Geochemistry of the thermal springs and fumaroles of Basse-Terre Island, Guadeloupe, Lesser Antilles

The purpose of this work was to study jointly the volcanic-hydrothermal system of the high-risk volcano La Soufriere, in the southern part of Basse-Terre, and the geothermal area of Bouillante, on its western coast, to derive an all-embracing and coherent conceptual geochemical model that provides the necessary basis for adequate volcanic surveillance and further geothermal exploration. The active andesitic dome of La Soufriere has erupted eight times since 1660, most recently in 1976-1977. All these historic eruptions have been phreatic. High-salinity, Na-CI geothermal liquids circulate in the Bouillante geothermal reservoir, at temperatures close to 250 degrees C. These Na-CI solutions rise toward the surface, undergo boiling and mixing with groundwater and/or seawater, and feed most Na-CI thermal springs in the central Bouillante area. The Na-Cl thermal springs are surrounded by Na-HCO3 thermal springs and by the Na-Cl thermal spring of Anse a la Barque (a groundwater slightly mixed with seawater), which are all heated through conductive transfer. The two main fumarolic fields of La Soufriere area discharge vapors formed through boiling of hydrothermal aqueous solutions at temperatures of 190-215 degrees C below the ``Ty'' fault area and close to 260 degrees C below the dome summit. The boiling liquid producing the vapors of the Ty fault area has SD and delta(18)O values relatively similar to those of the Na-CI liquids of the Bouillante geothermal reservoir, whereas the liquid originating the vapors of the summit fumaroles is strongly enriched in O-18, due to input of magmatic fluids from below. This process is also responsible for the paucity of CH;I in the fumaroles. The thermal features around La Soufriere dome include: (a) Ca-SO4 springs, produced through absorption of hydrothermal vapors in shallow groundwaters; (b) conductively heated, Ca-Na-HCO3 springs; and (c) two Ca-Na-Cl springs produced through mixing of shallow Ca-SO4 waters and deep Na-Cl hydrothermal liquids. The geographical distribution of the different thermal features of La Soufriere area indicates the presence of: (a) a central zone dominated by the ascent of steam, which either discharges at the surface in the fumarolic fields or is absorbed in shallow groundwaters; and (b) an outer zone, where the shallow groundwaters are heated through conduction or addition of Na-Cl liquids coming from hydrothermal aquifer(s).

Estimating traveltimes and groundwater flow patterns using 3D time-lapse crosshole ERT imaging of electrical resistivity fluctuations induced by infiltrating river water

The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Chemical and isotopic equilibrium between CO2 and CH4 in fumarolic gas discharges: Generation of CH4 in arc magmatic-hydrothermal systems

The chemical and isotopic composition of fumarolic gases emitted from Nisyros Volcano, Greece, and of a single gas sample from Vesuvio, Italy, was investigated in order to determine the origin of methane (CH,) within two subduction-related magmatic-hydrothermal environments. Apparent temperatures derived from carbon isotope partitioning between CH4 and CO2 of around 340degreesC for Nisyros and 470degreesC for Vesuvio correlate well with aquifer temperatures as measured directly and/or inferred from compositional data using the H2O-H-2-CO2-CO-CH4 geothermometer. Thermodynamic modeling reveals chemical equilibrium between CH4, CO2 and H2O implying that carbon isotope partitioning between CO2 and CH, in both systems is controlled by aquifer temperature. N-2/(3) He and CH4/(3) He ratios of Nisyros fumarolic gases are unusually low for subduction zone gases and correspond to those of midoceanic ridge environments. Accordingly, CH4 may have been primarily generated through the reduction of CO, by H, in the absence of any organic matter following a Fischer-Tropsch-type reaction. However, primary occurrence of minor amounts of thermogenic CH4 and subsequent re-equilibration with co-existing CO2 cannot be ruled out entirely- CO2/He-3 ratios and delta(13)C(CO2) values imply that the evolved CO2 either derives from a metasomatized mantle or is a mixture between two components, one outgassing from an unaltered mantle and the other released by thermal breakdown of marine carbonates. The latter may contain traces of organic matter possibly decomposing to CH4 during thermometamorphism. Copyright (C) 2004 Elsevier Ltd.

