Study on the Relationship between Lithological Differences and Electromagnetic Changes during Mine Water Inrush Relationship between Lithological Differences and Electromagnetic Changes

As the main energy source of China’s social and economic development, coal has significantly bolstered the long-term, stable, and rapid growth of the national economy. However, the hydrogeology of coal resources in China is very complicated, making China one of the countries most susceptible to intricate hydrogeological hazards that threaten coal mine safety [1-3]. Therefore, there is an urgent need to increase the precision of geophysical detection methods to assess the hydrogeological conditions of coal seams accurately and ensure safe production within coal mines.

In recent years, extensive research has been conducted on geophysical exploration, detection, and identification of sources and channels for mine water infiltration [4-6]. While reflecting the electrical conductivity efficiency of rocks, resistivity is also a critical geophysical parameter [7]. Through their investigation of porous rock models, Nakamura et al. [8, 9] elucidated the relationship between rock porosity and resistivity changes and applied this understanding to assess the porosity of primary rock formations. Zhang et al. [10] employed resistivity tomography to capture variations in resistivity and anisotropy curves across different depths, and simultaneously obtained resistivity images of stress changes with formation depth, which played a positive role in the in-depth understanding and research of the resistivity change mechanism. Choi et al. [11] obtained good results in classifying rock by studying their resistivity. Coli et al. [12] estimated tunnel-adjacent rock characteristics by examining correlations among permeability, porosity, and resistivity across various rock samples. However, these studies focused primarily on the resistive response characteristics of identical rock under varying environmental conditions without considering how lithological differences among distinct rocks influence these responses.

Currently, analyzing the internal damage of coal and rock through resistivity change characteristics is crucial for mine disaster prevention and control, enabling timely detection of precursor information and early warning systems [13]. Using the generalized specific volume database derived from transient electromagnetic method (TEM) geoelectric data and pumping tests, Chen et al. [14] introduced a quantitative evaluation method for aquifer water content. Jiang et al. [15] derived the wavenumber domain equation for the three-dimensional source-excited full-space electromagnetic field within a two-dimensional geoelectric model and concluded that low-resistivity bodies predominantly govern the diffusion of transient electromagnetic fields in an unbounded medium. Zhang et al. [16] employed an integrated geophysical exploration approach combining TEM with the high-density resistivity method to accurately delineate both the extent and location of water accumulation areas in a coal mine located in Datong, Shanxi Province. The application of TEM has rapidly expanded in detecting hydrogeological conditions associated with coal seams, and it is more urgent to study the lithology differences and electromagnetic change laws among different rocks [17-19]. Consequently, enhancing geophysical exploration accuracy or facilitating water source detection under complex geological scenarios by analyzing the factors influencing rock conductivity efficiency based on Archie’s formula while highlighting how lithology, porosity, and water salinity affect the electromagnetic behavior of coal and rock. The analysis results were verified through laboratory experiments as well as multiple field monitoring results, and finally, the lithology difference and electromagnetic change rule under the condition of water filling in the mine were determined. The research results can be used to improve the accuracy of geophysical detection and identification of mine water-filling sources and channels.

The electrical conductivity of rock is defined as the ratio of the actual electrical conductivity of the rock to that of a straight capillary tube, which is assumed to have an equivalent length and water volume as the rock itself [16, 20]. This relationship can be expressed as follows:

where $Rw$ is the formation water resistivity, $Rt$ is the rock sample resistivity, and $ϕw$ is the water-bearing porosity.

According to Archie’s formula [21, 22]:

where $ϕ$ is the porosity, $Sw$ is the water saturation, $m$ is the porosity index, and $n$ is the saturation index.

