Forward and inverse modeling of electrical resistivity geophysical data of a landslide surface discretized by unstructured mesh - A case study: Tehran-North Freeway

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Abstract

Geoelectrical surveys are commonly used to image the subsurface and provide valuable information about the electrical properties of targets in the subsurface. In this study, we focused on investigating areas with rough topography and complex-shaped electrical structures using unstructured meshing. Electrical resistivity tomography (ERT) was employed as a common method for near-surface geophysical investigations, allowing us to determine different earth layers based on their electrical properties, and also, to identify potential landslide-prone areas. To solve the geoelectrical problems, we utilized a program called ResIPy, which employed a triangular mesh based on finite element algorithm. By simulating an artificial landslide, we found that the triangular mesh provided more accurate identification of geological formations compared to a structural mesh with rectangular elements. Additionally, the algorithm execution time with the new mesh was reduced, requiring less memory. We then analyzed the field data from a landslide-prone area located approximately 10 kilometers northwest of Tehran Province. The data were collected from 31 stations along four ERT survey lines with a separation distance of 20 meters over the landslide surface. The surface in this area is characterized by low electrical resistivity property and is composed of heterogeneous materials such as alluvium and tuff, making it very slippery. We identified three distinct subsurface layers with significant differences in electrical resistivity. The surface layer consists of heterogeneous materials with electrical resistivity ranging from 30 to 100 Ohm-m, and in some regions, up to 200 Ohm-m, indicating crushed areas of alluvium and tuff. This layer is observed up to the depth of 15 to 20 meters in electrical cross-sections. The second layer with a resistivity below 40 Ohm-m is identified as an alluvial and conglomerate layer. At greater depths, we found a layer composed of high resistivity Alborz tuff.

Keywords

References

Abassi, R.,Yassaghi, R., 2005, Geometry and kinematic analysis of Laniz structural sub-zone; evidence for structural evlution of south central Alborz. Geoscience, 56:152–167.
Abedi, M., 2020, A focused and constrained 2D inversion of potential field geophysical data through Delaunay triangulation, a case study for iron-bearing targeting at the Shavaz deposit in Iran. Prostaglandins and Other Lipid Mediat, 95:106408
Adamczyk, A., Malinowski, M., Malehmir, A., 2013, Application of first-arrival tomography to characterize a quick clay landslide site in Southwest Sweden. Acta Geophys, 61:1057–1073.
Akca, I., 2016, ELRIS2D: A MATLAB Package for the 2D Inversion of DC Resistivity/IP Data. Acta Geophys, 64:443–462.
Akça, I., Basokur, A.T., 2010, Extraction of structure-based geoelectric models by hybrid genetic algorithms. Geophysics, 75.
Alpaslan, N., Bayram, M., 2020, Landslide study with 2D electrical resistivity tomography (ERT): A case study from Turkey. Carpathian J Earth Environ Sci, 15:391–403.
Blanchy, G., Saneiyan, S., Boyd, J., Mclachlan, M., Binley, A., 2020, ResIPy, an intuitive open source software for complex geoelectrical inversion/modeling. Comput Geosci,
Boyd, J., Blanchy, G., Saneiyan, S., McLachlan, P., Binley, A., 2019, 3D Geoelectrical Problems With ResiPy, an Open Source Graphical User Interface for Geoelectrical Data Processing. FastTimes, 24:85–92.
Damavandi, K., Abedi, M., Norouzi, GH., Mojarab, M., 2022, Geoelectrical characterization of a landslide surface for investigating hazard potency, a case study in the Tehran- North freeway, Iran. Int J Min Geo-Engineering.
Demirci, I., Erdoǧan, E., Candansayar, M.E., 2012, Two-dimensional inversion of direct current resistivity data incorporating topography by using finite difference techniques with triangle cells: Investigation of Kera fault zone in western Crete. Geophysics, 77.
Erdoğan, E., Demirci, I., Candansayar, M.E., 2008, Incorporating topography into 2D resistivity modeling using finite-element and finite-difference approaches.
 Kamranzad, F., Mohasel Afshar, E., Mojarab, M., Memrian, H., 2016, Landslide hazard zonation in Tehran province using data-driven and AHP methods. Geoscience, 25:101–114.
Highland, L.M., Bobrowsky, P., 2008, The landslide Handbook - A guide to understanding landslides. US Geol Surv Circ, 1–147.
Jeshvaghani, M.S., Darijani, M., 2014, Two-dimensional geomagnetic forward modeling using adaptive finite element method and investigation of the topographic effect. J Appl Geophys, 105:169–179.
Key, K., 2016, MARE2DEM: A 2-D inversion code for controlled-source electromagnetic and magnetotelluric data. Geophys J Int, 207:571–588.
Loke, M.H., 2015, Tutorial: 2D and 3D electrical imaging surveys.
Mita, M., Glazer, M., Kaczmarzyk, R., Dabrowski, M., Mita, K, 2018, Case study of electrical resistivity tomography measurements used in landslides investigation, Southern Poland. Contemp Trends Geosci, 7:110–126.
Pasierb, B., Grodecki, M., Gwóźdź, R., 2019, Geophysical and geotechnical approach to a landslide stability assessment: a case study. Acta Geophys, 67:1823–1834.
Ren, Z., Tang, J., 2010, 3D direct current resistivity modeling with unstructured mesh by adaptive finite-element method. Geophysics, 75:6–17.
Report of BZP consult engineers, 2018.
Rücker, C., Günther, T., Wagner, F.M., 2017, pyGIMLi: An open-source library for modelling and inversion in geophysics. Comput Geosci, 109:106–123.
Stucchi, E., Ribolini, A., Anfuso, A., 2014, High-resolution reflection seismic survey at the Patigno landslide, Northern Apennines, Italy. Near Surf Geophys, 12:559–571.
Thomas, G., Carsten, R., 2011, Boundless Electrical Resistivity Tomography BERT – the user tutorial. Interface 1–28.
Volume 8, Issue 3
July 1401
Pages 202-212

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