A review of open software resources in python for electrical resistivity modelling

Geophysical modelling performs to obtain subsurface structures in agreement with measured data. Freeware algorithms for geoelectrical data inversion have not been widely used in geophysical communities; however, different open-source modelling/inversion algorithms were developed in recent years. In this study, we review the structures and applications of openly Python-based inversion packages, such as pyGIMLi (Python Library for Inversion and Modelling in Geophysics), BERT (Boundless Electrical Resistivity Tomography), ResIPy (Resistivity and Induced Polarization with Python), pyres (Python wrapper for electrical resistivity modelling), and SimPEG (Simulation and Parameter Estimation in Geophysics). In addition, we examine the recovering ability of pyGIMLi, BERT, ResIPy, and SimPEG freeware through inversion of the same synthetic model forward responses. A versatile pyGIMLi freeware is highly suitable for various geophysical data inversion. The SimPEG framework is developed to allow the user to explore, experiment with, and iterate over multiple approaches to the inverse problem. In contrast, BERT, pyres, and ResIPy are exclusively designed for geoelectric data inversion. BERT and pyGIMLi codes can be easily modified for the intended applications. Both pyres and ResIPy use the same mesh designs and inversion algorithms, but pyres uses scripting language, while ResIPy uses a graphical user interface (GUI) that removes the need for text inputs. Our numerical modelling shows that all the tested inversion freeware could be effective for relatively larger targets. pyGIMLi and BERT could also obtain reasonable model resolutions and anomaly accuracies for small-sized subsurface structures. Based on the heterogeneous layered model and experimental target scenario results, the geoelectrical data inversion could be more effective in pyGIMLi, BERT, and SimPEG freeware packages. Moreover, this study can provide insight into implementing suitable inversion freeware for reproducible geophysical research, mainly for geoelectrical modelling.

Development of an Underground Tunnels Detection Algorithm for Electrical Resistivity Tomography Based on Deep Learning

Kinmen Island was in a state of combat readiness during the 1950s–1980s. It opened for tourism in 1992, when all troops withdrew from the island. Most military installations, such as bunkers, anti airborne piles, and underground tunnels, became deserted and disordered. The entries to numerous underground bunkers are closed or covered with weeds, creating dangerous spaces on the island. This study evaluates the feasibility of using Electrical Resistivity Tomography (ERT) to detect and discuss the location, size, and depth of underground tunnels. In order to discuss the reliability of the 2D-ERT result, this study built a numerical model to validate the correctness of in situ measured data. In addition, this study employed the artificial intelligence deep learning technique for reprocessing and predicting the ERT image and discussed using an artificial intelligence deep learning algorithm to enhance the image resolution and interpretation. A total of three 2D-ERT survey lines were implemented in this study. The results indicate that the three survey lines clearly show the tunnel location and shape. The numerical simulation results also indicate that using 2D-ERT to survey underground tunnels is highly feasible. Moreover, according to a series of studies in Multilayer Perceptron of deep learning, using deep learning can clearly show the tunnel location and path and effectively enhance the interpretation ability and resolution for 2D-ERT measurement results.

Cross-Section Resistivity Detection of Tree (Swietenia Magahoni and Gmelina) Using ERT Method

The existence of trees is very beneficial for humans’ life. There are utilizations of tree such as urban planning and reforestation. However, the tree can be dangerous when the tree is aged and decay because of several factors that might be cause fallen tree. Furthermore, the monitoring activity is needed to know the condition of the tree. One of the methods that can be used to detect hollow in living tree is Electrical Resistivity Tomography (ERT). The ERT is an efficient and nondestructive method that can be potential to estimate resistivity cross section. The measurement of ERT conducted on Swietenia mahagoni and Gmelina with unhealthy and healthy condition visually. The data processed using Res2Dinv and reconstructed for obtaining 2D resistivity cross section. The results shows that the unhealthy Swietenia mahagoni has logarithmic resistivity value range between 0.1-1 Ωm and the healthy Swietenia mahagoni has 1-4 Ωm. Meanwhile, the unhealthy and healthy Gmelina has logarithmic resistivity value range between 0.5-4.5 Ωm and 0.5-3 Ωm, respectively. It is shows that the tree indicated health visually from biological view does not mean the tree is decay. It might be influenced by phenology factor and/or the species of the tree.

