Jorge Nicolas Hayek

Modelling the dynamic response of reservoirs to fluid injection often relies on fully coupled thermo-hydro-mechanical models, which provide a high-fidelity representation of the governing physical processes. These models support operational and design decisions under significant geological and parametric uncertainties. However, their high computational cost severely limits their applicability in large-scale statistical analysis and thus limiting the potential to account for these uncertainties. We present Platypus, a Python package that bridges full-order process-based reservoir simulations and surrogate-based analysis. The package provides automated, reproducible workflows covering the full pipeline from parameter sampling and simulation interfacing, through ensemble curation and data management, to surrogate model construction and global sensitivity analysis. Surrogate models are built via the non-intrusive reduced-basis method to deliver computationally efficient, physics-consistent approximations of the transient reservoir response, enabling statistical analysis that require a large number of evaluations. The package is demonstrated on two geothermal applications: a synthetic reservoir benchmark and the Groß Schönebeck geothermal site. These examples illustrate the package's ability to handle time-dependent coupled hydrothermal and thermo-hydro-mechanical processes, manage large simulation ensembles, and perform global sensitivity analyses enabled by surrogates. Platypus is designed to be modular and extensible, providing a flexible tool for ensemble-based reservoir modelling workflows across a range of subsurface applications.

We derive global stress fields through time using an analytical asthenospheric flow estimation that involves plate motions, subduction geometry and variable plume flux. Among these, the most effective way to drive rapid regional stress changes in the continents is by varying plume flux, especially when more than one plume is present, as is the case for Europe. We apply our paleostress model to the case study of western Europe, a region that experienced rapid, substantial and large-scale lithospheric stress changes in the Late Mesozoic and Cenozoic. We find that the behaviour of pressure-driven asthenosphere flow, resulting from variations in plume flux, dominates the rapidly temporo-spatially varying stress signal. Given the potential causes of stress change in this particular region, we further interpret the tectonic changes in the context of dynamic topography as expressed by the stratigraphic record, shifts in plate motion, paleostress indicators and past interpretations of the tectonic evolution of Europe. Through this approach, we move away from the paradigm of stress changes being driven by plate-boundary or body forces in the lithosphere and emphasize the active role of the mantle and the importance of interpreting models in relation to multiple process-linked observations.

Understanding the internal dynamics, structure, and composition of our planet is a fundamental goal of Earth science, and geodynamic modelling has been central to this effort by providing a theoretical window into mantle convection. Moreover, the asthenosphere plays a key role in linking mantle dynamics to surface observations; its channelized nature allows it to be described analytically within the framework of Couette and Poiseuille flow regimes.Using this framework, we predict global stress fields and compare them directly with observations from the World Stress Map (WSM), a global compilation of crustal stress indicators. Our approach enables fast hypothesis testing and the development of first-order expectations for how different mantle flow states influence surface stress patterns. It also identifies three distinct basal shear traction regimes, depending on whether the asthenosphere locally moves faster than, slower than, or at the same velocity as the overlying plate. As a result, some regions experience driving tractions, others resisting tractions, while some are nearly traction-free. These results show that stress field patterns cannot be explained without realistic upper mantle flow geometries, particularly the spatial distribution and combined effects of plumes, slabs, and plate-driven flow.

We derive global stress fields through time using an analytical asthenospheric flow estimation that involves plate motions, subduction geometry, and time-variable plume flux. Among these, the most effective way to drive rapid regional stress changes in the continents is by varying plume flux, especially when more than one plume is present, as is the case for Europe. We apply our paleostress model to the case study of western Europe, a region that experienced rapid, substantial, and large-scale lithospheric stress changes in the Late Mesozoic and Cenozoic. We find that the behaviour of pressure-driven asthenosphere flow, resulting from variations in plume flux, dominates the rapidly temporo-spatially varying stress signal. Given the potential causes of stress change in this particular region, we further interpret the tectonic changes in the context of dynamic topography as expressed by the stratigraphic record, shifts in plate motion, paleostress indicators, and past interpretations of the tectonic evolution of Europe. Through this approach we move away from the paradigm of stress changes being driven by plate-boundary or body forces in the lithosphere, and emphasize the active role of the mantle and the importance of interpreting models in relation to multiple process-linked observations.

The development of digital twins for subsurface applications faces several challenges, in this contribution we are focusing on the issue of providing near real-time predictions for numerical multi-physics applications describe by partial differential equations. Even when fronted against state-of-the-art high-performance computing infrastructures, conventional multi-physics simulations are not real-time compatible because of their huge computational demand. At the same time, they are subject to uncertainties from, for instance, the geometry, material properties, and boundary conditions.To address the computational demand, we introduce the usage of surrogate models. Surrogate models comprise data-driven and physics-based approaches. While data-driven techniques, such as neural-networks, well capture complex system responses, they typically lack interpretability, hindering the degree of reliability of the model outcomes. This, in turn, poses challenges for the integration into digital twins especially in applications where risks need to be assessed. In contrast, physics-based approaches are fully interpretable, but often limited to elliptic and parabolic partial differential equations. Hence, they cannot capture the full complexity of the systems dynamics. To overcome the limitations of both data-driven and physics-based techniques, we introduce a hybrid approach namely the non-intrusive reduced basis method within the class of projection-based model order reduction techniques.In this contribution, we demonstrate for a geothermal case study how this interpretable physics-based AI method can be used to reliably and efficiently accelerate the high-fidelity numerical multi-physics simulations. Furthermore, we illustrate their integration into a Bayesian uncertainty quantification framework, including hierarchical approaches. At last, we discuss possibilities to extend the aforementioned approaches to allow for a continuous integration of observational data.

