Federal Institute for Geosciences and Natural Resources

The European EMODnet Geology project started in 2009. One of its aims is to provide geological map data of the European seas, harmonised as far as possible and made available according to FAIR data principles.The EMODnet Geology Workpackage “Seafloor Geology” is not only compiling map layers of the geology of the seafloor (Quaternary and pre-Quaternary but is also mapping layers of the geomorphology of the European seas and beyond. Semantic and geometric harmonisation is essential to understand geological information across administrative (EEZ) boundaries. The main method to provide semantically harmonised data layers is common and agreed upon terms to describe a unit: a vocabulary.To describe the characteristics of the seafloor geology, the vocabularies of the European INSPIRE Directive Data Specifications Geology (INSPIRE Thematic Working group Geology 2013) could be applied to describe the age, lithology and genesis (event environment, event process) of the marine geology.While the INSPIRE vocabularies are comprehensive, they nevertheless lack terms to describe the marine geomorphological features. EMODnet Geology fills that gap and is developing hierarchical scientific vocabularies for marine geomorphology to describe the concepts to which geometrical descriptions (lines and polygons) can be linked. This controlled vocabulary consists of a hierarchical, machine-readable list of terms and definitions needed to describe the European seafloor geomorphological units.The process to set up vocabularies for the marine domain faces considerable challenges, such as:Finding suitable terms and definitionsAvoiding duplicationAgreeing internationally on the terms and descriptionCoping with obsolete and/or strictly regional termsConsidering multiple hierarchiesThe presentation demonstrates the project’s approach to build pan-European applicable vocabularies to describe marine geomorphological features and presents use cases for its application.

The explosive yield- seismic magnitude relation of shallow submarine explosions are not well confined. Local agencies often use local seismic magnitude, such as the traditional richter scale, which are often not calibrated for submarine environments. The importance of an estimated explosive yield in TnT equivalent becomes obvious when security concerns arise. After the North Stream events a number of very differing magnitude were presented by several seismological surveys and therefore the related yield estimates varied a lot. This lead to derived estimates ranging from tens of kg to hundreds of kg TnT equivalent explosive used in the North Stream explosions, giving different plausible scenarios for potential perpetrators.We present an relatively simple and fast approach to use the comparison of recorded and forward modelled envelope and cepstral information to derive the moment magnitude of several large and small submarine explosion in the Baltic sea. Moment magnitudes are more robust in comparison to local magnitudes. We asses the performance of this approach by relating the moment magnitudes to yield estimates from known explosive events. We use events from the Baltic sea, including events from offshore Bornholm from September 2025 with around 400kg TnT yield, recorded at local and regional distances up to 500km.Infrasound recordings of stations in Germany are in good correlation with the seismic recordings, showing the possibility of combined energy release estimates. The strong importance of the source depth and shallow submarine geology is highlighted by the modelling results, providing still a large uncertainty range for unknown sources. We do find in general a good agreement between the estimated yield and actual yield for the known sources.

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.

