Frédéric Nguyen

Characterization of seawater intrusion using 2D electrical imaging

We have investigated the potential of 2D electrical imaging for the characterization of seawater intrusion using field data from a site in Almeria, SE Spain. Numerical simulations have been run for several scenarios, with a hydrogeological model reflecting the local site conditions. The simulations showed that only the lower salt concentrations of the seawater-freshwater transition zone could be recovered, due to the loss of resolution with depth. We quantified this capability in terms of the cumulative sensitivity associated with the measurement setup and showed that the mismatch between the targeted and imaged parameter values occurs from a certain sensitivity threshold. Similarly, heterogeneity may only be determined accurately if located in an adequately sensitive area. At the field site, we identified seawater intrusion at the scale of a few kilometres down to a hundred metres. Borehole logs show a remarkable correlation with the image obtained from surface data but indicate that the electrically derived mass fraction of pure seawater could not be recovered due to the discrepancy between the in-situ and laboratory-derived petrophysical relationships. Surface-to-hole inversion results suggest that the laterally varying resolution pattern associated with such a setup dominates the image characteristics compared to the laterally more homogeneous resolution pattern of surface only inversion results and hence, surface-to-hole images are not easily interpretable in terms of larger-scale features. Our results indicate that electrical imaging can be used to constrain seawater intrusion models if image appraisal tools are appropriately used to quantify the spatial variation of sensitivity and resolution. The most crucial limitation is probably the apparent non-stationarity of the petrophysical relationship during the imaging process.

Use of microtremor measurement for assessing site effects in Northern Belgium – interpretation of the observed intensity during the MS = 5.0 June 11 1938 earthquake

To provide quantitative information on site effects in the northern part of Belgium, forty-seven H/V microtremor measurements were performed with 5 second seismometers over an area of about 15.000 km2. Most of the results show a northward regular increase of the fundamental period in agreement with the augmentation of the Mesozoic and Cainozoic soft sedimentsthickness from a few meters 40 km south of Brussels to 900 m at the Netherlands-Belgium border. The measured resonance frequency values wereconsistent with theoretical computations performed at different sites onthe basis of existing information and shallow seismic experiments. At oneparticular site (Uccle) where borehole data were available, microtremor measurements using an array of four seismological stations with differentapertures allowed to obtain the low frequency part of the Rayleigh wave dispersion curve, extending the range covered by the analysis of surfacewaves artificially generated. The Vs profile derived from the surface waveinversion corroborates the 1 Hz natural frequency of the site. Comparison of these results with the macroseismic information concerning the MS = 5.0 1938 earthquake which occurred 50 km west of Brussels,confirmed the hypothesis that the geological structure of the Brabant massifis likely to control damage distribution during such an earthquake. Comparisonbetween the intensity map of the 1938 earthquake and the resonance period ofsediments obtained by our microtremor study shows a clear relation betweenthe two parameters. During the 1938 earthquake, site effects played a prominent role due to the dimension of the source whose corner frequency wasabout 1 Hz.

Uncertainty in training image-based inversion of hydraulic head data constrained to ERT data: Workflow and case study

In inverse problems, investigating uncertainty in the posterior distribution of model parameters is as important as matching data. In recent years, most efforts have focused on techniques to sample the posterior distribution with reasonable computational costs. Within a Bayesian context, this posterior depends on the prior distribution. However, most of the studies ignore modeling the prior with realistic geological uncertainty. In this paper, we propose a workflow inspired by a Popper-Bayes philosophy that data should first be used to falsify models, then only be considered for matching. We propose a workflow consisting of three steps: (1) in defining the prior, we interpret multiple alternative geological scenarios from literature (architecture of facies) and site-specific data (proportions of facies). Prior spatial uncertainty is modeled using multiple-point geostatistics, where each scenario is defined using a training image. (2) We validate these prior geological scenarios by simulating electrical resistivity tomography (ERT) data on realizations of each scenario and comparing them to field ERT in a lower dimensional space. In this second step, the idea is to probabilistically falsify scenarios with ERT, meaning that scenarios which are incompatible receive an updated probability of zero while compatible scenarios receive a nonzero updated belief. (3) We constrain the hydrogeological model with hydraulic head and ERT using a stochastic search method. The workflow is applied to a synthetic and a field case studies in an alluvial aquifer. This study highlights the importance of considering and estimating prior uncertainty (without data) through a process of probabilistic falsification.

