Application of Aeromagnetic Survey in Detecting Potential Mineralization Zones Around Dongzhongla Deposit, Gangdese Metallogenic Belt

Abstract

The Dongzhongla deposit is a skarn-type lead–zinc ore deposit located in the eastern segment of the Gangdese metallogenic belt, situated in the Xizang province, China. The high-altitude mountainous terrain of the region poses significant challenges to ground-based exploration. To facilitate more accurate mineral exploration in the deposit and its surrounding area, a high-resolution airborne magnetic survey was conducted over the mining area and its periphery. The airborne magnetic data were processed using derivative and Euler deconvolution methods, yielding results that reflect the geological structural features of the study area. By integrating the geological characteristics of the ore deposit, we inferred that the areas of magnetic anomaly extensions and the peripheries of other magnetic anomalies are favorable zones for mineralization, providing positive leads for further mineral exploration.

1. Introduction

The Gangdese region in the southern part of Xizang province is one of the most important metallogenic regions in China. The Nyainqentanglha lead–zinc metallogenic belt (NLMB) within this region is a major Pb-Zn (Ag) ore belt, hosting multiple large-scale ore deposits, including the Yaguila, Mongyai, and Narusongduo deposits. The Dongzhongla (DZL) ore deposit, which is the focus of this study, is a medium-sized Pb-Zn ore deposit located in the eastern segment of the NMLB [1,2,3,4,5,6,7]. DZL is situated approximately 90 km northeast of Lhasa city, Xizang province, and was discovered in 2002, with formal production commencing in recent years. Within a radius of several kilometers around the DZL deposit, multiple ore deposits, including the Mengya’a, Yaguila, Dongzhongla, and Xiangla deposits, have been discovered, forming a polymetallic ore cluster, with favorable geological conditions for mineralization.

Previous studies have investigated the ore-forming model, ore-forming age, and material sources of the DZL deposit at the ore-body scale [8,9,10,11]. Currently, the deposit owners plan to assess the mineral potential within the exploration area and conduct detailed exploration work. However, the harsh natural environment and high altitude of the study area pose significant challenges and risks to ground-based exploration. Aeromagnetic surveys can effectively eliminate these risks and provide rapid, area-wide measurements, supporting the identification of target areas for ground-based exploration [12,13,14,15,16]. Skarn deposits, such as the DZL deposit, are formed through the interaction of magmatic and hydrothermal fluids with carbonate rocks, resulting in the formation of skarn minerals, including garnet and pyroxene. The close spatial, temporal, and genetic relationships between the ore body and skarn rocks make airborne magnetic surveys a viable method for identifying potential ore bodies, as most economic skarn deposits are related to magmatic activity, which can produce magnetic anomalies [17]. We successfully applied airborne magnetic surveys to identify potential iron ore deposits in 2018 [18]. We were commissioned by Xizang Xinhu Mining Co., Ltd. (lhasa, China) of Yunnan Chihong Zinc & Germanium Co., Ltd. (Qujing, China) to conduct an airborne magnetic survey over the DZL deposit and its surrounding area in 2021. This survey acquired high-resolution airborne magnetic data, which were analyzed using derivative calculations and 3D magnetic inversion to identify the magnetic characteristics of the DZL area, highlighting the significance of airborne magnetic surveys in guiding mineral exploration in the surrounding area.

2. Geological Settings

2.1. Regional Geology

The Himalayan orogenic belt is the most classic, largest-scale, and youngest mountain-building system globally, resulting from the continental collision between the Indian and Eurasian plates. This process led to the thinning of the lithosphere, shortening and thickening of the crust, and massive magmatic and fluid activities, ultimately triggering large-scale magmatic–hydrothermal (Pb-Zn-Fe-Cu-Ag-Mo) mineralization [5,6,7]. The study area is located in the southern part of the Himalayan orogenic belt, between the Bangong–Nujiang suture zone (BNSZ) and the Yarlung Zangbo suture zone (IYZSZ), within the Lhasa terrane. The Lhasa terrane is bounded by the Shiquanhe–Nam Tso Melange Zone (SNMZ) and the Luobadui–Milashan fault zone (LMF) and can be divided into three secondary terranes from south to north: the southern Lhasa subterrane (SLS), central Lhasa subterrane (CLS), and northern Lhasa subterrane (NLS). These terranes exhibit distinct and zoned mineralization characteristics, with the SLS primarily hosting porphyry copper deposits, forming the Gangdese porphyry copper belt, and the CLS hosting skarn-type Pb-Zn deposits, forming the Nianqing Tanggula skarn-type Pb-Zn belt [19]. The DZL deposit is situated at the eastern end of the CLS (Figure 1).

