Machine learning enhanced data assimilation framework for multi-scale carbonate rock characterization - Zhenkai Bo; Ahmed H. Elsheikh; Hannah P. Menke; Julien Maes; Sebastian Geiger; Muhammad Z. Kashim; Zainol A.A. Bakar; Kamaljit Singh (Advances in Water Resources, 2026)

Unsupervised learning for geologically consistent fluid flow analysis in fractured reservoirs - Elahe Kamel Targhi; Guillaume Rongier; Pierre-Olivier Bruna; Alexandros Daniilidis; Sebastian Geiger (Computational Geosciences, 2026)
Naturally fractured reservoirs are essential for subsurface energy production and storage. However, the complexity and uncertainty inherent to fracture network properties make it difficult to characterise fluid flow within them. This study presents an unsupervised machine learning workflow that constrains uncertainty by establishing a systematic link between the pressure transient response observed at the well and the underlying fracture network properties. We generate a geologically consistent ensemble of 4,850 discrete fracture networks (DFNs) and simulate pressure transient responses for the same geometries under three matrix-fracture permeability configurations. For each dataset, we group pressure derivative responses into geologically interpretable flow behaviour clusters using Dynamic Time Warping (DTW) based K-medoids clustering. The resulting cluster medoids provide representative pressure derivative responses that summarise the dominant flow regime sequence within each class. The workflow consistently identifies four stable clusters across all datasets, each characterised by a distinct and repeatable sequence of diagnostic flow regimes consistent with a bounded range of fracture network properties. Feature importance ranking and SHAP values derived from a random forest classifier show that fracture intensity, wellbore fracture length, and backbone fracture fraction provide the strongest geological controls on cluster separation and hence on the emergent diagnostic signatures. Comparing clusters across datasets shows that 64.1% of DFNs retain their cluster membership, indicating that the clustering structure is primarily controlled by DFN geometry. However, for a fixed DFN, the pressure transient response varies across matrix-fracture permeability configurations, producing systematic shifts in derivative levels and in the dominance of specific flow regimes. The representative pressure derivative responses associated with each flow behaviour cluster are therefore not identical across datasets and must be interpreted within the matrix-fracture permeability configuration. Overall, the proposed framework provides a basis to constrain geological uncertainty and prioritise high-impact parameters for data acquisition in naturally fractured reservoirs, thereby improving reservoir characterisation and decision making in the early appraisal stage.

Data-worth analysis using ensemble smoother with multiple data assimilation to constrain uncertainty in geothermal energy production from clastic fluvial reservoirs - Guofeng Song; Denis Voskov; Hemmo A. Abels; Philip J. Vardon; Sebastian Geiger (Computational Geosciences, 2026)
Geothermal energy is a key option for decarbonizing heating and cooling in the energy transition. Forecasting geothermal production has inherent uncertainty due to the heterogeneity of geological formations that host the geothermal resource and the limited data available to characterize and quantify these heterogeneities. This uncertainty leads to operational risks such as early thermal breakthrough. Identifying the most valuable monitoring data and data acquisition strategies for operators is key to constraining uncertainties and ultimately de-risking operations in a reliable and cost-effective way. Data-worth analysis quantifies the value of data provided by existing observations or proposed data collection strategies. This study combines Ensemble Smoother with Multiple Data Assimilation and data-worth analysis to constrain uncertainty in production forecasts and reservoir response for a geothermal doublet system located in a clastic, channelized fluvial reservoir. The main monitoring data includes production temperature, injection pressure, and temperature and pressure profiles along the well paths. We show that production temperature and injection pressure alone only can constrain uncertainties in production forecasts. Using observations of well temperature and pressure profiles demonstrates a threefold increase in data worth, which improves both the quantification of production forecasts and reservoir dynamics. At constant injection rates in doublet system, temperature profiles monitored along the wells provide higher data worth compared to pressure profiles. Data from a deviated monitoring borehole is advantageous. Early-time (first year) observations of temperature and pressure profiles along the injector, producer, and monitoring borehole already constrain production uncertainty prior to thermal breakthrough. Data-worth analysis is shown to be most beneficial when conducted across multiple plausible geological scenarios to ensure a more reliable assessment of collection strategies. The findings of this study yield insight into designing informative data-acquisition strategies for direct-use geothermal systems.

A comparative multiscale analysis for CO2 storage in giant saline aquifers inspired by the storage case of Santos Basin in Brazil - Mathias José Kreutz Erdtmann; Filipe Silva Lira; Sebastian Geiger; Hadi Hajibeygi (International Journal of Greenhouse Gas Control, 2026)

Feasibility of subsurface storage of hydrochar in the Netherlands as carbon dioxide removal technique - Timothy F. Baars; Hemmo A. Abels; Anne-Catherine A.M. Dieudonné; Joachim B. Hanssler; Sebastian Geiger (International Journal of Greenhouse Gas Control, 2026)

Capillary pinning in sedimentary rocks for CO2 storage: Mechanisms, terminology and State-of-the-Art - Qin Zhang; Sebastian Geiger; Joep E.A. Storms; Denis V. Voskov; Matthew D. Jackson; Gary J. Hampson; Carl Jacquemyn; Allard W. Martinius (International Journal of Greenhouse Gas Control, 2025)