Case studies of incorporation of prior information in electrical resistivity tomography: comparison of different approaches

Many geophysical inverse problems are ill-posed and their solution non-unique. It is thus important to reduce the amount of mathematical solutions to more geologically plausible models by regularizing the inverse problem and incorporating all available prior information in the inversion process. We compare three different ways to incorporate prior information for electrical resistivity tomography (ERT): using a simple reference model, adding structural constraints to Occam’s inversion and using geostatistical constraints. We made the comparison on four real cases representing different field applications in terms of scales of investigation and level of heterogeneities. In those cases, when electromagnetic logging data are available in boreholes to control the solution, it appears that incorporating prior information clearly improves the correspondence with logging data compared to the standard smoothness constraint. However, the way to incorporate it may have a major impact on the solution. A reference model can often be used to constrain the inversion; however, it can lead to misinterpretation if its weight is too strong or the resistivity values inappropriate. When the computation of the vertical and/or horizontal correlation length is possible, the geostatistical inversion gives reliable results everywhere in the section. However, adding geostatistical constraints can be difficult when there is not enough data to compute correlation lengths. When a known limit between two layers exists, the use of structural constraint seems to be more indicated particularly when the limit is located in zones of low sensitivity for ERT. This work should help interpreters to include their prior information directly into the inversion process through an appropriate way.

Calibration of seawater intrusion models: Inverse parameter estimation using surface electrical resistivity tomography and borehole data

Electrical resistivity tomography (ERT) can be used to constrain seawater intrusion models because of its high sensitivity to total dissolved solid contents (TDS) in groundwater and its relatively high lateral coverage. However, the spatial variability of resolution in electrical imaging may prevent the correct recovery of the desired hydrochemical properties such as salt mass fraction. This paper presents a sequential approach to evaluate the feasibility of identifying hydraulic conductivity and dispersivity in density-dependent flow and transport models from surface ERT-derived mass fraction. In the course of this study, geophysical inversion was performed by using a smoothness constraint Tikhonov approach, whereas the hydrological inversion was performed using a gradient-based Levenberg-Marquardt algorithm. Two synthetic benchmarks were tested. They represent a pumping experiment in a homogeneous and heterogeneous coastal aquifer, respectively. These simulations demonstrated that only the lower salt mass fraction of the seawater-freshwater transition zone can be recovered for different times. This ability has here been quantified in terms of cumulative sensitivity and our study has further demonstrated that the mismatch between the targeted and the recovered salt mass fraction occurs from a certain threshold. We were additionally able to explore the capability of sensitivity-filtered ERT images using ground surface data only to recover (in both synthetic cases) the hydraulic conductivity while the dispersivity is more difficult to estimate. We attribute the latter mainly to the lack of ERT-derived data at depth (where resolution is poorer) as well as to the smoothing effect of the ERT inversion.

A comparison study of different image appraisal tools for electrical resistivity tomography

To date, few studies offer a quantitative comparison of the performance of image appraisal tools. Moreover, there is no commonly accepted methodology to handle them even though it is a crucial aspect for reliable interpretation of geophysical images. In this study, we compare quantitatively different image appraisal indicators to detect artefacts, estimate depth of investigation, address parameters resolution and appraise ERT-derived geometry. Among existing image appraisal tools, we focus on the model resolution matrix (R), the cumulative sensitivity matrix (S) and the depth of investigation index (DOI) that are regularly used in the literature. They are first compared with numerical models representing different geological situations in terms of heterogeneity and scale and then used on field data sets. The numerical benchmark shows that indicators based on R and S are the most appropriate to appraise ERT images in terms of the exactitude of inverted parameters, DOI providing mainly qualitative information. In parallel, we test two different edge detection algorithms – Watershed’s and Canny’s algorithms – on the numerical models to identify the geometry of electrical structures in ERT images. From the results obtained, Canny’s algorithm seems to be the most reliable to help practitioners in the interpretation of buried structures. On this basis, we propose a methodology to appraise field ERT images. First, numerical benchmark models representing simplified cases of field ERT images are built using available a priori information. Then, ERT images are produced for these benchmark models (all simulated acquisition and inversion parameters being the same). The comparison between the numerical benchmark models and their corresponding ERT images gives the errors on inverted parameters. These discrepancies are then evaluated against the appraisal indicators (R and S) allowing the definition of threshold values. The final step consists in applying the threshold values on the field ERT images and to validate the results with a posteriori knowledge. The developed approach is tested successfully on two field data sets providing important information on the reliability of the location of a contamination source and on the geometry of a fractured zone. However, quantitative use of these indicators remains a difficult task depending mainly on the confidence level desired by the user. Further research is thus needed to develop new appraisal indicators more suited for a quantitative use and to improve the quality of inversion itself.

