References of "Hermans, Thomas"
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See detailPrediction-focused approaches: an opportunity for hydrology
Hermans, Thomas ULiege

in Groundwater (in press)

Our ability to predict the evolution of complex hydrological system is fundamental. For decades, such problems have been solved by calibrating a conceptual model of the subsurface to fit data ... [more ▼]

Our ability to predict the evolution of complex hydrological system is fundamental. For decades, such problems have been solved by calibrating a conceptual model of the subsurface to fit data. Unfortunately, model calibration does not allow a realistic uncertainty quantification, whereas stochastic inversion is often computationally prohibitive. In this contribution, prediction-focused approaches (PFAs) are introduced to overcome those main shortcomings. This new paradigm focused on generating predictions directly from the data instead of generating models. A group of prior models is used to generate the data and the prediction in order to derive a direct relationship between both types of variables. The advantages, limitations and research perspectives are discussed. [less ▲]

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See detailThe mathematical challenges in agrogeophysics: examples and ways ahead
Garré, Sarah ULiege; Nguyen, Frédéric ULiege; Lesparre, Nolwenn ULiege et al

Conference (2017, October 05)

Electrical resistivity tomography (ERT) is increasingly used in the context of agriculture since the measured resistivity distribution can be linked to soil moisture, soil structure or pore water salinity ... [more ▼]

Electrical resistivity tomography (ERT) is increasingly used in the context of agriculture since the measured resistivity distribution can be linked to soil moisture, soil structure or pore water salinity. Due to its minimally invasive character, its spatial coverage and its monitoring abilities, ERT can be used to study field heterogeneity and competition between plants, quantify water fluxes throughout a growing season or distinguish preferential flow pathways in soils. Nevertheless, a lot of challenges still remain. From a mathematical point of view, the inverse problem linked to ERT is ill-posed. To solve it, the inverse problem is often regularized with a Tikhonov-type approach. The latter is typically done using a gradient operator, resulting in smoothed resistivity distribution. However, strong contrasts can exist due to e.g. compacted soil layers due to ploughing, water infiltration fronts, etc. In such a case, other operators such as the total variation or the minimum gradient support may be used. In such approaches, the selection of the regularization parameter with respect to the data quality and the definition of image appraisal indicators still remains a challenge. Uncertainty quantification of ERT-derived results often relies on data-error propagation around the inverse solution. Given the inherent non-uniqueness of the problem, both mathematically but also from a pedological point of view, challenges for stochastic approaches lie in providing realistic uncertainty estimation, encompassing all uncertainties (e.g. prior, pedophysics or data error). Monitoring data allows further elements to constrain the inverse problems, data can be replaced by data difference and regularization may incorporate the temporal dimension for instance. However, such constraints require their compatibility with the studied temporal process. Whereas the above challenges stay true for monitoring data, several alternative strategies are being developed more specifically, such as coupled hydrogeophysical inversion, with the challenge of addressing the non-stationarity of pedophysical relationships and the accuracy of the conceptual flow and transport model using deterministic approaches. Stochastic approaches allow to a certain extent to tackle those challenges in particular using a prior falsification/validation approach following a Popper-Bayes philosophy. In this presentation, we will illustrate the challenges and some of the recent developments with numerical and field examples. [less ▲]

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See detailUsing Geophysical Hard Data to Enhance the Reliability of Hydrological Models
De Schepper, Guillaume; Paulus, Claire; Molron, J. et al

in EarthDoc (2017, September 06)

Appropriate design of geophysical experiments combined with common hydrological measurements offer opportunities to use geophysical data as hard data in hydrological models, regarding their ... [more ▼]

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. [less ▲]

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See detailSpatio-temporal Monitoring of Heat Storage in a Shallow Aquifer Using Electrical Resistivity 4D Imagery and DTS
Lesparre, Nolwenn ULiege; Hermans, Thomas ULiege; Nguyen, Frédéric ULiege et al

in EarthDoc (2017, September 06)

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 ... [more ▼]

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. [less ▲]