Effective permeability of fluvial lithofacies in the Bunter Sandstone Formation, UK - Shakhawat Hossain; Gary J. Hampson; Carl Jacquemyn; Matthew D. Jackson; Dmytro Petrovskyy; Sebastian Geiger; Julio D. Machado Silva; Sicilia Judice; Fazilatur Rahman; M. Costa Sousa (Advances in Water Resources, 2025)

The FluidFlower Validation Benchmark Study for the Storage of CO$$_2$$ - Bernd Flemisch; Jan M. Nordbotten; Martin Fernø; Ruben Juanes; Jakub W. Both; Holger Class; Mojdeh Delshad; Florian Doster; Jonathan Ennis-King; Jacques Franc; Sebastian Geiger; Dennis Gläser; et al. (Transport in Porous Media, 2024)
Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the “FluidFlower”), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Poro-Mechanical Coupling for Flow Diagnostics - Lesly Gutierrez-Sosa; Sebastian Geiger; Florian Doster (Transport in Porous Media, 2022)
Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows using complex reservoir models is challenging, mainly because of the high computational cost. We hence introduce an alternative approach that couples hydrodynamics through existing flow diagnostics simulations with poro-mechanics to screen the impact of coupled poro-mechanical processes on reservoir performance without significantly increasing computational overheads. In flow diagnostics, time-of-flight distributions and influence regions can be used to characterise the flow field in the reservoir, which depends on the distribution of petrophysical properties that are altered due to production-induced changes in pore pressure and effective stress. These extended flow diagnostics calculations hence enable us to quickly screen how the dynamics in the reservoirs (e.g. reservoir connectivity, displacement efficiency, and well allocation factors) are affected by the complex interactions between poro-mechanics and hydrodynamics. Our poro-mechanically informed flow diagnostics account for steady-state and single-phase flow conditions based on the poro-elastic theory and assume that the reservoir does not contain fractures. Fluid flow and rock deformation calculations are coupled sequentially. The equations are discretised using a finite-volume method with two-point flux-approximation and the virtual element method, respectively. The solution of the coupled system considers stress-dependent permeabilities. Due to the steady-state nature of the calculations and the effective proposed coupling strategy, these calculations remain computationally efficient while providing first-order approximations of the interplay between poro-mechanics and hydrodynamics, as we demonstrate through a series of case studies. The extended flow diagnostic approach hence provides an efficient complement to traditional reservoir simulation and uncertainty quantification workflows and enable us to assess a broader range of reservoir uncertainties.

Diversity of Insects in Nature protected Areas (DINA): an interdisciplinary German research project - Gerlind U. C. Lehmann; Nikita Bakanov; Martin Behnisch; Sarah J. Bourlat; Carsten A. Brühl; Lisa Eichler; Thomas Fickel; Matthias F. Geiger; Birgit Gemeinholzer; Thomas Hörren; Sebastian Köthe; Alexandra Lux; et al. (Biodiversity and Conservation, 2021)
Insect declines and biodiversity loss have attracted much attention in recent years, but lack of comprehensive data, conflicting interests among stakeholders and insufficient policy guidance hinder progress in preserving biodiversity. The project DINA (Diversity of Insects in Nature protected Areas) investigates insect communities in 21 nature reserves in Germany. All selected conservation sites border arable land, with agricultural practices assumed to influence insect populations. We taught citizen scientists how to manage Malaise traps for insect collection, and subsequently used a DNA metabarcoding approach for species identification. Vegetation surveys, plant metabarcoding as well as geospatial and ecotoxicological analyses will help to unravel contributing factors for the deterioration of insect communities. As a pioneering research project in this field, DINA includes a transdisciplinary dialogue involving relevant stakeholders such as local authorities, policymakers, and farmers, which aims at a shared understanding of conservation goals and action pathways. Stakeholder engagement combined with scientific results will support the development of sound policy recommendations to improve legal frameworks, landscape planning, land use, and conservation strategies. With this transdisciplinary approach, we aim to provide the background knowledge to implement policy strategies that will halt further decline of insects in German protected areas.

Five structural genes required for ceramide synthesis in Caulobacter and for bacterial survival - Roberto Jhonatan Olea‐Ozuna; Sebastian Poggio; EdBergström; Elva Quiroz‐Rocha; Daniela A. García‐Soriano; Diana X. Sahonero‐Canavesi; Jonathan Padilla‐Gómez; Lourdes Martínez‐Aguilar; Isabel M. López‐Lara; Jane Thomas‐Oates; Otto Geiger (Environmental Microbiology, 2021)
Summary Sphingolipids are essential and common membrane components in eukaryotic organisms, participating in many important cellular functions. Only a few bacteria are thought to harbour sphingolipids in their membranes, among them the well‐studied α‐proteobacterium Caulobacter crescentus , a model organism for asymmetric cell division and cellular differentiation. Here, we report that C. crescentus wild type produces several molecular species of dihydroceramides, which are not produced in a mutant lacking the structural gene for serine palmitoyltransferase ( spt ). Whereas growth of a spt ‐deficient mutant and wild type are indistinguishable during the exponential phase of growth, survival of the spt ‐deficient mutant is much reduced, in comparison with wild type, during stationary phase of growth, especially at elevated temperatures. The structural gene for spt is located within a genomic cluster, comprising another 16 genes and which, like spt , are important for fitness of C. crescentus . Mutants deficient in genes linked to spt by high cofitness were unable to produce dihydroceramide or to survive in stationary phase of growth at elevated temperatures. At least five structural genes are required for dihydroceramide biosynthesis in C. crescentus and sphingolipid biosynthesis is needed for survival of this bacterium and the integrity of its outer membrane.

