Constructing the Apparent Geological Model by Fusing Surface Resistivity Survey and Borehole Records. Issue 4 (16th January 2019)

• Record Type: Journal Article
• Authors: Tsai, Jui‐Pin; Chang, Ping‐Yu; Yeh, Tian‐Chyi J.; Chang, Liang‐Cheng; Hsiao, Chin‐Tsai
• Is Part Of: Ground water. Volume 57:Issue 4(2019)
• Page Start: 590
• Page End: 601
• Publication Date: 2019-01-16
• Subjects: Groundwater -- Periodicals; Wells -- Periodicals; Eau souterraine -- Périodiques; Puits -- Périodiques; Grondwater; Eau souterraine; Puits; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 551.49
• DOI: 10.1111/gwat.12830
• Languages: English
• ISSNs: 0017-467X

Abstract

Abstract: We constructed an apparent geological model with resistivity data from surface resistivity surveys. We developed a data fusion approach by integrating dense electrical resistivity measurements collected with Schlumberger arrays and wellbore logs. This approach includes an optimization algorithm and a geostatistic interpolation method. We first generated an apparent formation factor model from the surface resistivity measurements and groundwater resistivity records with an inverse distance method. We then converted the model into a geology model with the optimized judgment criteria from the algorithms relating the apparent formation factors to the borehole geology. We also employed a non‐parametric bootstrap method to analyze the uncertainty of the predicted sediment types, and the predictive uncertainties of clay, gravel, and sand were less than 5%. Overall, our model is capable of capturing the spatial features of the sediment types. More importantly, this approach can be arranged in a self‐updated sequence to enable adjustments to the model to accommodate newly collected core records or geophysical data. This approach yields a more detailed apparent geological model for use in future groundwater simulations, which is of benefit to multi‐discipline studies. Abstract : Article impact statement : A novel approach to see into the earth with detailed geological features for a groundwater basin by fusing resistivity and borehole data.