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Integrated methods for stochastic ensemble aquifer modelling (ENSEMBLE)

English title Integrated methods for stochastic ensemble aquifer modelling (ENSEMBLE)
Applicant Renard Philippe
Number 132249
Funding scheme Sinergia
Research institution Centre d'hydrogéologie et de géothermie Université de Neuchâtel
Institution of higher education University of Neuchatel - NE
Main discipline Hydrology, Limnology, Glaciology
Start/End 01.03.2011 - 28.02.2015
Approved amount 1'288'852.00
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All Disciplines (4)

Discipline
Hydrology, Limnology, Glaciology
Geology
Geophysics
Mathematics

Keywords (18)

numerical modelling; hydrogeophysics; ensemble modelling; geostatistics; alluvial deposits; inverse methods; error analysis; model simplification; kriging; optimization; Braided rivers; Heterogeneity; Hydrogeology; Geostatistics; Geophysics; Uncertainty Quantification; Model reduction; Sedimentology

Lay Summary (English)

Lead
The ENSEMBLE project integrates recent developments in geology, hydrology, numerical, and stochastic modeling to improve uncertainty quantification for groundwater applications.
Lay summary
The state of the art in modeling groundwater systems is related to developments in geology, physics, geophysics, hydrogeology, and mathematics. Too often, the research in these areas is pursued independently by different teams and is therefore not integrated around a unique vision. The aim of the ENSEMBLE project is therefore to integrate the recent developments in quantitative geology, hydrology, numerical, and stochastic modeling to increase our ability to understand and predict complex hydrological systems.The teams involved in the ENSEMBLE project (ETH Zürich, Stanford University, Universities of Basel, Bern, Neuchâtel and Lausanne) will focus their research on developing new integrated methods (multiple point statistics, joint hydrogeological and geophysical inversion, fast methods for uncertainty analysis, etc.) for the characterization of the heterogeneity of alluvial systems and for the efficient stochastic ensemble simulation of groundwater flow and solute transport in those systems. Four common field sites corresponding to different alluvial systems (Tagliamento, Thur, Birs, Herten) will be used to illustrate and test the concepts and methods developed in the project.
Direct link to Lay Summary Last update: 14.05.2014

