Auscultation des barrages en béton par écoute microsismique : détectabilité et localisation des événements

Auscultation des barrages -- Auscultation des ouvrages d'art au moyen de la technique des émissions acoustiques -- Rayon d'action théorique -- Évaluation de l'atténuation sismique sur un barrage en béton -- Détermination d'un modèle de bruit -- Calcul des sismogrammes synthétiques -- Calcul des rayons critiques -- Localisation des événements -- Techniques de localisation des hypo-centres -- Modélisation numérique de la propagation des ondes sismiques -- Localisation des événements par inversion conjointe hypocentre-vitesse des temps d'arrivée -- Axes de recherche suggérés -- Détection des événements par traitement du signal -- Étude des mécanismes au foyer

Yves Combeau, Toujours prêts. Histoire du scoutisme catholique en France | Charles-Édouard Harang, L’aventure par nature, 100 ans des Scouts et guides de France

Les célébrations du centenaire du scoutisme (1907) puis de la fondation des Scouts de France (1921) ont stimulé un courant de recherche, soutenu en son temps par Gérard Cholvy. On disposait de volumineuses synthèses (Philippe Laneyrie, Les Scouts de France, Paris, 1985 ; Christian Guérin, L’utopie Scouts de France, Paris, 1997 et Marie-Thérèse Cheroutre, Le Scoutisme au féminin, Paris, 2002) et de colloques (Gérard Cholvy, Marie-Thérèse Cheroutre (dir.), Le Scoutisme, Paris, 1994, et Gérard C..

Characteristics of Precambrian basement intruded by Cretaceous geological intrusions in Monteregian Igneous Province and their impacts on regional thermal structure

With the progress of geothermal exploration in deep buried geological bodies, high radiogenic geological intrusions have become the hot spot in recent years. However, the assessment of the complex structure, lithology of geological intrusions by the geophysical methods has uncertainty, making it a challenging to accurately predict the thermal structure around the geological intrusions. In southern Québec, Canada, recent studies show that a relative high surface heat flux has been detected in the region enclosed by Montréal, Salaberry-de-Valleyfield and Saint-Jean-sur-Richelieu, around the southwest of the Monteregian Hills, which belong to the Early Cretaceous alkaline and carbonatite intrusions. It is not clear whether these Monteregian intrusions have impacts on the thermal anomaly of the Montréal, Salaberry-de-Valleyfield and Saint-Jean-sur-Richelieu region. The objective of this paper is to numerically investigate the thermal structure in the thermal anomaly region, considering the impact of different Monteregian intrusions. The simplified Monteregian intrusions are embedded into a three-dimensional geological model consisting of the sedimentary formations in the St. Lawrence Lowlands and the simulator Underworld2 is used for the thermal modelling. Simulation results show that the geological intrusions in this region have large impacts on the thermal structure at the local-scale, depending on the radiogenic heat production, thermal conductivity, emplacement depth and size. Temperature in the sedimentary formations may be lower or higher than that of the adjacent geological intrusions, highly depending on the thermal physical characteristics of these intrusions. Furthermore, the complex fault systems also strongly control the thermal distribution in different fault blocks, making the Potsdam Group sandstone located between the Grand-St-Esprit and Notre-Dame-du-Bon-Conseil faults as the potential geothermal reservoir.Cited as: Liu, H., Ban, S., Bédard, K., Giroux, B. Characteristics of Precambrian basement intruded by Cretaceous geological intrusions in Monteregian Igneous Province and their impacts on regional thermal structure. Advances in Geo-Energy Research, 2022, 6(3): 206-220. https://doi.org/10.46690/ager.2022.03.0

Effects of Plant Cover Improvements for Nesting Ducks on Grassland Songbirds

Several islands located along the St. Lawrence River in southern Quebec have been used as natural pastureland by cattle for decades. Recently, a rest-rotation grazing system and dense nesting cover were established on four islands near Varennes to improve duck nesting conditions. The effects of these two plant cover improvements on the abundance of grassland songbirds were assessed through four treatments: (1) idle fields with no vegetation improvement but exclusion of cattle (IDLE), (2) improved pastures with seeding of forage plants for cattle (IMPP), (3) dense seeded nesting cover fields improved for ducks and where cattle were excluded (DNC), and (4) natural or unimproved pastures grazed by cattle after the duck nesting season (UIPP). The overall abundance of birds was similar among treatments before cover improvements as well as two years after. The abundance of Bobolinks (Dolichonyx oryzivorus) was significantly greater in DNC and UIPP two years after treatments while Red-winged Blackbirds (Agelaius phoeniceus) were more abundant in DNC and IDLE. Plant cover improvements had little impact on Savannah Sparrow (Passerculus sandwichensis) abundance. Furthermore, few annual or treatment-related changes were observed for less abundant species. On the short-term, duck nesting cover improvements in natural pastures did not have any major effect on grassland songbirds on Varennes islands