2.2. Deposit Geology

Due to the harsh working environment, the basic geological work in the study area has been limited to small-scale investigations, with only some detailed geological mapping conducted on the already discovered ore deposits. Figure 2 is a simplified geological map of the study area, modified from a 1:250,000 regional geological map. The geological features shown in Figure 2 are relatively rough and can only display larger geological units and structural backgrounds, lacking detailed information on ore deposit scales. The exposed strata in the area mainly include the pre-Ordovician Songduo Group (AnOsd), the Paleogene Linzizong Group Pana Formation (E₂p), and Quaternary loose deposit, flood, and fluvial sediments (Q). The AnOsd is distributed in the southeastern part of the study area, with rock types mainly consisting of quartzite, quartz-mica schist, and others. The strata have undergone deep metamorphism, with hard and resistant rocks that are less susceptible to weathering, often forming steep and rugged terrain. E₂p is only distributed in the northeastern corner of the study area, consisting of a suite of intermediate-acidic volcanic rocks and volcaniclastic rocks. The volcanic rocks unconformably overlie the older strata and rocks, with an angular relationship. Large areas of intrusive rocks have developed in the study area, roughly bounded by a diagonal line from the southwestern to the northeastern corner. Except for Quaternary cover, almost the entire northwestern part of the study area is composed of Mesozoic intermediate-acidic intrusive rocks, with rock types mainly consisting of biotite granite and gabbro. This suite of intrusive rocks is the source rock for the mineralization of the already discovered ore deposits in the area. Structurally, the mining area is located in the middle part of the Pangduo thrust fault zone [20], which is characterized by a set of near-NE-trending faults in the study area.

Thanks to the many years of exploration work at the DZL deposit, the geological map of the DZL mining area (Figure 3a) provides more detailed geological information compared to Figure 2. The exposed strata in the mining area mainly include the Ordovician Songduo Formation (Songduo Fm.), the Triassic Luobadui Formation (Luobadui Fm.), and Quaternary fluvial, flood, and glacial deposits. The Songduo Fm. is mainly distributed in the southeastern part of the mining area, with rock types primarily consisting of quartzite; the Luobadui Fm. is distributed in the central and eastern parts of the mining area, with a main rock assemblage of slate, limestone, and dolomite, and a dip direction mainly towards the southeast, with dip angles between 60° and 85°. A large area of Mesozoic intermediate-acidic intrusive rocks is exposed in the northwestern part of the mining area, with rock types mainly consisting of quartz porphyry, granite porphyry, and diorite. The main structural direction in the mining area is near-NE-trending, with a set of secondary structures developed in the SE and near-SN directions later on, and no obvious folds are observed on the surface.

Figure 1. The location of the study area and its tectonic outline map (modified from [7]). (a) The location of the Himalayan orogenic belt. (b) The location of the Gangdese metallogenic belt. (c) The location of the Lhasa terrane and the characteristics of ore deposit distribution. IYZSZ—Yarlung Zangbo suture zone; BNSZ—Bangong–Nujiang suture zone; JSSZ—Jinsha River suture zone; SNMZ—Shiquanhe–Nam Tso Melange zone; LMF—Luobadui–Milashan fault zone; SLS—southern Lhasa subterrane; CLS—central Lhasa subterrane; NLS—northern Lhasa subterrane. DZL—Dongzhongla deposit; LML—Longmala deposit; MYA—Mengya’a deposit; YGL—Yaguila deposit; SR—Sharang deposit.

Figure 1. The location of the study area and its tectonic outline map (modified from [7]). (a) The location of the Himalayan orogenic belt. (b) The location of the Gangdese metallogenic belt. (c) The location of the Lhasa terrane and the characteristics of ore deposit distribution. IYZSZ—Yarlung Zangbo suture zone; BNSZ—Bangong–Nujiang suture zone; JSSZ—Jinsha River suture zone; SNMZ—Shiquanhe–Nam Tso Melange zone; LMF—Luobadui–Milashan fault zone; SLS—southern Lhasa subterrane; CLS—central Lhasa subterrane; NLS—northern Lhasa subterrane. DZL—Dongzhongla deposit; LML—Longmala deposit; MYA—Mengya’a deposit; YGL—Yaguila deposit; SR—Sharang deposit.

