Tanguy Robert

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.

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.

Reliability of ERT-derived Temperature - Insights from Laboratory Measurements

We performed laboratory measurements on fully saturated sand samples in the context of deriving reliable temperature from time-lapse electrical resistivity tomography (ERT). The experiment consisted in monitoring an increase of temperature in sand samples with electrical resistivity measurements. We neglected the effect of surface conductivity since experiments showed two orders of magnitude between surface and fluid conductivities. We show that using simple linear relationship between fluid electrical conductivity and temperature alone does not allow reliable temperature estimates. Indeed, chemical analyses highlight the importance of accounting chemical reactions occurring when temperature changes, including dissolution/precipitation processes. We performed two experiments based on typical in-situ conditions. We first simulated the injection of a less conductive tap water and second, the injection of heated formation water. In the second case, minerals solubility decreases and precipitation occurs, leading to an increase of bulk resistivity. This mechanism competes with dissolution of minerals when tap water is injected, since tap water is not in equilibrium with the medium. In any case, further research is needed to fully understand the mechanisms and to develop a fully integrated law to derive better temperature estimates.

Image Appraisal Tools for Electrical Resistivity Tomography

Image appraisal is a problem frequently encountered in electrical resistivity Tomography (ERT), and more generally in non-linear geophysical Inversion. It may include several aspects such as the identification of the geometry of buried structures, the detection of numerical artefacts, the estimation of the depth of Investigation or the exactitude of inverted parameters. Geophysicists can rely on several Tools published in the literature to address these issues. However, few studies offer a quantitative comparison on the performance of these Tools concerning the different mentioned aspects. Moreover, to our knowledge, there is no commonly accepted methodology to handle image appraisal. in this contribution, we compared quantitatively the ability of different image appraisal indicators to reach different objectives (geometry, artefacts, depth of Investigation, parameter resolution). Among possible image appraisal Tools, the model resolution matrix (MRM), the cumulative sensitivity matrix (CSM) and the depth of Investigation index (DOI) are the most cited ones and were studied here. We compared them first on numerical models representing different geological situations. This numerical benchmark showed that indicators based on the MRM and CSM were the more appropriate to appraise ERT images in terms of the geometry of structures and the exactitude of inverted parameters, DOI providing mainly qualitative Information. On this basis, we propose a methodology to appraise field ERT images focusing on the resolution and geometric aspects (others being implicitly studied). First, True Synthetic Models (TSM), representing simplified cases of field ERT images, are built using available Information. then, through forward modelling, synthetic ERT data are computed and inverted to provide the inverted Synthetic Models (ISM). Afterwards, a comparison between TSM and ISM (or their gradients for geometry) is made in order to define the errors on inverted parameters. This discrepancy is then plotted with respect to resolution indicator values and points out in every tested cases a resolution range over which the errors abruptly increase 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.

Using Electrical Resistivity Tomography and Self-potential Methods for Wells Implementations in Fractured Limestones

Electrical resistivity tomography (ERT) and self-potential (SP) investigations were conducted in fractured limestones in Belgium. The aim of this study was to find suitable positions for high yield water wells. Large ERT profiles (640 meters) allowed us to image the resistivity distribution of the first 60 meters of the subsurface and to detect and characterize (in terms of direction, width and depth) fractured zones expected to be less resistive. Data errors, DOI indexes and sensitivity models were analysed in order to calculate the depth of investigation of ERT and to avoid the misinterpretation of the resulting images. Self-potential measurements were performed along electrical profiles to narrow the possible locations given by the electrical images. Some negative anomalies possibly related to preferential flow were detected. ‘Ground truth’ geological data as well as pumping tests information gave us a way to assess the contribution of geophysics to a drilling programme. Wells implemented in low resistivity zones associated with SP anomalies have very high yields. Inversely, wells drilled in resistive zones or outside SP anomalies have poorer capacities. An apparent coupling coefficient between SP signals and differences in hydraulic heads was also estimated in order to image the water table.

How to incorporate prior information in geophysical inverse problems: deterministic and geostatistical approaches.

