Integration of Electrical Resistivity Tomography and Induced Polarization for Characterization and Mapping of (Pb-Zn-Ag) Sulfide Deposits

Abstract

The accurate characterization and mapping of low-grade ore deposits necessitate the utilization of a robust exploration technique. Induced polarization (IP) tomography is a powerful geophysical method for mineral exploration. An integrated survey using electrical resistivity tomography (ERT) and IP was employed in this study to characterize and map (Zn-Pb-Ag) ore deposits in NE New Brunswick, Canada. The survey encompassed twelve parallel lines across the study area. The 2D and 3D inversion of the results provided a detailed image of the resistivity and chargeability ranges of subsurface formations. The boundaries of sulfide mineralization were determined based on resistivity values of (700–2000 Ohm.m) and chargeability values of (3.5 mV/V) and were found to be located at an approximate depth of 80–150 m from the surface. The findings were validated through a comparison with data from borehole logs and mineralogy data analysis. The size and shape of sulfide deposits were successfully characterized and mapped in the study area using this cost-effective mapping approach.

1. Introduction

Subsurface mineral prospecting presents significant challenges, especially within geologically complex formations. These challenges become even more challenging when we explore low-grade ore deposits. Metal sulfides are crucial ore minerals for global non-ferrous metal supplies [1]. Volcanic-related massive sulfide deposits, referred to as “Volcanogenic Massive Sulfide” (VMS) deposits, are widely spread and represent the most frequently occurring type of such deposits. These deposits are influential sources of various valuable metals, including zinc (Zn), lead (Pb), copper (Cu), silver (Ag), and gold (Au), while also serving as notable sources for cobalt (Co), selenium (Se), manganese (Mn), cadmium (Cd), indium (In), bismuth (Bi), tin (Sn), tellurium (Te), gallium (Ga), and germanium (Ge). Canada stands out with a substantial number of more than 350 VMS deposits, which contribute significantly to the production of different metals. Specifically, in Canada, VMS deposits account for 27% of copper production, 49% of zinc production, 20% of lead production, 40% of silver production, and 3% of gold production [1,2,3]. The prevalence of copper–zinc and zinc–copper VMS deposits in Canada is attributed to the abundance of primitive oceanic arc settings in the Precambrian era [1].

In recent decades, geophysical techniques have played a crucial role in providing valuable insights into subsurface mineralization [4,5,6,7,8]. These techniques gained paramount importance in mineral exploration for several reasons. Firstly, each technique relies on a unique physical property such as resistivity, conductivity, chargeability, gravity, magnetic, and seismic properties. This diversity allows for a comprehensive understanding of the subsurface by integrating multiple data sets for comparison. Secondly, geophysical approaches are cost-effective, non-invasive, and easy to deploy. Thirdly, they have the capability to cover both small and large areas, making them suitable for exploration purposes. Furthermore, data acquired through these techniques can be interpreted instantly in the field, providing initial information about the explored targets.

Induced polarization (IP) tomography has proven to be particularly effective in identifying and delineating sulfide deposits [9,10,11,12], being the sole geophysical technique with the capability to distinguish conductive or semi-conductive minerals dispersed within a background of high electrical resistivity (host rocks) [13,14,15]. By utilizing resistivity and chargeability measurements, we can effectively differentiate the mineral deposit content within rocks [16].

This study focuses on the characterization and mapping of a low-grade (Pb-Zn-Ag) sulfide deposit using electrical resistivity tomography (ERT) and IP (ERT-IP) in Nash Creek (NC), NE New Brunswick, Canada. The ore deposit of interest is located along the western edge of the Jacquet River Graben and is known for its low-grade mineralization [3,17]. The exploration history of the NC deposits has been extensively described by [18]. Mineral exploration in the NC region dates back to at least the 1930s, with a staking rush starting in the early 1950s following the discovery of the Heath Steele Mine in the Bathurst–Miramichi region. Several regions in the vicinity, including NC, Knowles Vein, Mitchell Settlement, Falls Brook, Jack Burns Lake, and McNeil Brook, have been periodically explored. Previous exploration programs relied on selected geophysical, geochemical, and shallow drilling data, with no DCIP exploration conducted in the past 15 years.