Figure 2. A simplified geological map of the study area (modified from a 1:250,000 geological map provided by the client).

Figure 2. A simplified geological map of the study area (modified from a 1:250,000 geological map provided by the client).

All the discovered ore bodies in the mining area are mainly hosted in the contact zone between the quartz porphyry or granite porphyry and the surrounding rocks (limestone or dolomite, etc.) (Figure 3b). The ore bodies are mainly distributed in an NE-SW direction, with a dip direction towards the southeast, and a dip angle of around 50 to 70°. The ore bodies are relatively thick and stable. The ore type is mainly massive sulfide ore, with a simple mineral assemblage, and the main ore minerals are galena, sphalerite, and chalcopyrite. The alteration of the surrounding rocks is mainly skarnization. The ore bodies and surrounding rocks are low-magnetic or non-magnetic, while the intrusive rocks have relatively high-magnetic properties. Therefore, using magnetic field characteristics to infer the distribution range of intrusive rocks and identify favorable areas for mineralization is a feasible and commonly used exploration method. The main task of this airborne magnetic survey is to use the magnetic survey results to outline the distribution range of intrusive rocks and suggest favorable areas for mineralization, providing a basis for reducing the workload and increasing the success rate of subsequent detailed exploration work.

Figure 3. A geological map and geological cross-section of the DZL deposit (modified from data provided by the client). (a) The geological map of the DZL deposit. Points “A” and “B” are the endpoints of the geological section in (b). (b) The geological section crossing the main mining body; the lithology of the geological section is controlled by drill holes, and the ore body develops in the skarn band on the south side of the intrusive rock.

Figure 3. A geological map and geological cross-section of the DZL deposit (modified from data provided by the client). (a) The geological map of the DZL deposit. Points “A” and “B” are the endpoints of the geological section in (b). (b) The geological section crossing the main mining body; the lithology of the geological section is controlled by drill holes, and the ore body develops in the skarn band on the south side of the intrusive rock.

3. Data Acquisition and Processing

3.1. Data Acquisition

The DZL area is located in a high-altitude, high-mountain region, with elevations ranging from 4560 m to over 5800 m, and an average elevation of 5200 m. The maximum relative height difference exceeds 700 m, and most of the working area has elevations above 5000 m, posing significant challenges for both ground-based and airborne geophysical work (Figure 4).

To ensure the safety of the aerial survey, this project selected the AS350 (H125) helicopter, manufactured by Airbus Helicopter (Marignane, France), which has excellent high-altitude performance, as the flight platform. The airborne magnetic survey equipment was also chosen to be lightweight and compact. The airborne magnetic survey system used in this project consists of the AARC510 airborne compensation and recording system produced by RMS Instruments (Mississauga, ON, Canada), the CS-VL high-precision cesium vapor magnetometer produced by Scintrex (Concord, ON, Canada), the T34 radar altimeter produced by SmartMicro (Braunschweig, Germany), and the DL-4 navigation system produced by NovAtel (Calgary, AB, Canada). The equipment was installed on the helicopter using a rigid rod mounting system (Figure 5). To keep the magnetometer away from the aircraft and reduce interference, a hollow rod was installed under the belly of the aircraft, using a triangular bracket structure to make it more stable. A streamlined compartment at the front of the rod was used to house the magnetometer. The recording system and positioning navigation system were installed in the cabin, and the radar altimeter was installed under the belly of the aircraft. Researchers have studied the magnetic interference problem of the AS350 helicopter, and found that placing the magnetometer 4 m away from the rotor coverage area can reduce the interference to below 1 nT [21]. As a result, the length of the probe is 4.5 m outside the rotor range in this project. Magnetic interference tests were conducted after the installation, and the static magnetic noise reached 1.45 pT, while the dynamic magnetic noise was 41.4 pT on the baseline.

The geological structure of the mining area is mainly oriented in the NE and EW directions, so the survey lines were designed to be approximately perpendicular to the main structural direction, with an SN orientation. The line spacing was 100 m, and the tie lines were in the EW direction with a spacing of 2 km. This airborne magnetic survey covered an area of approximately 20 km × 9 km around the DZL deposit, with a total flight distance of about 2000 km, an average flight height of 115 m, and an average deviation of 3 m.