Fluid Flow Characterization Framework for Naturally Fractured Reservoirs Using Small-Scale Fully Explicit Models - Daniel Lorng Yon Wong; Florian Doster; Sebastian Geiger; Eddy Francot; François Gouth (Transport in Porous Media, 2020)
Flow modelling challenges in fractured reservoirs have led to the development of many simulation methods. It is often unclear which method should be employed. High-resolution discrete fracture and matrix (DFM) studies on small-scale representative models allow us to identify dominant physical processes influencing flow. We propose a workflow that utilizes DFM studies to characterize subsurface flow dynamics. The improved understanding facilitates the selection of an appropriate method for large-scale simulations. Validation of the workflow was performed via application on a gas reservoir represented using an embedded discrete fracture model, followed by the comparison of results obtained from hybrid and dual-porosity representations against fully explicit simulations. The comparisons ascertain that the high-resolution small-scale DFM studies lead to a more accurate upscaled model for full field simulations. Additionally, we find that hybrid implicit–explicit representations of fractures generally outperform pure continuum-based models.

Fast flow computation methods on unstructured tetrahedral meshes for rapid reservoir modelling - Zhao Zhang; Sebastian Geiger; Margaret Rood; Carl Jacquemyn; Matthew Jackson; Gary Hampson; Felipe Moura De Carvalho; Clarissa Coda Marques Machado Silva; Julio Daniel Machado Silva; Mario Costa Sousa (Computational Geosciences, 2020)

Comparison of Flow and Transport Experiments on 3D Printed Micromodels with Direct Numerical Simulations - Francesca Watson; Julien Maes; Sebastian Geiger; Eric Mackay; Mike Singleton; Thomas McGravie; Terry Anouilh; T. Dawn Jobe; Shuo Zhang; Susan Agar; Sergey Ishutov; Franciszek Hasiuk (Transport in Porous Media, 2019)

Constitutive Relations for Reactive Transport Modeling: Effects of Chemical Reactions on Multi-phase Flow Properties - Shuo Zhang; Hui-Hai Liu; Marinus I. J. van Dijke; Sebastian Geiger; Susan M. Agar (Transport in Porous Media, 2016)

Habitat use and diet of Skylarks (Alauda arvensis) wintering in an intensive agricultural landscape of the Netherlands - Flavia Geiger; Arne Hegemann; Maurits Gleichman; Heiner Flinks; Geert R. de Snoo; Sebastian Prinz; B. Irene Tieleman; Frank Berendse (Journal of Ornithology, 2014)

Accurate Modelling of Pore-Scale Films and Layers for Three-Phase Flow Processes in Clastic and Carbonate Rocks with Arbitrary Wettability - Adnan Al-Dhahli; Marinus I. J. van Dijke; Sebastian Geiger (Transport in Porous Media, 2013)

Analytical solutions for co- and counter-current imbibition of sorbing, dispersive solutes in immiscible two-phase flow - Karen Sophie Schmid; Sebastian Geiger; Kenneth Stuart Sorbie (Computational Geosciences, 2012)

Exponential time integrators for stochastic partial differential equations in 3D reservoir simulation - Sebastian Geiger; Gabriel Lord; Antoine Tambue (Computational Geosciences, 2012)

The potential influence of shallow gas and gas hydrates on sea floor erosion of Rock Garden, an uplifted ridge offshore of New Zealand - Gareth J. Crutchley; Sebastian Geiger; Ingo A. Pecher; Andrew R. Gorman; Hai Zhu; Stuart A. Henrys (Geo-Marine Letters, 2010)

Three-Phase Flow Modelling Using Pore-Scale Capillary Pressures and Relative Permeabilities for Mixed-Wet Media at the Continuum-Scale - Randi Holm; Marinus I. J. van Dijke; Sebastian Geiger (Transport in Porous Media, 2010)

Multiphase Thermohaline Convection in the Earth’s Crust: II. Benchmarking and Application of a Finite Element – Finite Volume Solution Technique with a NaCl–H2O Equation of State - Sebastian Geiger; Thomas Driesner; Christoph A. Heinrich; Stephan K. Matthäi (Transport in Porous Media, 2006)

Multiphase Thermohaline Convection in the Earth’s Crust: I. A New Finite Element – Finite Volume Solution Technique Combined With a New Equation of State for NaCl–H2O - Sebastian Geiger; Thomas Driesner; Christoph A. Heinrich; Stephan K. Matthäi (Transport in Porous Media, 2006)