When the resistivity of formation water remains constant, the resistivity of rock decreases with increasing water saturation, porosity, porosity index, and saturation index. The porosity index and saturation index of rocks are influenced by factors such as temperature, pressure, formation water salinity, and shale content [23]. The conductivity efficiency of rock is clearly associated primarily with the resistivity, porosity, and resistivity of formation water within rock pores, as well as the water saturation and porosity. To simplify the analysis, this manuscript focuses on the lithology, porosity, and water salinity while examining how variations in coal and rock resistivity affect their conductivity.

A DZ-II type rock resistivity parameter tester was employed for the gas drive saturated water–rock resistivity measurement experiment, as shown in Figure 1. This system is capable of monitoring a resistivity measurement range from 0.00001 Ω to 99999 KΩ, with a temperature control range spanning from room temperature to 150 °C and an accuracy of ±1°C. The sample dimensions are ф 25 × 25 to 80 mm. During the experiment, the system continuously monitors and records real-time data including gas drive pressure, confining pressure, temperature, back pressure, and other relevant parameters. Upon completion of the experiment, the required resistivity data and curve change chart of the sample can be derived.

The selected coking coal, coarse sandstone, fine-grained sandstone, mudstone, and sandy shale samples were drilled and cut, and the drilled cores were cut and polished into cylindrical samples according to the requirements of the experimental equipment. Following the simulation of formation water salinity [24-27], three types of NaCl solutions were prepared, and nine rock samples were drilled separately for gas displacement saturated water resistivity measurement experiments. Each rock had nine samples labeled 1–9. In the next step, the nine samples from the five coal and rock were placed in NaCl solutions simulating formation water salinity: Samples 1–3 were soaked in 1% NaCl solution, samples 4–6 were soaked in 5% NaCl solution, and samples 7–9 were soaked in 10% NaCl solution. The samples were soaked for 48 hours until a constant weight was reached, with the experimental simulation temperature set at 28 °C and the simulated burial depth set at 400 m. After the physical parameters of the rock samples were entered into the experimental instrument, gas displacement saturated water–rock resistivity measurements were conducted. The obtained rock resistivity experimental data were analyzed and organized, revealing the conductivity efficiency changes in the deposit rocks under various influencing factors.

The relationships between resistivity, water saturation and gas drive time for coking coal under three concentrations of NaCl solution are shown in Figure 2. As the gas drive time increases, the resistivity of the nine coking coal samples gradually increases, and the water saturation gradually decreases. For the coking coal samples soaked in the same concentration of NaCl solution, such as samples 1, 2, and 3, the resistivity is relatively high, and the water saturation is relatively low after gas displacement starts. This pattern is also observed for the other two concentrations of NaCl solutions. For the coking coal samples with the three tested NaCl concentrations, the resistivity is the lowest in the water-saturated state, and the resistivity of coking coal samples is in the range of 1–3 > 4–5 > 6–9. This indicates that as the NaCl solution concentration increases, the resistivity decreases, and the conductivity efficiency of the coking coal samples increases, with a relatively stable trend of resistivity change. The analysis revealed that the influences of the water saturation in the coking coal and the formation water salinity on the conductivity efficiency were positively related.

Owing to the extremely low porosity and permeability of mudstone and sandy shale, it is impossible to carry out gas displacement experiments even when the gas displacement pressure is increased from 3 to 8 MPa. Moreover, since the confining pressure needs to be greater than the gas displacement pressure by 2 MPa, continuously increasing the pressure leads to excessive confining pressure, causing the rock samples to break within the holder. Therefore, the experimental instrument cannot perform gas displacement resistivity measurement experiments on sandy shale and mudstone. As a result, only the values of the rocks saturated with NaCl solution are measured. The resistivities of mudstone and sandy shale under three concentrations of NaCl solution are obtained, as shown in Figure 3.