3.2. Processing and Interpretation

The data preprocessing mainly included coordinate projection transformation, diurnal correction, lag correction, direction difference correction, International Geomagnetic Reference Field (IGRF 13th) correction, and magnetic field leveling. The standard deviation of the magnetic field differences at the intersection points of the survey lines and tie lines after preprocessing was 2.5 nT. To eliminate the effects of magnetic inclination and declination on the aeromagnetic data, the aeromagnetic data were reduced to the pole using the magnetic inclination (47.72°) and declination (−0.25°) calculated based on the latitude, longitude, and elevation of the study area.

The tilt angle was applied to the reduced-to-the-pole data. The tilt angle is a commonly used method for identifying the boundaries of magnetic bodies. The calculation formula for the tilt angle is

$$Tilt={tan}^{-1}\left({\displaystyle \frac{𝜕f/𝜕z}{\sqrt{{\left(𝜕f/𝜕x\right)}^2+{\left(𝜕f/𝜕y\right)}^2}}}\right)$$

(1)

where Tilt is the tilt angle, f is the magnetic field, and x, y, and z are the derivative directions. Zero-contour lines of the tilt angle are used to outline magnetic bodies (assuming there are no geological bodies with strong remanent magnetism within the area).

The Euler deconvolution method is a widely employed inversion technique in geoscience, utilized for estimating the depth and location of source fields. This approach was first introduced by Thomson, who utilized the Euler homogeneous function equation to invert source field information [22]. Subsequently, Reid et al. expanded this method to invert source field information from gravity and magnetic grid data [23]. The three-dimensional Euler homogeneous function equation can be expressed as

$$\left(x-x_0\right){\displaystyle \frac{𝜕f}{𝜕x}}+\left(y-y_0\right){\displaystyle \frac{𝜕f}{𝜕y}}+\left(z-z_0\right){\displaystyle \frac{𝜕f}{𝜕z}}=SI(B-f)$$

(2)

where f represents the measured magnetic field value at (x, y, z), (x₀, y₀, z₀) denotes the source location, B is the regional background field, and SI is the structural index. Given that the magnetic field value and measurement position are known, the partial derivatives of the magnetic field in three directions (∂f/∂x, ∂f/∂y, ∂f/∂z) can be calculated, representing the rate of change of the magnetic field in each direction. By specifying SI, the solution set (x₀, y₀, z₀) and background field value B can be obtained by solving the Euler equation set. The Euler deconvolution method can effectively identify the boundaries of geological anomalies such as faults and steep contacts and estimate their depths.

The standard Euler deconvolution involves moving a window of fixed size across the data grid and calculating the solutions for each window. Due to the window size being much smaller than the study area, a large number of solutions are produced, including many spurious solutions. To reduce the number of false solutions, one approach is to use the Euler deconvolution method based on the prior selection of the horizontal position of the magnetic source boundary (located Euler deconvolution). It first locates the positions containing peak data, then estimates the window size using the positions of adjacent peak points, and finally performs Euler deconvolution calculations using these points and windows, which removes a large number of non-peak position solutions, thereby focusing the solutions more on the area of interest. The choice of SI in Euler deconvolution has a significant impact on the solutions. We used the AN-EUL method to estimate the SI of the study area [24]. This method substitutes the derivative of the Euler equation into the analytical signal equation, allowing for the simultaneous estimation of magnetic source parameters, depth, and SI, with the calculation equations as follows:

$$Depth=\frac{AS2\ast AS1}{AS3\ast AS1-AS2\ast AS2}$$

(3)

$$SI=\frac{2AS2\ast AS2-AS3\ast AS1}{AS3\ast AS1-AS2\ast AS2}$$

(4)

where

$$AS1(x,y)=\sqrt{{\left(𝜕f/𝜕x\right)}^2+{\left(𝜕f/𝜕y\right)}^2+{\left(𝜕f/𝜕z\right)}^2}$$

(5)

$$AS2(x,y)=\sqrt{{\left(𝜕f/𝜕x𝜕z\right)}^2+{\left(𝜕f/𝜕y𝜕z\right)}^2+{\left(𝜕f/𝜕z𝜕z\right)}^2}$$

(6)

$$AS3(x,y)=\sqrt{{\left(𝜕f/𝜕x𝜕z𝜕z\right)}^2+{\left(𝜕f/𝜕y𝜕z𝜕z\right)}^2+{\left(𝜕f/𝜕z𝜕z𝜕z\right)}^2}$$

(7)

In Equations (3) and (4), depth and SI represent the depth and structural index at the (x, y) position, and in Equations (5)–(7), f denotes the magnetic field, while x, y, and z represent the directions of the derivative. We used this method to obtain the average SI value of the study area for located Euler deconvolution. Compared to the standard Euler deconvolution, the number of false solutions is significantly reduced, and the solution set is more concentrated.