To better understand the distribution and extent of sulfide mineralization, a 2D ERT-IP survey was conducted in the study area. The ERT-IP survey comprised twelve parallel lines, covering a significant portion of the target area. The acquired data were subjected to 2D and 3D inversion processes to generate resistivity and chargeability models. The resulting models provided valuable information about the subsurface formation resistivity, ranging from 4 to 5000 Ωm, and chargeability values ranging from 0 to 12 mV/V. Based on the resistivity and chargeability models, the boundaries of the sulfide mineralization were identified. The mineralized zones exhibited specific resistivity values in the range of 700–2000 Ωm and chargeability values of approximately greater than or equal to 3.5 mV/V. These mineralization zones were found at depths of approximately 80–150 m below the surface. The reliability of these findings was validated by comparing them with borehole logging data and mineralogical analysis.

This study aims to contribute to the understanding of (Pb-Zn-Ag) sulfide deposits and their geological characteristics through the application of ERT-IP tomography. The results obtained from the 2D ERT-IP survey and subsequent inversion techniques provide valuable insights into the spatial distribution and characteristics of the mineralization. The findings from this study have the potential to enhance exploration strategies and resource estimation in similar geological settings.

2. Geology and Mineralization

The study area is situated approximately 5.6 km away from NC, with a latitude of 47.88° and a longitude of −66.11°. The geological map (Figure 1) encompasses various types of volcanic and sedimentary rocks, including rhyolites, volcanic mafic flows, pillow lavas, tuffs, breccias, siltstones, and limestones [18,19]. The NC sulfide mineralization is formed within a bi-modal volcanic–sedimentary sequence located in the half-graben. Generally, there are three main lithologic units in the NC area: mafic rock, felsic rock, and sedimentary rocks [19]. These volcanic and sedimentary rocks were formed within a half-graben structure that is bounded by faults on the western side [20]. The prospective “Dalhousie Group” is locally overlain by carboniferous rocks. Previous studies show that the formations within the Dalhousie Group have been the main target for mineral exploration at NC. These formations are the Mitchell Settlement Fm, Jacquet River Fm, Archibald Fm, Sunnyside Fm and Big Hole Brook Fm. Most of the discovered mineralization exists within the more felsic Archibald Settlement Fm of the Hayes Zone and in the Sunnyside Fm at the Hickey Zone.

The previous works such as the drilling program conducted in NC has intersected a sulfide mineralization deposit containing sphalerite, galena, pyrite, and occasionally chalcopyrite. The silver (Ag) grades show a moderate correlation with the (Zn-Pb) sulfides. Overall, the distribution of the sulfides ore reveals an increasing trend in assay results from the northern portion of the study area. These drilling programs have revealed the presence of the mineralization deposit at approximately 180 m depth [19].

3. Techniques

3.1. Electrical Resistivity

The ERT method uses the measurement of electrical resistivity to produce images of subsurface structures. The principle of ERT is based on the fact that different materials have different electrical resistivities. By injecting electrical current into the ground through two current electrodes (A, B) and tracking the potential difference between two potential electrodes (M, N), the electrical resistivity distribution can be mapped within the subsurface. Due to the electrical homogeneous and isotropic medium of the subsurface, the data collected during resistivity surveys are called apparent resistivity ρ_a. The apparent resistivity can be calculated using the equation below.

ρ_a = G U/I,

(1)

where, U = potential difference; I = Applied current; ρ_a = Apparent resistivity of the medium; G = Geometrical factor that depends on electrode array.

3.2. Induced Polarization

Induced polarization (IP) is observed when a direct current passing through two electrodes is cut off: the voltage decays slowly and takes time to reach zero. This is an indication that charge was stored within the rocks. Four nonpolarizable electrodes are used during IP surveys: two electrodes to inject the electrical current and two additional electrodes to measure the resulting difference of the electrical potential. This phenomenon can be quantified in either the time domain (TDIP) by observing the rate of decay of voltage, or in the frequency domain induced polarization (FDIP) or spectral induced polarization (SIP). In the TDIP, the chargeability value in the IP measurements is derived from the integration of an IP decay curve. TDIP imaging measures the time-dependent response of the subsurface to electrical current to identify variations in chargeability or polarization properties. On the other hand, FDIP or SIP are determined by measuring phase shifts between sinusoidal currents and voltages. Chargeability can be expressed in terms of primary voltage (existing in steady-state conditions during the injection of the electrical current) divided by the secondary voltage (see Figure 2) and Equation (2).

