Speaker: Guillaume Pirot

Date: Thursday 18th of January 2024, 1:15pm.

Abstract:

The mining industry faces various challenges to satisfy the increasing demand of minerals for clean energy transitions. One of them is to improve geological characterization at the stage of undercover exploration. This usually requires costly drilling operations. Can we reduce our exploration footprint and costs while reducing geological uncertainty by optimising our drilling location design? Here I propose two ways to look at this problem, based on data from the Hamersley basin, WA, Australia. One examines legacy drillholes in the area and investigate the impact of removing drillholes on the quality of geological models. The other one explores an iterative drilling optimisation approach to reduce modelled geological uncertainty, based on a synthetic case.

Speaker: Franck Sfiligoi-Taillandier

Date: Thursday 11th of January 2024, 1:15pm.

Abstract:

Les modèles Agent (ou modèles multi-agents), issus du domaine de l’Intelligence Artificielle, sont particulièrement intéressants pour la modélisation et la simulation des systèmes sociaux et sociaux-techniques. Contrairement aux approches par apprentissage (Deep learning, Machine learning…), ils passent par une modélisation et une simulation explicite et naturelle des entités constitutives des systèmes et de leurs interactions, ce qui permet de faciliter la compréhension du système et de l’explorer. Ce côté intuitif et ouvert (par opposition aux boites noires), rend ces modèles particulièrement adaptés aux approches de modélisation et de simulation participatives. La modélisation participative est une approche dans laquelle les parties prenantes sont directement impliquées dans la construction du modèle. La simulation participative renvoie à une simulation interactive dans laquelle l’utilisateur peut modifier le cours de la simulation ; cette approche est beaucoup utilisée dans le cadre des jeux sérieux. Dans cette présentation, je reviendrai sur ces différents éléments en me basant sur des applications liées à la gestion des territoires, et en essayant de vous convaincre de l’intérêt de ces approches dans un dispositif d’aide à la décision ainsi que de leur valeur scientifique.

Speaker: Simon Daout

Date: Thursday 21st of December 2023, 1:15pm.

Abstract:

In this presentation, I will present you the results obtained in a recent publication entitled: «  Along-strike variations of strain partitioning within the Apennines determined from large-scale multi-temporal InSAR analysis, https://doi.org/10.1016/j.tecto.2023.230076 ». In this paper, we produced and analyzed a large set of GPS and InSAR measurements over the Apennines (Italy), where the origin of the long-wavelength topography and the driving mechanisms of the extension are debated. Our continuous mapping of the surface displacements across the range allows to understand how the different deformation scales (fault tectonic, landslides, surface processes, hydrological loading, mantle processes) are imbricated and how faults behave in relation to driving mechanisms at the boundaries of the system. Although, I hope this presentation can be relevant from the scientific point of view of various fields (seismology, geomorphology, geodynamic, remote sensing), here, I would like to particularly focus on numerical models and the development of inversion tools to derive the spatio-temporal evolution of seismic and aseismic slip on faults.

Speaker: Thibault Faney

Date: Wednesday 13th of December 2023, 1:30pm.

Speaker: Ahmad Marvi Mashhadi

Date: Thursday 30th of November 2023, 1:15pm.

Abstract:

At the present time, however, the geological storage of H2 remains very little studied despite of the specific behaviour of this gas. A key point in the development of such technology is to characterize and constrain the biological processes that could alter qualitatively and quantitatively the resource within the storage framework in porous reservoir rocks.  As first electron donor for life and crucial energy source for subsurface microbial processes, indeed, H2 allows the autotrophic growth of microorganisms under oligotrophic conditions (i.e. limited supply of carbon) in deep environments. In the presence of an available terminal electron acceptor such as nitrate (NO3-), ferric iron (Fe3+), sulfate (SO42-) or carbon dioxide (CO2), H2 is susceptible to be consumed by microorganisms to gain energy. To date, unravelling the contribution of H2-consuming microbes in the biogeochemical cycle of hydrogen is of high importance in a number of subsurface industries including H2 gas storage in the energy transition context. Particularly, bacterial activity is susceptible to produce methane (CH4) or hydrogen sulfide (H2S) to the detriment of H2. The main objective of this work will be to evaluate the kinetics of H2 consumption by bacterial model strains and multi-bacterial consortia under geological storage conditions in terms of temperature, pressure, salt concentration and electron acceptor availability. Batch and flow-through experiment will be designed to reproduce these storage conditions.

Speaker: Amandine Fratani

Date: Thursday 23rd of November 2023, 1:15pm.

