3D electrical resistivity survey for reduction of groundwater drilling uncertainties in a clay-rich environment

被引:1
作者
McKnight J. [1 ]
Saneiyan S. [1 ]
机构
[1] University of Oklahoma, School of Geosciences, Norman, OK
关键词
electrical; groundwater; near surface; resistivity;
D O I
10.1190/tle43020117.1
中图分类号
学科分类号
摘要
Drilling for groundwater is expensive and challenging. It is even more challenging to find a location that will result in a high-yield well in heterogeneous environments. To tackle the heterogeneity issue, geophysical surveys can help in mapping the subsurface structure and delineating the drilling trajectory. The current study displays the effectiveness of 3D electrical resistivity tomography (ERT) to locate a permeable groundwater zone within a highly heterogeneous and clayey subsurface. Ground truthing the acquired geophysical data with in-situ sampling helps ensure accuracy in classifying groundwater zones in the final inverted 3D data set while also delineating boundaries between permeable groundwater zones and less permeable clayey structures. In-situ samples of groundwater and soil were used to measure the saturated region's resistivity in the laboratory using a column setup. Clay zones in the data set are classified from the nearby well data at similar depth ranges and from very low resistivity values from ERT data and laboratory measurements. The results display highly differentiating resistivity zones that are attributed to the scattered clay lenses (low resistivity) in conjunction with the freshwater zone (high resistivity). The distinction between clayey and nonclayey bodies is important to better inform drilling locations for optimal groundwater yield. This study concludes that with the aid of low-cost geophysical surveys and minimal in-situ sampling data correlations, permeable groundwater boundaries and clay lens volumes can be identified easily. © 2024 by The Society of Exploration Geophysicists.
引用
收藏
页码:117 / 124
页数:7
相关论文
共 58 条
  • [1] Ammar A.I., Kamal K.A., El-Boghdady M.F.M., Ebrahem O., 2D and 3D visualization of aquifer sediments, surface water seepage and groundwater flow using DC-resistivity, DC-IP, and SP methods, West El-Minia, Egypt, Environmental Earth Sciences, 82, (2023)
  • [2] Archie G.E., The electrical resistivity log as an aid in determining some reservoir characteristics, Transactions of the AIME, 146, 1, pp. 54-62, (1942)
  • [3] Azffri S.L., Electrical resistivity tomography and induced polarization study for groundwater exploration in the agricultural development areas of Brunei Darussalam, Environmental Earth Sciences, 81, 8, (2022)
  • [4] Bai D., Lu G., Zhu Z., Zhu X., Tao C., Fang J., Using electrical resistivity tomography to monitor the evolution of landslides' safety factors under rainfall: A feasibility study based on numerical simulation, Remote Sensing, 14, 15, (2022)
  • [5] Bai L., Li J., Zeng Z., Groundwater flow monitoring via joint time-lapse electrical resistivity and self potential data tomography: IOP Conference Series, Earth and Environmental Science, 660, (2021)
  • [6] Bellanova J., Calamita G., Giocoli A., Luongo R., Macchiato M., Perrone A., Uhlemann S., Piscitelli S., Electrical resistivity imaging for the characterization of the Montaguto landslide (Southern Italy), Engineering Geology, 243, pp. 272-281, (2018)
  • [7] Bhatnagar S., Taloor A.K., Roy S., Bhattacharya P., Delineation of aquifers favorable for groundwater development using Schlumberger configuration resistivity survey techniques in Rajouri District of Jammu and Kashmir, India, Groundwater for Sustainable Development, 17, (2022)
  • [8] Binley A., Slater L., Resistivity and Induced Polarization: Theory and Applications to the Near-surface Earth, (2020)
  • [9] Blanchy G., Saneiyan S., Boyd J., McLachlan P., Binley A., ResIPy, an intuitive open source software for complex geoelectrical inversion/modeling, Computers & Geosciences, 137, (2020)
  • [10] Boyd J., Blanchy G., Saneiyan S., McLachlan P., Binley A., 3D Geoelectrical Problems with ResiPy, An Open Source Graphical User Interface for Geoelectrical Data Processing, (2019)