European climate variations over the past half-millennium reconstructed from groundwater

Temperature reconstructions for recent centuries are the basis of estimations of the natural variability in the climate system before and during the onset of anthropogenic perturbation. Here we present, for the first time, an independent and physically based reconstruction of mean annual temperature over the past half millennium obtained from groundwater in France. The reconstructed noble gas temperature (NGT) record suggests cooler than present climate conditions throughout the 16th-19th centuries. Periods of warming occur in the 17th-18th and 20th century, while cooling is reconstructed in the 19th century. A noticeable coincidence with other temperature records is demonstrated. Deuterium excess varies in parallel with the NGT, and indicates variation in the seasonality of the aquifer recharge; whereas high excess air in groundwater indicates periods with high oscillations of the water table.

Application des méthodes géophysiques à l'étude de deux sites (Kappelen et Grenchen) de l'aquifère poreux complexe du Seeland

L'aquifère du Seeland représente une richesse en ressources hydriques qu'il est impératif de préserver contre tout risque de détérioration. Cet aquifère prolifique est constitué principalement de sédiments alluviaux post-glaciaires (graviers, sables et limons). Il est soumis aux contraintes environnementales des pratiques d'agriculture intensive, du réseau routier, des villes et de leurs activités industrielles. La connaissance optimale de ces ressources est donc primordiale pour leur protection. Dans cette optique, deux sites Kappelen et Grenchen représentatifs de l'aquifère du Seeland ont été étudiés. L'objectif de ce travail est de caractériser d'un point de vue hydrogéophysique l'aquifère au niveau de ces deux sites, c'est-à-dire, comprendre la dynamique des écoulements souterrains par l'application des méthodes électriques de surface associées aux diagraphies en intégrant des méthodes hydrogéologiques. Pour le site de Kappelen, les méthodes électriques de surface ont permis d'identifier les différents faciès géoélectriques en présence et de mettre en évidence leur disposition en une structure tabulaire et horizontale. Il s'agit d'un aquifère libre constitué d'une série de graviers allant jusqu'à 15 m de profondeur reposant sur de la moraine argileuse. Les diagraphies électriques, nucléaires et du fluide ont servis à la détermination des caractéristiques pétrophysiques et hydrauliques de l'aquifère qui contrôlent son comportement hydrodynamique. Les graviers aquifères de Kappelen présentent deux minéraux dominants: quartz et calcite. Les analyses minéralogiques indiquent que ces deux éléments constituent 65 à 75% de la matrice. La porosité totale obtenue par les diagraphies nucléaires varie de 20 à 30 %, et de 22 à 29 % par diagraphies électrique. Avec les faibles valeurs de Gamma Ray ces résultats indiquent que l'aquifère des graviers de Kappelen est dépourvu d'argile minéralogique. La perméabilité obtenue par diagraphies du fluide varie de 3.10-4 à 5.10-2 m/s, et par essais de pompage de 10-4 à 10-2 m/s. Les résultats des analyses granulométriques indiquent une hétérogénéité granulométrique au niveau des graviers aquifères. La fraction de sables, sables très fins, silts et limons constitue de 10 à 40 %. Ces éléments jouent un rôle important dans le comportement hydraulique de l'aquifère. La porosité efficace de 11 à 25% estimée à partir des résultats des analyses granulométriques suppose que les zones les plus perméables correspondent aux zones les plus graveleuses du site. Etablie sur le site de Kappelen, cette méthodologie a été utilisée sur le site de Grenchen. Les méthodes électriques de surface indiquent que l'aquifère captif de Grenchen est constitué des sables silteux comprenant des passages sableux, encadrés par des silts argileux imperméables. L'aquifère de Grenchen est disposé dans une structure relativement tabulaire et horizontale. Son épaisseur totale peut atteindre les 25 m vers le sud et le sud ouest ou les passages sableux sont les plus importants. La détermination des caractéristiques pétrophysiques et hydrauliques s'est faite à l'aide des diagraphies. Les intensités Gamma Ray varient de 30 à 100 cps, les plus fortes valeurs n'indiquent qu'une présence d'éléments argileux mais pas de bancs d'argile. Les porosités totales de 15 à 25% et les