Responsible applicant and co-applicants

Employees

Publications

Publication
Image synthesis with graph cuts: a fast model proposal mechanism in probabilistic inversion
Zahner Tobias, Lochbühler Tobias, Mariethoz Grégoire, Linde Niklas (2016), Image synthesis with graph cuts: a fast model proposal mechanism in probabilistic inversion, in Geophysical Journal International, 204(2), 1179-1190.
Functional error modeling for uncertainty quantification in hydrogeology
Josset Laureline, Ginsbourger David, Lunati Ivan (2015), Functional error modeling for uncertainty quantification in hydrogeology, in Water Resources Research , 51(2), 1050-1068.
Geological realism in hydrogeological and geophysical inverse modeling: A review
Linde Niklas, Renard Philippe, Mukerji Tapan, Caers Jef (2015), Geological realism in hydrogeological and geophysical inverse modeling: A review, in Advances in Water Resources, 86, 86-101.
Summary statistics from training images as prior information in probabilistic inversion
Lochbühler Tobias, Vrugt Jasper A., Sadegh Mojtaba, Linde Niklas (2015), Summary statistics from training images as prior information in probabilistic inversion, in Geophysical Journal International, 201, 157-171.
Tomogram-based comparison of geostatistical models: Application to the Macrodispersion Experiment (MADE) site
Linde Niklas, Lochbühler Tobias, Dogan Mine, Van Dam Remke L., Van Dam Remke L. (2015), Tomogram-based comparison of geostatistical models: Application to the Macrodispersion Experiment (MADE) site, in Journal of Hydrology, 531, 543-556.
Conditioning of Multiple-Point Statistics Facies Simulations to Tomographic Images
Lochbühler Tobias, Pirot Guillaume, Straubhaar Julien, Linde Niklas (2014), Conditioning of Multiple-Point Statistics Facies Simulations to Tomographic Images, in Mathematical Geosciences, 46, 625-645.
Falsification and corroboration of conceptual hydrological models using geophysical data
Linde Niklas (2014), Falsification and corroboration of conceptual hydrological models using geophysical data, in WIREs Water, 1(2), 1-21.
Prediction-focused subsurface modeling: Investigating the need for accuracy in flow-based inverse modeling
Scheidt Céline, Renard Philippe, Caers Jef (2014), Prediction-focused subsurface modeling: Investigating the need for accuracy in flow-based inverse modeling, in Mathematical Geosciences, 47(2), 173-191.
Probabilistic electrical resistivity tomography of a CO2 sequestration analog
Lochbuehler Tobias, Breen Stephen J., Detwiler Russell L., Vrugt Jasper A., Linde Niklas (2014), Probabilistic electrical resistivity tomography of a CO2 sequestration analog, in Journal of Applied Geophysics, 107, 80-92.
Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling
Fenwick Darryl, Scheidt Céline, Caers Jef (2014), Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling, in Mathematical Geosciences, 46(4), 493-511.
Simulation of braided river elevation model time series with multiple-point statistics
Pirot Guillaume, Straubhaar Julien, Renard Philippe (2014), Simulation of braided river elevation model time series with multiple-point statistics, in Geomorphology, 214, 148-156.
A practical guide to performing multiple-point statistical simulations with the Direct Sampling algorithm
Meerschman Eef, Pirot Guillaume, Mariethoz Gregoire, Straubhaar Julien, Meirvenne Marc Van, Renard Philippe (2013), A practical guide to performing multiple-point statistical simulations with the Direct Sampling algorithm, in Computers & Geosciences, 52, 307-324.
Distance-based kriging relying on proxy simulations for inverse conditioning
Ginsbourger David, Rosspopoff Bastien, Pirot Guillaume, Durrande Nicolas, Renard Philippe (2013), Distance-based kriging relying on proxy simulations for inverse conditioning, in Advances in Water Resources, 52, 275-291.
Local and Global Error Models to Improve Uncertainty Quantification
Josset Laureline, Lunati Ivan (2013), Local and Global Error Models to Improve Uncertainty Quantification, in Mathematical Geosciences, 45(5), 601-620.
Structure-coupled joint inversion of geophysical and hydrological data
Lochbühler Tobias, Doetsch Joseph, Brauchler Ralf, Linde Niklas (2013), Structure-coupled joint inversion of geophysical and hydrological data, in Geophysics, 78(3), ID1-ID14.
Efficient deconvolution of ground-penetrating radar data.
Schmelzbach C., Huber E., Efficient deconvolution of ground-penetrating radar data., in IEEE Transactions on Geoscience and Remote Sensing.
Updating joint uncertainty in trend and depositional scenario for reservoir exploration and early appraisal
Scheidt Céline, Tahmasebi Pejman, Pontiggia M, Da Pra A, Caers Jef, Updating joint uncertainty in trend and depositional scenario for reservoir exploration and early appraisal, in Computational Geosciences.