A characterization regarding the mechanical response of subsurface reservoirs is of increasing interest for energy-related applications, including geothermal energy production and storage of georesources and waste. Modelling the dynamic response of geological formations to fluid injection often relies on fully coupled thermo-hydro-mechanical (THM) models, which provide a high-fidelity representation of the governing physical processes. These models support operational and design decisions under significant geological and parametric uncertainties. However, their high computational cost severely limits their applicability in large-scale statistical analysis and thus limiting the potential to account for these uncertainties.Still, understanding how uncertainties in reservoir and operational parameters influence application-relevant outcomes is essential for stimulation design and risk mitigation. Global sensitivity analysis offers a quantitative framework to identify the controls on selected quantities of interest (QoIs). The choice of a QoI is inherently problem-dependent and reflects the specific operational objective or risk-related question being addressed, making it a central element in the interpretation of model results.To overcome the computational demands of full-order THM simulations, we employ non-intrusive reduced-order modeling techniques to efficiently and accurately approximate the transient reservoir response. Projection-based model reduction methods target accurate, physics-based response characterization, resulting in interpretable, physics-consistent, and scalable surrogate models. We train surrogate models using solutions of the coupled THM equations. These surrogates are then used to perform global sensitivity analyses for different choices of QoIs. Finally, we demonstrate the proposed workflow through an application to the Groß Schönebeck geothermal field, featuring a multistage injection scenario, that provides a basis for future analyses targeting induced seismicity.

Dynamic topography is a crucial geodynamic observable that emerges as a consequence of flow in the mantle. Buoyancies associated with mantle convection induce vertical deflections at the Earth's surface. Negative surface deflections create depositional environments and allow sedimentation to occur, while positive surface deflections create erosional/non-depositional environments, that induce gaps (hiatuses) in the geological record. The temporal and spatial extent of these gaps can be mapped using geological maps and regional studies, thus providing a means of tracking mantle processes through geological time.Here, we compare a manual and digital extraction of hiatus distributions in China. We utilise a manually compiled dataset of un/conformable contacts and compare it to a digital contact extraction using the recently published digital geological map of China. The digital approach is limited to surface data, whereas the manual approach allows the utilisation of subsurface information. We find that the digital approach is substantially faster than the manual extraction. Our results indicate that the optimal methodology combines digital processing with refinement of manual subsurface information. Furthermore, we observe that mapping the absence and presence of a geological series shows very similar results when processed using either approach. The current limitation to a wider application of this approach is the limited availability of digital geological maps. A standardised digital database of geological maps enhanced with subsurface information (i.e., covered geological maps) is necessary to promote the use of geological data within the wider Earth science community, and would increase the opportunities for interdisciplinary collaboration.

Tectonic deformation shapes the Earth's surface, with strain localization resulting in the formation of shear zones and faults that accommodate significant tectonic displacement. Earthquake dynamic rupture models, which provide valuable insights into earthquake mechanics and seismic ground motions, rely on initial conditions such as pre‐stress states and fault geometry. However, these are often inadequately constrained due to observational limitations. To address these challenges, we loosely couple 3D geodynamic models to 3D strike‐slip dynamic rupture simulations, for the first time accounting for off‐fault plastic deformation, providing a mechanically consistent framework for earthquake analysis. Our approach does not prescribe fault geometry but derives it from the underlying lithospheric rheology and tectonic evolution of the system, captured by long‐term geodynamic modeling. We perform three long‐term geodynamics models of a strike‐slip system, each involving different continental crust rheology. We link these with 14 dynamic rupture models, in which we investigate the role of varying fracture energy and plastic strain energy dissipation in the dynamic rupture behavior. Our results highlight the important role of the brittle‐ductile transition and indicate that the long‐term 3D stress field, which is directly related to the rheology of the lithosphere, favors slip on fault segments better aligned with the regional plate motion. Fault bends and minor variations in the long‐term 3D stress field can strongly affect rupture dynamics, providing a physical mechanism for arresting earthquake propagation. Our geodynamically informed earthquake models highlight the need for detailed 3D fault modeling across time scales for a comprehensive understanding of earthquake mechanics.

Continental rifting is the process by which land masses separate and create new ocean basins. The emplacement of large igneous provinces (LIPs) is thought to have played a key role in (super) continental rifting; however, this relationship remains controversial due to the lack of a clearly established mechanism linking LIP emplacement to continental fragmentation. Here, we show that plume flow links LIP magmatism to continental rifting quantitatively. Our findings are further supported by the sedimentary record, as well as by the mineralogy and petrology of the rocks. This study analyzes the early Cretaceous separation of West Gondwana into South America and Africa. Prior to rifting, Jurassic hiatuses in the stratigraphic record of continental sediments from both continents indicate plume ascent and the resulting dynamic topography. Cretaceous mafic dyke swarms and sill intrusions are products of major magmatic events that coincided with continental rifting, leading to the formation of large igneous provinces in South America and Africa, including the Central Atlantic Magmatic Province, Equatorial Magmatic Province, Paraná–Etendeka, and Karoo. It has been suggested that dyke intrusions may weaken the lithosphere by reducing its mechanical strength, creating structural weaknesses that localize extensional deformation and facilitate rift initiation. The sedimentary analysis and petrological evidence from flood basalt magmas indicate that plumes may have migrated from the depths toward the surface during the Jurassic and erupted during the Cretaceous. It is thought that the resulting fast plume flow, induced by one or more mantle plumes, generated a dynamic force that, in combination with lithospheric weakening from dyke intrusion, eventually rifted the lithosphere of West Gondwana.