Rapid gold vein positioning method combining X-ray fluorescence spectrometer and geological radar

Abstract

The invention relates to the technical field of geological exploration, in particular to an X-ray fluorescence spectrometer and geological radar combined gold vein rapid positioning method, which comprises the following steps: S1, arranging an exploration survey line in a pre-selected exploration area; s2, along the same measuring line, measuring the content of the gold mineralization indication element in the earth surface or the shallow medium by using an X-ray fluorescence spectrometer, synchronously recording the position information of a measuring point, and generating element content spatial distribution data; the gold mineralization indicating element comprises at least one of arsenic As, antimony Sb and mercury Hg; s3, carrying out detection by using a geological radar along the same measuring line, obtaining a reflected wave signal of an underground medium, synchronously recording position information of a detection point, identifying fault zone and joint zone geological structure anomalous bodies through data processing, and generating geological radar space distribution data; through XRF and GPR data fusion, a CAI quantitative model is established to precisely delineate an ore prospecting target area, a hidden ore body is effectively identified, the exploration precision and efficiency are greatly improved, and the exploration cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, specifically a method for rapid location of gold veins using a combination of X-ray fluorescence spectrometer and ground-penetrating radar. Background Technology

[0002] Gold exploration, as an important field of mineral resource exploration, has traditionally relied mainly on methods such as geological mapping, geochemical sampling, and geophysical exploration. With the advancement of exploration technology, the combined application of multiple exploration methods has become an important way to improve mineral exploration efficiency. According to CN115586155B, a method for rapidly delineating vein-like gold deposits and obtaining their indicator indicators is disclosed. This technology discloses a method for obtaining the indicator indicators that includes: conducting surface and borehole sampling centered on the gold deposit; testing the gold content of sampled rock samples from different areas; dividing the area into mineralized or unmineralized zones based on the gold content; performing multiple short-wave infrared spectroscopy tests on each sampled rock sample from both mineralized and unmineralized zones; optimizing the data from the multiple short-wave infrared spectra; determining the muscovite group minerals in the sampled rock samples based on the optimized short-wave infrared spectra; and determining the indicator indicators based on their correspondence with the mineralized or unmineralized areas. This method achieves the technical effect of "accurately delineating the distribution location of the ore body using simple, effective, and economical indicator indicators, thereby achieving the goal of accurate assessment and efficient utilization of gold resources." In existing gold exploration, geochemical exploration and geophysical exploration are usually carried out as independent workflows, with the two processes disconnected in data acquisition, interpretation, and target area delineation. This results in elemental anomaly areas identified by geochemical measurements potentially lacking favorable mineralization structures, while structural anomalies delineated by geophysical exploration often lack direct mineralization indicators as corroboration. This data-separated interpretation model leads to scattered exploration targets, making it difficult to accurately identify comprehensive anomalies truly caused by mineralization, resulting in inaccurate target location and limited success rate of engineering verification. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a rapid gold vein location method that combines X-ray fluorescence spectrometry (XRF) with ground-penetrating radar (GPR). By fusing XRF and GPR data, a CAI (Continuous Artificial Intelligence) quantitative model is established to accurately delineate prospecting target areas, effectively identify concealed ore bodies, significantly improve exploration accuracy and efficiency, and reduce exploration costs.

[0004] To achieve the above objectives, the present invention provides a rapid gold vein location method using X-ray fluorescence spectrometry combined with ground-penetrating radar, comprising the following steps: S1, deploying survey lines within the pre-selected survey area; S2. Along the same survey line, X-ray fluorescence spectrometry is used to measure the content of gold mineralization indicator elements in the surface or shallow medium, and the location information of the measurement points is recorded simultaneously to generate spatial distribution data of element content; gold mineralization indicator elements include at least one of arsenic (As), antimony (Sb), and mercury (Hg); S3, along the same survey line, uses ground-penetrating radar to detect and obtain reflected wave signals of the underground medium, and simultaneously records the location information of the detection points. Through data processing, it identifies geological structural anomalies such as fault zones and joint zones, and generates ground-penetrating radar spatial distribution data. S4. Spatial registration is performed between the spatial distribution data of elemental content generated in step S2 and the spatial distribution data of ground-penetrating radar generated in step S3. A comprehensive anomaly index is calculated using a quantitative model. Based on the spatial distribution of this index, the area where elemental geochemical anomalies and geological structural anomalies are spatially coupled is delineated as a primary mineral exploration target area.