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See detailQuantification of Temperature with Time-lapse Electrical Resistivity Using the Prediction-focused Approach -A Field Case
Hermans, Thomas ULiege; Nguyen, Frédéric ULiege; Caers, Jef

in EarthDoc (2017, September 06)

Standard inversion of time-lapse geophysical suffers from spatially and temporally varying resolution due to the regularization procedure used during the inversion process. In this study, we apply the ... [more ▼]

Standard inversion of time-lapse geophysical suffers from spatially and temporally varying resolution due to the regularization procedure used during the inversion process. In this study, we apply the recently developed prediction-focused approach (PFA) to directly estimate temperature with electrical resistance data, without classic tomographic inversions. PFA is based on a set of prior subsurface models coherent with our prior knowledge of the site. From this set of models, we generate a prior set of temperature distribution and resistance data mimicking the field experiment. Then, we use dimension-reduction techniques to derive a direct relationship between the data and the desired prediction. The use of canonical correlation analysis linearize the relationship and allows using Gaussian regression to sample the posterior. In this paper, we demonstrate the ability of PFA to process time-lapse ERT data during a field experiment. We propose an analysis of time-lapse reciprocals to derive an error model and generate the posterior distribution of temperature. We validate the results using direct measurements in the aquifer. This successful application opens new ways to process and integrate geophysical data in hydrogeological model. [less ▲]

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See detailThe Prediction-Focused Approach: An opportunity for hydrogeophysical data integration and interpretation in the critical zone
Hermans, Thomas ULiege; Nguyen, Frédéric ULiege; Klepikova, Maria et al

Poster (2017, July 27)

Two important challenges remain in hydrogeophysics: the inversion of geophysical data and their integration in quantitative subsurface models. Classical regularized inversion approaches suffer from ... [more ▼]

Two important challenges remain in hydrogeophysics: the inversion of geophysical data and their integration in quantitative subsurface models. Classical regularized inversion approaches suffer from spatially varying resolution and yield geologically unrealistic solutions, making their utilization for model calibration less consistent. Advanced techniques such as coupled inversion allow for a direct integration of geophysical data; but, they are difficult to apply in complex cases and remain computationally demanding to estimate uncertainty. We investigated a prediction-focused approach (PFA) to directly estimate subsurface physical properties relevant in the critical zone from geophysical data, circumventing the need for classic inversions. In PFA, we seek a direct relationship between the data and the subsurface variables we want to predict (the forecast). This relationship is obtained through a prior set of subsurface models for which both data and forecast are computed. A direct relationship can often be derived through dimension reduction techniques (Figure 1). For hydrogeophysical inversion, the considered forecast variable is the subsurface variable, such as the salinity or saturation for example. An ensemble of possible solutions is generated, allowing uncertainty quantification. For data integration, the forecast variable is the prediction we want to make with our subsurface models, such as the concentration of contaminant in a drinking water production well. Geophysical and hydrological data are combined to derive a direct relationship between data and forecast. We illustrate the methodology to predict the energy recovered in an ATES system considering the uncertainty related to spatial heterogeneity. With a global sensitivity analysis, we identify sensitive parameters for heat storage prediction and validate the use of a short term heat tracing experiment to generate informative data. We illustrate how PFA can be used to successfully derive the distribution of temperature in the aquifer from ERT during the heat tracing experiment. Then, we successfully integrate the geophysical data to predict heat storage in the aquifer using PFA. The result is a full quantification of the posterior distribution of the prediction conditioned to observed data in a relatively limited time budget. [less ▲]

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See detailBuilding flow and transport models with electrical resistivity tomography data
Gottschalk, Ian; Hermans, Thomas ULiege; Knight, Rosemary et al

Poster (2017, July 26)

Aquifer recharge and recovery (ARR) is the process of enhancing natural groundwater resources and recovering water for later use by constructing engineered conveyances. Insufficient understanding of ... [more ▼]