Coupling heat and chemical tracer experiments for estimating heat transfer parameters in shallow alluvial aquifers

Geothermal energy systems, closed or open, are increasingly considered for heating and/or cooling buildings. The efficiency of such systems depends on the thermal properties of the subsurface. Therefore, feasibility and impact studies performed prior to their installation should include a field characterization of thermal properties and a heat transfer model using parameter values measured in situ. However, there is a lack of in situ experiments and methodology for performing such a field characterization, especially for open systems. This study presents an in situ experiment designed for estimating heat transfer parameters in shallow alluvial aquifers with focus on the specific heat capacity. This experiment consists in simultaneously injecting hot water and a chemical tracer into the aquifer and monitoring the evolution of groundwater temperature and concentration in the recovery well (and possibly in other piezometers located down gradient). Temperature and concentrations are then used for estimating the specific heat capacity. The first method for estimating this parameter is based on a modeling in series of the chemical tracer and temperature breakthrough curves at the recovery well. The second method is based on an energy balance. The values of specific heat capacity estimated for both methods (2.30 and 2.54MJ/m(3)/K) for the experimental site in the alluvial aquifer of the Meuse River (Belgium) are almost identical and consistent with values found in the literature. Temperature breakthrough curves in other piezometers are not required for estimating the specific heat capacity. However, they highlight that heat transfer in the alluvial aquifer of the Meuse River is complex and contrasted with different dominant process depending on the depth leading to significant vertical heat exchange between upper and lower part of the aquifer. Furthermore, these temperature breakthrough curves could be included in the calibration of a complex heat transfer model for estimating the entire set of heat transfer parameters and their spatial distribution by inverse modeling.

Gravimetric water distribution assessment from geoelectrical methods (ERT and EMI) in municipal solid waste landfill

The gravimetric water content of the waste material is a key parameter in waste biodegradation. Previous studies suggest a correlation between changes in water content and modification of electrical resistivity. This study, based on field work in Mont-Saint-Guibert landfill (Belgium), aimed, on one hand, at characterizing the relationship between gravimetric water content and electrical resistivity and on the other hand, at assessing geoelectrical methods as tools to characterize the gravimetric water distribution in a landfill. Using excavated waste samples obtained after drilling, we investigated the influences of the temperature, the liquid phase conductivity, the compaction and the water content on the electrical resistivity. Our results demonstrate that Archies law and Campbells law accurately describe these relationships in municipal solid waste (MSW). Next, we conducted a geophysical survey in situ using two techniques: borehole electromagnetics (EM) and electrical resistivity tomography (ERT). First, in order to validate the use of EM, EM values obtained in situ were compared to electrical resistivity of excavated waste samples from corresponding depths. The petrophysical laws were used to account for the change of environmental parameters (temperature and compaction). A rather good correlation was obtained between direct measurement on waste samples and borehole electromagnetic data. Second, ERT and EM were used to acquire a spatial distribution of the electrical resistivity. Then, using the petrophysical laws, this information was used to estimate the water content distribution. In summary, our results demonstrate that geoelectrical methods represent a pertinent approach to characterize spatial distribution of water content in municipal landfills when properly interpreted using ground truth data. These methods might therefore prove to be valuable tools in waste biodegradation optimization projects.

Nondestructive detection of delaminations in concrete bridge decks

To detect delaminations in concrete bridge decks, nondestructive techniques (NDT) permit a frequent and large inspection of the slabs without damaging structures. This research was devoted to detect simulated defects in twelve repaired concrete slabs. These were scanned with high frequency ground penetrating radar (GPR) with the common offset (CO) and common midpoint (CMP) methods. The electromagnetic waves speed was determined from CMPs. A 3D visualization program was also created to display the CO measurements. The visibility of the inserted defects revealed to be dependent on their lateral extension, their thickness and their constitutive material.

Covariance-constrained difference inversion of time-lapse electrical resistivity tomography data

ABSTRACTHydrogeophysics has become a major field of research in the past two decades, and time-lapse electrical resistivity tomography (ERT) is one of the most popular techniques to monitor passive and active processes in shallow subsurface reservoirs. Time-lapse inversion schemes have been developed to refine inversion results, but they mostly still rely on a spatial regularization procedure based on the standard smoothness constraint. We have applied a covariance-based regularization operator to the time-lapse ERT inverse problem. We first evaluated the method for surface and crosshole ERT with two synthetic cases and compared the results with the smoothness-constrained inversion (SCI). These tests showed that the covariance-constrained inversion (CCI) better images the target in terms of shape and amplitude. Although more important in low-sensitivity zones, we have observed improvements everywhere in the tomograms. Those synthetic examples also show that an error made in the range or in the type of the...