Abstract:

During geological exploration, interpretation of faults can be ambiguous and uncertain because of disparate and often sparse observations such as fault traces on 2D seismic images or outcrops. The problem of associating partial fault observations was considered by Godefroy et al (2019), who decided to define a graph where each possible association of two fault observations (the graph nodes) are represented by an edge. The likelihood of this association was computed by using expert geological rules. However, fault observations are not pairwise independent, which limits the consideration of higher-order effects. For instance, the multiple-point association can be used to infer the evolution of the throw along the fault. In addition, the definition of rules in a multiple-point problem is also difficult because of the very large number of cases to consider. Here, we propose a machine learning approach to compute the likelihood of three-point fault data association. First, a computation of fault features (i.e. the length of the fault trace) from sections extracted from known 3D geological models is realized to create a data set of fault observations. The supervised machine learning problem is formulated as a classification problem to determine the probability that 3 fault observations belong to the same fault objects based on the feature vector. To prevent overfitting, we propose to mimic a partly interpreted case: we split the 3D domain in two disjoint sectors A and B, and use only data from sector A as training and data from sector B to test the method. However, the results are not conclusive, so an analysis of the features are proposed to choose the correct ones. At the same time, methods to deal with imbalanced dataset are explored.

Speaker: Consuelo Garcia Zavala

Date: Thursday 16th of November 2023, 1:15pm.

Abstract:

Lithium plays an essential role in global decarbonisation as lithium-based batteries are widely used in renewable energy and electric vehicles. The so-called “Lithium Triangle” extends over part of Chile, Argentina, and Bolivia, and holds around half of the world’s estimated reserves of lithium in the “salars”. Lithium extraction in this arid region raises challenges for the socio-ecological systems, which include fragile ecosystems and indigenous communities. Addressing these challenges requires companies to operationalise sustainability goals assuring continuous improvement of social and environmental performance, for which mining companies usually use socio-environmental management instruments. The question of whether these instruments are adequate to address the main social and environmental issues considering the particularities of this extractive activity taking place in unique geographic settings remains to be assessed. This project aims to understand the main socio-environmental issues associated with lithium extraction in the Lithium Triangle; and, through case studies, to assess whether existing socio-environmental assessment instruments are adequate for this activity and the complexity of this region.

Speaker: Enrico Scarpa

Date: Thursday 9th of November 2023, 1:15pm.

Abstract:

Starting from the 1990s, channel modeling research has been exploring how to replicate channel systems and examining the influence of modeling parameters on hydrocarbon recovery. Today, amid our strong commitment to ecological transitions, some of these investigations are shifting toward applications in CO2 storage and geothermal energy production. However, little attention has been directed towards understanding how facies elements within deposits affect the flow and heat transfer in geothermal energy systems. Often, small-scale heterogeneities in rock types are not represented in reservoir modeling due to the complexity of the geological models and the lack of data. This oversight leads to neglecting the reservoir connectivity of channel deposits. To tackle this absence, I aim to analyze how layers of shale within turbidite channels impact the performance of geothermal reservoirs. By using an appropriate stratigraphic grid setup, the volumes of the channels and the shale layers are preserved, allowing for the stochastic simulation of physical properties. Consequently, I will explore two geological scenarios: one with varied channels and another incorporating varied channels with shale layers. Using simple dynamic measurements, I will quantify the flow outcomes and compare these models. Results show that shale layers affect energy production, but the time for thermal breakthrough remains steady in both scenarios. This preliminary investigation prompts the inquiry of whether enhanced model realism is necessary for geothermal energy extraction.

Speaker: Jeremie Giraud

Date: Wednesday 8th of November 2023, 1:15pm.

Abstract:

This seminar will be divided into two main parts: In the first part, I will present an updated version of abstract S1214 that I presented in August at the IAMG 2023 Annual Meeting (Trondheim): I will introduce a trans-dimensional inversion technique for 3D gravity inversion, extending a multi-level set approach using signed-distance functions to model rock unit interfaces. It accommodates an unknown number of rock units through a birth-and-death process, allowing the addition or removal of units. It also allows the recovery of rock unit geometry and densities. In this presentation, I will show an application example in an undercover imaging scenario using data from the Boulia region (Queensland, Australia). Results suggest the presence of rock units concealed from surface geology and show the potential for the method to recover hidden geological features. In the second part, I will present some the non-scientific things I learned through my now-completed Marie Skłodowska-Curie Fellowship. The work that I will present was funded by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 101032994.