Collaboration

Group / person Country
Types of collaboration
Engineering Geology, ETH Zürich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Civil and Environmental Engineering, University of California, Irvine United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Exchange of personnel
Centre de Géosciences Mines Paris Tech France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
Earth Sciences Division, Lawrence Berkeley National Laboratory United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
University of New South Wales Australia (Oceania)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Faculté des géosciences et de l'environnement Université de Lausanne Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
GdR Mascot-Num annual conference Talk given at a conference Functional error modeling for Bayesian inference in hydrogeology 08.04.2015 Saint-Etienne, France Josset Laureline Marie;
AGU 2014 Fall Meeting Poster Vertical Mixing and Horizontal Anisotropies in Coarse Fluvial Aquifers 15.12.2014 San Francisco, United States of America Huber Emanuel; Huggenberger Peter;
AGU 2014 Fall Meeting Talk given at a conference Validating Prior Geological Scenario Uncertainty with Geophysical Data 15.12.2014 San Francisco, United States of America Scheidt Céline; Caers Jef;
AGU 2014 Fall Meeting Poster Influence of different conceptual models on contaminant transport uncertainty in braided river aquifers, using data from analog sites 15.12.2014 San Francisco, United States of America Huggenberger Peter; Renard Philippe; Scheidt Céline; Huber Emanuel;
2nd EAGE Integrated Reservoir Modeling Conference Talk given at a conference Hybrid Geostatistics: Object Simulations Using Multiple Point Statistics 16.11.2014 Dubai, United Arab Emirates Renard Philippe;
2nd EAGE Integrated Reservoir Modeling Conference Talk given at a conference A New Generic Method for Fast and Interactive Geological Models Perturbation 16.11.2014 Dubai, United Arab Emirates Renard Philippe;
2nd EAGE Integrated Reservoir Modeling Conference Talk given at a conference Updating joint uncertainty in trend and depositional models for exploration and early appraisal stage 16.11.2014 Dubai, United Arab Emirates Scheidt Céline; Caers Jef;
Swiss Geoscience Meeting Talk given at a conference Uncertainty quantification in porous media using stochastic sampling algorithm and functional data analysis 15.11.2014 Lausanne, Switzerland Ginsbourger David; Josset Laureline Marie; Lunati Ivan;
GeoENV 2014 Talk given at a conference Multiple point statistics: How good is my Training Image? A user point of view 09.07.2014 Parus, France Renard Philippe;
GeoENV 2014 Talk given at a conference Updating joint uncertainty in trend and depositional models for exploration and early appraisal stage 09.07.2014 Paris, France Scheidt Céline; Caers Jef;
GeoENV 2014 Talk given at a conference Identify model scale parameters with Ground Penetrating Radar data 09.07.2014 Paris, France Renard Philippe; Scheidt Céline; Pirot Guillaume; Huber Emanuel;
GeoEnv 2014 Talk given at a conference Approximate model based on simplified physics and functional principal component to accelerate Monte Carlo Markov chain 09.07.2014 Paris, France Josset Laureline Marie; Lunati Ivan;
GeoEnv 2014 Talk given at a conference Geophysical stereology: quantifying uncertainty of 3D object parameters from 2D GPR data of a braided river system. Application to the Tagliamento River (NE Italy) 09.07.2014 Paris, France Huber Emanuel; Caers Jef; Huggenberger Peter;
Computational Methods in Water Resources Talk given at a conference Tomographic model selection 10.06.2014 Stuttgart, Germany Lochbühler Tobias;
GdR MascotNum conference Talk given at a conference Multiple-point statistics to assess complex spatial uncertainty 25.04.2014 Zürich, Switzerland Renard Philippe;
2013 AGU Fall Meeting Poster Probabilistic inversion of electrical resistivity data from bench-scale experiments: On model parameterization for CO2 sequestration monitoring 09.12.2013 San Francisco, United States of America Lochbühler Tobias; Linde Niklas;