Serpentinisation is a water–rock reaction in ultramafic lithologies that can generate natural hydrogen and strongly modifies rock density and magnetic susceptibility. Quantifying the spatial distribution of serpentinized bodies is therefore essential for assessing the subsurface potential of natural hydrogen systems.The Münchberg Massif (northern Bavaria, Germany) is an exhumed stack of tectonic nappes of different metamorphic grades that hosts several outcropping serpentinite bodies. This provides a rare opportunity to study serpentinisation in a setting that is typically buried at considerable crustal depths. The serpentinites are mainly exposed in the southern and southeastern part of the massif and coincide with pronounced, high-amplitude magnetic anomalies attributed to elevated magnetite contents. Despite detailed petrological and geochemical studies, the structural continuation of these bodies toward the north and northwest beneath overlying nappes remains poorly constrained.We address this problem through joint inversion of gravity and magnetic data, exploiting the characteristic properties of reduced bulk density and elevated magnetic susceptibility in serpentinized ultramafic rocks relative to the surrounding crystalline basement. We integrate newly acquired high-resolution airborne gravity and magnetic observations with vintage seismic reflection constraints and site-specific petrophysical measurements (density and magnetic susceptibility) conducted on samples collected from surface outcrops. We used topography-aware forward modelling and wavelet compression to efficiently handle dense airborne datasets. Geological and petrophysical information is incorporated through bound/interval constraints, while seismic reflectors provide structural guidance to steer the inversion toward geologically plausible geometries and reduce non-uniqueness.Preliminary joint inversion results of serpentinites reproduce the observed magnetic anomaly patterns consistent with outcrop-based measurements. First joint gravity–magnetic models indicate that combining density and susceptibility constraints with structural guidance from vintage seismic reflection data improves the robustness of inferred serpentinite geometries compared to magnetic-only inversions, particularly with respect to thickness distribution and subsurface continuity beneath the massif.The Münchberg Massif thus serves as a natural test site for developing and validating geophysical workflows to characterize potential natural hydrogen systems in settings where serpentinites are concealed beneath crystalline or sedimentary cover.

Reliable, stable, and internally consistent moment magnitude (Mw) estimates are essential for seismic hazard assessment and earthquake source characterization. Full waveform inversion provides physically robust seismic moment estimates; however, its applicability is often constrained by data quality, network geometry, and modeling assumptions. Conversely, coda-based approaches are a more efficient alternative that are less sensitive to radiation pattern and path effects. This study presents a systematic comparison between coda-derived moment magnitudes (Mw-coda) estimated using the Qopen framework and those (Mw-ISOLA) obtained from moment tensor inversion conducted through the ISOLA software.Analysis is based on the same dataset examined by Özkan et al. (2024), comprising 303 local earthquakes (2.5 ≤ ML ≤ 5.7) recorded by 49 broadband stations in the Sea of Marmara region, NW Türkiye. Qopen is utilized to jointly invert S-wave and coda-wave envelopes by employing Radiative Transfer Theory. This process yields frequency-dependent attenuation parameters and coda-derived source spectra, from which the Mw-coda is estimated. For a subset of these events with sufficient waveform quality and azimuthal coverage, independent seismic moment estimates are obtained through time-domain waveform inversion using ISOLA.Overall, we aim to evaluate the agreement and consistency between Mw-coda and Mw-ISOLA in terms of magnitude scaling, scatter, and potential systematic bias, with particular emphasis on magnitude range, source depth, and signal-to-noise conditions in a tectonically complex region characterized by strong lateral heterogeneity and frequency-dependent attenuation.

Carbon capture and storage (CCS) projects raise fundamental questions beyond technical performance, including how injected CO₂ behaves in the subsurface over long-time scales, how reliable model predictions are, and how experimental observations and simulations can be meaningfully combined. Addressing these questions requires not only process-based physical understanding, but also transparent modeling workflows, experimental validation, and effective collaboration across disciplines and institutions. In this contribution, we use the ongoing CO₂ Long-term Periodic Injection Experiment (CL-Experiment) at the Mont Terri Rock Laboratory in Switzerland as a central case study to illustrate how such integrated understanding can be developed. The core of the work is a numerical benchmark modeling study of CO₂ injection into the Opalinus Clay formation, using a two-dimensional axisymmetric representation of the injection system to investigate hydraulic propagation and coupled geochemical processes over a 20-year period. The simulations assume a fully water-saturated domain and single-phase injection at 3 MPa, using artificial porewater containing dissolved CO₂ corresponding to a partial pressure of 2 MPa. As part of a benchmark study, international teams use different numerical codes. Evaluation of the results enables a transparent assessment of model assumptions, sensitivities, and limitations, as well as model verification.To gain insights into CO₂–water–rock interactions, laboratory experiments were conducted using crushed Opalinus Clay from the in-situ sandy facies field site in an open system under controlled CO₂ conditions. Differences and consistencies between laboratory observations and numerical simulations are explicitly examined, highlighting key parameters and controlling processes that influence both model behavior and experimental responses.This study integrates numerical benchmarking, laboratory experiments, and interdisciplinary collaboration as a learning process to improve understanding of CO₂ storage in clay formations. Continuum-scale modeling shows that the CO₂ plume remains confined within approximately 1 m of the injection zone over 20 years (based on a cutoff concentration of 10 mmol/L), while CO₂-induced carbonate dissolution causes localized porosity increases within about 5 cm of the injection zone. At the laboratory scale, modeling indicates that carbonate reactions are the dominant factor on the pH evolution. However, strong spatial mineralogical heterogeneity observed in the in-situ samples limits the applicability of homogeneous batch-scale representations. For the international benchmark exercise, effective coordination relied on a hierarchical benchmarking strategy in which model complexity was increased stepwise by progressively introducing key variables and parameters. Together, the results of this study demonstrate the strength of coordinated benchmarking initiatives, and continuous exchange across disciplines, tools, and teams.

