Abstract
Hydrofacies distribution and heterogeneity influence groundwater flow and solute transport. The characterization of hydrofacies distribution is challenging because of the scarcity of observation data, and because of the various types of uncertainties in whatever observation data exist and in the geostatistical methods used. This paper presents a method to integrate geophysical data and borehole data to improve the characterization of hydrofacies distribution and to reduce uncertainty in the simulations of porous media, in particular, unconsolidated sedimentary clay/sand environments in unsaturated states. A sandbox experimental investigation was conducted by the combined use of drilling and electrical resistivity tomography (ERT). Borehole data reveal the vertical variation in hydrofacies in the model, and ERT data can well represent the continuity of hydrofacies in the profiles. A histogram probability matching method was used to assimilate the two kinds of data. The ERT profile was converted into a hydrofacies section based on a cutoff value of resistivity, and then a series of highly credible virtual boreholes were extracted from the hydrofacies profiles. Finally, the transition probability geostatistics (TPG) method, based on the Markov chain, was employed to simulate the hydrofacies distribution. The results show that the ERT data, as a kind of high-density soft data, can provide more lithological information for TPG simulation. The presented method with TPG can construct a relatively high-accuracy hydrofacies model by the combined use of ERT geophysical data and borehole data.
Résumé
La répartition et l’hétérogénéité des hydrofaciès influencent l’écoulement des eaux souterraines et le transport soluble. La caractérisation de la répartition des hydrofaciès est difficile en raison de la rareté des données d’observation et des divers types d’incertitudes quelles que soient les données d’observation qui existent et les méthodes géostatistiques utilisées. Cet article présente une méthode pour intégrer des données géophysiques et des données de forage afin d’améliorer la caractérisation de la répartition des hydrofaciès et de réduire l’incertitude dans la simulation des milieux poreux, en particulier les environnements argilo/sableux sédimentaires non consolidés dans des états insaturés. Une étude expérimentale sur boîte à sable a été conduite par l’utilisation combinée d’une foration et d’une tomographie de résistivité électrique (TRE). Les données de forage montrent la variation verticale des hydrofaciès dans le modèle et les données TRE peuvent représenter correctement la continuité des hydrofaciès dans les profils. Une méthode d’appariement de la probabilité de l’histogramme a été utilisée pour rapprocher les deux types de données. Le profil TRE a été traduit en section de l’hydrofaciès sur la base d’une valeur de coupure de la résistivité, puis une série de forages virtuels hautement crédibles a été extraite des profils d’hydrofaciès. Au final, la méthode de la géostatistique des probabilités de transition (GPT), basée sur la chaîne de Markov, a été utilisée pour simuler la distribution des hydrofaciès. Les résultats montrent que les données TRE, en tant que type de données souples de haute densité, peuvent apporter plus d’information lithologique pour la simulation de la GPT. La méthode présentée avec GPT permet de construire un modèle relativement très fiable d’hydrofaciès, par l’utilisation conjointe des données de géophysique TRE et des données de forage.
Resumen
La distribución y la heterogeneidad de las hidrofacies influyen en el flujo de las aguas subterráneas y en el transporte de solutos. La caracterización de la distribución de las hidrofacies es un reto debido a la escasez de datos de observación y a los diversos tipos de incertidumbres en los datos existentes y en los métodos geoestadísticos utilizados. Este trabajo presenta un método para integrar los datos geofísicos y de sondeos con el fin de mejorar la caracterización de la distribución de las hidrofacies y reducir la incertidumbre en las simulaciones de medios porosos, en particular, de entornos sedimentarios arcillosos/arenosos no consolidados en estado no saturado. Se llevó a cabo una investigación experimental de la caja de arena mediante el uso combinado de la perforación y la tomografía de resistividad eléctrica (ERT). Los datos de perforación revelan la variación vertical de las hidrofacies en el modelo, y los datos ERT pueden representar bien la continuidad de las hidrofacies en los perfiles. Para asimilar los dos tipos de datos se utilizó un método de correspondencia de probabilidades de histograma. El perfil de ERT se convirtió en una sección de hidrofacies basada en un valor de corte de resistividad, y luego se extrajo una serie de sondeos virtuales de alta credibilidad a partir de los perfiles de hidrofacies. Por último, se empleó el método de geoestadística de probabilidad de transición (TPG), basado en la cadena de Markov, para simular la distribución de las hidrofacies. Los resultados muestran que los datos ERT, como tipo de datos blandos de alta densidad, pueden proporcionar más información litológica para la simulación TPG. El método presentado con TPG puede construir un modelo de hidrofacies de relativa alta precisión mediante el uso combinado de datos geofísicos de ERT y de perforación.