2013 AGU Fall Meeting Talk given at a conference Summary statistics from training images as model constraints in probabilistic geophysical inversion 09.12.2013 San Francisco, United States of America Lochbühler Tobias; Linde Niklas;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Functional data analysis for uncertainty quantification 02.09.2013 Madrid, Spain Ginsbourger David; Lunati Ivan; Josset Laureline Marie;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Corrected kriging update formulae for batch-sequential data assimilation 02.09.2013 Madrid, Spain Ginsbourger David;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Simulation of successive braided river digital elevation models with Multiple-Point Statistics 02.09.2013 Madrid, Spain Renard Philippe; Pirot Guillaume;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Constraining stochastical geophysical inversions with summary statistics from training data 02.09.2013 Madri, Spain Lochbühler Tobias;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Stochastic aquifer modeling using patterns and local flow solutions 02.09.2013 Madrid, Spain Josset Laureline Marie; Renard Philippe;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Quantifying Parameter Interaction in a Generalized Sensitivity Analysis 02.09.2013 Valencia, Spain Caers Jef; Scheidt Céline;
15th Annual Conference of the International Association for Mathematical Geosciences Talk given at a conference Modeling Geological Scenario Uncertainty from Seismic Data using Pattern Similarity. 02.09.2013 Madrid, Spain Scheidt Céline; Caers Jef;
American Geophysical Union, Fall Meeting 2012 Talk given at a conference An event-based model of braided river system aquifers heterogeneity based on Multiple Points Statistics 09.12.2012 San Francisco, USA, United States of America Renard Philippe; Pirot Guillaume;
American Geophysical Union, Fall Meeting 2012 Talk given at a conference Error models for uncertainty quantification 09.12.2012 San Francisco, United States of America Josset Laureline Marie; Lunati Ivan;
American Geophysical Union, Fall Meeting 2012 Poster Testing geological conceptual models with GPR simulations 09.12.2012 San Francisco, United States of America Pirot Guillaume; Huber Emanuel; Lochbühler Tobias; Caers Jef;
American Geophysical Union, Fall Meeting 2012 Talk given at a conference Linking scales through numerical simulations (Invited) 09.12.2012 San Francisco, United States of America Lunati Ivan;
American Geophysical Union, Fall Meeting 2012 Poster Multiple-point statistics facies simulation conditioned to crosshole radar tomograms 09.12.2012 San Franciscon, United States of America Linde Niklas; Lochbühler Tobias; Pirot Guillaume;
American Geophysical Union, Fall Meeting 2012 Talk given at a conference Incorporating Sedimentological Observations, Hydrogeophysics and conceptual Knowledge to Constrain 3D Numerical Heterogeneity Models of Coarse Alluvial Systems 09.12.2012 San Francisco, United States of America Huggenberger Peter; Huber Emanuel;
geoENV Conference Talk given at a conference Purpose-Focused Inversion (PFI) vs. Model-Based Inversion (MBI) 19.09.2012 Valencia, Spain Scheidt Céline; Renard Philippe; Caers Jef;
geoENV Conference Talk given at a conference Multiple-Point Statistics simulations of braided-rivers topography with the Direct-Sampling algorithm 19.09.2012 Valencia, Spain Renard Philippe; Pirot Guillaume;
geoENV Conference Talk given at a conference A purpose-driven inverse modeling vs model-driven inverse modeling 19.09.2012 Valencia, Spain Scheidt Céline; Caers Jef; Renard Philippe;
geoENV Conference Talk given at a conference A multiscale method for distance-based uncertainty analysis 19.09.2012 Valencia, Spain Scheidt Céline; Lunati Ivan; Josset Laureline Marie;
Ninth International Geostatistics Congress Talk given at a conference Simulating braided river aquifer heterogeneity using a pseudo-genetic approach and multiple-points geostatistics 11.06.2012 Oslo, Norway Pirot Guillaume; Renard Philippe;
Ninth International Geostatistics Congress Talk given at a conference Sampling Posterior Distributions in High Dimesions: Inverse-Based versus Prediction-Based Approaches 11.06.2012 Oslo, Norway Scheidt Céline; Caers Jef;
Ninth International Geostatistics Congress Poster Guidelines to Perform Multiple-Point Statistical Simulations with the Direct Sampling Algorithm 11.06.2012 Oslo, Norway Renard Philippe; Pirot Guillaume;
Ninth International Geostatistics Congress Talk given at a conference On internal consistency, conditioning and models of uncertainty 11.06.2012 Oslo, Norway Caers Jef;
European Geosciences Union, General Assembly 2012 Poster Joint inversion of crosshole GPR and temporal moments of tracer data for improved estimation of hydraulic conductivity at the aquifer scale 22.04.2012 Vienna, Austria, Austria Lochbühler Tobias;
American Geophysical Union, Fall Meeting 2011 Poster Optimizing Direct Sampling algorithm's parameters to performing multiple-points geostatistical simulations 05.12.2011 San Francisco, USA, United States of America Renard Philippe; Pirot Guillaume;