Aquifer recharge and recovery (ARR) is the process of enhancing natural groundwater resources and recovering water for later use by constructing engineered conveyances. Insufficient understanding of lithological heterogeneity at ARR sites often hinders attempts to predict where and how quickly infiltrating water will flow in the subsurface, which can adversely affect the quality and quantity of available water in the ARR site. In this study, we explored the use of electrical resistivity tomography (ERT) to assist in characterizing lithological heterogeneity at an ARR site, so as to incorporate it into a flow and contaminant transport model. In this case, we had non-collocated well core log data and ERT data from a full-scale ARR basin. We compared three independent methods for producing conditional lithology-resistivity probability distributions: 1) a search template to relate the nearest logged well lithologies with ERT resistivity panels, given search criteria; 2) a maximum likelihood estimation (MLE) to match bimodal normal distributions to the histogram of each ERT line; and 3) variogram-based lithology indicator simulations constrained to well data. Each approach leverages Bayes’ Rule to estimate lithology probability given electrical resistivity. The simplest approach (method 1) yields an erroneous conditional probability function where sand dominates the conditional probability at nearly all resistivities, due in part to the strong presence of sand in the wells nearest the ERT lines. The approaches using MLE and lithology simulations (methods 2 and 3) produce similar, more realistic lithofacies probability functions. The range of resistivities where clay and sand overlap differs between methods 2 and 3: ranging between 100 and 200 ohm-m for method 2, and between 30 and 50 ohm-m for the method 3. These differences affect the posterior lithology distributions in multiple point geostatistical (MPS) simulations, and in turn, predictions of flow from models which integrate these results. To test the models, we can compare measured breakthrough times of recharged water at the site to groundwater flow simulation results using the lithofacies models created by each method. The methods described here can inform the integration of non-collocated geophysical data into a variety of applications. [less ▲]

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See detailThe effect of initial water distribution and spatial resolution on the interpretation of ERT monitoring of water infiltration
Dumont, Gaël ULiege; Pilawski, Tamara ULiege; Robert, Tanguy et al

Poster (2017, July 25)

A better understanding of the water balance of a landfill is crucial for its management, as the waste water content is the main factor influencing the biodegradation process of organic waste. In order to ... [more ▼]

A better understanding of the water balance of a landfill is crucial for its management, as the waste water content is the main factor influencing the biodegradation process of organic waste. In order to investigate the ability of long electrical resistivity tomography (ERT) profiles to detect zones of high infiltration in a landfill cover layer, low resolution time lapse data were acquired during a rainfall event. Working at low resolution allows to cover large field areas but with the drawback of limiting quantitative interpretation. In this contribution, we use synthetic modeling to quantify the effect of the following issues commonly encountered when dealing with field scale ERT data: (i) the effect of low resolution on electrical resistivity changes interpretation, (ii) the effect of the original heterogeneous resistivity distribution on the observed relative resistivity changes, (iii) the need for temperature and pore fluid conductivity data in order to compute water content and absolute changes of water content, and (iv) the interpretation error commonly made while neglecting the dilution effect during fresh water infiltration. Firstly, due to the lack of spatial resolution, the regularized inversion process yields a smoothed distribution of resistivity changes that fail to detect small infiltration zones and yields an overestimation of the infiltration depth and an underestimation of the infiltrated volume in large infiltration areas. Secondly, the analysis of relative changes, as commonly used in literature, is not adequate when the background water content is highly heterogeneous. In such a case, relative changes reflect both the initial water content distribution and the observed changes. Thirdly, the computation of absolute water content changes better reflects the infiltration pattern, but requires spatially distributed temperature and pore fluid conductivity input data. Lastly, the dilution effect, if not considered, leads to an underestimation of the infiltrated volume. Taking into account these elements, we extracted the maximum amount of information from our field data without over-interpreting the results. This allowed the detection of larger infiltration areas possibly responsible for a large part of the annual water infiltration and landfill gas loss. [less ▲]

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See detailThe Prediction-Focused Approach: An opportunity for hydrogeophysical data integration and interpretation
Hermans, Thomas ULiege; Nguyen, Frédéric ULiege; Klepikova, Maria et al

Conference (2017, April 28)

Hydrogeophysics is an interdisciplinary field of sciences aiming at a better understanding of subsurface hydrological processes. If geophysical surveys have been successfully used to qualitatively ... [more ▼]

