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Schorpp, Ludovic
Nom
Schorpp, Ludovic
Affiliation principale
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Doctorant.e
Email
ludovic.schorpp@unine.ch
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Voici les éléments 1 - 4 sur 4
- PublicationAccès libreData integration and automated geological modeling of Quaternary aquifersCette thèse a pour sujet d’étude la modélisation de l’hétérogénéité des aquifères et formations géologiques du Quaternaire. Plus particulièrement, elle cherche à intégrer au mieux les données géologiques existantes au sein des procédures de modélisation et à trouver des façons de les automatiser au maximum. Différents axes de recherches sont investigués afin de répondre à ces problématiques. Dans un premier temps, une revue littéraire des méthodes de modélisation de faciès, caractérisant largement l’hétérogénéité du sous-sol, est réalisée afin d’avoir une vue aussi complète que possible sur les algorithmes et méthodes existantes. Le but était aussi de proposer une classification récente et actualisée de ces méthodes dans le but d’aider à la sélection d’une méthode en fonction des situations. Les potentielles lacunes en matière de recherche dans ce domaine sont également identifiées. A la suite de cela, une proposition d’une approche hiérarchique, semi-automatique et stochastique, appelée ArchPy est proposée. Elle permet de facilement combiner l’expertise géologique, représentée sous la forme d’une pile stratigraphique, et les différentes données géologiques. Cette approche hiérarchique opère en trois étapes: unité stratigraphique, faciès et propriétés pétrophysiques. Elles représentent différentes échelles de complexité géologique et permettent d’atteindre une grande complexité en terme d’hétérogénéité. ArchPy a ensuite été utilisé sur différents sites géologiques afin de démontrer ses capacités de modélisation. Cependant, ArchPy est confronté à certains problèmes qui limitent son automatisation. En particulier, la difficulté associée à la construction de la pile stratigraphique a conduit à la proposition d’un nouvel algorithme pour déterminer automatiquement la pile stratigraphique sur la base des données lithologiques des forages. Une méthode est également proposée afin de résoudre le problème récurrent des informations stratigraphiques manquantes dans les données de forages. Une fois l’approche ArchPy mise en place, il est nécessaire d’affiner sa deuxième étape - la modélisation des faciès - qui est particulièrement délicate à modéliser en fonction du contexte géologique. Dans ce but, une nouvelle méthode de modélisation des faciès, appelée EROSim, permet de mieux représenter les structures sédimentaires. Cette méthode a la particularité qu’elle utilise des surfaces pour représenter les différents évènements géologiques pouvant affecter l’hétérogénéité d’une formation sédimentaire. Les outils et méthodes présentées montrent l’intérêt et le bénéfice des méthodes stochastiques, automatisées et en accès libre pour la modélisation géologique. ArchPy pose notamment les bases d’une boite à outils de modélisation géologique stochastique ayant un large panel d’utilisations, tel que la réalisation de modèles géologiques complexes ou le couplage dans des processus d’inversion. Cette thèse participe ainsi au développement d’une modélisation géologique devenant de plus en plus accessible et libre d’accès, pour le bien commun de la communauté géoscientifique, et au-delà. ABSTRACT The subject of this thesis is the modeling of heterogeneity in Quaternary aquifers and geological formations. More specifically, it seeks to integrate existing geological data into modeling procedures and find ways of automating them as far as possible. Various lines of research are being investigated to address these challenges. First, a literature review of facies modeling methods, characterizing the heterogeneity of the subsurface, is carried out in order to gain an overview as complete as possible of existing algorithms and methods. The aim was also to propose a recent and up-to-date classification of these methods, to help in the selection of a method according to the situation. Potential research gaps in this field are also identified. Second, an approach and module is developed to tackle the challenges of the thesis. The result is the proposal of a hierarchical, semi-automatic and stochastic approach, called ArchPy, which makesit easy to combine geological expertise, represented in the form of a stratigraphic pile, and various geological data. This hierarchical approach operatesin three stages: stratigraphic unit, facies and petrophysical properties. These represent different scales of geological complexity, and enable a high degree of heterogeneity to be achieved. In order to demonstrate ArchPy’s usefulness, it is then applied to different geological sites and improved at several pointsdepending on the situation. However, ArchPy faces some issues that limits its automation. In particular, the difficulty associated with the construction of the stratigraphic pile led to the proposition of a new algorithm to automatically determine the stratigraphic pile based on borehole records. A method is also proposed to solve the recurrent problem of missing stratigraphic information in drilling data. Once ArchPy approach is set up, it is necessary to refine its second step - facies modeling - which is particularly to accurately model depending on the geological context. To this aim, a novel facies modeling methods, called EROSim, to better represent sedimentary structures is proposed. This method is distinctive because it employs surfaces to represent various geological events that can impact the heterogeneity of a sedimentary formation. The presented tools and methods showcase the advantages and usefulness of stochastic, automated, and open-access methods for geological modeling. Specifically, ArchPy establishes the groundwork for a stochastic geological modeling toolbox with a broad range of applications, including the creation of intricate geological models or coupling in inversion processes. This thesis contributes to the development of geological modeling, which is becoming more accessible and available to the geoscientific community and beyond.