M = U_IP/U_DC,

(2)

where, M = Chargeability; U_IP = Secondary potential; U_DC = Initial potential.

3.3. The Integration of ERT-IP and Tomography Measurements

The integration of ERT-IP tomography methods involves combining the measurements obtained from both techniques to gain a more comprehensive understanding of subsurface properties. ERT measures the electrical resistivity distribution of the subsurface, providing information about the lithology, moisture content, and presence of geological structures. IP, on the other hand, measures the polarization or chargeability of subsurface materials, which is related to the presence of mineralization, clay content, and fluid conductivity. By integrating ERT and IP data, it is possible to distinguish between resistive and polarizable materials, allowing for more accurate characterization of subsurface conditions and improved detection of geological features such as mineral deposits. This integration can enhance the interpretation of geophysical data and aid in various applications like groundwater exploration, mineral prospecting, and environmental studies.

In a 2D survey using the ERT-IP method, the sequence of data measurement typically involves the following steps:

• Electrode Placement: Electrodes are placed on the ground surface in a specific configuration. In ERT, this usually involves the use of a pair of current electrodes (current injection) and a set of potential electrodes (voltage measurement) that are arranged in a linear or rectangular array. In IP, additional electrodes may be used to apply a voltage waveform and measure the resulting electrical response;
• Current Injection: A known electric current is injected into the ground through the current electrodes. The injected current flows through the subsurface, and its distribution is influenced by the electrical properties of the materials encountered;
• Voltage Measurement: The potential electrodes measure the voltage distribution in the ground resulting from the injected current. These measurements are recorded and used to determine the electrical resistivity distribution in ERT and the polarization or chargeability distribution in IP;
• Data Acquisition: A series of measurements are taken by varying the electrode positions along the survey line. This involves moving the electrode array and repeating steps 2 and 3 at different locations along the line. The electrode spacing may be kept constant or adjusted depending on the desired level of resolution and the subsurface conditions;
• Data Interpretation: Once the data acquisition is complete, the collected voltage and current data are processed and analyzed. In ERT, inverse modeling techniques are used to create a resistivity model of the subsurface, representing the distribution of different geological units or features. In IP, the chargeability or polarization data are analyzed to identify zones of interest, such as mineralized areas;
• Data Integration: Finally, the ERT and IP data are integrated and correlated to obtain a more comprehensive understanding of the subsurface. This may involve overlaying the resistivity and chargeability models, identifying areas of anomalous responses, and interpreting the geological implications of the integrated results.

The sequence of data measurement may vary depending on the specific survey designs and equipment used, but the general steps outlined above provide a framework for conducting a 2D ERT-IP survey and analyzing the collected data.

4. Data Acquisition and Processing

4.1. Data Acquisition

TDIP data were collected using the IRIS Syscal Pro system. Syscal Pro is a resistivity and IP measurement system that can perform electrical resistivity tomography (ERT) and IP imaging for various near-surface applications. It can be used to measure the primary voltage and the voltage decay curve and thus provides resistivity and chargeability (IP) data. Notably, the Syscal Pro system features 20 chargeability slices, enhancing its capability to accurately capture and measure discharge phenomena. It also has a 1 µV resolution on the primary voltage. This is helpful for geophysical surveys that require a shallow investigation of the subsurface structures and the characterization of the electrical properties of the subsurface materials.