[0005] Preferably, in step S2, the X-ray fluorescence spectrometer is used in either continuous scanning mode or equidistant fixed-point measurement mode.

[0006] Preferably, in step S2, the X-ray fluorescence spectrometer is calibrated using a standard sample before measurement; and / or, the location information is obtained via GPS or BeiDou positioning system.

[0007] Preferably, in step S2, the gold mineralization indicator element also includes one or more of copper (Cu), lead (Pb), zinc (Zn), silver (Ag), and sulfur (S).

[0008] Preferably, in step S3, the ground-penetrating radar selects antennas with different center frequencies according to the exploration depth requirements; when used for shallow fine structure detection, a 100MHz-500MHz antenna is used, and when used for medium-deep structural detection, a 25MHz-100MHz antenna is used.

[0009] Preferably, in step S3, the data processing includes one or more of the following: time zero-point correction, gain recovery, and background denoising.

[0010] Preferably, in step S4, the quantification model is: calculating the comprehensive anomaly index CAI for each spatial unit, where CAI = f(E) × g(G), f(E) is the elemental anomaly function based on the content of gold mineralization indicator elements, and g(G) is the structural anomaly function based on the response characteristics of structural anomalies in ground-penetrating radar data.

[0011] Preferably, the element anomaly function f(E) is the weighted sum of the standardized outliers of each indicator element, i.e., f(E) = Σ[w_i × (C_i / C_{i0})], where C_i is the measured content of element i, C_{i0} is the background value of element i, w_i is the weight coefficient of element i, and when C_i ≤ C_{i0}, let (C_i / C_{i0}) = 0; the constructed anomaly function g(G) is the integral of the difference between the envelope area of ​​the ground-penetrating radar reflected wave amplitude and the background reflection intensity within the target depth range.

[0012] Preferably, the method further includes the following steps: S5. For the delineated primary mineral exploration target areas, X-ray fluorescence spectrometer is used for intensified measurement, and ground-penetrating radar is used for cross-line detection to form secondary mineral exploration target areas. S6. Drilling is conducted to verify the exploration within the secondary mineral exploration target area. S7. Based on the drilling results, compare the actual gold mineralization location with the elemental and structural anomalies in step S4, and optimize the target area delineation model by correcting the elemental background threshold, structural identification parameters and / or the quantification model, so as to guide subsequent exploration.

[0013] This invention provides a rapid method for locating gold veins using a combination of X-ray fluorescence spectrometry and ground-penetrating radar. Compared with existing technologies, it has the following advantages: 1. By establishing a comprehensive anomaly index (CAI) model, XRF elemental anomalies and GPR tectonic anomalies are quantitatively fused. The multiplicative property of CAI = f(E) × g(G) is used to ensure that the target area must simultaneously possess significant geochemical anomalies and clear geological structures. This dual constraint mechanism effectively suppresses false anomalies caused by surface pollution and tectonic responses unrelated to mineralization, significantly improving the positioning accuracy and enabling rapid focusing from regional scale to local target areas that can be verified by engineering.

[0014] 2. By adopting a synchronous working mode of XRF and GPR along the same survey line, two types of data can be acquired simultaneously in a single field operation, avoiding the repetitive work of implementing geochemical and geophysical exploration in separate steps in traditional methods; combining the rapid on-site analysis of XRF and the continuous detection characteristics of GPR significantly improves the efficiency of surface scanning; through the progressive procedure of primary target area delineation and secondary target area fine evaluation, it ensures that exploration funds are accurately allocated to the optimal location, thereby improving overall economic benefits.