Mudstone and sandy shale samples have very low permeability and porosity. However, under the same saturated NaCl solution conditions, the resistivity fluctuations in the mudstone are very small and can be ignored. Under different NaCl solution concentrations, the influence of the NaCl solution concentration on the mudstone resistivity is also very small, with resistivity changes ranging from 0.1 to 0.4 Ω·m, indicating that the water salinity has little effect on the conductivity efficiency of the mudstone. The influence of water salinity on sandy shale resistivity is quite unique and different from that on other rocks. Under 5% and 10% NaCl solution conditions, the sandy shale resistivity remains stable at approximately 25 Ω·m, and as the water salinity increases, the sandy shale resistivity basically remains unchanged. However, under 1% NaCl solution conditions, the sandy shale resistivity sharply increases by 29 times to approximately 725 Ω·m. This indicates that in addition to water saturation and formation water salinity, lithology is also a major influencing factor on rock conductivity efficiency.

The correlations between resistivity, water saturation and gas drive time for fine sandstone under three concentrations of NaCl solution are shown in Figure 4. The trends in resistivity, water saturation, and gas displacement time for fine sandstone are fundamentally analogous to those observed for coking coal, with resistivity increasing and water saturation decreasing as gas displacement progresses. A comparison between Figures 2 and 4 reveals that in the same NaCl solution, when the rock resistivity is relatively elevated after gas displacement initiation, the water saturation is relatively reduced, demonstrating an inversely proportional relationship. Upon examining the resistivity fluctuations of the fine sandstone samples under various NaCl solution concentrations, it becomes evident that the resistivity decreases as the NaCl solution concentration increases. Nevertheless, the magnitude of change in fine sandstone is less pronounced than that in coking coal, indicating that water salinity has a substantial influence on rock resistivity. Concurrently, this substantiates that different lithological strata in actual formations experience dissimilar impacts from the degree of formation water salinity.

The relationships between the resistivity, water saturation and gas drive time for coarse sandstone under three concentrations of NaCl solutions are shown in Figure 5. The increase in resistivity for coarse sandstone is significantly faster than that for coking coal and fine sandstone. The primary reason for this observation is attributed to the higher porosity and permeability of coarse sandstone relative to those of coking coal and fine sandstone.

A comprehensive analysis of various coal and rock samples revealed that the resistivity of rocks with different lithologies varies in response to changes in water salinity and saturation in three NaCl solutions. Therefore, the influences of formation water salinity and saturation differ among rock layers with different lithologies in geological formations.

When the upper rock layers of coal seam are composed of thick shale or mudstone, they can effectively act as aquitards because of their very low permeability and porosity. Therefore, in coal mining, shale and mudstone layers are commonly referred to as aquitards. On the other hand, when the upper rock layers of coal seam are composed of sandstone, their high porosity and permeability can result in high water content, making sandstone layers commonly referred to as aquifers. Thus, owing to lithological differences, their roles in coal mining vary. Therefore, to explore the hydrogeological conditions of coal seams accurately, it is important to study the relationships between different lithologies and their electrical conductivities under saturated conditions. To investigate the influence of lithology on electrical conductivity, a 1% NaCl solution is chosen for the analysis of rock resistivity because of its relatively low concentration of electrolytes, which minimally affects the intrinsic electrical conductivity of rock. Therefore, the experimental results are more convincing. The distribution of electrical resistivity of saturated coal and rock samples in a 1% NaCl solution is shown in Figure 6.