The resistivity and chargeability data sets were collected simultaneously. The study area consists of 12 surface lines, each about 2 km long, 100 m apart and covering a total area of about 9.5 km² (Figure 3). In ERT-IP surveys, electrode spacing refers to the distance between the current injection electrodes (A, B, source electrodes) and the potential measurement electrodes (M, N, receiver electrodes). The choice of electrode spacing depends on several factors, including the survey’s objectives, the subsurface’s geological conditions, and the desired depth of investigation. Generally, different electrode spacings are used to target different depths and resolutions. In surveys targeting shallow depths, such as environmental or engineering applications, the electrode spacing is usually smaller, ranging from a few meters upwards. This helps to provide high-resolution data and to capture subtle changes in subsurface resistivity or induced polarization. For surveys targeting greater depths, such as mineral exploration or groundwater studies, larger electrode spacings are employed. These can range from several meters upwards, allowing for deeper penetration into the subsurface but at the cost of reduced resolution. It is important to note that the choice of electrode spacing is a trade-off between the depth of the investigation, resolution, and practical considerations such as the size of the survey area and the available equipment. A pole–dipole configuration with an initial electrode spacing of 25 m was applied for the ERT-IP tomography survey. The pole–dipole array is commonly used in mineral exploration due to its ability to provide detailed information about subsurface targets [23,24]. It offers good depth penetration and excellent lateral resolution [24]. This array configuration is cost-effective, and is efficient in data acquisition and processing, making it a preferred choice for this study, which requires the accurate characterization of subsurface mineral deposits. In the ERT-IP data acquisition using the pole–dipole array, the sequence of moving electrodes for data acquisition follows a specific pattern. With this initial electrode spacing, the survey progressed through a series of 10 levels. At each level, a current injection electrode (source electrode) is selected, and potential measurement electrodes (receiver electrodes) are positioned at varying distances along the survey line. The first receiver electrode was placed 25 m away from the source electrode, creating the initial 25 m electrode spacing. Subsequently, the other receiver electrodes were positioned at increasing distances from the source electrode, maintaining the same spacing interval. The electrode sequence continues with the second receiver electrode being positioned 50 m away from the source, the third receiver electrode at 75 m, and so on, until all 10 levels have been completed. This sequential movement of the electrodes allows for systematic data acquisition at different distances and provides measurements at increasing depths as the survey progresses. To account for the topographic effect on the data resolution, the GPS data of each electrode along the survey lines were collected using handheld Garmin GPS devices. The GPS measurements had an accuracy of approximately ±5 m for horizontal coordinates and ±10 m for elevation data. The specific parameters used for ERT-IP measurements can be summarized as follows:

• Number of survey lines: 12 lines;
• Geophysical instrument: Syscal Pro;
• Array types: Pole–dipole;
• Electrode spacing: Electrode spacing refers to the distance between the current injection electrode (A, source) and the potential measurement electrode (M, receiver). In this survey, a pole–dipole configuration with an initial electrode spacing of 25 m was utilized;
• Number of levels: 10 levels;
• IP domain: time domain;
• Current injection duration (on-time): 240 s;
• Voltage measurement window (off-time): 20 time windows (gates), semi-logarithmic;
• Time interval between measurements: 80 s.

4.2. Data Inversion

RES2DINV (V4.08, Geotomo Software, Penang, Malaysia) and RES3DINV (V3.14, Geotomo Software, Penang, Malaysia) [25,26] RES2DINV and RES3DINV are popular commercial inversion software packages used for the interpretation and modelling of electrical resistivity and IP data obtained from geophysical surveys. RES2DINV is designed for 2D ERT-IP surveys, while RES3DINV is specifically developed for 3D and quasi-3D (2.5D) surveys. RES2DINV allows the interpretation of ERT-IP data collected along 2D survey lines and provides a 2D model of the subsurface resistivity distribution. The software utilizes the finite element method to perform the inversion process, which involves determining the best-fit resistivity model that can reproduce the observed resistivity data. RES2DINV incorporates various regularization techniques to stabilize the inversion process and minimize artifacts in the resulting resistivity models. On the other hand, RES3DINV is tailored for the interpretation of 3D and 2.5D ERT-IP data acquired from surveys using different electrode configurations, such as dipole–dipole or pole–dipole arrays. RES3DINV employs the voxel-based inversion method, dividing the subsurface into a three-dimensional grid of small cells and determining the resistivity values of each cell to create a 3D resistivity model. The software incorporates sophisticated algorithms to handle the complexities of 3D data inversion, including the handling of varying electrode spacing and geometry. Both RES2DINV and RES3DINV provide user-friendly interfaces with robust visualization capabilities, allowing users to view the input data, the resulting models, and the associated inversion parameters. They also offer tools for data quality control, sensitivity analysis, and model validation. The software packages are widely used in various geophysical applications, including environmental studies, groundwater exploration, mineral exploration, and engineering investigations.