[0015] 3. By using GPR to detect ore-controlling structures under the overburden and combining it with XRF to detect remote indicator elements, a correspondence between deep structures and surface anomalies can be established. This can effectively detect concealed mineral (mineralized) bodies buried at depths of tens of meters. In thick overburden areas, by identifying structural and elemental coupling anomalies, reliable evidence can be provided for deep mineral exploration, expanding the space and depth of mineral exploration. Attached Figure Description

[0016] Figure 1 This is an overall flowchart of the method of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 This invention provides a technical solution: a method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar, comprising the following steps: S1, deploying survey lines within the pre-selected survey area; S2. Along the same survey line, X-ray fluorescence spectrometry is used to measure the content of gold mineralization indicator elements in the surface or shallow medium, and the location information of the measurement points is recorded simultaneously to generate spatial distribution data of element content; gold mineralization indicator elements include at least one of arsenic (As), antimony (Sb), and mercury (Hg); S3, along the same survey line, uses ground-penetrating radar to detect and obtain reflected wave signals of the underground medium, and simultaneously records the location information of the detection points. Through data processing, it identifies geological structural anomalies such as fault zones and joint zones, and generates ground-penetrating radar spatial distribution data. S4. Spatial registration is performed between the spatial distribution data of elemental content generated in step S2 and the spatial distribution data of ground-penetrating radar generated in step S3. A comprehensive anomaly index is calculated using a quantitative model. Based on the spatial distribution of this index, the area where elemental geochemical anomalies and geological structural anomalies are spatially coupled is delineated as a primary mineral exploration target area.

[0019] In this implementation plan, firstly, in pre-selected exploration areas with favorable mineralization geological conditions, exploration survey lines are systematically laid out at certain intervals. Subsequently, field personnel use handheld or vehicle-mounted X-ray fluorescence spectrometers (XRF) along the same survey line, employing continuous scanning or equidistant fixed-point modes for measurement. This instrument emits X-rays to excite gold mineralization indicator elements in soil and rocks, generating characteristic X-ray fluorescence. Energy dispersive spectroscopy analysis is used to obtain the elemental content in real time, and an integrated GPS / BeiDou module is used to synchronously record the precise coordinates of each measuring point, thereby generating spatial distribution data of elemental content reflecting the enrichment patterns of elements on the surface. Simultaneously, ground-penetrating radar (GPR) equipped with antennas of different frequencies is used for synchronous detection along the same survey line, which... By transmitting high-frequency electromagnetic pulses underground and receiving reflected wave signals from interfaces of different electrical media, and processing the reflected signals through time zero-point correction, gain restoration, and background denoising, the spatial morphology of underground structural anomalies such as fault zones and joint zones can be clearly identified, generating spatial distribution data of ground-penetrating radar. Finally, in a professional data processing software platform, the above elements are spatially registered with radar data with high precision, and fusion calculations are performed based on a quantization model. By analyzing the spatial distribution of the CAI index, the region where surface element anomalies and underground structural anomalies are highly coupled in three-dimensional space is accurately delineated, which is identified as a primary prospecting target area for revealing the existence of concealed gold veins, providing precise guidance for subsequent drilling projects.

[0020] Specifically, in step S2, the X-ray fluorescence spectrometer is used in either continuous scanning mode or equidistant fixed-point measurement mode.

[0021] In this embodiment, during the elemental content data acquisition stage in step S2, the operator selects the appropriate measurement mode for the X-ray fluorescence spectrometer (XRF) based on the required survey accuracy and terrain accessibility: When rapid surveying is required, a continuous scanning mode is used. In this mode, the operator holds the instrument close to the ground surface and moves it at a constant speed (typically about 10-20 cm per second). The instrument continuously emits X-ray beams at a high frequency (e.g., 10 Hz) and instantaneously receives the returned characteristic X-ray fluorescence signals. A continuous curve of elemental content is recorded and output in real time through rapid energy spectrum analysis. This mode is highly efficient and suitable for large-area scanning. When higher precision and statistical stability data are required, an equidistant fixed-point measurement mode is used. In this case, the measurement point spacing (e.g., 1 meter, 5 meters, or 10 meters) needs to be preset, and the instrument probe is tightly secured at each measurement point. The instrument is pressed and fixed to the surface medium to be tested, ensuring full coupling between the measurement window and the sample. It performs a single excitation and measurement for a relatively long duration (usually 10-30 seconds), significantly improving the signal-to-noise ratio and reducing statistical errors by accumulating more photon counts, thereby obtaining more accurate quantitative or semi-quantitative results for each point. Regardless of the mode used, the physical principle is based on the primary X-ray photons emitted by the X-ray tube exciting the inner-shell electrons of the sample atoms. When the excited atoms undergo electron transitions to fill the inner-shell vacancies, they release characteristic X-ray fluorescence with specific energy values ​​of the element. After the detector captures these signals, the built-in software identifies different energy peak positions through energy spectrum analysis to determine the element type. By calculating the characteristic peak intensity or peak area and comparing it with the calibration curve of the standard sample, the content of the corresponding indicator element (such as As, Sb, Hg) in the sample is finally calculated.