The electrical resistivity of different coal and rock samples shows different behaviors in the same NaCl solution. In the 1% NaCl solution, the order of electrical resistivity from high to low is coking coal > shale > sandstone > siltstone > mudstone. The electrical resistivity of coal is significantly greater than that of shale, sandstone, and mudstone because the electrical resistivity of coal increases with increasing degree of coalification. The higher the degree of metamorphism is, the higher the electrical resistivity and the lower the conductivity. In coal seams, shale and mudstone are considered low-porosity and low-permeability reservoirs. The ionic solutions within the rocks cannot move and conduct electricity, so the electrical conductivity of the shale and mudstone mainly depends on their clay content. The greater the amount of clay minerals within the rock is, the greater the electrical conductivity. Siltstone has a lower electrical conductivity than sandstone and mudstone because of its special thin, sheet-like or layered joints, which constrain the ionic solutions within the rocks and lower the conductivity. The electrical conductivity of sandstone itself is poor, and its electrical conductivity is mainly determined by the degree of cementation, saturation, and amount of clay minerals within it. In the experiment, the electrical resistivity of the siltstone was greater than that of the sandstone. This is because siltstone has lower porosity and permeability than sandstone does, and its cementing material is mainly composed of silica, resulting in a greater degree of cementation than sandstone does. Additionally, the mud content of the experimental sandstone was higher than that of the siltstone, resulting in a higher electrical resistivity and lower conductivity. From the above analysis, it can be concluded that the order of electrical conductivity from high to low for different lithologies in the 1% NaCl solution is mudstone > coarse sandstone > fine sandstone > shale > coking coal.

As shown in Figures 7–9, the changes in electrical resistivity and water saturation of the coking coal, fine sandstone, and coarse sandstone samples during gas driving were studied, as it was not possible to conduct gas-driven electrical resistivity measurements on the shale and mudstone samples in the experiment.

Figure 7 shows that under the conditions of the three NaCl solutions, all three groups of coking coal samples have the lowest electrical resistivity and the highest conductivity in the state of water saturation. As the gas-driven experiment proceeded, the amount of NaCl solution inside the coking coal decreased, and the electrical resistivity of the coking coal gradually increased while the conductivity gradually decreased. Therefore, it can be inferred that the greater the amount of formation water in the coking coal pores is, the greater the conductivity is. For a group of coking coal samples with the same NaCl solution concentration, the changes in water saturation and electrical resistivity are essentially the same. However, for the three groups of coking coal samples with different NaCl solution concentrations, the changes in electrical resistivity are different. Therefore, the salinity of the formation water not only affects the water saturation and electrical resistivity of coking coal but also affects the changes in electrical resistivity with changes in water saturation. The main reason for these phenomena is that coking coal is a sedimentary rock and an ion-conductive rock. The electrical resistivity of coking coal is affected mainly by its own metamorphic degree and the formation water. When the number of positively and negatively conductive ions in the solution inside the coking coal decreases, its electrical resistivity increases, and its conductivity decreases. However, owing to the different salinity levels of the formation water, the number of ions inside the coking coal will differ; even if the water saturation changes are the same, the changes in electrical resistivity will also differ. To better reflect the relationship between the water saturation and electrical resistivity of coking coal, linear regression was performed on the data of each group of coking coal samples, and Formula (3) was obtained as follows:

Figure 8 shows that the relationship between water saturation and resistivity changes in fine sandstone is similar to that in coking coal. The resistivity is lowest under water-saturated conditions, and as the amount of internal NaCl solution decreases during the experiment, the resistivity increases, and the conductivity efficiency decreases. The resistivity changes of rock samples 1–3 in the first 10 minutes of the experiment are different from those of the other two groups of samples. The main reason is considered to be that fine sandstone mainly relies on the formation water it contains for conductivity. Under 1% NaCl solution conditions, the amount of cations (⁠$Na+$⁠) and anions (⁠$Cl−$⁠) in the fine sandstone is less than that in the 5% NaCl and 10% NaCl solutions. During the first 10 minutes of the experiment, many ions in the rock pore spaces were displaced by the water solution, resulting in a rapid increase in the resistivity of the fine sandstone. During the subsequent 60 minutes of the experiment, the number of ions available for displacement gradually decreased, and the resistivity changes in the fine sandstone samples tended to stabilize. To better reflect the relationship between water saturation and resistivity changes in fine sandstone, linear fitting is performed on the data of each group of rock samples, obtaining Formula 2 as follows:

Figure 9 shows that the relationship between the rock resistivity and water saturation in coarse sandstone is similar to the trends observed in coking coal and fine sandstone. A comparison of Figures 8 and 9 reveals that the increase in resistivity is the fastest for coarse sandstone and is greater than that for fine sandstone and coking coal. This is mainly because coarse sandstone has larger particles and more developed internal pore spaces, resulting in high permeability and a larger space for internal conductive ions to move. Under the same gas displacement pressure, the water saturation of the coarse sandstone samples decreases rapidly, and the trend of the resistivity increase is more significant. To better reflect the relationship between water saturation and resistivity changes in coarse sandstone, linear fitting is performed on the data of each group of rock samples, obtaining Formula 3 as follows:

A comparison of Figures 7 and 9 reveals that for coking coal, fine sandstone, and coarse sandstone, the resistivity is the lowest when the samples are in a water-saturated state, and the conductivity efficiency is the highest. As the internal solution decreases, the conductivity efficiency of the rock decreases, and the resistivity increases. The resistivity of rocks with different lithologies is different when they are in a saturated water state, but the resistivity of the samples and the water saturation both show a linear relationship, which can be expressed as a single lithology soaked in the same NaCl solution, and the relationship between water saturation and resistivity is basically the same. For a single lithology soaked in different concentrations of NaCl solutions, the trends are the same, but the details are different. The rate of change is the same; that is, the faster the water saturation decreases, the faster the resistivity increases. The permeability decreased in the order of coarse sandstone > fine sandstone > coking coal, the rate of decrease in water saturation decreased in the order of coarse sandstone > fine sandstone > coking coal, and the increase in resistivity decreased in the order of coarse sandstone > fine sandstone > coking coal. Therefore, the higher the permeability is, the faster the experimental gas displacement speed, the faster the water saturation decreases, and the faster the rock resistivity increases. Moreover, the saturation of multiple rock samples becomes stable after a rapid decline at the beginning of the experiment. The reason is that the experimental rocks are all sedimentary rocks, and their conductivity mainly depends on the formation water inside. At the beginning of the experiment, the rocks were in a water-saturated state and filled with sodium chloride solution. When the experiment begins, a large amount of NaCl solution is displaced by gas, causing some internal pore spaces in the rocks to connect. In the subsequent gas displacement experiment, the nitrogen gas used for gas displacement first passed through the already connected pore spaces, resulting in a rapid decrease in the NaCl solution content and a rapid increase in resistivity within the first 10 minutes of the experiment, followed by a more gradual change.

Considering the physical parameters of the rock samples, the development of intergranular pore spaces in the rocks, low cementation degree, and high conductivity efficiency are found; thus, the conductivity efficiency of coarse sandstone > fine sandstone > coking coal.

To better reflect the influence of rock water saturation on the conductivity efficiency of rock, the resistivity index (RI) is used to express the change rate of resistivity. Based on the experimental data, the relationship between water saturation (S_w) and RI of coking coal under 5% NaCl solution conditions is analyzed, as shown in Figure 10, the relationship between S_w and RI of fine sandstone under 5% NaCl solution conditions is analyzed, as shown in Figure 11, and the relationship between S_w and RI of coarse sandstone under 5% NaCl solution conditions is analyzed, as shown in Figure 12.

The resistivity index increases as the water saturation decreases, and the larger the resistivity index is, the faster the resistivity increases. A linear relationship is obtained by fitting the resistivity indices of coking coal, fine sandstone, and coarse sandstone. Based on the slope characteristics of the linear relationship, the influence of water saturation on the resistivity of coking coal and rock is as follows: coarse sandstone > fine sandstone > coking coal. The resistivity index of coarse-grained sandstone increases the fastest, mainly because of its rock properties, such as poor cementation, high porosity, and permeability. The NaCl solution inside rock can be easily displaced, and the resistivity index varies greatly with the amount of internal solution. Consequently, the rock properties and water saturation not only affect the magnitude of the rock resistivity but also influence the rate of change in resistivity, as well as the range of variation in the rock conductivity efficiency.