Self-organised

Title Date Place
Advancing Hydrogeophysics Workshop 22.02.2013 Hornberg, Germany

Awards

Title Year
Outstanding Student Paper Award / American Geophysical Union Fall Meeting - 2014 - San Francisco, United States of America 2014

Associated projects

Number Title Start Funding scheme
153637 Efficient hydrogeological Monte Carlo inversion based on Multiple-Point Statistics 01.01.2015 Project funding (Div. I-III)
134614 Stochastic simulation of climatic data with the Direct Sampling method 01.08.2011 Project funding (Div. I-III)
106557 Mathematical hydrogeology: from characterization to forecasts 01.10.2005 SNSF Professorships
155924 Summary statistics and model selection in Hydrogeophysics 01.02.2015 Project funding (Div. I-III)
146354 Bayesian set estimation relying on random fields priors 01.09.2013 Project funding (Div. I-III)
144922 A Multiscale Approach to Multiphase Flow in Geological Formations 01.07.2013 SNSF Professorships

Abstract

Numerical models are the only tools that allow forecasting the behavior of complex hydrological systems. However, the current state of the art suggests major shortcomings in our ability to understand and predict such systems. Recent developments in quantitative hydrology as well as numerical and stochastic modeling open new possibilities for addressing some of the most important shortcomings. However, these recent advances have not yet been integrated in a unique modeling framework. In this project, we use this untapped potential by building a common numerical framework based on the latest advances in quantitative geology, mathematics, and physics. This will enable stochastic modeling with unprecedented levels of realism and purpose. Our objectives are motivated by the new computational challenges posed by the pressing groundwater and energy resources engineering issues to be addressed in the coming decades.The state of the art in modeling groundwater systems is related to developments in geology, physics, and mathematics. However, research in these areas is often pursued completely independently by different teams and is therefore not integrated around a unique vision. Therefore, no advantage is taken of the potential that lies in combining these recent advances. For instance, stochastic geological modeling for alluvial systems using process based knowledge and multiple-point statistics can dramatically increase the ability to generate realistic models of aquifers. However, no geophysical inversion has yet been set up to improve the characterization of such geological structures. Another example is related to computational feasibility. Uncertainty assessment for hydrological systems always necessitates a large amount of simulations based on different setups and scenarios. In many cases, these computational requirements hamper the application of a sound risk analysis. Highly promising solutions to this apparently impossible problem can be found in recent developments in computational statistics. Furthermore, models are always driven by a specific purpose, and exhaustive knowledge of the entire system is usually not required by the modeler. In fact the identification of the relevant processes and complexities are basically unknown unless the entire complexity of the system is simulated. Recent mathematical advances suggest that by simultaneously simulating a limited number of simple and complex models in a joint procedure, the relevant aspects of the models can be identified, and the amount of realizations required for a sound analysis can be dramatically reduced. Like advances in quantitative geology, such promising techniques have not yet been applied in hydrological modeling.The ENSEMBLE project involves 6 research groups covering all major aspects of hydrogeological modeling: geology (University of Basel), geostatistical modeling (Stanford University and University of Neuchâtel), geophysics and fluid mechanics (University of Lausanne), mathematics (University of Bern), and engineering (ETHZ Zürich). Each group is leading one subproject and will closely co-operate with the others towards two highly ambitious goals: 1) Combine the recent but not yet applied advances in each discipline. In order to achieve this goal, all subprojects will share a common numerical framework, common experimental sites, and synthetic data sets for testing the tools and demonstrating the applicability of the integrated method. 2) Beyond combining the already available tools, each group will pursue fundamental research targeted towards the most important factors limiting today’s ability to model hydrogeological systems. These two goals will allow both focused and targeted research.
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