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A Comparison of Array Configurations in Python-Based Software for ERT Data in Shallow Hazard Detection

Electrical Resistivity Tomography (ERT) is a widely used geophysical technique for imaging subsurface resistivity variations, providing critical insights for geological engineering and hazard assessment applications. While open-source inversion tools such as BERT and PyGIMLi offer accessible solutions for geoelectrical modeling, their comparative performance across different electrode configurations and noise conditions remains underexplored. This study evaluates the effectiveness of these software packages in reconstructing subsurface anomalies related to cavity detection and landslide assessment. Four commonly used electrode configurations—dipole–dipole, Schlumberger, Wenner-Alpha, and Wenner-Beta—were tested on two synthetic models designed to simulate real geological conditions: one representing cavity detection and the other simulating a landslide scenario. Inversions were conducted under both ideal conditions and with synthetic noise to assess their robustness against measurement uncertainties. Results indicate that while all configurations successfully identified major subsurface features, the dipole–dipole array provided the highest resolution for detecting small-scale anomalies. BERT demonstrated superior accuracy under ideal conditions, while PyGIMLi showed consistent performance across multiple configurations, particularly in resolving smaller features under noisy conditions. These findings emphasize the importance of selecting appropriate electrode configurations to enhance imaging accuracy and ensure reliable geo-electrical data interpretation. This study highlights the robustness of open-source geophysical software for subsurface investigations and provides practical insights into optimizing geoelectrical survey configurations for shallow hazard detection.

Ketersediaan
#
Perpustakaan BIG (Eksternal Harddisk) 550
451
Tersedia
Informasi Detail
Judul Seri
Geosciences
No. Panggil
550
Penerbit
Switzerland : MPDI.,
Deskripsi Fisik
22 hlm PDF, 5.255 KB
Bahasa
Inggris
ISBN/ISSN
2076-3263
Klasifikasi
550
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
online resource
Edisi
Vol.15, Issue 4, April 2025
Subjek
Inversion
geophysical modeling
shallow hazards
array configurations
cavity detection
landslide assessment
Info Detail Spesifik
Geosciences
Pernyataan Tanggungjawab
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Tidak tersedia versi lain

Lampiran Berkas
  • A Comparison of Array Configurations in Python-Based Software for ERT Data in Shallow Hazard Detection
    Electrical Resistivity Tomography (ERT) is a widely used geophysical technique for imaging subsurface resistivity variations, providing critical insights for geological engineering and hazard assessment applications. While open-source inversion tools such as BERT and PyGIMLi offer accessible solutions for geoelectrical modeling, their comparative performance across different electrode configurations and noise conditions remains underexplored. This study evaluates the effectiveness of these software packages in reconstructing subsurface anomalies related to cavity detection and landslide assessment. Four commonly used electrode configurations—dipole–dipole, Schlumberger, Wenner-Alpha, and Wenner-Beta—were tested on two synthetic models designed to simulate real geological conditions: one representing cavity detection and the other simulating a landslide scenario. Inversions were conducted under both ideal conditions and with synthetic noise to assess their robustness against measurement uncertainties. Results indicate that while all configurations successfully identified major subsurface features, the dipole–dipole array provided the highest resolution for detecting small-scale anomalies. BERT demonstrated superior accuracy under ideal conditions, while PyGIMLi showed consistent performance across multiple configurations, particularly in resolving smaller features under noisy conditions. These findings emphasize the importance of selecting appropriate electrode configurations to enhance imaging accuracy and ensure reliable geo-electrical data interpretation. This study highlights the robustness of open-source geophysical software for subsurface investigations and provides practical insights into optimizing geoelectrical survey configurations for shallow hazard detection.
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