These two software packages were utilized for the ERT-IP data processing and inversion in this study through employing the finite element method for discretizing the subsurface. The topography of the study area was incorporated into the inversion models seamlessly. The inversion process divided the subsurface into rectangular cells and aimed to produce a model that closely matched the measured data through iterative updates using the Gauss–Newton optimization technique. Also, instead of the conventional least square method, the robust L1-norm inversion method, which considers absolute errors, was employed due to the presence of sharp boundaries expected in the subsurface mineralized features. By minimizing the absolute difference between the measured and estimated data values, the impact of outlier data points was reduced to an acceptable range of error (i.e., reaching minimal further changes in RMS after a certain number of iterations) [25,27]. As per Loke [25], it is important to note that the model with the lowest RMS error may exhibit unrealistic variations and may not necessarily be the most accurate geological representation. Instead, Loke suggests selecting a model where the RMS error remains stable and does not undergo significant changes [25]. Taking this into consideration, the work models presented here are derived from the fifth iteration of the inversion process. The appendix contains the error statistics, including absolute and RMS errors, for the resistivity and IP inverse models. Please refer to Figure A1 and Figure A2 in the appendix for the respective figures.

5. Results and Discussion

5.1. 2D Resistivity and Chargeability Models

In order to avoid redundancy when presenting the 2D inversion results (resistivity and chargeability models) for each individual line, we have chosen to display the results for only two lines located in the middle. Specifically, lines 5 and 6 were selected to showcase the inversion results, as shown in Figure 4. The complete figure featuring the 2D inversion results of all the survey lines can be found in the appendix (Figure A3). The survey sequence of these lines was performed in the northwest-trending zone (Figure 3). The inverted models were represented in the west–east direction (Figure 4). The resistivity model exhibited a range of formation resistivity values from 4 to 5000 Ωm, indicating significant variations in the subsurface lithology and mineralization. In general, lower resistivity values are associated with the presence of conductive zones, representing sulfide mineralization, while higher resistivity values represent the surrounding non-conductive host rocks (Mafic Lithic Tuff) [28]. However, it is important to note that in certain cases, the zones of sulfide mineralization exhibited moderate to high resistivity values, as influenced by the broader geology of the study area [9]. This inconsistency in the interrelationship between resistivity values and mineralization zones makes it difficult to directly isolate mineralization zones from other features that could represent low resistivity values. Moreover, it has become hard to identify the boundaries of mineralization zones solely based on resistivity anomalies. The chargeability models, on the other hand, revealed chargeability values ranging from 0 to 12 mV/V. The number of chargeability anomalies is lower and shows well-identified boundaries compared to the resistivity anomalies. Higher chargeability values were observed in zones with increased sulfide mineralization, indicating the presence of conductive minerals. The chargeability response was particularly useful in delineating the boundaries and extent of the mineralized zones [28]. While high chargeability anomalies can be an indication of the presence of either clay minerals or sulfide mineral deposits, previous geological and petrophysical studies on the area did not report any presence of clay minerals. For example, Figure 5a shows that the lithology of the area is fully dominated by igneous rocks. Thus, we assume that the high chargeability anomalies in the study area are mainly driven by the presence of sulfide ore deposits.

