Dan-Thuy LamSwiss Federal Statistical Office · Data Science
Dan-Thuy Lam
PhD
About
4
Publications
540
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7
Citations
Citations since 2017
Introduction
My PhD focuses on the implementation of Data Assimilation algorithms for identifying the parameters of numerical groundwater flow models. Although the ensemble-based Kalman algorithms (e.g. EnKF, ES-MDA) are known for their computational efficiency, their strong linearity assumptions make their application very challenging for discrete parameter estimation problems in subsurface flow modeling. For such suboptimal contexts, it becomes necessary to develop parameterization strategies...
Additional affiliations
January 2022 - April 2022
Swiss Federal Statistical Office
Position
- Trainee data scientist
October 2015 - March 2020
Position
- PhD Student
Description
- Calibration of transient groundwater flow models with data assimilation approaches
March 2014 - September 2014
Position
- Intern in quantitative hydrogeology
Description
- Numerical modeling of flow and contaminant transport in the unsaturated zone
Education
September 2009 - November 2014
Publications
Publications (4)
**Please note that the uploaded PDF is for educational and academic purposes only and is not intended for mass dissemination.** - - A new methodology is presented for the conditioning of categorical multiple‐point statistics (MPS) simulations to dynamic data with an iterative ensemble smoother (ES‐MDA). The methodology relies on a novel multi‐resol...
Data assimilation (DA) consists in combining observations and predictions of a numerical model to produce an optimal estimate of the evolving state of a system. Over the last decade, DA methods based on the Ensemble Kalman Filter (EnKF) have been particularly explored in various geoscience fields for inverse modelling. Although this type of ensembl...
Over the last decade, data assimilation methods based on the ensemble Kalman filter (EnKF) have been particularly explored in various geoscience fields to solve inverse problems. Although this type of ensemble methods can handle high-dimensional systems, they assume that the errors coming from whether the observations or the numerical model are mul...
Prediction of hydraulic perturbations induced by the construction and the operation of deep geological radioactive waste repository is need to support: (i) the engineering and monitoring operations, and (ii) the assessment of the consequences on groundwater resources. Andra (French National Radioactive Waste Management Agency) has developed a three...
Projects
Project (1)
This project focuses on the application of existing state-of-the-art ensemble Kalman algorithms for the calibration of a transient groundwater flow model. Given the strong linearity assumptions made by these algorithms, it becomes necessary in suboptimal but rather common contexts of application to reflect on proper parameterization strategies. The goal is to test & develop approaches which leverage these methods in a way that still enables meaningful results.