Hydrogeophysics is an interdisciplinary field of sciences aiming at a better understanding of subsurface hydrological processes. If geophysical surveys have been successfully used to qualitatively characterize the subsurface, two important challenges remain for a better quantification of hydrological processes: (1) the inversion of geophysical data and (2) their integration in hydrological subsurface models. The classical inversion approach using regularization suffers from spatially and temporally varying resolution and yields geologically unrealistic solutions without uncertainty quantification, making their utilization for hydrogeological calibration less consistent. More advanced techniques such as coupled inversion allow for a direct use of geophysical data for conditioning groundwater and solute transport model calibration. However, the technique is difficult to apply in complex cases and remains computationally demanding to estimate uncertainty. In a recent study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties from geophysical data, circumventing the need for classic inversions. In PFA, we seek a direct relationship between the data and the subsurface variables we want to predict (the forecast). This relationship is obtained through a prior set of subsurface models for which both data and forecast are computed. A direct relationship can often be derived through dimension reduction techniques. PFA offers a framework for both hydrogeophysical “inversion” and hydrogeophysical data integration. For hydrogeophysical “inversion”, the considered forecast variable is the subsurface variable, such as the salinity. An ensemble of possible solutions is generated, allowing uncertainty quantification. For hydrogeophysical data integration, the forecast variable becomes the prediction we want to make with our subsurface models, such as the concentration of contaminant in a drinking water production well. Geophysical and hydrological data are combined to derive a direct relationship between data and forecast. We illustrate the process for the design of an aquifer thermal energy storage (ATES) system. An ATES system can theoretically recover in winter the heat stored in the aquifer during summer. In practice, the energy efficiency is often lower than expected due to spatial heterogeneity of hydraulic properties combined to a non-favorable hydrogeological gradient. A proper design of ATES systems should consider the uncertainty of the prediction related to those parameters. With a global sensitivity analysis, we identify sensitive parameters for heat storage prediction and validate the use of a short term heat tracing experiment monitored with geophysics to generate informative data. First, we illustrate how PFA can be used to successfully derive the distribution of temperature in the aquifer from ERT during the heat tracing experiment. Then, we successfully integrate the geophysical data to predict medium-term heat storage in the aquifer using PFA. The result is a full quantification of the posterior distribution of the prediction conditioned to observed data in a relatively limited time budget. [less ▲]

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See detailA new approach for time-lapse data weighting in ERT
Lesparre, Nolwenn ULiege; Nguyen, Frédéric ULiege; Kemna, Andreas et al

in Geophysics (2017), 82(6), 325-333

Applications of timelapse inversion of electrical resistivity tomography (ERT) allows monitoring variations in the subsurface that play a key role in a variety of contexts. The inversion of timelapse data ... [more ▼]

Applications of timelapse inversion of electrical resistivity tomography (ERT) allows monitoring variations in the subsurface that play a key role in a variety of contexts. The inversion of timelapse data provides successive images of the subsurface properties showing the medium evolution. Images quality is highly dependent on the data weighting determined from the data error estimates. However, the quantification of errors in the inversion of timelapse data has not yet been addressed. We propose a methodology for the quantification of timelapse data error based on the analysis of the discrepancy between normal and reciprocal readings acquired at different times. We apply the method to field monitoring data sets collected during the injection of heated water in a shallow aquifer. We tested different error models to show that the use of an appropriate time-lapse data error estimate yields significant improvements in terms of imaging. An adapted inversion weighting for time-lapse data implies that the procedure does not allow an over-fitting of the data, so the presence of artifacts in the resulting images is greatly reduced. Our results demonstrate that a proper estimate of time-lapse data error is mandatory for weighting optimally the inversion in order to obtain images that best reflect the medium properties evolution through time. [less ▲]

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See detailPROPOSITION D'UN SUPPORT D'AIDE À LA DÉCISION POUR L'AMÉLIORATION DE L'ACCÈS À UNE EAU SOUTERRAINE DE MEILLEURE QUALITÉ DANS UN CONTEXTE DE CONTAMINATION GÉOGÉNIQUE AU FLUORURE AU BENIN (AFRIQUE DE L'OUEST)
Tossou, Joël; Hermans, Thomas ULiege; Orban, Philippe ULiege et al

in Geo-Eco-Trop : Revue Internationale de Géologie, de Géographie et d'Ecologie Tropicales (2017)

