This seminar is part of the Tuesday Seminar Series organized by the Center for Hydrogeology and Geothermics (CHYN) at the University of Neuchâtel. We are pleased to welcome Prof. Niklas Linde from the University of Lausanne (UNIL), who will discuss innovative approaches to improving the realism of inverse modeling in hydrogeophysics.

Abstract
Geophysics provides critical insights about subsurface heterogeneity and processes for water resource management, ecosystem understanding and others. After data acquisition and processing, the data are inverted to infer spatially distributed estimates of physical properties. The classical approach to inverse modeling consists of fitting the data by perturbing a subsurface model by gradient-based optimization such that one unique model is obtained. A geophysicist or groundwater hydrologist pursuing interdisciplinary collaborations may then be placed in one of two equally uncomfortable situations when presenting the model obtained by such an inversion strategy: the collaborators may consider it as reality (it is not) or as useless as it doesn’t contain realistic-looking texture or features. As an alternative, the late Albert Tarantola proposed a movie strategy in which the disciplinary scientist should judge if the images passing by in the ‘‘movie’’ appeared realistic and the geophysicist should produce realizations that not only had this realistic look, but also explained the available data. Such an inversion approach needs to be probabilistic in nature, using for instance a Bayesian formulation and it comes with several conceptual and computational challenges. This talk will explain how such inversions can be achieved using multiple-point statistics methodologies or deep generative modeling. It will then demonstrate how computational speed-ups can be achieved by Bayesian variational inference and/or using surrogate models emulating computationally expensive physics-based numerical simulations. Finally, Bayesian model selection will be introduced to demonstrate how data can be used to test alternative conceptual models. Illustrative examples will be given in the context of environmental geophysics and groundwater hydrology.

Speaker biography
Niklas Linde is a professor of environmental geophysics at the University of Lausanne (UNIL) in Switzerland. He studied environmental engineering at Uppsala University in Sweden before completing a PhD in geophysics at the same university in 2005. During his PhD, he spent one year at Lawrence Berkeley National University, California. After a one-year post-doc at Aix-Marseille University in France and a two-year postdoc at ETHZ in Switzerland, he joined the faculty at UNIL in 2008. His main research interests revolve around hydrogeophysics, inverse theory, uncertainty quantification, deep learning and Bayesian model selection for environmentally relevant applications. He recently ended a three-year term as Dean of the Faculty of Earth Sciences and the Environment at UNIL and is currently enjoying a one-year sabbatical leave.