Many geophysical inverse problems are ill-posed leading to non-uniqueness of the solution. 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 go beyond standard Occam’s inversion for electrical resistivity tomography (ERT) using electromagnetic logging data in the context of salt water infiltration: a simple reference model, a structural constraint and a geostatistical constraint based on a vertical correlation length. Results with the traditional smoothness constraint yield small contrasts of resistivity, far from the reality revealed by borehole measurements. Incorporating prior information from boreholes clearly improves the misfit with logging data. If a good reference model can always be used, it can lead to misinterpretation if its weight is too strong. When the computation of the correlation length is possible, the geostatistical inversion gives satisfactory results everywhere in the section. In this specific case, the geostatistical approach seems to be a more robust way to incorporate prior information. The structural constraint seems to be more indicated when integrating information from other geophysical methods such as GPR or seismic.

Electrical resistivity tomography and distributed temperature sensing monitoring to assess the efficiency of horizontal recirculation drains on retrofit bioreactor landfills

In bioreactor landfills, the recirculation of water can accelerate biodegradation and increase gas production. The dedicated infrastructure aims at increasing the waste water content over a wide area, with a long-lasting effect. To assess the efficiency of horizontal drains in bioreactor landfills, we use electrical resistivity tomography (ERT) and distributed temperature sensing (DTS) to monitor two injection experiments. The first monitoring experiment focuses on image resolution and takes advantage of a pseudo 3D ERT data set. This technique successfully highlights the waste horizontal anisotropy and the crucial role of existing gas wells, acting as vertical preferential flow paths. The observations are supported by borehole temperature logging. The second monitoring experiment focuses on temporal resolution and requires repeated 2D ERT measurements. The hourly acquisition frequency offers a better insight on the water flow dynamics such as the flow direction and velocity, and the water retention troug...

Direct prediction of aquifer thermal energy storage system efficiency using short-term push-pull tests

Aquifer thermal energy storage (ATES) systems are designed to recover in winter the heat stored in the aquifer during summer. In practice however, spatial heterogeneity or non-favorable hydrogeological conditions reduces the energy efficiency. In many cases, a deterministic approach is used to calibrate the subsurface component of those systems, neglecting the quantification of uncertainty. In this contribution, we propose to use the recently-developed prediction-focused approach to forecast the heat storage capacity of an alluvial aquifer. We compare the ability of two different push/pull tests to make this prediction. We first analyze the performance of the method using synthetic cases and validate the approach using field data. For both, we show that the method is able to forecast the posterior distribution with realistic uncertainty. We also identify the experiment which has the highest information content for the desired prediction. Then we forecast the long-term heat storage capacity of the aquifer and assess its uncertainty. This final result can be used to design properly the heat pump associated with the system.

Spatio-temporal Monitoring of Heat Storage in a Shallow Aquifer Using Electrical Resistivity 4D Imagery and DTS

The design of groundwater heat pumps requires a good understanding of the aquifer and heat flow conditions. Issues of short-circuit or recycling between cold and hot wells have to be carefully considered. Surface geophysical methods allow monitoring subsurface processes without additional perturbations of the medium. Within available methods, the electrical resistivity imagery (ERI) applied in time-lapse (TL) is appropriate. Here, we monitored with ERI and distributed temperature sensors (DTS) a heat plume propagation during an experiment of hot water injection in a shallow aquifer. DTS and TL ERI measurements acquired from two boreholes provide a local estimate of the heat propagation through the medium. TL ERI were also performed from a grid at surface to follow the 3D plume shape formation and evolution through time. The different complementary data validate the potential of surface TL ERI for monitoring in 3D the behavior of shallow heat plumes. ERI highlight the heterogeneity of the aquifer by distinguishing regions with higher or lower hydraulic conductivity. In the higher hydraulic conductivity zone, the heat might be evacuated through water flow, while in the lower hydraulic conductivity area heat storage is achievable. Thus, in that last region the plume temperature decreases progressively with time.

Using geophysical hard data to enhance the reliability of hydrological models

Appropriate design of geophysical experiments combined with common hydrological measurements offer opportunities to use geophysical data as hard data in hydrological models, regarding their conceptualisation or their calibration. Two study sites located in Wallonia, Belgium, were investigated. In the first case (fractured limestone aquifer), streaming potentials were linked to piezometric measurements, allowing us to better conceptualise the local groundwater flow model and calibrate it. In the second example (alluvial sandy aquifer), the use of 4D electrical resistivity tomography and temperature measurements appeared to be a reliable methodology to predict heat storage and recovery cycles in hydrological models with a better constrained calibration process.