Les eaux souterraines des aquifères de socle cristallin de la partie centrale du Bénin (Département des Collines) présentent des concentrations élevées en fluorure, allant jusqu'à 7 mg/L alors que la ... [more ▼]

Les eaux souterraines des aquifères de socle cristallin de la partie centrale du Bénin (Département des Collines) présentent des concentrations élevées en fluorure, allant jusqu'à 7 mg/L alors que la norme recommandée par l'OMS est de 1.5 mg/L. La consommation de ces eaux à fortes teneurs en fluorure impacte la santé humaine. La population de la région est effectivement largement affectée par la fluorose dentaire. Les investigations hydrogéochimiques révèlent que l’origine de ces teneurs anormales est géogénique avec une forte contribution des minéraux ferromagnésiens, principalement la biotite. Ce travail se propose de réaliser une double cartographie à l'échelle du département des Collines: (i) une carte de l'estimation des teneurs en fluorure dans les eaux souterraines par krigeage ordinaire et (ii) une carte de la probabilité d'excéder la valeur guide de l’OMS (1.5 mg/L) en fluorure dans les eaux par krigeage d'indicatrices. Outre la cartographie en elle-même, l'analyse de la structure spatiale des données (teneurs en fluorure des eaux souterraines) à travers le calcul des variogrammes montre qu'il existe un lien fort entre celles-ci et les structures géologiques dominantes, confirmant l'origine géogénique du fluorure. Ces informations cartographiques serviront de support à la décision pour les décideurs et les gestionnaires de la ressource quant au choix judicieux des zones de captage d'eau potable pour minimiser/éviter les risques de fortes teneurs en fluorure. [less ▲]

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See detailFacies discrimination with electrical resistivity tomography using a probabilistic methodology: Effect of sensitivity and regularization
Hermans, Thomas ULiege; Irving, James

in Near Surface Geophysics (2017), 15

Electrical resistivity tomography (ERT) has become a standard geophysical method in the field of hydrogeology, as it has the potential to provide important information regarding the spatial distribution ... [more ▼]

Electrical resistivity tomography (ERT) has become a standard geophysical method in the field of hydrogeology, as it has the potential to provide important information regarding the spatial distribution of facies. However, inverted ERT images tend to be grossly smoothed versions of reality because of the regularization of the inverse problem. In this study, we use a probabilistic methodology based upon co-located measurements to assess the utility of ERT to identify hydrofacies in alluvial aquifers. With this methodology, ERT images are interpreted in terms of the probability of belonging to pre-defined hydrofacies. We first analyze through a synthetic study the ability of ERT to discriminate between different facies. As ERT data suffer from a loss of sensitivity with depth, we find that low sensitivity regions are more affected by misclassification. To counteract this effect, we adapt the probabilistic framework to include the spatially varying data sensitivity. We then apply our learning to a field case. For the latter, we consider two different regularization procedures. In contrast to the data sensitivity which affects the facies probability to a limited amount, the regularization can affect the probability maps more considerably because it has a strong influence on the spatial distribution of inverted resistivity. We find that a regularization strategy based on the most realistic prior information tends to offer the most reliable discrimination of facies. Our results confirm the ability of ERT surveys, when properly designed, to detect facies variations in alluvial aquifers. The method can be easily extended to other contexts. [less ▲]

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See detail3D electrical resistivity tomography of karstified formations using cross-line measurements
Van Hoorde, Maurits; Hermans, Thomas ULiege; Dumont, Gaël ULiege et al

in Engineering Geology (2017), 220

The acquisition of a full 3D survey on a large area of investigation is difficult, and from a practitioner’s point of view, very costly. In high-resolution 3D surveys, the number of electrodes increases ... [more ▼]

