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Geophysical data integration, stochastic simulation and significance analysis of groundwater responses using ANOVA in the Chicot Aquifer system, Louisiana, USA

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Abstract

Data integration is challenging where there are different levels of support between primary and secondary data that need to be correlated in various ways. A geostatistical method is described, which integrates the hydraulic conductivity (K) measurements and electrical resistivity data to better estimate the K distribution in the Upper Chicot Aquifer of southwestern Louisiana, USA. The K measurements were obtained from pumping tests and represent the primary (hard) data. Borehole electrical resistivity data from electrical logs were regarded as the secondary (soft) data, and were used to infer K values through Archie’s law and the Kozeny-Carman equation. A pseudo cross-semivariogram was developed to cope with the resistivity data non-collocation. Uncertainties in the auto-semivariograms and pseudo cross-semivariogram were quantified. The groundwater flow model responses by the regionalized and coregionalized models of K were compared using analysis of variance (ANOVA). The results indicate that non-collocated secondary data may improve estimates of K and affect groundwater flow responses of practical interest, including specific capacity and drawdown.

Résumé

L’intégration de données entre en jeu lorsque plusieurs niveaux intermédiaires d’assistance sont nécessaires pour corréler données primaires et secondaires de diverses manières. Le présent article décrit une méthode géostatistique qui intègre les mesures de conductivité hydraulique (K) et les données de résistivité électrique, afin d’estimer plus efficacement la distribution de K dans l’Aquifère Supérieur de Chicot, au sud-ouest de la Louisiane (Etats-Unis). Les mesures de K sont issues des pompages d’essai et représentent les données primaires (“dures”). Les données des diagraphies de résistivité électrique ont été considérées comme des données secondaires (“molles”), à partir desquelles les valeurs de K ont été déduites, par la loi d’Archie et l’équation de Kozeny-Carman. Un pseudo semi-variogramme croisé a été développé afin de pallier à l’absence de colocalisation des données de résistivité. Les incertitudes sur les semi-variogrammes automatiques et sur les pseudo semi-variogrammes croisés ont été quantifiées. Les réponses du modèle d’écoulement des eaux souterraines aux modèles régionalisés et co-régionalisés de K ont été comparés, par les analyses de variance (ANOVA). Les résultats montrent que les données secondaires non-colocalisées peuvent améliorer les estimations de K, et affecter efficacement les réponses des écoulements souterrains, y compris les débits spécifiques et les rabattements.

Resumen

La integración de datos es un gran desafío cuando existen diferentes niveles de apoyo entre datos primarios y secundarios que es necesario correlacionar de varias maneras. Se describe un método geoestadístico el cual integra mediciones de conductividad hidráulica (K) y datos de resistividad eléctrica para tener una mejor estimación de la distribución de K en el Acuífero Chicot Superior del suroeste de Luisiana, Estados Unidos de América. Las mediciones de K se obtuvieron de pruebas de bombeo y representan los datos primarios (duros). Los datos de sondeos de resistividad eléctrica se consideraron como datos secundarios (suaves) y se usaron para inferir valores de K a través de la ley de Archie y la ecuación de Carman-Kozeny. Se desarrolló un pseudo semivariograma cruzado para enfrentar la falta de colocación de datos de resistividad. Se cuantificaron las incertidumbres en los auto-semivariogramas y en los semivariogramas cruzados. Las respuestas del modelo de flujo de agua subterránea por los modelos coregionalizados y regionalizados de K se compararon usando el análisis de varianza (ANOVA). Los resultados indican que los datos secundarios no colocados pueden mejorar los estimados de K y afectar las respuestas de flujo de agua subterránea de interés práctico, incluyendo capacidad específica y descenso.

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Acknowledgements

The research was partially supported by Louisiana Department of Transportation and Development; Louisiana Geological Survey; and Louisiana State University Faculty Research Grant Program. Special thanks go to C.V. Deutsch, Dept. of Civil and Environmental Engineering, University of Alberta, Canada for his invaluable discussion. We also acknowledge the help from R. Milner of the Louisiana Geological Survey for resistivity-log data interpretation.

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Rahman, A., Tsai, F.TC., White, C.D. et al. Geophysical data integration, stochastic simulation and significance analysis of groundwater responses using ANOVA in the Chicot Aquifer system, Louisiana, USA. Hydrogeol J 16, 749–764 (2008). https://doi.org/10.1007/s10040-007-0258-x

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