Speaker: Bastien Morin
Date: Thursday 09th of October 2025, 1:15pm
Abstract:
L’exploitation de ressources minières souterraines implique des systèmes d’exhaure destinés à maintenir les travaux au sec. Après l’arrêt de l’activité, la remontée de nappe provoque l’ennoyage des vides et la création de réservoirs artificiels d’eau souterraine. Ces réservoirs « miniers » constituent des hydrosystèmes originaux, fortement anthropisés mais en interaction directe avec les aquifères naturels environnants. Ils s’inscrivent dans la problématique de la zone critique, où pressions anthropiques et changements climatiques affectent le cycle de l’eau. L’étude de leur dynamique requiert des approches de modélisation spécifiques, capables d’évaluer leur évolution quantitative et d’éclairer les enjeux liés à ces nouveaux réservoirs souterrains.
La présente étude porte sur la mine de charbon de Gardanne (Bouches-du-Rhône), ennoyée depuis l’arrêt de l’exhaure en 2003. En raison de la qualité chimique défavorable du réservoir, un pompage a repris en 2010 pour éviter tout débordement par une galerie de drainage, où l’eau s’oxyderait et se colorerait, rendant impossible un rejet direct. L’objectif est de valoriser les données de volume d’eau exhaurée pendant l’exploitation pour mieux comprendre l’évolution post-ennoyage et reproduire le fonctionnement hydrologique actuel du réservoir. Pour cela, nous avons construit, avec le logiciel Gardénia (BRGM), un modèle global à réservoirs capable de simuler des chroniques de débit et de niveau de nappe.
Un premier modèle est calibré sur la période 1993-2003, afin de reproduire les débits d’exhaure à partir des chroniques de précipitations et d’évapotranspiration potentielle. Une bonne calibration a été obtenue en répartissant l’infiltration entre deux réservoirs souterrains, traduisant une composante rapide (Q1) et une composante lente (Q2) des débits d’exhaure. Ensuite, un second modèle, « pluie-niveau », a été élaboré sur la période post-ennoyage 2008-2024, en conservant le schéma conceptuel et les paramètres de sol issus du modèle d’exhaure. Le modèle montre une très bonne performance avec sept années de validation.
Ce modèle reproduit les variations de niveau du réservoir et constitue un cadre robuste pour explorer des scénarios climatiques. En suivant l’approche narrative proposée par DRIAS, des simulations prospectives permettent d’anticiper l’évolution future des niveaux et d’optimiser la gestion opérationnelle du pompage dans un contexte de changement climatique.
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- Category: Seminar
Speaker: Imadeddine Laouici
Date: Thursday 12th of June 2025, 1:15pm.
Abstract:
Building structural models of geological entities is generally addressed as an interpolation problem that requires human experts to interpret input data and use knowledge (Wellmann and Caumon, 2018). Although experts can effectively interpret, their interpretations can be subjective and occasionally prone to error (Bond, 2015). This is largely due to under-sampling of data, requiring experts to make choices in the selection and preparation of these data and knowledge (Bond et al., 2012), and selection and configuration of modeling algorithms (Caumon et al., 2009). Modeling algorithms also do not reflect the complex expert interpretation process, as they incorporate only a portion of the knowledge typically held by experts and have limited ability to directly interact with experts during the interpretation process itself. This makes it challenging to build geologically complex models and systematically identify and address inconsistencies in a model. A crucial step toward resolving these issues is the formalization of the interpretation process and the explicit use of formalized knowledge. In this work we develop and prototype such a formalization. A prototype algorithm and tool (Figure 1) are presented and applied to simple folding structures, and the results are favorably compared to existing approaches. This comparison highlights the potential of the proposed approach to reduce the need for expert involvement and increase the range of knowledge utilized.
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- Category: Seminar
Speaker: Roberto Cilli
Date: Thursday 25th of September 2025, 1:15pm
Abstract:
The seminar will first discuss a downstream application of a pretrained SentenceBERT + Random Forest (RF) for the lithological classification of texts from borehole logs. A custom lightweight architecture relying on a single Transformer module is proposed to handle contextual and positional relationships of each lithological text description. The proposed method achieves an accuracy gain of approximately 10% compared to a RF fed with SentenceBERT embeddings. Finally, a comparison between benchmark uncertainty quantification (UQ) algorithms, including Bayesian NN (Blundell et al. 2015), MAPIE Conformal Learning (Taquet et al. 2023) and Deep Ensemble (Lakshminarayanan et al. 2016) is shown. Preliminary results indicate that the Deep Ensemble UQ method seems the most reliable while still feasible in low-resource computing environments.