densités globales de 2.25 à 2.45 g/cm3 indiquent que la phase minérale (matrice) est composée essentiellement de quartz et de calcaire. Les densités de matrice varient entre 2.65 et 2.75 g/cm3. La perméabilité varie de 2 10-6 à 5 10-4 m/s. La surestimation des porosités totales à partir des diagraphies électriques de 25 à 42% est due à la présence d'argiles. -- The vast alluvial Seeland aquifer system in northwestern Switzerland is subjected to environmental challenges due to intensive agriculture, roads, cities and industrial activities. Optimal knowledge of the hydrological resources of this aquifer system is therefore important for their protection. Two representative sites, Kappelen and Grenchen, of the Seeland aquifer were investigated using surface-based geoelectric methods and geophysical borehole logging methods. By integrating of hydrogeological and hydrogeophysical methods, a reliable characterization of the aquifer system at these two sites can be performed in order to better understand the governing flow and transport process. At the Kappelen site, surface-based geoelectric methods allowed to identify various geoelectric facies and highlighted their tabular and horizontal structure. It is an unconfined aquifer made up of 15 m thick gravels with an important sandy fraction and bounded by a shaly glacial aquitard. Electrical and nuclear logging measurements allow for constraining the petrophysical and hydrological parameters of saturated gravels. Results indicate that in agreement with mineralogical analyses, matrix of the probed formations is dominated by quartz and calcite with densities of 2.65 and 2.71 g/cc, respectively. These two minerals constitute approximately 65 to 75 % of the mineral matrix. Matrix density values vary from 2.60 to 2.75 g/cc. Total porosity values obtained from nuclear logs range from 20 to 30 % and are consistent with those obtained from electrical logs ranging from 22 to 29 %. Together with the inherently low natural gamma radiation and the matrix density values obtained from other nuclear logging measurements, this indicates that at Kappelen site the aquifer is essentially devoid of clay. Hydraulic conductivity values obtained by the Dilution Technique vary between 3.10-4 and 5.10-2 m/s, while pumping tests give values ranging from 10-4 to 10-2 m/s. Grain size analysis of gravel samples collected from boreholes cores reveal significant granulometric heterogeneity of these deposits. Calculations based on these granulometric data have shown that the sand-, silt- and shale-sized fractions constitute between 10 and 40 % of the sample mass. The presence of these fine elements in general and their spatial distribution in particular are important as they largely control the distribution of the total and effective porosity as well as the hydraulic conductivity. Effective porosity values ranging from 11 to 25% estimated from grain size analyses indicate that the zones of higher hydraulic conductivity values correspond to the zones dominated by gravels. The methodology established at the Kappelen site was then applied to the Grenchen site. Results from surface-based geoelectric measurements indicate that it is a confined aquifer made up predominantly of shaly sands with intercalated sand lenses confined impermeable shally clay. The Grenchen confined aquifer has a relatively tabular and horizontal structure with a maximum thickness of 25 m in the south and the southwest with important sand passages. Petrophysical and hydrological characteristics were performed using electrical and nuclear logging. Natural gamma radiation values ranging from 30 to 100 cps indicate presence of a clay fraction but not of pure clay layers. Total porosity values obtained from electrical logs vary form 25 to 42%, whereas those obtained from nuclear logs values vary from 15 to 25%. This over-estimation confirms presences of clays. Density values obtained from nuclear logs varying from 2.25 to 2.45 g/cc in conjunction with the total porosity values indicate that the dominating matrix minerals are quartz and calcite. Matrix density values vary between 2.65 and 2.75 g/cc. Hydraulic conductivity values obtained by the Dilution Technique vary from 2 10-6 to 5 10-4 m/s.

Conditioning of multiple-point statistics facies simulations to tomographic images

Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment.

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.