摘要
水相分布和非均质性影响地下水流和溶质运移。由于观测数据的不足,以及存在的任何观测数据和采用地质统计方法存在不同类型的不确定性,水相分布的表征具有挑战性。本文提出了一种整合地球物理数据和钻孔数据的方法,以改进水相分布的表征并减少多孔介质模拟中的不确定性,特别是非饱和状态下的松散沉积粘土或砂层环境。通过结合使用钻孔和电阻率层析成像(ERT)进行砂箱实验研究。钻孔数据揭示了模型中水相的垂直变化,ERT数据可以很好地呈现剖面中水相的连续性。使用直方图概率匹配方法来同化这两种数据。ERT剖面根据电阻率截断值转换为水相剖面,然后从水相剖面中提取出一系列可信度高的虚钻孔数据。最后,采用基于马尔可夫链的转移概率地质统计学(TPG)方法模拟水相分布。结果表明,ERT数据作为一种高密度软数据,可以为TPG模拟提供更多的岩性信息。所提出的通过结合使用ERT地球物理数据和钻孔数据的TPG方法可以构建一个相对高精度的水相模型。
Resumo
A distribuição e a heterogeneidade das hidrofácies influenciam o fluxo das águas subterrâneas e o transporte de solutos. A caracterização da distribuição de hidrofácies é desafiadora devido à escassez de dados de observação e por causa dos vários tipos de incertezas em quaisquer dados de observação existentes e nos métodos geoestatísticos usados. Este artigo apresenta um método para integrar dados geofísicos e dados de poços para melhorar a caracterização da distribuição de hidrofácies e reduzir a incerteza nas simulações de meios porosos, em particular, ambientes sedimentares não consolidados de argila/areia em estados não saturados. Uma investigação experimental em caixa de areia foi conduzida pelo uso combinado de perfuração e tomografia de resistividade elétrica (TRE). Os dados de poços revelam a variação vertical das hidrofácies no modelo, e os dados de TRE podem representar bem a continuidade das hidrofácies nos perfis. Um método de correspondência de probabilidade de histograma foi usado para assimilar os dois tipos de dados. O perfil TRE foi convertido em uma seção de hidrofácies com base em um valor de corte de resistividade e, em seguida, uma série de poços virtuais altamente confiáveis foram extraídos dos perfis de hidrofácies. Por fim, o método de probabilidade de transição geoestatística (PTG), baseado na cadeia de Markov, foi empregado para simular a distribuição de hidrofácies. Os resultados mostram que os dados TRE, como um tipo de dados auxiliares de alta densidade, podem fornecer mais informações litológicas para simulação de PTG. O método apresentado com PTG pode construir um modelo de hidrofácies de precisão relativamente alta pelo uso combinado de dados geofísicos de TRE e dados de poços.
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This study is supported by the National Natural Science Foundation of China (Nos. 41831289, 42072276, and 41972278).
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Ma, L., Deng, H., Yan, Y. et al. Hydrofacies simulation based on transition probability geostatistics using electrical resistivity tomography and borehole data. Hydrogeol J 30, 2117–2134 (2022). https://doi.org/10.1007/s10040-022-02539-9
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DOI: https://doi.org/10.1007/s10040-022-02539-9