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Your search keyword '"Collet, Olivia"' showing total 16 results
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16 results on '"Collet, Olivia"'

1. Supervised Deep Learning for Detecting and Locating Passive Seismic Events Recorded with DAS: A Case Study.

Author

Al-Hemyari, Emad, Collet, Olivia, Tertyshnikov, Konstantin, and Pevzner, Roman

Abstract

Exploring shallow mineral resources requires acquiring denser seismic data, for which Distributed Acoustic Sensing is an effective enabler and relevant to mining operations monitoring. Passive seismic can be of interest in characterizing the subsurface; however, dealing with large amounts of data pushes against the limits of existing computational systems and algorithms, especially for continuous monitoring. Hence, more than ever, novel data analysis methods are needed. In this article, we investigate using synthetic seismic data, paired with real noise recordings, as part of a supervised deep-learning neural network methodology to detect and locate induced seismic sources and explore their potential use to reconstruct subsurface properties. Challenges of this methodology were identified and addressed in the context of induced seismicity applications. Data acquisition and modelling were discussed, preparation workflows were implemented, and the method was demonstrated on synthetic data and tested on relevant seismic monitoring field dataset from the Otway CO2 injection site. Conducted tests confirmed the effects of time shifts, signal-to-noise ratios, and geometry mismatches on the performance of trained models. Those promising results showed the method's applicability and paved the way for potential application to more field data, such as seismic while drilling. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Diagnostic des méthodes, outils et pratiques de prise en charge de jeunes ayant un trouble du spectre autistique

Author

Collet, Olivia, Université de Rennes 2 - UFR Activités physiques et sportives (UR2 UFRAPS), Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Violences, Innovations, Politiques, Socialisations et Sports (VIPS2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Le Mans Université (UM)-École normale supérieure - Rennes (ENS Rennes), and Geneviève Cabagno

Subjects
Tools, Activité physique adaptée, Outils, Method, Adapted physical activity, Méthode, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Diagnostic, Autism spectrum disorder, Troubles du spectre autistique (TSA), [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Understanding and managing automatic spectrum disorders (ASD), following their increasing prevalence, are important issues in terms of public health, for the inclusion in society of people with this disorder. ASD is characterized by behavioural disorders and a deficit in social communication. Individuals with ASD may also have other disorders associated with this disability. The profiles of this population are varied, resulting in different needs and types of care. Adapted physical activities represent an interesting way for improving the many difficulties encountered by this population. Other methods like TEACCH and ABA and tools, such as Makaton and PECS, also make it possible to improve the behavioural and communication disorders of this population. This paper reviews various studies concerning the effect of adapted physical activities and the use of these methods and tools in the management of an audience with ASD. It highlights the need to conduct a field diagnosis of these tools, methods and practices used by professionals, in order to compare them with what is stated in the literature. This diagnosis also makes it possible to target the advantages and constraints of the various means of support and to identify the problems in the field that may cause a discrepancy between what is stated and what is achieved.; La compréhension et la gestion des Troubles du Spectre Autistique (TSA), suite à l’augmentation de leur prévalence, sont devenus des enjeux importants en termes de santé publique, pour l’inclusion dans la société des personnes porteuses de ce trouble. Le TSA se caractérise par des troubles du comportement et un déficit de communication sociale. Les personnes qui en sont atteintes peuvent également présenter d’autres troubles associés à ce handicap. Les profils de cette population sont variés induisant différents besoins et types de prises en charge. Les activités physiques adaptées représentent une piste intéressante dans l’amélioration des nombreuses difficultés rencontrées par ce public. D’autres méthodes comme TEACCH et ABA et outils tels que Makaton et PECS, permettent également d’améliorer les troubles comportementaux et de communication de ce public. Ce mémoire passe en revue différentes études concernant l’effet de la pratique des activités physiques adaptées et de l’utilisation de ces méthodes et outils dans la prise en charge d’un public ayant un TSA. Il met en avant la nécessité d’effectuer un diagnostic de terrain de ces outils, méthodes et pratiques utilisés par les professionnels, afin de les comparer avec ce qui est énoncé dans la littérature. Ce diagnostic permet également de cibler les avantages et contraintes des différents moyens d’accompagnement et d’identifier les problématiques de terrain pouvant être à l’origine d’un décalage entre ce qui est énoncé et ce qui est réalisé.