- PublicationAccès libreHydrogeological modeling of the Roussillon coastal aquifer (France): stochastic inversion and analysis of future stresses(2023)
; ; - PublicationAccès libreAutomated Hierarchical 3D Modeling of Quaternary Aquifers: The ArchPy Approach(2022)
; ; When modeling groundwater systems in Quaternary formations, one of the first steps is to construct a geological and petrophysical model. This is often cumbersome because it requires multiple manual steps which include geophysical interpretation, construction of a structural model, and identification of geostatistical model parameters, facies, and property simulations. Those steps are often carried out using different software, which makes the automation intractable or very difficult. A non-automated approach is time-consuming and makes the model updating difficult when new data are available or when some geological interpretations are modified. Furthermore, conducting a cross-validation procedure to assess the overall quality of the models and quantifying the joint structural and parametric uncertainty are tedious. To address these issues, we propose a new approach and a Python module, ArchPy, to automatically generate realistic geological and parameter models. One of its main features is that the modeling operates in a hierarchical manner. The input data consist of a set of borehole data and a stratigraphic pile. The stratigraphic pile describes how the model should be constructed formally and in a compact manner. It contains the list of the different stratigraphic units and their order in the pile, their conformability (eroded or onlap), the surface interpolation method (e.g., kriging, sequential Gaussian simulation (SGS), and multiple-point statistics (MPS)), the filling method for the lithologies (e.g., MPS and sequential indicator simulation (SIS)), and the petrophysical properties (e.g., MPS and SGS). Then, the procedure is automatic. In a first step, the stratigraphic unit boundaries are simulated. Second, they are filled with lithologies, and finally, the petrophysical properties are simulated inside the lithologies. All these steps are straightforward and automated once the stratigraphic pile and its related parameters have been defined. Hence, this approach is extremely flexible. The automation provides a framework to generate end-to-end stochastic models and then the proposed method allows for uncertainty quantification at any level and may be used for full inversion. In this work, ArchPy is illustrated using data from an alpine Quaternary aquifer in the upper Aare plain (southeast of Bern, Switzerland). - PublicationAccès libreStochastic multi-fidelity joint hydrogeophysical inversion of consistent geological models(2022)
; ; In Quaternary deposits, the characterization of subsurface heterogeneity and its associated uncertainty is critical when dealing with groundwater resource management. The combination of different data types through joint inversion has proven to be an effective way to reduce final model uncertainty. Moreover, it allows the final model to be in agreement with a wider spectrum of data available on site. However, integrating them stochastically through an inversion is very time-consuming and resource expensive, due to the important number of physical simulations needed. The use of multi-fidelity models, by combining low-fidelity inexpensive and less accurate models with high-fidelity expensive and accurate models, allows one to reduce the time needed for inversion to converge. This multiscale logic can be applied for the generation of Quaternary models. Most Quaternary sedimentological models can be considered as geological units (large scale), populated with facies (medium scale), and finally completed by physical parameters (small scale). In this paper, both approaches are combined. A simple and fast time-domain EM 1D geophysical direct problem is used to first constrain a simplified stochastic geologically consistent model, where each stratigraphic unit is considered homogeneous in terms of facies and parameters. The ensemble smoother with multiple data assimilation (ES-MDA) algorithm allows generating an ensemble of plausible subsurface realizations. Fast identification of the large-scale structures is the main point of this step. Once plausible unit models are generated, high-fidelity transient groundwater flow models are incorporated. The low-fidelity models are populated stochastically with heterogeneous facies and their associated parameter distribution. ES-MDA is also used for this task by directly inferring the property values (hydraulic conductivity and resistivity) from the generated model. To preserve consistency, geophysical and hydrogeological data are inverted jointly. This workflow ensures that the models are geologically consistent and are therefore less subject to artifacts due to localized poor-quality data. It is able to robustly estimate the associated uncertainty with the final model. Finally, due to the simplification of both the direct problem and the geology during the low-fidelity part of the inversion, it greatly reduces the time required to converge to an ensemble of complex models while preserving consistency.