The acquisition of a full 3D survey on a large area of investigation is difficult, and from a practitioner’s point of view, very costly. In high-resolution 3D surveys, the number of electrodes increases rapidly and the total number of electrode combinations becomes very large. In this paper, we propose an innovative 3D acquisition procedure based on the roll-along technique. It makes use of 2D parallel lines with additional cross-line measurements. However, in order to increase the number of directions represented in the data, we propose to use cross-line measurements in several directions. Those cross-line measurements are based on dipole-dipole configurations as commonly used in cross-borehole surveys. We illustrate the method by investigating the subsurface geometry in a karstic environment for a future wind turbine project. We first test our methodology with a numerical benchmark using a synthetic model. Then, we validate it through a field case application to image the 3D geometry of karst features and the top of unaltered bedrock in limestone formations. We analyze the importance of cross-line measuring and analyze their capability for accurate subsurface imaging. The comparison with standard parallel 2D surveys clearly highlighted the added value of the cross-lines measurements to detect those structures. It provides crucial insight in subsurface geometry for the positioning of the future wind turbine foundation. The developed method can provide a useful tool in the design of 3D ERT survey to optimize the amount of information collected within a limited time frame. [less ▲]

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See detailRapport des prospections géophysiques ESO-ESU
Nguyen, Frédéric ULiege; Hermans, Thomas ULiege

Report (2017)

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See detailIntegrating Non-Collocated Well and Geophysical Data to Capture Lithological Heterogeneity at a Managed Aquifer Recharge and Recovery Site
Gottschalk, Ian; Hermans, Thomas ULiege; Caers, Jef et al

Poster (2016, December 15)

Aquifer recharge and recovery (ARR) is the process of enhancing natural groundwater resources and recovering water for later use by constructing engineered conveyances. Insufficient understanding of ... [more ▼]

Aquifer recharge and recovery (ARR) is the process of enhancing natural groundwater resources and recovering water for later use by constructing engineered conveyances. Insufficient understanding of lithological heterogeneity at ARR sites often hinders attempts to predict where and how quickly infiltrating water will flow in the subsurface, which can adversely affect the quality and quantity of available water in the ARR site. In this study, we explored the use of electrical resistivity tomography (ERT) to assist in characterizing lithological heterogeneity at an ARR site, so as to incorporate it into a flow and contaminant transport model. In this case, we had non-collocated well core log data and ERT data from a full-scale ARR basin. We compared three independent methods for producing conditional lithology-resistivity probability distributions: 1) a search template to relate the nearest logged well lithologies with ERT resistivity panels, given search criteria; 2) a maximum likelihood estimation (MLE) to match bimodal normal distributions to the histogram of each ERT line; and 3) variogram-based lithology indicator simulations constrained to well data. Each approach leverages Bayes’ Rule to estimate lithology probability given electrical resistivity. The simplest approach (method 1) yields an erroneous conditional probability function where sand dominates the conditional probability at nearly all resistivities, due in part to the strong presence of sand in the wells nearest the ERT lines. The approaches using MLE and lithology simulations (methods 2 and 3) produce similar, more realistic lithofacies probability functions. The range of resistivities where clay and sand overlap differs between methods 2 and 3: ranging between 100 and 200 ohm-m for method 2, and between 30 and 50 ohm-m for the method 3. These differences affect the posterior lithology distributions in multiple point geostatistical (MPS) simulations, and in turn, predictions of flow from models which integrate these results. To test the models, we can compare measured breakthrough times of recharged water at the site to groundwater flow simulation results using the lithofacies models created by each method. The methods described here can inform the integration of non-collocated geophysical data into a variety of applications. [less ▲]

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See detailElectrical Resistivity Monitoring of Heat Tracer to Characterize Lab-Scale Hydraulic Conductivity Distributions
Adetokunbo, Peter; Hermans, Thomas ULiege; Oware, Erasmus

Poster (2016, December 14)

Knowledge of the spatial variations of hydraulic conductivity (K) is crucial to almost every hydrogeological investigation. The representative scale of K estimates from traditional slug and pumping tests ... [more ▼]

