Poster: Hydrogeophysical monitoring of a controlled infiltration experiment at the Ploemeur Hydrological Observatory (Brittany, France)

Event: Journées des Doctorants – Ecole Doctorale Géosciences, Ressources Naturelles et Environnement – Paris (France), 19/03/2019
Poster by Lara Blazevic, Ludovic Bodet, Laurant Longuevergne, Sylvain Pasquet, Damien Jougnot


Blazevic_JDD2019Poster_v2


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Poster: Finding appropriate rocks physics models to interpret seismic data in hydrogeophysics applications

Event: AGU Fall Meeting 2018, Washington DC (USA)
poster by Lara Blazevic, Ludovic Bodet, Damien Jougnot, Laurent Longuvergne

Abstract

Seismic methods have been recently applied to the monitoring of spatial and temporal variations of near surface characteristics for hydrogeological purposes. The seismic signal is certainly related to mechanical properties that partly depend on porosity and saturation. The behavior of pressure (P) and shear (S) waves in the presence of water is partially decoupled, and the ratio of their propagation velocities VP/VS has been used to study water saturation changes.

However, the interpretation of the mechanical properties remains complex in unconsolidated near surface materials, limiting the quantitative description of linked hydrodynamic properties. In this study, we investigate the theories behind wave propagation velocities in poorly consolidated media and how they are affected by water content, focusing our discussion on the partially saturated response.

We present a field case where we used a Hertz-Mindlin based rock physics model to estimate water saturation from VP and VS from seismic data. The model is able to distinguish between dry and fully saturated areas at two distinct hydrological periods, but fails in identifying partially saturated areas in both cases. This work underlines the need for more elaborated models to infer hydrodynamic properties from seismic data.


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Poster: Flow dynamics and resulting reactivity in the transition zone between streams and riparian aquifers

Event: EGU 2019 General Assembly, Vienna (Austria)
Poster by Guilherme Nogueira, Christian Schmidt, Nico Trauth, Jan H. Fleckenstein


Abstract

Stream-groundwater mixing zones are well known for their role in facilitating ecosystem metabolism which also results in enhanced water quality (e.g. by denitrification). However, due to their highly dynamic biogeophysical characteristics (i.e. temperature, flow directions, residence times), a simple and general quantification of the reactivity potential is not readily possible.

Here, we combined conservative and reactive tracer-tests with high frequency measurements of electrical conductivity (EC) and dissolved oxygen (DO) to enhance the understanding of the hydraulic variations on aquifer’s reactivity potential. We analysed the reactivity in terms of Damköhler numbers (DA) and assess its patterns over time and space, while comparing its dependency on short and long term temperature and river discharge fluctuations.


ESR2_GN_EGU_2019


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Poster: Quantification of the real-time flow contribution of the fractures in fractured wellbores using Distributed Temperature Data

Event: EGU 2019 General Assembly, Vienna (Austria)
Poster by Behzad Pouladi, Olivier Bour, Laurent Longuevergne, Jérôme de La Bernardie


Abstract

Heat has been increasingly used as a tracer for characterization of the subsurface media both in fractured and porous aquifers. In fractured wellbore, understanding of the role of each fracture in total production of the fluid and the change of their contribution with change of the system conditions can help us increase our understanding about the system.

Considering the fact that when fluid being produced from an aquifer, the produced fluid experiences changing temperatures with depth while it travels up toward the surface and this change is related to the fluid velocity (flow rate), fluid properties as well as wellbore and formation properties. Using the Distributed Temperature Sensing (DTS) which in fact allows to measure the temperature both in time and space along the fiber optic, one can perform real time flow profiling and see the change of flow in each fracture with time.

In this work, a wellbore heat transfer model for a water production scenario, based on the wellbore heat transfer model presented by Hasan, Kabir [1] has been implemented in the MATLAB ® software. The model considers steady state heat transfer inside the wellbore and transient heat transfer from the wellbore to the formation. We use this analytical model to back calculate the flow rate in each section of the wellbores and thus flow contribution of each fracture using the temperature profile inside the wellbore.

The approach has been verified both numerically and experimentally. Distributed temperature data were recorded in different ambient and pumping flow rate in a fractured wellbore in Ploemeur site in Brittany, France. For cross validation, flow rates were also measured by Heat pulse flow meter.

The results show that model can predict real time contribution of each fracture to the total flow rate satisfactorily in different ambient and pumping rate. We also propose an automatic inflow zone (fracture/perforation location) detection which can help diagnosis of flowing zones (fracture locations). This model provides a basis for studying the transient behaviour and contribution of the fractures in different hydraulic conditions. For instance, the contribution of fractures in flow in different time of the years, studying the tidal effects on fracture flows, etc.



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Poster: Modeling a heat tracer test in alluvial sediments using Monte Carlo: on the importance of the prior

Event: IAH Congress – Groundwater management and governance coping with water scarcity, Malaga (Spain), 2019
Poster by Richard Hoffmann, Alain Dassargues, Pascal Goderniaux, Thomas Hermans


Abstract

In hydrogeology, deterministic model calibrations are useful to understand the influence of parameters on the considered variables or to image large-scale spatial parameter distribution. Oftentimes, deterministic solutions bias the problem with too smoothed parameter distributions leading to unrealistic transport predictions with underestimated uncertainties.

Instead of predictions using an optimum parameterization in conjunction with reference data confirming the model, a realistic heterogeneity consideration is crucial for robust transport simulations and managing aquifer systems sustainable. Thus, using random generated models as multiple hypotheses (e.g. with Monte Carlo), then a hypothesis may be rejected, when the model does not confirm reference data (falsification step).

For that, the reference data set in this study is a heat tracer experiment in alluvial sediments (Belgium). Between an injection well and a pumping well 20 m apart, three observation panels are located at distances of 3, 8 and 15 m downgradient from the injection well. Each panel consists of 3 wells with screened intervals in the upper and lower aquifer parts. A deterministic calibration of the experiment on temperature data, using jointly HydroGeoSphere and PEST, hardly describes the experimental observations.

The resulting spatial hydraulic conductivity distribution (K) is probably too smooth. Instead, 250 realizations using Monte Carlo in combination with sequential gaussian simulation for the K-distributions define the prior (hypotheses). For the K-distribution two scenarios are used: (1) a random K-distribution with unknown mean, variance and spatial correlation and (2) the same approach but with a downwards increasing vertical trend for the K-distribution, to mimic the observed increasing grain sizes of the sediment with depth.

With Scenario 1, the prior range (250 simulations) surrounds the reference data (i.e. heat breakthrough curves) for most of the experiment, but not for the tailing. The prior generated using Scenario 2 (with the vertical K-trend) improves the simulation of the breakthrough tailings for panel 1 and 2. In panel 3 (15 m downgradient), simulations for the lower aquifer part show significant lower peaks than measured. Scenario 1 is falsified (rejected), because the prior (250 models) do not confirm the reference data, while scenario 2 is not-falsified till panel 2 (8 m downgradient). Scenario 2 addresses the heterogeneity of the test site more realistically than all previous unsatisfying deterministic attempts.

A global sensitivity analysis at panel 1 and 2 identifies then the spatial K-distribution and its variance as the most sensitive parameters. This confirms, that future efforts needed for panel 3, should focus on identification of heterogeneous patterns in the aquifer and their subsequent introduction in the model.

As a perspective, the use of a direct predictive framework (e.g. Bayesian Evidential Learning), avoiding the commonly used calibration procedure, promises robust decisions made by more realistic quantifications of the uncertainty caused by heterogeneity.


ESR11_IAH2019_MonteCarlo_Poster208_HoffmannEtAl


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