 3D geomechanical numerical model serves as the reference model in our study and includes seven faults, implemented as contact surfaces with Coulomb friction. It is then systematically compared to three fault agnostic models i.e., models without any implemented faults. These fault agnostic models use identical rock properties and model input parameters, are calibrated with the same 45 horizontal stress magnitude dataset and have the same model extent, but differ in their discretization and mechanical properties’ assignment procedure. The results show that at distances of < 1 km from faults, differences in maximum horizontal stress orientation between models range from 3°–6°, and horizontal stress magnitude differences are about 1–2 MPa. Beyond 1 km distance, the differences reduce to < 1.5° and < 0.5 MPa, respectively. These stress differences are far smaller than the uncertainties associated with the horizontal stress magnitude measurements at the ZNO siting region, which average to ±0.7 MPa for the minimum horizontal stress magnitude and ±3.5 MPa for the maximum horizontal stress magnitude. An important implication of this lateral quantification of fault influence on stress state is that explicit representation of faults may not be necessary in geomechanical models predicting the stress state of rock volumes located a kilometer or more from major active faults, an important prerequisite for any DGR campaign. This structural simplification allows for faster model set-up and discretization, leading to a significant reduction in the set-up phase and computational time by more than one order, without compromising the reliability of stress field predictions.