Abandoned oil and gas wells can be significant sources of methane emissions into the atmosphere. However, the extent of these potential emissions is often unclear, and mitigation requires detailed knowledge of the location of emitters. In Germany, the Federal Institute for Geosciences and Natural Resources has investigated a selection of wells of the in total ~25.000 onshore oil and gas wells for the first time. One challenge in investigating these wells is the mandatory decommissioning process, i.e. plugging, cutting and burying. For such soil buried wells, a measurement strategy was developed in which emissions were measured in an area of 30 x 30 m around the well and, for comparison, in a nearby reference area to record the natural background (Jordan et al., 2025). Between 2022 and 2025, nearly 90 wells of varying ages were investigated in northern Germany, where most of Germany's current and historical oil and gas production has taken place. In addition to investigating potential methane and CO2 emissions, soil gas compositions and stable carbon isotopes (and occasionally also hydrogen isotopes) in the soil gas methane were measured at each study site. In analogy to the reference areas and as is typical for forest, arable, and meadow soils, most well sites acted as methane sinks. Abnormalities compared to the reference areas were only determined at a few wells. For instance, a maximum of ~40 mg h-1 methane emissions were detected at one well, where small amounts of crude oil also appear to be escaping. However, covering the wells with soil offer an advantage here, as the gas and oil composition geochemically indicates a strong and depth-increasing influence of hydrocarbon-degrading microorganisms (Blumenberg et al., 2025). Final evaluations have not yet been completed, but for Germany, our results indicate that methane emissions from old oil and gas wells are relatively low. Open questions that are currently being addressed include the temporal variability of methane emissions, but also the importance of e.g., seasonal factors on the effectiveness of the microbial filter.

Groundwater systems exhibit substantially different response dynamics depending on site-specific and hydrogeological characteristics: While shallow aquifers often respond rapidly to meteorological forcing, deeper groundwater systems typically show delayed and strongly damped dynamics. In particular, monitoring wells with large depths to groundwater and long response times to external drivers remain challenging to model reliably using data-driven approaches. However, these systems are hydrogeologically highly relevant, as their substantial storage capacity and persistence across wet and dry periods strongly influence long-term water availability and the attenuation of climatic extremes.To assess the potential of data-driven models for capturing contrasting groundwater dynamics, groundwater level time series from approximately 400 monitoring wells in the federal state of Brandenburg (Germany) are selected. All wells provide continuous observations since 1980, are distributed across three major aquifer complexes at different depths, and thus represent a wide spectrum of response behaviours. Recurrent neural networks (Gated Recurrent Units - GRU) are applied to predict groundwater levels based on meteorological inputs (precipitation and air temperature). Two key aspects are systematically investigated: (1) the length of the input sequence and (2) the optional integration of aggregated meteorological predictors. This design evaluates whether extended look-back periods or the incorporation of site-specific smoothed climate signals improves the predictability of damped groundwater systems.The results indicate that input sequence lengths of two to three years substantially improve model performance for slow-responding groundwater systems, whereas shorter sequences are sufficient for more dynamic systems. Incorporating site-specific aggregated meteorological inputs further enhanced the representation of characteristic response times and led to a considerable increase in predictive skill for slow-responding aquifers. Although some strongly damped systems remain difficult to predict even with optimised model configurations, the overall results demonstrate a clear potential to better capture slow-responding groundwater dynamics and improve predictive performance.