Equation (5) was used to calculate the analytical signal grid from the reduced-to-pole grid, and then the picking peaks method was used to obtain the peak positions. In a regular grid, a cell G is surrounded by eight neighbors, forming four groups in two directions (rows, columns, and two diagonals), with G at the center. If both neighbors in a direction have values less than G, G is a peak value in that direction. After comparing the four direction groups, the number of G being a peak in different directions can be from 0 (none) to 4 (all). Therefore, an integer from 1 to 4 can be set as a sensitivity coefficient to determine if G is a peak point: 1 means that G is a peak value in at least one direction, while 4 requires it in all directions. Obviously, using 1 can obtain more peak positions. Then, based on these peak positions, Equations (3) and (4) were used to calculate the estimated depth of the magnetic source and SI in the study area. Then, the average values of these SI were used as input parameters for located Euler devolution. The width of the main anomaly in the study area is approximately 3 km. The reduced-to-pole data were re-gridded with a spacing of 150 m, so that a window of 20 grid cells could just cover these anomalies, and an upward continuation of 100 m was applied to reduce the influence of high-frequency data. During the calculation, the maximum depth tolerance was set to 15%, and the maximum depth was not limited. After removing the points with negative depth values and positions that deviate significantly from the main range, a color symbol map of the located Euler deconvolution results was plotted.

4. Results and Discussion

A color-shaded map of the study area was generated using reduced-to-the-pole data (Figure 6), providing a visual representation of the regional magnetic field characteristics and their correlation with the regional geological structural background. The magnetic field of the study area is characterized by multiple northeast–southwest trending anomalous strips (striped magnetic anomaly, SMA) in the northwest region, a blocky magnetic anomaly zone (blocky magnetic anomaly, BMA) in the southeast region, and several isolated positive anomalies (isolated magnetic anomaly, IMA) dispersed throughout the area.

The DZL ore deposit is located in SMA1, and SMA2 is located in the northwest of the study area. In terms of spatial position, they correspond to the exposed areas of the Cretaceous intrusive rocks on the geological map. SMA1 extends from the northeast corner of the study area to the southwest, passing through the middle of the study area, where the DZL ore deposit is located. The magnetic field intensity in this area is relatively high, with most of the magnetic anomaly intensities ranging from 200 nT to 300 nT, mainly caused by the intrusive rocks in this area, which is also a reflection of the known main ore-bearing rocks in the study area. Compared to the eastern segment, the magnetic field intensity of the western segment of SMA1 is relatively weak, which may be due to the weakening of the magnetic source, reduction in size, or increase in burial depth. SMA2 is located in the northwest of the study area, with a similar trend to SMA1, but with a slightly weaker intensity. The magnetic anomaly intensity increases from tens of nano-Tesla to over 200 nT from east to west. SMA2 extends out of the study area from both the west and north sides, which should be caused by intrusive rocks.

BMA occupies the entire southeastern part of the study area, which is a blocky weakly magnetic background field with occasional small positive magnetic anomalies. BMA reflects the overall magnetic background of the study area, mainly due to the non-magnetic or weakly magnetic sedimentary layers. There are a few isolated positive anomalies and weak linear anomalies within BMA, which may indicate the presence of small-scale high-magnetic rocks.

IMA1 to IMA5 are representative isolated positive magnetic anomalies with relatively high magnetic field intensities within the study area, mainly distributed in the southwestern part of the study area, outside of SMAs and BMA, which should be a reflection of high-magnetic intrusive rocks.

We know that the DZL ore deposit is developed in the silicate rocks at the contact zone of the intrusive rocks, so we used aeromagnetic data to identify potential intrusive rocks in the study area, and the boundary of the rocks is a favorable area for future mineral exploration. Figure 7 shows the tilt angle map of the study area. The zero-contour lines can be used to indicate the boundaries of the magnetic source (mainly intrusive rocks in this study).