[0022] Specifically, in step S2, the X-ray fluorescence spectrometer is calibrated using a standard sample before measurement; and / or, location information is obtained via GPS or BeiDou positioning system.

[0023] In this embodiment, to ensure the accuracy and spatial traceability of the data obtained in step S2, strict quality control and positioning operations were performed before and during the formal measurement: In terms of instrument calibration, before each daily measurement and when the measurement environment changed significantly, a series of national standard materials or working standard samples with known precise elemental contents that matched the matrix of the medium to be measured (e.g., soil or rock standard samples containing specific gradients of As, Sb, and Hg content) were used to calibrate the X-ray fluorescence spectrometer (XRF); the specific operation was to closely align the instrument probe with the surface of the standard sample for measurement, and the instrument's built-in software would automatically collect the characteristic X-ray fluorescence energy spectrum of the standard sample and perform regression analysis on the measured value and the known reference value on the standard certificate, thereby establishing or verifying a calibration curve that converts the count rate (or intensity) measured by the instrument into the actual elemental content. This process aims to eliminate systematic errors caused by instrument state drift, matrix effects, and environmental factors, and ensure the accuracy of subsequent field measurement data at the quantitative or semi-quantitative level; In terms of spatial positioning, the measurement work is carried out simultaneously with high-precision positioning technology. Whether in continuous scanning or fixed-point measurement mode, the geographic coordinates of the measurement points are obtained in real time using GPS (Global Positioning System) and / or BeiDou (BDS) satellite navigation and positioning modules integrated into or linked to the XRF equipment. The working principle is that the positioning module receives signals from multiple navigation satellites, calculates the signal propagation time difference, and determines the three-dimensional spatial position (longitude, latitude, and elevation) of the receiver antenna phase center in real time based on the resection principle. This position information (usually with an accuracy of sub-meter or even centimeter level, depending on the positioning technology and differential correction method) is automatically bound and synchronously stored with the element content data collected at the same time. This gives each geochemical data point a precise spatial attribute, which is an absolute prerequisite for the subsequent generation of element content spatial distribution maps and accurate spatial registration and fusion with ground-penetrating radar data.

[0024] Specifically, in step S2, the gold mineralization indicator elements also include one or more of copper (Cu), lead (Pb), zinc (Zn), silver (Ag), and sulfur (S).

[0025] In this embodiment, when using X-ray fluorescence spectrometry (XRF) for measurement, in addition to the core volatile elements such as arsenic (As), antimony (Sb), and mercury (Hg), one or more elements such as copper (Cu), lead (Pb), zinc (Zn), silver (Ag), and sulfur (S) are also included in the detection system for gold mineralization indicator elements. Gold (Au) often has a close symbiotic relationship with these elements during hydrothermal mineralization: Cu, Pb, and Zn, as typical basic sulfide elements, are common gold minerals in hydrothermal deposits. Belonging to sulfide assemblages, anomalous enrichment of these elements often indicates the presence of sulfide precipitation stages. Gold is frequently found as microscopic or ultramicroscopic inclusions in sulfides such as pyrite (FeS2), galena (PbS), and sphalerite (ZnS). Ag and Au often coexist due to their similar geochemical properties (copper affinity), and Ag anomalies can serve as direct indicators of gold mineralization. S is the core component of all sulfides, and its high content directly delineates the sulfide mineralization range, i.e., the "chemical traps" where gold may accumulate. In practice, by pre-setting the characteristic X-ray energy ranges of these elements in the XRF analysis software (e.g., Kα line of Cu approximately 8.04 keV, Lα line of Pb approximately 10.55 keV, Kα line of Zn approximately 8.64 keV, Kα line of Ag approximately 22.16 keV, and Kα line of S approximately 2.31 keV), the instrument can simultaneously detect and analyze the characteristic X-ray fluorescence intensity of these elements when exciting the sample. By analyzing the symbiotic assemblage characteristics of these multi-element indicator elements (such as Cu-Pb-Zn assemblage indicating a polymetallic sulfide stage), spatial zoning (such as the possible zoning from the inside to the outside of Cu-Zn→Pb-Ag→As-Sb-Hg), and relative intensity ratios, hydrothermal mineralization centers can be delineated more effectively, mineralization types can be identified (for example, a high Cu / Zn ratio may indicate mineralization associated with intermediate-acidic rock bodies), and the degree of erosion of ore bodies can be assessed. This significantly improves the accuracy and reliability of inferring underground concealed gold deposits using surface element anomalies.