Knowledge of the spatial variations of hydraulic conductivity (K) is crucial to almost every hydrogeological investigation. The representative scale of K estimates from traditional slug and pumping tests are, however, inadequate to accurately predict hydrogeological processes. There is increasing interest in the application of electrical resistivity tomography (ERT) to quantify spatially continuous K variations. ERT estimation of high-resolution K distributions, however, requires continuous injection of saline tracer (ST) into an aquifer over an extended period, which is feasible but impractical. Here, we present electrical resistivity thermography (ERTh) to evaluate the potential application of time-lapse ER monitoring of heat tracer (HT) to characterize high-resolution K architectures. Unlike ST, long term HT experiments are comparatively easier to manage and repeatable with minimal environmental impact. We estimate K variations via petrophysical coupling of flow and heat transport with joint time-lapse ER and discrete multi-level temperature breakthrough curves. We illustrate the strategy with a 2-D lab-scale sandbox experiment. To construct the heterogeneous field, three lenses with high-K properties with each consisting of gravel, coarse sand, and a mixture of coarse and fine sand, were created within a background of comparatively low-K fine sand. The experiment involved continuous injection and extraction of heat, respectively, at the left and right boundaries of the lab-scale aquifer. We simultaneously performed time lapse ER monitoring of the heat transport and temperature measurements at four discrete multi-levels near the heat extraction well. Results of the coupled inversions demonstrate that ER monitoring of heat tracer provides a unique opportunity to characterize high-resolution spatially continuous K variations, which seems more practical for field applications in contrast to that of the traditional ST. [less ▲]

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See detailComparison of temperature from DTS and ERT with direct measurements during heat tracer experiments in heterogeneous aquifers
Nguyen, Frédéric ULiege; Hermans, Thomas ULiege; Jamin, Pierre ULiege et al

Conference (2016, September 27)

Geothermal field characterization and heat tracer experiments often rely on scarce temperature data collected in boreholes. Electrical resistivity tomography (ERT) and distributed temperature sensing (DTS ... [more ▼]

Geothermal field characterization and heat tracer experiments often rely on scarce temperature data collected in boreholes. Electrical resistivity tomography (ERT) and distributed temperature sensing (DTS) have the potential to provide spatial information on temperature changes in the subsurface. In this contribution, we show how DTS and ERT have been used to investigate the heterogeneity of a heterogeneous aquifer during a heat tracing experiment under forced gradient conditions. Optic fibers were installed in the heat injection well and in two piezometers intersecting the main flow directions at 8 m from the injection well. These piezometers were also equipped with ERT. The DTS measurement in the injection well clearly shows the two-layer nature of the aquifer. After the end of injection, the temperature in the bottom part of the well decreases faster than in the upper part due to the higher water fluxes. Those results are confirmed by DTS measurements in natural flow conditions during a heating wire test. DTS and ERT in the cross-panel both show the vertical and lateral heterogeneity of the aquifer. Temperatures only increase significantly in the bottom part of the aquifer where advection is predominant. However, strong differences are observed laterally. ERT additionally shows that the hot plume is divided in two main flow paths, which is confirmed by direct temperature measurements. The comparison of DTS and ERT shows that one of the well is suffering from water mixing. Indeed, temperature from DTS are homogeneous over the whole tichkness of the aquifer, whereas ERT temperature, less affected by local variations, are varying. Our study demonstrate the value of spatially distributed measurements for the monitoring of heat tracer experiment and highligths the issue of multilevel sampling. The detailed temperature measurements can be subsequently used in hydrogeological model to better estimates heat flow and transport parameters. [less ▲]

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See detailQuantitative characterization and calibration of salt water intrusion models with electrical resistivity tomography
Beaujean, Jean; Hermans, Thomas ULiege; Vandenbohede, Alexander et al

Poster (2016, July 26)

Groundwater quality and coastal ecosystems in coastal areas are among the most vulnerable as they are threatened by excessive groundwater withdrawals, sea level rise and storm events potentially leading ... [more ▼]