Sedimentary rocks rely primarily on formation water for conduction, so the formation water salinity directly affects the conductivity efficiency of sedimentary rock layers. The conductivity efficiency of rock layers is directly proportional to the formation water salinity. Therefore, three different concentrations of NaCl solution are chosen to soak the rocks, and the resistivity values are measured and compared for analysis, as shown in Figure 13.

Figure 13 shows that the distribution of the resistivity of saturated coal and rock samples, the resistivity of coal and rock samples is 1–3 > 4–5 > 7–9, with a higher salinity resulting in a lower resistivity. This is primarily because the conductivity of sedimentary rocks mainly depends on the resistivity of water in rock pores. The resistivity of water solutions primarily depends on the contained electrolytes, salinity, and formation water temperature. NaCl is the main conductive medium of formation water, and NaCl is generally approximated as a NaCl solution to study its electrical properties. As the NaCl water salinity increases, the number of ions in the solution increases, increasing the conductivity efficiency and reducing the resistivity.

The different lithologies exhibit varying resistivity behaviors under different NaCl solution concentrations: in the 1% NaCl solution, the order from high to low resistivity is coking coal > siltstone > fine sandstone > coarse sandstone > mudstone; in the 5% NaCl solution, the order is coal > siltstone > fine sandstone > coarse sandstone > mudstone; and in the 10% NaCl solution, the order is coking coal > siltstone > mudstone > coarse sandstone > fine sandstone.

Rock samples exhibit varying resistivity changes under different NaCl solution conditions, with different solution salinities affecting the rock resistivity differently. In descending order of influence between 1% and 5% NaCl, the sequence is siltstone > coking coal > fine sandstone > coarse sandstone > mudstone; between 5% and 10% NaCl, the sequence is coking coal > fine sandstone > coarse sandstone > siltstone > mudstone. Siltstone is a special case that exhibits abnormally high resistance under low-salinity conditions and low resistance under high-salinity conditions. As the salinity increases, the resistivity no longer changes significantly. Since coal mines often have weak or moderate formation water salinity, when a thick siltstone layer is encountered, judgments should be made based on actual field conditions. Mudstone resistivity is the most stable and essentially remains unaffected, mainly because of ion conduction on the surface of clay particles. Coking coal has the highest resistivity, which is determined mainly by its lithology. Coking coal is a type of bituminous coal, and the greater the degree of metamorphism of bituminous coal is, the greater its resistivity.

The engineering experiment was conducted in a coal mine in Jixi city, China. Three exploration instruments, a transient electromagnetic instrument (TEI), a continuous conductivity imager (EH-4), and an electromagnetic detection system (Geode EM3D) were used for engineering tests at the same sites. The variation in rock conductivity efficiency under the influence of lithology differences, water saturation, formation water salinity and rock structure is combined with the variation in the rock magnetic field to improve the accuracy of formation detection.

According to the inverse resistivity data of the test, Surfer software was used to draw the apparent resistivity profile of the data collected by TEI, EH-4, and Geode EM3D, for analysis and comparison. Blue represents the low resistance area, red represents the high-resistance area, and the other colors represent the formation resistivity change process. The black isoline is the formation resistivity isoline, and the black mark on the isoline represents the formation resistivity, as shown in Figure 14.