Published
2020

9. Theory-guided data science-based reservoir prediction of a North Sea oil field

Author

Downton, Jon, Collet, Olivia, Colwell, Tanya, Hampson, Dan, Downton, Jon, Collet, Olivia, Colwell, Tanya, and Hampson, Dan

Abstract

Data science-based methods, such as supervised neural networks, provide powerful techniques to predict reservoir properties from seismic and well data without the aid of a theoretical model. In these supervised learning approaches, the seismic-to-rock property relationship is learned from the data. One of the major factors limiting the success of these methods is whether there exists enough labeled data, sampled over the expected geology, to train the neural network adequately. To overcome these issues, this paper explores hybrid theory-guided data science (TGDS)-based methods. In particular, we build a two-component model in which the outputs of the theory-based component are the inputs in the data science component. First, we simulate many pseudowells based on the well statistics in the project area. The reservoir properties, such as porosity, saturation, mineralogy, and thickness, are all varied to create a well-sampled data set. Elastic and synthetic seismic data are then generated using rock physics and seismic theory. The resulting collection of pseudowell logs and synthetic seismic data, called the synthetic catalog, is used to train the neural network. The derived operator is then applied to the real seismic data to predict reservoir properties throughout the seismic volume. This TGDS method is applied to a North Sea data set to characterize a Paleocene oil sand reservoir. The TGDS results better characterize the geology and well control, including a blind well, compared to a solely theory-based approach (deterministic inversion) and a data science-based approach (neural network using only the original wells). These results suggest that theory and data science can complement each other to improve reservoir characterization predictions.

Published
2020

15. Estimating azimuthal stress-induced P-wave anisotropy from S-wave anisotropy using sonic log or vertical seismic profile data.

Author

Collet, Olivia, Gurevich, Boris, and Duncan, Guy

Subjects
*SEISMIC anisotropy, *SHEAR waves, *P-waves (Seismology), *VERTICAL seismic profiling, *SEDIMENTARY rocks, *SEISMIC waves
Abstract

ABSTRACT Most sedimentary rocks are anisotropic, yet it is often difficult to accurately incorporate anisotropy into seismic workflows because analysis of anisotropy requires knowledge of a number of parameters that are difficult to estimate from standard seismic data. In this study, we provide a methodology to infer azimuthal P-wave anisotropy from S-wave anisotropy calculated from log or vertical seismic profile data. This methodology involves a number of steps. First, we compute the azimuthal P-wave anisotropy in the dry medium as a function of the azimuthal S-wave anisotropy using a rock physics model, which accounts for the stress dependency of seismic wave velocities in dry isotropic elastic media subjected to triaxial compression. Once the P-wave anisotropy in the dry medium is known, we use the anisotropic Gassmann equations to estimate the anisotropy of the saturated medium. We test this workflow on the log data acquired in the North West Shelf of Australia, where azimuthal anisotropy is likely caused by large differences between minimum and maximum horizontal stresses. The obtained results are compared to azimuthal P-wave anisotropy obtained via orthorhombic tomography in the same area. In the clean sandstone layers, anisotropy parameters obtained by both methods are fairly consistent. In the shale and shaly sandstone layers, however, there is a significant discrepancy between results since the stress-induced anisotropy model we use is not applicable to rocks exhibiting intrinsic anisotropy. This methodology could be useful for building the initial anisotropic velocity model for imaging, which is to be refined through migration velocity analysis. [ABSTRACT FROM AUTHOR]

Published
2016
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16. Proceedings of the 2021 Colloquium of the Network of Doctoral Students in Sports Studies

Author

Réseau Des Doctorants En études Sportives (REDESP), Rogeaux Augustin, Crublet Claire, Chiron Eléa, Chesnais Nolwenn, Collet Olivia, Puech Julien, Dizin Emmanuel, Orlane Messey, Florent Lefèvre, Malo Camus Le Pape, Axel Maugendre, Cyril THOMAS, Clémence Beaufrère, Arnaud Daviré, Jean-François MAREC, Inès Souid, Alexandre Perreau-Niel, Simon Lancelevé, Réveillé Jonathan, Félix Pavlenko, Julien Puech, and Maxime Rouzaut

Subjects
Sociall Change, Social Innovation, Physical Education, Social Inclusion, Sport
Abstract

This paper presents the abstracts of the oral presentations given at the 2021 Colloquium of the French Network of Doctoral Students in Sport Studies (Réseau des Doctorants en études Sportives - REDESP)., We would like to thank the Laboratory Violences Innovations Politiques Socialisations et Sport (VIPS2), the University of Rennes 2, the Ecole Normale Supérieure (ENS) of Rennes and the doctoral school Sociétés Temps Territoire (STT) for their support.

Published
2021
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