Geoelectrical methods are considered common subsurface geophysical imaging tools that provide significant insight into the electrical properties of targets. Considering the three-dimensional nature of subsurface structures, geoelectrical survey data and their 3D inverted models can yield reliable and accurate results. In this research, using an unstructured tetrahedral meshing, three-dimensional forward and inverse models of electrical resistivity and chargeability data were performed for geological structures with travertine layers.  The Application of the unstructured mesh for the discretization of subsurface geological units increases the speed and accuracy of the modelling procedure, as well as the flexibility in designing and implementing meshing on tough topographies and the complex-shaped geometry of the target mass. Using an open-source and full-item Python software named ResIPy, the forward and inverse models were calculated and interpreted precisely. According to the geological background of the studied area, to investigate the applicability and efficiency of the 3D geoelectrical modelling method in imaging the subsurface travertine deposits, three synthetic scenarios were modeled according to the geological setting of the studied area.  The results of the 3D inversion of the synthetic models indicated the accuracy and validity of this procedure in the exploration of underground travertine deposits. As a real case study, the electrical resistivity and chargeability survey datasets in the Atashkohe travertine mine were inverted in 3D, aimed to inferring schematic geological sections along the three surveyed profiles. The survey was conducted with electrode spacing of 10 and 15 meters, using a combination of dipole-dipole and pole-dipole arrays. Considering the two-dimensional nature of these data and the relatively large distance between the two main profiles, the three-dimensional inversion results may increase the error rate. Therefore, the 2D batch inversion was preferably utilized in order to obtain a more realistic and sensible geological model. According to the geological studies and instrumental analysis of the rock samples, three types of geological structures were identified throughout the study area. Based on the subsurface electrical characteristics inferred along each profile, three geological layers were designed to illustrate the underground structures. The comparison of the inferred geological models and the drilling results along one of the survey profiles demonstrated acceptable compatibility and concordance, indicating the efficiency of the research utilized approach.

This research aims to construct 3D geophysical models of electrical resistivity and induced polarization by interpolating 2D inverted physical models through the geostatistical approach. The applicability of the method was examined for the Ghalandar porphyry-skarn copper deposit in the Agh-Daragh region, northwest of Iran. The 3D geophysical properties and block models of Cu grades were prepared by implementing the kriging interpolation method, whereby the recovered electrical models were closely linked to the Cu-sulfide mineralization. In order to evaluate the efficiency of the applied technique, the variogram models were validated using a cross-validation analysis of the kriging operation, proving the accuracy of data interpolation for each model. For the sake of meaningful correlation between geophysical models and Cu grades, the mineralization zones were extracted and subsequently propagated in the 3D space according to the generated physical properties. Meanwhile, the evaluation matrix was utilized to assess the performance of acquired results, where it confirmed that simultaneous consideration of physical models could much better determine the location of the copper mineralization. Also, the Swath plot was used as a second validation way to compare the anomalous zones.

The induced polarization (IP) response in media containing clay and/or metallic minerals has been modeled in different research. Increasing the IP applications and measurements has revealed these models’ limitations. For instance, no model has described IP response in the media with metallic minerals higher than 22 percent. So, our goal in this contribution is to explain the IP response of clay-rich samples containing low- to high-grade pyrite, galena, and sphalerite from the Zn-Pb sedimentary-exhalative mine Koushk, central Iran. The samples’ background consists of clayey/micaceous minerals, including illite, muscovite, and chlorite, that, along with the metallic minerals, make the consecutive layers in some samples, while others have a different formation. The samples also contain some insulating grains such as quartz and gypsum. Therefore, there are different conduction and polarization mechanisms in them. These properties make our samples unique and substantial to study the IP response. To do this, we measured the samples’ complex conductivity, density, porosity, cation exchange capacity (CEC), and metallic/non-metallic minerals. Then, we investigated the relationship between electrical and petrophysical properties. The results showed that the chargeability has no relationship with CEC and is a complete representation of the metallic minerals’ polarization. The normalized chargeability depends linearly on the quadrature conductivity and is affected by the metallic minerals besides CEC. The content and type of clay/mica minerals control the CEC. Hence, the normalized chargeability is influenced by the metallic and non-metallic polarizable components. The conductivity linearly relates to metallic minerals’ content and, in vein mineralizations, has higher values than disseminated ones. Ultimately, comparing our samples’ IP response with Revil et al.’s and Pelton et al.’s models for chargeability, metallic minerals volume content, and time constant determined that increasing the metallic minerals makes the chargeability decrease and the time constant increase. So, in high-grade porous media or non-dispersive formations, chargeability is a function of the metallic minerals’ volume content and the time constant. Complex media like our samples are expected in geological environments. Hence, recognizing the parameters affecting IP response in these media helps to better understand their properties and, in general, IP response characteristics.

Induced polarization (IP) tomography measurements as a near-surface geophysical method can provide information about the degree of chargeability of subsurface materials, and are commonly used in mineral exploration, engineering studies (e.g., sediment/bedrock interface identification, crushed zones and faults detection, and landslide and soil properties imaging.), as well as in environmental investigations (contaminant plums identification and landfill characterization). The purpose of these measurements is to obtain the distribution of polarizability characteristics inside an object, generally below the surface, at the boundary of the object, or outside the area in question. The result of such measurements can be mathematically modeled for the specific polarizability properties by the solution of Poisson’s equation restricted by appropriate boundary conditions. In this paper, we focus on the importance of simulating induced-polarization responses and retrieving chargeability distributions in geo-materials to enhance the characterization of subsurface structures. We present the methods for forward modeling and nonlinear inversion of induced-polarization measurements. To this end, in the first step, Poisson’s equation for a two-dimensional ground with arbitrary distribution of conductivity is solved using the finite difference numerical method and in the next step, based on the existing relations between conductivity and chargeability (Siegel’s formulation), the apparent induced polarization response is calculated. Finally, we solve the nonlinear chargeability inversion problem following a nonlinear apparent resistivity inversion. This is achieved by imposing physical constraints to prevent the estimation of unrealistic model parameters, using a Newton-based optimization method. To evaluate the efficiency of the proposed methodology, we utilized the proposed algorithm to two simulated examples and a real data set. Our numerical results show that the algorithm reliably represents the main features and structure of the Earth’s subsurface in terms of the resistivity and chargeability models. All the algorithms presented in this paper have written in the MATLAB programming language.

Forward modeling is an integral part of every geophysical modeling resulting in the numerical simulation of responses for a given physical property model. This Forward procedure is helpful in geophysics both as a means to interpret data in a research setting and as a means to enhance physical understanding in an educational setting. Calculation of resistivity and induced polarization forward responses is carried out using simulation of the current flow into the earth’ s surface through solving the Poisson’ s equation. In this contribution, a finite-difference algorithm is applied to discretize the simulated models restricted by a mixed boundary condition. To account for the 3D source characteristic, a spatial Fourier transform of the partial differential equations with respect to a range of wave numbers is performed along the strike direction. Then, an inverse Fourier transformation is conducted to obtain the potential solutions in the spatial domain. The present package provides a user-friendly interface designed to understand and handle for various conventional electrical configurations in the frame of the MATLAB programming language. To verify the program, initial responses of some simple models are compared with those of analytic solutions, which proved satisfactory in terms of accuracy. For further evaluation, the code is also examined on some complicated models.