From Figure 14, the Geode EM3D survey line profile shows that there is a low-resistance anomaly area in the shallow side of the 820 N measurement point, which indicates that there are multiple collapse pits on the surface near this point. Moreover, according to the data, the underground coal seam in this range has indeed been mined, so it can be determined that the shallow anomaly area is a water-conducting fracture. However, in the transient electromagnetic instrument and EH-4 survey line profile, this abnormal area was not found, mainly because the abnormal area was in the detection blind area of the transient electromagnetic and EH-4 shallow parts, and the geological information of the shallow part of the formation was determined mainly by the reaction of the early signals received, whereas the transient electromagnetic and EH-4 received and processed the geological signals in the middle and late stages. This results in a blind spot in the exploration. The existing processing methods discard and ignore this geological information, resulting in unclear geological information in shallow areas. However, Geode EM3D processes shallow signals better, and the combination of the three can better reflect the geological information of the strata. There is a low-resistivity anomaly area in the range of +120~−60 m on all survey line profiles, which may be caused by coal mining. After coal seam mining, fractures in the upper rock formation water conduction crack, forming water, and surface water along the water conduction crack into the goaf, forming a low resistance abnormal area. The color scale of the resistivity isoline reveals that the lowest resistivity in the abnormal area is 10Ω·m, which is similar to the resistivity of mudstone, because there is not only an aqueous solution but also a large amount of mud in the goaf, which is similar to the properties of mudstone. The resistivity of the deep rock in the test area is basically consistent with that of the fine sandstone and coarse sandstone measured in the laboratory, which verifies the accuracy of the experimental results.

1. Laboratory measurements of rock resistivity demonstrate that lithology is a significant factor influencing the conductivity efficiency of rocks, with varying resistivity measurements observed for different lithologies. The resistivity of coking coal is the highest, resulting in the lowest conductivity efficiency, whereas mudstone exhibits relatively low resistivity, which is nearly unaffected by water saturation and formation water salinity. The resistivity of siltstone is strongly influenced by the salinity of the formation water, which has a low resistance under high salinity conditions, with little change in resistivity as salinity increases; however, the resistivity is an abnormally high under low-salinity conditions, with a large magnitude of change. The sandstone conductivity efficiency varies with water saturation and salinity, indicating a direct relationship between these two parameters.

2. For rocks of the same lithology, under three NaCl solution concentrations, the resistivity of coal and rock samples 1–3 > 4–5 > 6–9, with a higher salinity resulting in a higher conductivity efficiency and lower resistivity. The different lithologies and NaCl solution conditions exhibit varying resistivity behaviors: in the 1% NaCl solution, the order from high to low resistivity is coking coal > siltstone > fine sandstone > coarse sandstone > mudstone; in the 5% NaCl solution, the order is coking coal > siltstone > fine sandstone > coarse sandstone > mudstone; and in the 10% NaCl solution, the order is coking coal > siltstone > mudstone > coarse sandstone > fine sandstone, with the conductivity efficiency exhibiting the opposite trend.

3. Under the same experimental conditions, the rock water saturation and resistivity are inversely proportional and exhibit a linear relationship. The larger the magnitude of resistivity variation is, the greater the resistivity index, and the greater the influence of water saturation changes on resistivity. In a 5% NaCl solution, the water saturation and resistivity index data for coking coal, fine sandstone, and coarse sandstone were analyzed and fitted to obtain a linear relationship. Based on the slope characteristics of the linear relationship, the influence of water saturation changes on the resistivity of coal and rock can be determined as coarse sandstone > fine sandstone > coking coal.

4. According to the tests of FEI, EH-4 and Geode EM3D, there is a blind spot in shallow detection by FEI and EH-4, whereas Geode EM3D can process shallow signals better, and the combination of the three methods can better reflect the geological information of strata. Moreover, the experimental results are compared with the field data to verify the accuracy of the experimental results.

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

We gratefully wish to acknowledge The Sponsored by Natural Science Foundation of Henan (242300420353) and Key Scientific Research Projects of Universities in Henan Province (23A440012, 24A440011) and Postgraduate Education Reform and Quality Improvement Project of Henan Province (YJS2023JD64) and Interdisciplinary Sciences Project, Nanyang Institute of Technology (NGJC-2022-02) and Research Program Project of Binzhou Polytechnic (2023yjkt06, 2023yjkt08) and Research Project on Science and Technology of Nanyang City (24KJGG015), Basic and Frontier Technology Research Project of Nanyang City (23JCQY2014) and Doctoral Research Start-up Fund Project, Nanyang Institute of Technology (NGBJ-2022-17).