Low Temperature Deep Geothermal Operations for Direct Use in France: development of a national geothermal database and last review

International audienceAs part of a better monitoring of low temperature (30-150 °C) deep geothermal operations for heat production in France and in order to promote this form of renewable energy throughout the national territory, BRGM (French Geological Survey) in collaboration with ADEME (French Environment and Energy Management Agency) have implemented an application (web-based geothermal database) to follow-up detailed information on geothermal operations. Initially the database was defined to collect and disseminate geothermal data of the "Dogger" aquifer exploitations of the Paris basin, first sustainable aquifer used for district heating in France. Since 2018, the database has been extended to all deep geothermal operations in France for direct use (i.e. Paris basin, Aquitaine basin, Rhine Graben, South East basin, Limagne) and counts about 220 geothermal wells with 135 wells still operating. The objective of this "national" database is to provide valuable information to project developers who need accurate data during feasibility studies and regulation and permitting processes. It also targets local authorities and private or public stakeholders to provide them information about current operations, resources and potential applications for heating. Moreover, the system is also promoting the use of geothermal energy as part of the objectives of the law on Energy Transition and Green Growth, which sets a target of 38% of renewable energy sources in final heat consumption by 2030 in France. The article gives also a review of low temperature geothermal operations in France. 1. INTRODUCTION In order to identify and monitor deep geothermal exploitations for low temperature heat production (temperature range between 30-150°C) in France, BRGM and ADEME have developed a geothermal database in the early 2000's. Initially this geothermal database included well and reservoir characteristics (location, deviation, casing information, depth, hydrodynamic parameters…) and well monitoring data (pressure, temperature, flowrate, chemistry) of the Dogger limestone aquifer in Paris basin which is the main targeted aquifer for district heating networks in France since the early 1970's. Since 2007, with the successful recovery of geothermal activity, and after 20 years of no new geothermal operations, 60 deep geothermal wells were drilled in the Paris basin in Ile-de-France region for the supply of district heating networks. Other operations are in progress or have been carried out in the Rhine Graben for heat production or cogeneration (heat and electricity) due to higher temperatures and also in the Aquitaine basin (second sedimentary basin in France harnessed for geothermal energy) in Nouvelle-Aquitaine region with the implementation of a first deep geothermal operation (doublet) targeting the Jurassic limestone in summer 2019

Hyperspectral images segmentation: a proposal

Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous wavebands in a given spectral band. These images provide information on the chemical make-up profile of objects, thus allowing the differentiation of objects of the same colour but which possess make-up profile. Yet, whatever the application field, most of the methods devoted to HIS processing conduct data analysis without taking into account spatial information.Pixels are processed individually, as an array of spectral data without any spatial structure. Standard classification approaches are thus widely used (k-means, fuzzy-c-means hierarchical classification...). Linear modelling methods such as Partial Least Square analysis (PLS) or non linear approaches like support vector machine (SVM) are also used at different scales (remote sensing or laboratory applications). However, with the development of high resolution sensors, coupled exploitation of spectral and spatial information to process complex images, would appear to be a very relevant approach. However, few methods are proposed in the litterature. The most recent approaches can be broadly classified in two main categories. The first ones are related to a direct extension of individual pixel classification methods using just the spectral dimension (k-means, fuzzy-c-means or FCM, Support Vector Machine or SVM). Spatial dimension is integrated as an additionnal classification parameter (Markov fields with local homogeneity constrainst [5], Support Vector Machine or SVM with spectral and spatial kernels combination [2], geometrically guided fuzzy C-means [3]...). The second ones combine the two fields related to each dimension (spectral and spatial), namely chemometric and image analysis. Various strategies have been attempted. The first one is to rely on chemometrics methods (Principal Component Analysis or PCA, Independant Component Analysis or ICA, Curvilinear Component Analysis...) to reduce the spectral dimension and then to apply standard images processing technics on the resulting score images i.e. data projection on a subspace. Another approach is to extend the definition of basic image processing operators to this new dimensionality (morphological operators for example [1, 4]). However, the approaches mentioned above tend to favour only one description either directly or indirectly (spectral or spatial). The purpose of this paper is to propose a hyperspectral processing approach that strikes a better balance in the treatment of both kinds of information....Cet article présente une stratégie de segmentation d’images hyperspectrales liant de façon symétrique et conjointe les aspects spectraux et spatiaux. Pour cela, nous proposons de construire des variables latentes permettant de définir un sous-espace représentant au mieux la topologie de l’image. Dans cet article, nous limiterons cette notion de topologie à la seule appartenance aux régions. Pour ce faire, nous utilisons d’une part les notions de l’analyse discriminante (variance intra, inter) et les propriétés des algorithmes de segmentation en région liées à celles-ci. Le principe générique théorique est exposé puis décliné sous la forme d’un exemple d’implémentation optimisé utilisant un algorithme de segmentation en région type split and merge. Les résultats obtenus sur une image de synthèse puis réelle sont exposés et commentés