As the study area is fully dominated by mafic volcanic rocks (Figure 1), the mineralization zones were abundant in the inverted models, with relatively low chargeability and moderate to high resistivity values. Previous petrophysical surveys conducted in the study area have indicated the presence of high-grade sulfide mineralization in Pyroclastic units composed of Felsic Lithic Tuff, while low-grade mineralization is embedded in Mafic Lithic Tuff and medium-grade mineralization is found in flow-banded Rhyolite units (Figure 5a) [3,20,29]. So, the mineralization zones appear with relatively low to moderate chargeability and moderate to high resistivity values. The inversion models for both resistivity and chargeability are presented in Figure 4. These data were also correlated to the borehole logging data (Figure 5b). The resistivity sections show various anomalies relatively with low resistivity values along the middle of most of the resistivity lines. Additionally, some other low resistivity anomalies are dispersed across some lines. This makes it difficult to pinpoint specific zones for potential mineralization.

On the other hand, the chargeability lines show a smaller number of anomalies compared to the resistivity lines. Moreover, the anomalies along the chargeability lines are narrower and well-defined. The presence of a low number of chargeability anomalies could indicate that the majority of the sulfide deposit within the exploration area is of medium to low grade. Furthermore, the limited extent of the mineralization zone suggests a weak occurrence of the deposit.

The mineralized zone in the 2D inversion models (Figure A3) appears at a depth of around 80 m to 140 m from the surface. From line 1 to line 4 (Figure A3), the mineralization zone seems to be a narrow ore body with a shallower depth and a low-grade ore. In contrast, line 5 and 6 (Figure 4) display a deeper mineralization zone of a higher grade and extent compared to the previous lines. Lines 7 to 9 (Figure A3) exhibit relatively shallow mineralization zones with a low grade and a medium extent. Finally, for lines 10 to 12, the mineralization zone is deeper and has a high grade and extent.

5.2. 3D Resistivity and Chargeability Models

Performing a 3D inversion of a 2D ERT-IP survey using RES3DINV involves several steps to ensure accurate and reliable results. The following is a detailed description of the process:

• Data Acquisition and Preprocessing: The first step was acquiring the 2D ERT-IP survey data using appropriate measurement equipment, as mentioned earlier. This involved positioning electrodes along the survey lines and measuring the voltage and current data. Once the data sets were collected, they underwent preprocessing, which included removing any noise or interference, correcting for electrode offsets, and applying geometric corrections to ensure accurate spatial positioning of the data;
• 3D Data model: The 3D model was constructed through combining the 2D lines [30,31]. These data were merged using the GPS coordinates of survey lines. This merged 3D view serves as a valuable resource for further interpretation, modelling, and exploration planning, facilitating a comprehensive assessment of the mineral deposits in the study area;
• Inversion: The 3D inversion process was performed using RES3DINV. The 3D model is helpful for visualizing the lateral distribution of the ore deposits.

The utilization of 3D inversion techniques for resistivity and chargeability modeling, based on 2D surveys, provides significant advantages over traditional 2D inversion approaches [32,33]. The incorporation of the third dimension allows for improved accuracy in representing lateral variations, enhanced depth resolution, realistic geometry representation, and improved visualization capabilities [34,35,36]. These advantages contribute to a more comprehensive characterization and mapping of sulfide deposits, assisting in the development of effective exploration strategies and resource evaluation.