In Figure 7, purple dashed lines are used to highlight the locations of magnetic susceptibility changes (i.e., zero-value lines). The warm-colored high-value areas inside the dashed lines are closer to the magnetic source center, while the cool-colored low-value areas outside the dashed lines represent regions farther away from the magnetic source. We find that the DZL ore deposit, which is currently being mined, is precisely located on the zero-value lines, consistent with the phenomenon mentioned earlier that it is developed in the contact zone between the rocks and the surrounding rocks. This also reversely proves that our approach of using aeromagnetic data to guide the next step of mineral exploration by identifying potential rock boundaries is feasible. We note that in the BMA region of the reduced-to-the-pole map, there are two long, linear anomalies trending northeast and north–south, respectively, which are not obvious in the reduced-to-the-pole map. They may be caused by intrusive rocks that developed along faults in the strata.

Figure 8 shows the solutions of the AN-EUL method. The locations were selected from the analytical signal grid of reduced-to-pole data, using parameter 1 to pick the peak values, and to avoid picking too many peaks at weak anomaly positions that may be caused by noise, the positions with analytical signal values less than 0.02 were filtered out after experimenting. The solutions of AN-EUL gave an average value of SI = 1.4. Then, the located Euler deconvolution was applied to the reduced-to-the-pole grid with SI = 1.5 based on the AN-EUL results, and the solutions are presented in Figure 9.

From both Figure 8 and Figure 9, the Euler deconvolution results show good linear characteristics. Based on the geological background of the study area, the linear clusters of these symbols may reflect the locations of the underlying magnetic body boundaries or faults. The linear structures formed by these colored symbols on the plane have a high degree of overlap with the zero-value line’s area, and a mutually verifying effect can be formed between the two methods. However, it is also easy to see that the solutions of the Euler inversion are more dispersed and discontinuous than the zero-value lines of the tilt angle, which is due to the Euler deconvolution solutions not being able to satisfy the error limit at every point, and the fact that the analytical signal peak used in the located Euler deconvolution cannot completely select all the boundary locations.

The main trends of both solutions are northeast–southwest or north–south, with a few being nearly east–west or north–south. These solutions are mainly shallow, with most of the magnetic sources having depths of mainly below 1000 m, with the main distribution between 100 m and 600 m. The locations of the DZL deposit and its western and northeastern sides, the central part of SMA2, and the locations of the IMAs all show very shallow magnetic source depths. If the magnetic sources are the contact zones of rock bodies, this suggests that most of the rock bodies in the study area have relatively shallow emplacement, which is very favorable for future exploration and mining work. Overall, the solutions from both methods in Figure 8 and Figure 9 have a similar appearance on the plane, but there are also some differences. The solutions in Figure 8 are more continuous at anomalous edges, and the range of shallow-source solution distribution is relatively larger as well. Additionally, Figure 8 contains several straight-line-type solutions that are quite regular in both east–west and north–south directions, whereas the solutions in Figure 9 appear to be somewhat “natural”. These differences mainly stem from their differing computational methods. AN-EUL calculates depth and SI directly using multiple orders of analytic signals based on selected peak positions; thus, its SI is non-fixed, which may better fit actual geological conditions in certain areas. However, as long as the denominator is not zero, it will have a solution, leading to continuous straight-line solutions at some locations—this also relates to the point peaking and masking. Located Euler devolution uses a fixed SI for calculations and excludes obviously unreasonable solutions through setting error limits and maximum values. Geological conditions are complex and variable; thus, a single fixed SI may not suit the entire study area, but having methods to exclude solutions can more easily eliminate interfering ones, focusing on areas of interest. Combining both approaches in this case might be an effective attempt.

To estimate the accuracy of the solutions, a survey line (L3400) across IMA3 was selected and the solutions were imported into the line. Based on their distribution patterns, a simple cross-sectional model was established (c). In Figure 10, geological body boundaries were roughly outlined according to the Euler deconvolution solutions. We assumed that sediment magnetic susceptibility is approximately zero while assigning higher values for rock bodies (around 0.01 to 0.02 SI units; iterative calculation can also be performed by fixing spatial ranges of rocks), and calculating magnetic field values based on regional inclination, declination, and other geomagnetic background parameters. A misfit of less than 20 nT has already shown a good result compared to magnetic anomalies of several hundred nanoteslas.

Figure 8. Color range symbols’ map of located AN-EUL deconvolution depths of the DZL area. The symbols are overlaid on the tilt angle with 40% transparency. The symbol colors range from cool to warm, and the sizes from small to large represent increasing-in-depth values.