Inventory and First Assessment of Oil and Gas Wells Conversion for Geothermal Heat Recovery in France

International audienceThe repurposing of oil and gas wells for geothermal energy production and resource assessment can provide sustainable solutions to meet the objectives of renewable energy balance targeted within 2030 by the French Parliament in the "energy transition law for a green growth" promulgated in August 2015. Approximately 12 500 wells have been drilled in France since the 19th century for hydrocarbon reservoir exploration and exploitation. Most of them are closed and abandoned or nearing the end of production due to the planned end of exploitation of hydrocarbons in France by 2040. Several sustainable cases of conversion for geothermal energy production have been reported in France and abroad, demonstrating the possibility of using former wells for heat extraction from aquifers or coaxial heat exchangers. This paper presents an overview of the wells drilled in France and the methodology proposed to identify and rank them according to the a priori feasibility of open and closed loop conversion. To this purpose, wells data, geological and hydrothermal information acquired by the BRGM (geometry and dynamic aquifer properties from models) and land occupation have been cross-referenced. The quantitative overview should be followed by a detailed analysis of selected wells to assess their conversion potential for geothermal energy production (possible use at surface, well drilling and abandonment reports, hydrodynamic properties of the reservoir, technology to be implemented, etc.)

Hyperspectral image segmentation: the butterfly approach

International audienceFew methods are proposed in the litterature for coupling the spectral and the spatial dimension available on hyperspectral images. This paper proposes a generic segmentation scheme named butterfly based on an iterative process and a cross analysis of spectral and spatial information. Indeed, spatial and spatial structures are extracted in spatial and spectral space respectively both taking into account the other one. To apply this layout on hyperspectral imgages, we focus particulary on spatial and spectral structures i.e. topologic concepts and latent variable for the spatial and the spectral space respectively. Moreover, a cooperation scheme with these structures is proposed. Finally, results obtained on real hyperspectral images using this specific implementation of the butterfly approach are presented and discussed

Innovations et gouvernance territoriale : une analyse par les dispositifs

Cette communication vise à présenter les outils méthodologiques d'analyse/évaluation de la gouvernance territoriale élaborés dans le cadre du projet de recherche PSDR Gouv.Innov sur les innovations organisationnelles relatives à la gouvernance territoriale. Il s'agit d'étudier les transformations introduites par les politiques de développement durable au niveau des dispositifs de gouvernance territoriale visant à favoriser une gestion intégrée des espaces ruraux. Dans un contexte de recomposition de l'action publique où les procédures d'aménagement sont plutôt normées par des représentations urbaines, l'accent est mis sur la question des modalités de représentation des activités rurales, pour lesquelles nous faisons l'hypothèse qu'elles sont sous représentées. Les premiers résultats méthodologiques permettent, dans une première partie, de proposer une définition générique et pragmatique de la gouvernance territoriale et de préciser la notion de dispositifs de gouvernance comme objet d'observation. A partir de cette définition une grille d'analyse permettant d'appréhender l'ensemble des dimensions en jeu dans les processus de gouvernance territoriale est élaboré. Dans la deuxième partie nous explorons l'intérêt de la notion de dispositif pour observer les processus de gouvernance et proposons une grille de collecte et de structuration des informations pour constituer des chroniques des dispositifs étudiés.(Résumé d'auteur

ETUDE EXPERIMENTALE D'UN JET PLAN EN IMPACT ANALYSE PARAMETRIQUE ET CARACTERISATION DES TRANSFERTS DE MASSE

NANTES-Ecole Centrale (441092306) / SudocNANTES-BU Sciences (441092104) / SudocSudocFranceF

Towards efficient fmri data re-use: can we run between-group analyses with datasets processed differently with spm ?