The results obtained from the 3D inversion method provide a significant improvement over 2D inversion in terms of accurately characterizing the resistivity and chargeability distribution of the mineralized zones. Moreover, the 3D model reveals an N–S trend on both resistivity and chargeability models that align with the N–S fault that crosses the study area (Figure 6). Detailed analysis of the presented horizontal and vertical sections (Figure A5, Figure A6, Figure A7 and Figure A8 in the appendix) reveals key insights. To facilitate effective comparison, particular attention is given to the fifth slice from the horizontal sections (Figure 6) and the 18th slice from the vertical sections (X-Z direction), spanning a distance from 9500 to 11500 m in the Y direction (Figure 7). These slices depict the resistivity and chargeability distribution, along with the accompanying RMS errors of the inverted models. The resistivity model derived from the 3D inversion showcases a broad range of formation resistivity values, spanning from 4 to 5000 Ωm. Similarly, the chargeability values range from 0 to 12 mV/V. Notably, when comparing the mineralized zones, the results obtained from the 3D inversion demonstrate a notable improvement over the 2D inversion. Specifically, the resistivity values within the mineralization zones, as shown in Figure 6a and Figure 7a, exhibit a moderate to high range, ranging from 800 to 1500 Ωm. This finding aligns closely with the interpretations derived from the 2D inversion models. Furthermore, the chargeability values associated with the mineralization zones, depicted in Figure 6b and Figure 7b, fall within a relatively low to moderate range. The chargeability signature zones >3.5 mV/V were more broadly clearly developed than the resistivity signature zones. These characteristics were relatively harmonious with those in the 2D models. Accordingly, the continuity of the chargeability signature zones was effectively visualized in the 3D model (Figure 8). The 3D model visualizations were more useful for characterizing the shape and size of sulfide deposits than the 2D models. Figure 9 shows the 3D model of the occurrence of sulfide signature zones at a 3.5 mV/V cut-off chargeability value. The size of the sulfide deposit ore (potential geological reserve) was estimated to be 393,107 m³ based on the inversion distance method (in the visualization software used (Voxler 4), there exists an option to calculate the volume of the iso-surface). While the data show an N–S trend that aligns with the N–S fault, it is not clear if the mineralization in the study area is structurally controlled by the fault and this point may require further work.

Overall, the 3D inversion method offers a significant advancement over the 2D inversion by providing a more accurate characterization of the resistivity and chargeability distribution within the mineralized zones. These improved results contribute to a better understanding of subsurface mineralization and further enhance the reliability and confidence of the study’s findings.

5.3. Validation with Borehole Logging and Mineralogy Data

Two candidate hotspot locations were identified on the chargeability 3D model (Figure 8b), and two test boreholes were drilled to validate our findings. Core samples were extracted from these boreholes for mineralogical analysis. The analysis confirmed the presence of sulfide minerals in the core samples (8.2% Zn, 10% Pb and 9.1% Zn, 2.1% Pb), which is consistent with the mineralization zones identified on the chargeability model (Figure 8b). The agreement between the ERT-IP survey results and the mineralogical analysis supports our interpretation of the characterization and mapping of this low-grade sulfide deposit using ERT-IP tomography.

The boundaries of the sulfide mineralization zone, as determined by ERT-IP criteria, coincided with the geological and petrophysical features of the area, such as faults and lithological contacts. This alignment provided confidence in the accuracy and reliability of the ERT-IP survey results. Consequently, it is considered that 2D/3D ERT-IP tomography is useful for the determination of the boundaries of sulfide mineralization alteration zones.

6. Conclusions

This study focused on the integrated analysis of electrical resistivity tomography and induced polarization (ERT-IP) for the characterization and mapping of low-grade (Pb-Zn-Ag) sulfide deposits at Nash Creek in NE New Brunswick, Canada. Both 2D and 3D inversion models were conducted and compared, providing a comprehensive understanding of the subsurface characteristics and distribution of the sulfide deposit. The ERT-IP inversion yielded detailed 2D and 3D resistivity and chargeability models, revealing the range of resistivity (4 to 5000 Ohm.m) and chargeability (0–12 mV/V) values for subsurface formations. Based on these models and considering existing geological and petrophysical studies, potential sulfide mineralization zones were identified using resistivity values (700–2000 Ohm.m) and chargeability values (≥3.5 mV/V) at depths of approximately 80–150 m. A 3D iso-surface model was constructed to visualize the distribution of these potential mineralization zones, allowing for a 3D geological model of the study area. The estimated size of the sulfide deposit ore (potential geological reserve) was determined to be 393,107 m³ using the inversion distance approach. The accuracy of the findings was confirmed through comparison with borehole logs and mineralogy data analysis. The study successfully characterized and mapped the size and shape of sulfide deposits in the study area, showcasing the effectiveness of this cost-effective mapping approach. The findings contribute to the understanding of sulfide deposits and their geological characteristics in the study area. The application of ERT-IP tomography demonstrated its efficacy in delineating mineralized zones and can enhance exploration strategies and resource estimation in similar geological settings. Further investigations and integration with additional geoscientific data can lead to a more comprehensive understanding of the deposit and optimize resource extraction techniques.