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Renard, Philippe

Nom
Renard, Philippe
Affiliation principale
Site web
Fonction
Directeur de Recherche
Email
Philippe.Renard@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/150
_
0000-0003-4504-435X

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  • Publication
    Accès libre
    An Attempt to Boost Posterior Population Expansion Using Fast Machine Learning Algorithms
    (2021-3)
    Juda, Przemyslaw 
    ;
    Renard, Philippe 
    In hydrogeology, inverse techniques have become indispensable to characterize subsurface parameters and their uncertainty. When modeling heterogeneous, geologically realistic discrete model spaces, such as categorical fields, Monte Carlo methods are needed to properly sample the solution space. Inversion algorithms use a forward operator, such as a numerical groundwater solver. The forward operator often represents the bottleneck for the high computational cost of the Monte Carlo sampling schemes. Even if efficient sampling methods (for example Posterior Population Expansion, PoPEx) have been developed, they need significant computing resources. It is therefore desirable to speed up such methods. As only a few models generated by the sampler have a significant likelihood, we propose to predict the significance of generated models by means of machine learning. Only models labeled as significant are passed to the forward solver, otherwise, they are rejected. This work compares the performance of AdaBoost, Random Forest, and convolutional neural network as classifiers integrated with the PoPEx framework. During initial iterations of the algorithm, the forward solver is always executed and subsurface models along with the likelihoods are stored. Then, the machine learning schemes are trained on the available data. We demonstrate the technique using a simulation of a tracer test in a fluvial aquifer. The geology is modeled by the multiple-point statistical approach, the field contains four geological facies, with associated permeability, porosity, and specific storage values. MODFLOW is used for groundwater flow and transport simulation. The solution of the inverse problem is used to estimate the 10 days protection zone around the pumping well. The estimated speed-ups with Random Forest and AdaBoost were higher than with the convolutional neural network. To validate the approach, computing times of inversion without and with machine learning schemes were computed and the error against the reference solution was calculated. For the same mean error, accelerated PoPEx achieved a speed-up rate of up to 2 with respect to the standard PoPEx.
  • Publication
    Accès libre
    An optical laser device for mapping 3D geometry of underwater karst structures: first tests in the Ox Bel’Ha system, Yucatan, Mexico
    (2016)
    Schiller, A
    ;
    Renard, Philippe 
    In the course of extended hydrological studies in the coastal Karst plain of Yucatan, near the town of Tulum amongst others, a novel laser scanning device was developed and applied for the acquisition of the 3d-geometry of ground water conduits. The method is derived from similar industrial systems and for the first time adapted to the specific measurement conditions in underwater cave systems. The device projects a laser line over the whole perimeter at a certain position. This line represents the intersection of a plane with the cave walls. The line is imaged with a wide angle camera system. Through proper design and calibration of the device it is possible to derive the true scale geometry of the perimeter via special image processing techniques. By acquiring regularly spaced images it is possible to reconstruct the true scale and 3 d-shape of a tunnel through the incorporation of location and attitude data. In a first test in the Ox Bel Ha under-water cave system, about 800 metres of tunnels have been scanned down to water depths of 20 metres. The raw data is further interpolated using the ODSIM-algorithm in order to delineate the 3D geometry of the cave system. The method provides easy, operable acquisition of the 3-D geometry of caves in clear water with superior resolution and speed and significantly facilitates the measurement in underwater tunnels as well as in dry tunnels. The data gathered represents crucial input to the study of the state, dynamics and genesis of the complex karst water regime., Durante el transcurso de intensivos estudios hidrológicos realizados en la llanura costera kárstica de Yucatán, cerca de la ciudad de Tulum entre otras, se desarrolló un novedoso dispositivo de escaneo láser, que se aplicó a la adquisición de la geometría 3D de conductos de agua subterránea. El método se deriva de sistemas industriales similares y que ha sido adaptado por primera vez a las condiciones de medición específicas de los sistemas de cuevas submarinas. El dispositivo proyecta una línea láser sobre todo el perímetro en una localización dada. Esta línea representa la intersección de un plano con las paredes de las cuevas. La línea es fotografiada con un sistema de cámara de gran angular. A través de un apropiado diseño y calibración del dispositivo es posible obtener la geometría verdadera del perímetro a través de técnicas especiales de procesamiento de imágenes. De este modo, adquiriendo regularmente imágenes a intervalos espaciados es posible reconstruir la escala verdadera y la forma 3D de un túnel con la incorporación de los datos de posición e inclinación. En una primera prueba en el sistema de la cueva submarina Ox Bel Ha, se escanearon alrededor de 800 metros de túneles hasta profundidades, bajo el agua, de 20 metros. Los datos en bruto son interpolados utilizando el algoritmo de ODSIM para delinear la geometría 3D del sistema de cuevas. El método proporciona una adquisición sencilla y operativa de la geometría tridimensional de cuevas submarinas con aguas claras, con muy buenas resolución y velocidad lo que facilita la medición en conductos submarinos así como en túneles subaéreos. Los datos recogidos representan una información fundamental para el estudio del estado, dinámica y génesis del complejo régimen del agua kárstica.
  • Publication
    Accès libre
    Analog-based meandering channel simulation
    (2014-1-10)
    Mariethoz, Grégoire 
    ;
    Comunian, Alessandro
    ;
    Irarrazaval, Inigo
    ;
    Renard, Philippe 
  • Publication
    Accès libre
    Grid-enabled Monte Carlo analysis of the impacts of uncertain discharge rates on seawater intrusion in the Korba aquifer (Tunisia)
    (2010)
    Kerrou, Jaouhar 
    ;
    Renard, Philippe 
    ;
    Lecca, Giuditta
    ;
    Tarhouni, Jamila
    L'aquifère de Korba, situé au nord de la Tunisie, est gravement touché par une salinisation du à l'intrusion marine. En 2000, l'aquifère a été exploité par plus de 9000 puits. Le problème, c'est qu'il n'y a pas d'information précise concernant les débits de pompage, leur répartition dans l'espace ainsi que leur évolution dans le temps. Dans cette étude, un modèle géostatistique des débits d'exploitation a été construit en se basant sur une régression multilinéaire combinant des données directes incomplètes ainsi que des données secondaires exhaustives. Les impacts de l'incertitude associée à la distribution spatiale des débits de pompage sur l'intrusion marine ont été évalués en utilisant un modèle tridimensionnel d'écoulement et de transport à densité variable. Pour contourner les difficultés liées à de longs temps de calcul, nécessaires pour résoudre des problèmes en régime transitoire, les simulations ont été réalisées en parallèle sur une grille informatique de calcul mise à disposition par le projet “Enabling Grid for E-Science in Europe”. Les résultats des simulations de Monte Carlo ont montré que 8.3% de la surface de l'aquifère est affectée par l'incertitude liée aux données d'entrée., The Korba aquifer, located in the north of Tunisia, suffers heavily from salinization due to seawater intrusion. In 2000, the aquifer was exploited from more than 9000 wells. The problem is that no precise information was recorded concerning the current extraction rates, their spatial distribution, or their evolution in time. In this study, a geostatistical model of the exploitation rates was constructed based on a multi-linear regression model combining incomplete direct data and exhaustive secondary information. The impacts of the uncertainty on the spatial distribution of the pumping rates on seawater intrusion were evaluated using a 3-D density-dependent groundwater model. To circumvent the large amount of computing time required to run transient models, the simulations were run in a parallel fashion on the Grid infrastructure provided by the Enabling Grid for E-Science in Europe project. Monte Carlo simulations results showed that 8.3% of the aquifer area is affected by input uncertainty.