CCWSIM: An Efficient and Fast Wavelet-Based CCSIM for Categorical Characterization of Large-Scale

Over the last couple of decades, there has been a surge in various approaches to multiple-point statistics simulation, commonly referred to as MPS. These methods have aimed to improve several critical aspects of realism in the results, including spatial continuity, conditioning, stochasticity, and computational efficiency. Nevertheless, achieving a simultaneous enhancement of these crucial factors has presented challenges to researchers. In the approach that we propose, CCSIM is combined with the Discrete Wavelet Transform (DWT) to address some of these concerns. The primary step in the method involves the computation of the DWT for both the Training Image (TI) and a region shared with previously simulated grids at a specific level of wavelet decomposition. Then, the degree of similarity between the wavelet approximation coefficients is measured using a Cross-Correlation Function (CCF). These approximation coefficients offer a compressed representation of the pattern while capturing its primary variations and essential characteristics, thereby expediting the search for the best-matched pattern. Once the best-matched pattern in the wavelet approximation coefficients is identified, the original pattern can be perfectly reconstructed by integrating the DWT detail coefficients through an Inverse-DWT transformation. Experiments conducted across diverse categorical TIs demonstrate simulations comparable to multi-scale CCSIM (MS-CCSIM), accompanied by an enhancement in facies connectivity and pattern reproduction. The source code implementations are available at https://github.com/MBS1984/CCWSIM

A fine-tuning workflow for automatic first-break picking with deep learning

First-break picking is an essential step in seismic data processing. First arrivals should be picked by an expert. This is a time-consuming procedure and subjective to a certain degree, leading to different results for different operators. In this study, we used a U-Net architecture with residual blocks to perform automatic first-break picking based on deep learning. Focusing on the effects of weight initialization on this process, we conduct this research by using the weights of a pretrained network that is used for object detection on the ImageNet dataset. The efficiency of the proposed method is tested on two real datasets. For both datasets, we pick manually the first breaks for less than 10% of the seismic shots. The pretrained network is fine-tuned on the picked shots and the rest of the shots are automatically picked by the neural network. It is shown that this strategy allows to reduce the size of the training set, requiring fine tuning with only a few picked shots per survey. Using random weights and more training epochs can lead to a lower training loss, but such a strategy leads to overfitting as the test error is higher than the one of the pretrained network. We also assess the possibility of using a general dataset by training a network with data from three different projects that are acquired with different equipment and at different locations. This study shows that if the general dataset is created carefully it can lead to more accurate first-break picking, otherwise the general dataset can decrease the accuracy. Focusing on near-surface geophysics, we perform traveltime tomography and compare the inverted velocity models based on different first-break picking methodologies. The results of the inversion show that the first breaks obtained by the pretrained network lead to a velocity model that is closer to the one obtained from the inversion of expert-picked first breaks

Non-destructive data assimilation as a tool to diagnose corrosion rate in reinforced concrete structures.

La transcription des symboles et des caractères spéciaux utilisés dans la version originale de ce résumé n’a pas été possible en raison de limitations techniques. La version correcte de ce résumé peut être lue en PDF.Reinforcement corrosion is a major problem in the long-term management of reinforced concrete structures. With sustainability in perspective, knowledge of the corrosion rate (Vcor) makes it possible to estimate the kinetics of the corrosion phenomenon and helps in refining the maintenance strategy of such structures. Although in situ Vcor measurements are possible, data acquisition is time-consuming because of the protocol intrinsic to its measurement (reinforcement polarization made point by point). Therefore, in the context of site diagnostics, these methods cannot reasonably be used systematically on site and must be combined with high performance non-destructive testing (NDT) surface methods (GPR, capacimetry, half-cell corrosion). In addition, depending on the case, Vcor (point measurements) and NDT(surface) data are statistically related. However, there is a lack of efficient data assimilation tools permitting accurate translation of NDT data into pseudo Vcor data. In this paper, we present a numerical tool allowing prediction of Vcor values from NDT measurements. The tool permits application of different data assimilation techniques, i.e., cokriging, Bayesian sequential simulation, and a decision tree-driven learning depending on statistical behavior and available data. The efficiency of our numerical tool has been tested on a dataset acquired on a structure located in the French Alps. Results show that, for the case study, our data assimilation tool allows prediction of Vcor with accuracy compared to in situ measurements and also permits one to infer the uncertainty of the prediction. This opens the door for quantitative use of multiple NDT in the management of reinforced concrete structures.</p