This contribution addresses the understanding of the observed time-dependent behavior of Opalinus Clay (OPA) due to excavation. During six years of the CD-A experiment at the Mont Terri Rock Laboratory (Switzerland), data from two parallel, unsupported niches (approximately 11 m long and 2.3 m in diameter) was collected. The twins were excavated in 2019, with one is exposed to seasonal climate fluctuations (leading to desaturation of the clay) andthe other sealed to maintain high humidity. Long-term measurements of deformation using extensometer and laser scans show a non-elastic convergence trend, especially in the open niche. This certainly cannot be explained by elastic models, but driven by a mechanical creep mechanism or by hydraulic-mechanically (HM) coupling. Comparisons of the behavior of the two niches provide useful insights here. Further measurements of hydraulic parameters, as well as geophysical surveys and geological characterization, support the investigation. Although many long-term measurements are available today, a clear statement cannot be made yet. One reason for this is the complex behavior of the OPA, especially in the unsaturated zone affected by excavation, where shrinkage effects are pronounced and damage and inhomogeneities occur. Coupled numerical HM modeling is an important tool for gaining further insights.In addition to the initial outcomes (Ziefle et al., 2022), this contribution provides an update. The 3D HM model has been significantly improved, and now includes a more accurate representation of the equilibrium state prior to excavation, time-dependent excavation processes, and a physics-based description of the swelling behavior. Model validation against extensometer data establishes the model as a robust basis for further investigations, including parameter studies and testing of alternative constitutive models. Ziefle, G. et al (2022): Multi-disciplinary investigation of the hydraulic-mechanically driven convergence behaviour: CD-A twin niches in the Mont Terri Rock Laboratory during the first year. Geomechanics for Energy and the Environment 31.

Exploration datasets such as borehole logs and geophysical profiles form the fundamental basis of geological modeling. Among these, borehole records are particularly influential, as they typically include detailed descriptions and interpretations of petrography and stratigraphy. Such information is essential for constructing three-dimensional representations of lithostratigraphic units, which can be affected by inconsistencies or errors skewing borehole interpretations. Distinguishing reliable borehole data from problematic records is therefore critical, but becomes increasingly challenging when dealing with large datasets. Although visual assessment of the resulting geological models can help identify questionable boreholes, this approach typically requires many iterative modeling steps, making the process inefficient and costly. To improve the efficiency of borehole data quality assessment, we developed B-QualMT, a Python-based borehole quality management tool with a GUI interface that enables automated filtering of borehole records using both a user-defined quality check as well as a purely data-driven approach. The software applies a suite of deterministic tests that incorporate auxiliary information such as existing 3D geological models and regional geological knowledge, including expected stratigraphic successions, to identify anomalous borehole logs within geologically similar areas. Furthermore, spatial outliers can be identified using a combination of borehole similarity analysis, various clustering techniques, and a Bayesian-based novelty detection system. To evaluate the functionalities and edge cases of these methods, synthetic borehole data besides real borehole data were used. Different test scenarios were utilized to systematically control and test the outlier detection approaches, enabling workflow optimization and a detailed assessment of their performance, limitations, and sensitivity under controlled synthetic conditions. The limitations identified during testing with synthetic data are subsequently used to inform and improve the interpretation of results derived from more complex real borehole logs.