Hydraulic conductivity estimation and lithological classification of an esker aquifer system using surface electrical resistivity surveys and a neural network

Oldenborger, Greg A.; Paradis, Daniel

doi:10.1016/j.jappgeo.2023.105106

Journal of Applied Geophysics

2023

DOI: 10.1016/j.jappgeo.2023.105106

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Hydraulic conductivity estimation and lithological classification of an esker aquifer system using surface electrical resistivity surveys and a neural network

Greg A. Oldenborger

Daniel Paradis

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2024

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Cited by 3 publications

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Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary

Mohammed,

Szabó,

Szűcs

2024

Model. Earth Syst. Environ.

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In this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of the Quaternary aquifer system in the Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) is used to map lithological variations within the aquifer system. Additionally, the Csókás method is used to discern both vertical and horizontal fluctuations in hydraulic conductivity. MFV-CA is introduced to cope with the limitation of the conventional Euclidean distance-based k-means clustering known for its low resistance to outlying values, resulting in deformed cluster formation. However, the computational time and demands of MFV-CA are evident, making them costly and time-consuming. As a result, Deep Learning (DL) methods are suggested to provide fast characterization of the groundwater aquifers. These methods include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), which are implemented for classification and regression. The classification categorized the inputs into three distinct lithologies trained initially by the results of MFV-CA. At the same time, the regression model offered a continuous estimations of hydraulic conductivity trained by the results of the Csókás model. The results demonstrated significant compatibility between the outcomes derived from the clustering and Csókás approaches and DL algorithms. Accordingly, the lithofacies and hydraulic conductivity variations across the main hydrostratigraphical units are mapped. This integration enhanced the understanding of the groundwater system, offering promising inputs for groundwater and development and management.

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Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary

Mohammed,

Szabó,

Szűcs

2024

Model. Earth Syst. Environ.

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Estimating hydraulic diffusivity in coastal confined aquifer under tidal fluctuation using a frequency domain model

Ma,

Shi,

Zhan

2024

Journal of Hydrology

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Vertical electrical sounding method and Dar Zarrouk analysis to identify the distribution of seawater intrusion in Pelauw Village, Maluku

Bahri,

Tualepe,

Batlolona

et al. 2024

J. Degrade. Min. Land Manage.

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Groundwater is one of the essential resources that support human life. Excessive exploitation activities can cause groundwater problems such as seawater intrusion, especially in coastal areas. Groundwater salination must be a concern and measured to determine the condition and level of distribution. One of the non-invasive, inexpensive, and efficient methods to see seawater intrusion phenomena is the vertical electrical sounding (VES) technique of electrical resistivity method. This research aimed to analyze the distribution of seawater intrusion in Pelauw Village, Maluku, Indonesia, using the VES and Dar-Zarrouk parameters S and T. The S and T are longitudinal conductance and transversal resistance, respectively. This study collected 16 VES stations spread across residential areas near the coast of Pelauw Village. Groundwater affected by seawater intrusion in the study area has S>1.00 mho and T<1,000 ohm m2. Three VES stations are suspected to have experienced seawater intrusion, namely V7, V8 and V12. These three stations are located near the shoreline and densely populated areas. Based on the 2D cross-section, the spread of seawater intrusion toward the land is about 200 meters. This seawater intrusion event is thought to have occurred due to groundwater exploitation by communities around the coast and active tectonic activity. The VES method and Dar Zarrouk Analysis proved compelling enough to delineate the spread of seawater intrusion, so based on these results, it can be a reference for mitigating groundwater pollution.

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Hydraulic conductivity estimation and lithological classification of an esker aquifer system using surface electrical resistivity surveys and a neural network

Cited by 3 publications

References 48 publications

Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary

Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary

Estimating hydraulic diffusivity in coastal confined aquifer under tidal fluctuation using a frequency domain model

Vertical electrical sounding method and Dar Zarrouk analysis to identify the distribution of seawater intrusion in Pelauw Village, Maluku

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