Figure 8. Color range symbols’ map of located AN-EUL deconvolution depths of the DZL area. The symbols are overlaid on the tilt angle with 40% transparency. The symbol colors range from cool to warm, and the sizes from small to large represent increasing-in-depth values.

Figure 9. Color range symbols’ map of located Euler deconvolution depths of the DZL area.

Figure 9. Color range symbols’ map of located Euler deconvolution depths of the DZL area.

Figure 10. Forward modeling using Euler deconvolution solutions from the L3400 line. Sus. represents the magnetic susceptibility assigned to a geological unit.

Figure 10. Forward modeling using Euler deconvolution solutions from the L3400 line. Sus. represents the magnetic susceptibility assigned to a geological unit.

Based on the genesis of the DZL ore deposit, the contact zones between rock bodies and surrounding rocks are favorable locations for mineralization. Therefore, we use the zero-value lines of the tilt angle as a basis to identify the potential rock bodies in the study area and combine them with the Euler deconvolution distribution characteristics to recommend the areas outside the identified rock bodies as potential targets for further exploration work (Figure 11). Among them, we prioritize the areas along the extension of the DZL ore deposit, as they have the most similar conditions to the DZL ore deposit and are more likely to help discover new ore bodies. This favorable zone (zone 1 in Figure 11) is roughly an arc-shaped belt extending westward from the DZL deposit, with a length of approximately 6 km. The magnetic source depths are relatively shallow at the DZL deposit, ranging from tens of meters to 300 m, and gradually deepen to around 700 m westward. Additionally, this zone is a relatively flat area within the study area, which is also conducive to conducting ground exploration. Zones 2 and 3 on both sides of the DZL deposit, as well as the DZL deposit itself, are located within the same large magnetic anomaly range and have relatively shallow magnetic source depths, suggesting that ground exploration should be carried out subsequently. Although the southern half of zone 3 has a magnetic source depth of over 700 m, which may pose some difficulties, considering its spatial and magnetic field relationship with the DZL deposit, it is still worth conducting exploration work. The next suggested step is to explore the areas with shallow magnetic source depths in zones 4, 5, and 6, as well as the isolated anomaly bodies with shallow-source characteristics in zones 7 to 11 and 14 to 15. Zones 12 and 13 have relatively weak magnetic field intensities, and it is recommended to first verify the cause of this phenomenon in zone 12 before planning subsequent work. Of course, this is a suggestion based on short-term economic considerations. For a longer-term work cycle, every potential rock body identified through the aeromagnetic survey is worth further study by the mine owner.

5. Conclusions

The natural conditions in the DZL region, characterized by high altitude and rugged terrain, pose significant challenges to conduct ground-based surveys, resulting in a scarcity of geological and mineral resource data. This limitation hinders the exploration of potential mineral deposits beyond the known ore bodies. However, airborne magnetic surveys have overcome the impact of the extreme natural environment in this high-altitude region, acquiring high-quality magnetic data for the DZL area. The reduced-to-the-pole map displays linear, sheet-like, and isolated magnetic anomalies, which vary in shape and amplitude, but collectively reflect the primary structural trend of the NEE-SWW direction, with E-W and N-S directions being secondary. The tilt angle of the reduced-to-the-pole data further highlights the secondary anomalies superimposed on the regional background field, which are not prominent in the reduced-to-the-pole map. Moreover, the zero-contour lines of the tilt angle are used to indicate the boundaries of magnetic sources in this study. These boundaries are believed to enclose areas with potential intrusive bodies. The Euler deconvolution method is applied to the reduced-to-the-pole data to represent magnetic source depth in the regional interpretation. The magnetic source distribution obtained from Euler deconvolution shows a good consistency with the results from the tilt angle methods. The Euler deconvolution results indicate that the magnetic sources in the study area are primarily shallow, which is favorable for subsequent exploration and mining activities. Multiple priority areas for further exploration are proposed, taking the DZL ore body as a reference, providing clues and suggestions for ore-body owners to conduct exploration in the surrounding areas, with the hope of discovering new mineral deposits. This study demonstrates the applicability of airborne magnetic surveys in delineating potential mineralization zones around known ore bodies in high-altitude mountainous terrain and high-risk areas. However, airborne magnetic surveys have a relatively weak vertical resolution, and conducting complementary ground-based surveys can help to focus on target areas more effectively. It is recommended to prioritize groundwork on the west sides of the DZL deposit.