International audienceThe increased amount of shared data creates an opportunity to reuse existing data to reach larger sample sizes and hence increase statistical power in neuroimaging studies. However, doing so may require to perform analyses using subject data processed differently. Here, we performed between-group analyses under the null hypothesis (making any detection a false positive), with data from the Human Connectome Project (HCP) (n=1080) processed with different pipelines. We compared the estimated false positive rates obtained to the theoretical false positive rate, to assess whether the variability in processing pipelines (called analytical variability) impacts the validity of the analyses. We found that some differences in parameter values caused invalidity, suggesting that analytical variability has to be taken into account before combining subject data processed with different pipelines

Des études de groupe aux analyses individuelles dans l'exploration de la fonction cérébrale en imagerie de perfusion par marquage de spins et en IRM fonctionnelle BOLD

Cette thèse aborde l'étude de la fonction cérébrale en Imagerie par Résonance Magnétique (IRM) à l'aide de deux séquences : l'IRM fonctionnelle (IRMf) BOLD et l'imagerie de perfusion par marquage de spins (ASL). Dans ce contexte, les analyses de groupe jouent un rôle important dans l'identification des dysfonctionnements globaux associés à une pathologie. D'autre part, les études individuelles, qui fournissent des conclusions au niveau d'un sujet unique, présentent un intérêt croissant. Dans ce travail, nous abordons à la fois les études de groupe et les analyses individuelles. Dans un premier temps, nous réalisons une analyse de groupe en IRMf BOLD en vue d'étudier la dysphasie chez l'enfant, une pathologie peu explorée en neuroimagerie. Nous mettons ainsi en évidence un fonctionnement et une latéralisation atypiques des aires langagières. Ensuite, nous nous concentrons sur les analyses individuelles. Nous proposons l'utilisation d'estimateurs robustes pour calculer les cartographies de débit sanguin cérébral en ASL. Ensuite, nous étudions la validité des hypothèses qui sous-tendent les analyses statistiques standard dans le contexte de l'ASL. Finalement, nous proposons une nouvelle méthode localement multivariée basée sur une approche a contrario. La validation de cette nouvelle approche est réalisée dans deux contextes applicatifs : la détection d'anomalies de perfusion en ASL et la détection de zones d'activation en IRMf BOLD.This thesis deals with the analysis of brain function in Magnetic Resonance Imaging (MRI) using two sequences: BOLD functional MRI (fMRI) and Arterial Spin Labelling (ASL). In this context, group statistical analyses are of great importance in order to understand the general mechanisms underlying a pathology, but there is also an increasing interest towards patient-specific analyses that draw conclusions at the patient level. Both group and patient-specific analyses are studied in this thesis. We first introduce a group analysis in BOLD fMRI for the study of specific language impairment, a pathology that was very little investigated in neuroimaging. We outline atypical patterns of functional activity and lateralisation in language regions. Then, we move forward to patient-specific analysis. We propose the use of robust estimators to compute cerebral blood flow maps in ASL. Then, we analyse the validity of the assumptions underlying standard statistical analyses in the context of ASL. Finally, we propose a new locally multivariate statistical method based on an a contrario approach and apply it to the detection of atypical patterns of perfusion in ASL and to activation detection in BOLD functional MRI.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Towards efficient fmri data re-use: can we run between-group analyses with datasets processed differently with spm ?

International audienceThe increased amount of shared data creates an opportunity to reuse existing data to reach larger sample sizes and hence increase statistical power in neuroimaging studies. However, doing so may require to perform analyses using subject data processed differently. Here, we performed between-group analyses under the null hypothesis (making any detection a false positive), with data from the Human Connectome Project (HCP) (n=1080) processed with different pipelines. We compared the estimated false positive rates obtained to the theoretical false positive rate, to assess whether the variability in processing pipelines (called analytical variability) impacts the validity of the analyses. We found that some differences in parameter values caused invalidity, suggesting that analytical variability has to be taken into account before combining subject data processed with different pipelines