ESR N°11 : Joint heat and solute tracer test inversion for imaging preferential pathways

Research Fellow: Richard Hoffmann

Find him on ResearchGate !

Host Institution : Hydrogeology &
Environmental Geology,
University of Liege, Belgium

Objectives:

1)   Characterization of preferential flow paths with multiple-scale transport modeling for heterogenous porous and fractured media using innovative joint heat and solute tracer tests.

2)   Assessing the impact of preferential flow paths and quantify the associated uncertainty in model predictions by using a dual-domain approach and Bayesian Evidential Learning (BEL).

More details about ESR11-project:


Secondments :

– 6 months at NRGI Hyderabad, India within BRGM – to confirm depending on visas and environmental conditions.

– 3 months at Research Center Jülich, Germany (Foreseen time schedule: May 06, 2019 till August 06, 2019 )

Tasks and methodology

Tasks: Carrying out a multi-tracer approach with multiple well injection and pumping tests in alluvial sediments and fractured rocks. Field tests measurements will be complemented by Distributed Temperature Sensing (DTS) and geophysical imaging.

Methodology: Using the complementary behavior of multiple tracers based on different diffusion coefficients and sensitivities to preferential flow paths and matrix diffusion. Uncertainty will be addressed using the BEL method.

Supervisors  

  • Prof. A. Dassargues, Hydrogeology and Environmental Geology, University of Liege
  •  Prof. P. Goderniaux, Geology and Applied Geology, University of Mons
  • Additional: Prof. F. Nguyen (University of Liege) and Prof. T. Hermans (Ghent University)
  • Secondment: Dr. J.-C. Maréchal (BRGM) and Dr. A. Selles (BRGM/IFCGR)

Dissemination and communication

( If you encounter issues to open the PDF documents using Chrome : please follow the Google advice : Chrome Help or use Firefox)

Media :

    • Video of a field experiment on the Hyderabad site (tracer tests at Hyderabad with the BRGM, NGRI, November 2018):

Database for the future datasets : H+ database


Glossary 

BEL: Bayesian Evidential Learning relies on a limited number of Monte Carlo simulations sampling the prior distribution of model parameters to analyze the global sensitivity of parameters

DTS: Distributed Temperature Sensing serves for recording temperature as continuous profile along an optical sensor cable.


Previous page : See ESR10-Project

Next page : See ESR12-Project