Groundwater quality and coastal ecosystems in coastal areas are among the most vulnerable as they are threatened by excessive groundwater withdrawals, sea level rise and storm events potentially leading to salt water intrusions or infiltration into fresh water aquifers. The environmental protection and sustainable management of these groundwater resources often involves the development and calibration of a groundwater model subsequently used to forecast the total dissolved solid content (TDS). However, groundwater models are often built based on a limited number of sparse data due to borehole availability. Geophysical methods can provide spatially and temporally distributed data for hydrogeological modeling at relatively limited costs. In particular, electrical resistivity tomography (ERT) is very sensitive to the conductivity of pore water which is directly linked to the TDS content. The method is therefore well-suited for the monitoring of salt water intrusions. However, the inversion of ERT data involves a regularization process so that the resulting tomogram is only an estimate of the true resistivity distribution, suffering from smoothing and varying resolution. In many cases, the interpretation of ERT remains qualitative and skewed. In this contribution, we propose two different methods to improve the information content that can be extracted from ERT data. First, we show with a field example from Belgium how alternative regularization methods can be developed to integrate independent information into the inversion process of ERT. This enabled us to obtain a resistivity distribution much closer to the one observed in validation boreholes. Then, a site-specific petrophysical relationship is used to derive the TDS content of the aquifer from ERT tomograms. This can be directly used as input in the calibration process of a hydrogeological model. We also show how it is possible to counterbalance the effect of resolution loss with depth for surface ERT by filtering the results relative to their sensitivity. We show that this filtering is mandatory to use the ERT-derived information for calibrating a hydrogeological model. In a second example, we show how a fully coupled inversion approach can be used to directly invert geophysical data together with hydrogeological data for the calibration of hydrogeological models. At each iteration of the calibration, the simulated TDS content is transformed in a resistivity distribution using a parameterized petrophysical relationship and forward geophysical modeling yields the geophysical response. We show that this approach enables to better estimate the hydrogeological parameters of the simulated coastal aquifer than with an uncoupled approach if the conceptual model is sufficiently representative. With those two examples, we demonstrate the usefulness of ERT in the monitoring of salt water intrusions, both qualitatively to identify most vulnerable zones and quantitatively to estimate ERT-derived TDS contents or geophysical data and calibrate hydrogeological models. An innovative approach may consist in a conjunctive use of filtered geophysically-derived and geophysical data within the coupled hydrogeophysical inversion framework. Such an uncoupled-coupled approach based on a resolution threshold approach may offer a promising developing trend in hydrogeophysical inversion. [less ▲]

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See detailHeat tracer test in an alluvial aquifer: field experiment and inverse modelling
Klepikova, Maria; Wildemeersch, Samuel; Hermans, Thomas ULiege et al

in Journal of Hydrology (2016), 540

Using heat as an active tracer for aquifer characterization is a topic of increasing interest. In this study, we investigate the potential of using heat tracer tests for characterization of a shallow ... [more ▼]

Using heat as an active tracer for aquifer characterization is a topic of increasing interest. In this study, we investigate the potential of using heat tracer tests for characterization of a shallow alluvial aquifer. A thermal tracer test was conducted in the alluvial aquifer of the Meuse River, Belgium. The tracing experiment consisted in simultaneously injecting heated water and a dye tracer in an injection well and monitoring the evolution of groundwater temperature and tracer concentration in the pumping well and in measurement intervals. To get insights in the 3D characteristics of the heat transport mechanisms, temperature data from a large number of observation wells closely spaced along three transects were used. Temperature breakthrough curves in observation wells are contrasted with what would be expected in an ideal layered aquifer. They reveal strongly unequal lateral and vertical components of the transport mechanisms. The observed complex behavior of the heat plume is explained by the groundwater flow gradient on the site and heterogeneities in the hydraulic conductivity field. Moreover, due to high injection temperatures during the field experiment a temperature-induced fluid density effect on heat transport occurred. By using a flow and heat transport numerical model with variable density coupled with a pilot point approach for inversion of the hydraulic conductivity field, the main preferential flow paths were delineated. The successful application of a field heat tracer test at this site suggests that heat tracer tests is a promising approach to image hydraulic conductivity field. This methodology could be applied in aquifer thermal energy storage (ATES) projects for assessing future efficiency that is strongly linked to the hydraulic conductivity variability in the considered aquifer. [less ▲]

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