Shallow Permafrost at the Crystal Site of Peaceful Underground Nuclear Explosion (Yakutia, Russia): Evidence from Electrical Resistivity Tomography

The site where a peaceful underground nuclear explosion, Crystal, was detonated in 1974, at a depth of 98 m in perennially frozen Cambrian limestones, was studied by electrical resistivity tomography (ERT) in 2019. The purpose of our research, the results of which are presented in this article, was to assess the current permafrost state at the Crystal site and its surroundings by inversion and interpretation of electrical resistivity tomography (ERT) data. Inversion of the ERT data in Res2Dinv verified against ZondRes2D forward models yielded 2D inverted resistivity sections to a depth of 80 m. The ERT images revealed locally degrading permafrost at the Crystal site and its surroundings. The warming effect was caused by two main factors: (i) a damage zone of deformed rocks permeable to heat and fluids, with a radius of 160 m around the emplacement hole; (ii) the removal of natural land cover at the site in 2006. The artificial cover of rock from a nearby quarry, which was put up above the emplacement hole in order to prevent erosion and migration of radionuclides, is currently unfrozen.

Identification of subsidence hazard zone by integrating engineering geological mapping and electrical resistivity tomography in Gunung Kidul karst area, Indonesia

The presence of natural cavities in karst morphology may cause severe civil engineering and environmental management problems. Karst formations will limit the expansion of urbanization, especially infrastructure development in limestone areas. Geophysical methods, especially electrical resistivity tomography (ERT) techniques, are effective and efficient solutions to detect voids below the surface. This study aimed to develop a subsidence hazard map as basic information for infrastructure development. The identification was made by measuring electrical resistivity tomography on eight profiles in the infrastructure development plan. In addition, it was also supported by geological mapping, particularly the structural geology and types of rocks around the site. The research area consists of massive limestone, bedded limestone, and cavity limestone with generally north-south joints. The analysis of geological mapping data and electrical resistivity tomography measurements showed that the cavity limestone was identified with a north-south elongated pattern in line with the fracture pattern found on the surface at the research area. The surface lithology type, the geological structures density, and the subsurface lithology were used to develop a subsidence hazard map. This information is beneficial in determining the safe location of infrastructure development based on disaster risk mitigation.

Detection of Cracks in Clay Soil Using Quasi-3D Electrical Resistivity Tomography Method: Numerical and Experimental Study

Soil cracks affect the geotechnical characteristics of clay soils frequently used in engineered earth structures. In this work, numerical simulation and laboratory tests using Wenner- Schlumberger array of Electrical Resistivity Tomography (ERT) method are adopted to detect soil cracks in compacted clay soil. 3D numerical simulation showed that air-filled cracks have an anomalous high resistivity signature that can be differentiated from the background due to the high resistivity contrast between cracks and the surrounding soil. Depth, geometry, and extension of the simulated cracks are reasonably indicated. At the laboratory scale, quasi-3D ERT experiment was conducted. The results showed that soil resistivity is significantly affected by an artificially introduced crack as the crack forms a barrier that disturbs the flow of electricity in the soil. Similarly, depth, geometry, and extension of the crack are detected. Both numerical and experimental findings demonstrated that ERT method can effectively be used to identify cracking in clay soils. It is suggested that ERT, as a non invasive method, can be adopted with other traditional geotechnical methods for detecting cracks in clay soils.

Prospección geofísica por tomografía eléctrica en el abrigo de Sopeña (Asturias, N de España)

Se realiza un análisis por prospección geofísica mediante tomografía eléctrica (ERT, electrical resistivity tomography) en el abrigo de Sopeña (Asturias) y su zona inmediata. El abrigo contiene un interesante yacimiento del Paleolítico Medio superior y Paleolítico Superior inicial, desvelado en un sondeo arqueológico de hasta 3 metros de profundidad sin haber alcanzado la base rocosa. Su entrada actual está protegida por grandes bloques caídos de la cornisa, recubiertos por gruesas coladas estalagmíticas. Esta disposición posiblemente atestigua una posición original de la zona de ocupación humana más interna, dentro de una cueva de mayores dimensiones. Mediante este análisis hemos localizado varios posibles rellenos sedimentarios a cierta profundidad en el exterior del abrigo. Se abre así la posibilidad de muestrear en un futuro esos rellenos, en busca de posibles niveles de ocupación más antiguos.