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- Category: Seminar
Speaker: Jeff Boisvert
Date: Monday 21st of July 2025, 2pm
Recording (Restricted access - Sponsors only) : Video
Abstract:
The earth sciences are being transformed by advances in machine learning (ML) and artificial intelligence. From optimizing mineral estimation and hydrocarbon production to improving wildfire prediction and management, these methods offer exciting opportunities for modeling and decision-making. However, these advances bring challenges with model validation, which is critical for ensuring that predictions are robust, reasonable, and actionable.
This lecture will delve into the evolving role of ML in the mining, hydrocarbon, or wildfire industry, highlighting successes, pitfalls, and future prospects. "The Good" will explore case studies and implementations where ML has significantly improved modeling, decision making, and inference. "The Bad" will examine common pitfalls, including data biases, overfitting, and the misuse of algorithms without understanding domain constraints. Finally, "The Ugly" will confront the ethical and operational risks posed by poorly validated models, emphasizing the importance of transparency and domain experts.
This lecture will not only focus on ML methods, but will also consider how to validate all types of earth science models including estimates, simulations, and decision making. We will discuss best practices for integrating ML models into traditional workflows while addressing the complexities of model validation.
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- Category: Seminar
Speaker: Jeremie Giraud
Date: Thursday 15th of May 2025, 11am.
Abstract:
We present and apply a pseudo trans-dimensional inversion method for 3D geometrical gravity inversion, in which the number of rock units, their geometry, and their density can vary during sampling. The method builds on a multiple level set framework and uses a birth-death process to insert or remove rock units from an existing model. Interface geometries are perturbed using random fields, and densities are sampled from distributions informed by prior geological knowledge. Sampling is performed using a non-reversible Metropolis-Hastings algorithm designed to efficiently explore complex model spaces while ensuring a parsimonious solution.
The method is applied to gravity data from the prospective Boulia region (Queensland, Australia) to image rocks beneath sedimentary cover. In this field case, an implicit geological model—constructed from the interpretation of 2D seismic lines, borehole data, and geological rules—is used to define prior geological constraints on the inversion. To aid interpretation, a workflow combining dimensionality reduction and clustering is applied to the ensemble of sampled models, allowing identification of families of geologically plausible solutions. Preliminary results suggest that up to two dense rock units, not initially identified by the geological model, may be needed to explain the observed data. Overall, our analysis of results suggests the ability of the method to infer the presence of previously unrecognized geological features, such as buried intrusions or facies variations, and indicates its potential as a tool to support exploration.
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- Category: Seminar
Speaker: Amandine Fratani
Date: Thursday 26th of June 2025, 1:15pm
Abstract:
The construction of geological models in sedimentary basins is largely constrained by the interpretation of faults and horizons in seismic and drillhole data and by associating observations into distinct entities (e.g., forming a single fault or one horizon). Due to the sparsity and incompleteness of data, several fault networks can usually be drawn from a given set of observations. This problem has been considered using graph formalism with nodes carrying the fault observation and the edges carrying information on the potential that they are associated. This potential has previously been proposed to be computed using machine learning, specifically the application of a Random Forest. However, the lack of open access structural models limits the use of machine learning. Therefore, this methodology has only been tested on partially interpreted cases. To generalise the approach, this work presents a database under development comprising synthetic structural models featuring normal faults. A random geological history and model generation code, Noddy, has been modified to include more realistic fault events. Faults are grouped into families where fault from a family have similar orientation for fault surfaces. Each family is defined as a mean dip and a mean dip direction, select randomly. A fault orientation is defined by sampling a Kent distribution centred on the dip and dip direction of the family to which it belongs. The resulting geological models are imported into geological modelling software where the surfaces are smoothed. Fault observations are then sampled in these models and will be used to train a Random Forest to retrieve the potential associations.
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- Category: Seminar
Speaker: Mohamed Sherif Mahrous
Date: Thursday 19th of June 2025, 1:15pm
Abstract:
A significant production of hydrogen is expected inside geological nuclear waste repository. The gaseous phase is foreseen to modify the flows and mechanical conditions of the rock and engineered material. As a part of EURAD 2 project (2024-2028), this work plans to implement the coupling between the different physical (THMC) processes involved in gas migration and to upscale results into the continuum scale. Towards this end, a pore scale Hydro-Mechanical-gas code has been developed in EURAD1 project, based on Smoothed Particle Hydrodynamics, to study water-gas migration accounting for drying within a deformable solid (elastic with thermodynamical damage model). The main objectives of this work are:
1. Apply the THMC couplings in the near- and far-field at the micro and meso scale (order of tens of pores) in the already existing SPH code.
2. Investigate the temperature dependency of multiphase flow parameters.
3. Compute effective properties (e.g., saturation curve, relative permeability, poromechanical properties).
4. Explore the consequences of usual simplifications.
5. Provide benchmarking and training data for predictive surrogate models.
6. Deliver results for code comparisons and experimental benchmarking.
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- Category: Seminar