[0026] Specifically, in step S3, the ground-penetrating radar selects antennas with different center frequencies according to the exploration depth requirements; 100MHz-500MHz antennas are used for shallow fine structure detection, and 25MHz-100MHz antennas are used for medium-deep structure detection.

[0027] In this embodiment, when using ground-penetrating radar for detection in step S3, antennas with different center frequencies are selected according to the burial depth and resolution requirements of the target body, following the principle of electromagnetic wave propagation: When it is necessary to finely depict the structural details of shallow parts (usually within 0-10 meters), such as identifying small joint zones, lithological interfaces, or near-surface mineralization alteration zones, a high center frequency antenna of 100MHz to 500MHz is used. The physical principle is that high-frequency electromagnetic waves have shorter wavelengths (e.g., when the dielectric constant of dry sandstone is 5, the wavelength of a 500MHz antenna is approximately 0.27 meters). According to the Rayleigh scattering criterion, its vertical resolution can reach the centimeter to decimeter level, clearly distinguishing thin layers and microstructures. However, because it attenuates quickly in the medium (the attenuation coefficient is proportional to the frequency), the detection depth is limited; conversely, when the detection target is the medium-deep part that controls the location of the ore vein (usually... When dealing with main fault zones (10-50 meters) or large structural fracture zones, a low center frequency antenna of 25MHz to 100MHz is selected. At this frequency, the electromagnetic wave wavelength is longer (e.g., a 25MHz antenna can reach a wavelength of 5.4 meters in the same medium). Although the vertical resolution is reduced to the meter level, its penetration capability is significantly enhanced. This is because the skin depth of electromagnetic waves in the medium is inversely proportional to the square root of the frequency. Low-frequency signals can penetrate thicker overburden or bedrock, effectively detecting the spatial distribution of deep large structures. In practice, in bedrock outcrops with thin overburden, high-frequency antennas can be used for fine scanning. In thick overburden areas, low-frequency antennas are preferred for deep structural framework detection. Sometimes, a combination of high- and low-frequency antennas can be used to achieve seamless three-dimensional detection from shallow to deep, ensuring that both shallow mineralization indicators and the deep structural origins controlling ore deposits can be revealed.

[0028] Specifically, in step S3, data processing includes one or more of the following: time zero-point correction, gain recovery, and background denoising.

[0029] In this embodiment, after acquiring the raw reflected wave signal from the ground-penetrating radar in step S3, a series of key data processing procedures need to be executed through professional processing software to improve data quality and interpretation reliability. First, zero-point time correction is performed. This is because the distance between the radar antenna and the ground (air coupling) and the electronic delay within the system cause the recorded two-way travel time starting point of the reflected wave to not be the true zero moment. During correction, the first peak or trough of the direct wave (air wave) or surface reflected wave is identified and manually or automatically aligned to the theoretically calculated or measured surface time position, thereby ensuring the accuracy of subsequent depth calculations. The principle is to establish a precise "time-depth" conversion relationship (depth = (wave velocity × time) / 2). Next, gain recovery processing is implemented because electromagnetic waves attenuate exponentially during underground propagation due to geometric diffusion and medium absorption, resulting in extremely weak deep reflected signals. Therefore, time-varying gain functions (such as SEC gain, exponential gain) are applied. (e.g.,) to compensate and amplify the amplitude of deep signals. The principle is to simulate the reverse attenuation process, so that the reflection amplitude energy of shallow, medium and deep parts tends to be balanced, thereby enhancing the identifiability of deep structures (such as basement faults). Finally, background denoising is performed. Radar data is usually mixed with various noises, including internal electronic noise, multiple reflections caused by surface obstacles and random interference. The methods used usually include moving average method (mean filtering) to suppress random high-frequency noise, and / or bandpass filtering to remove high-frequency noise and low-frequency drift outside the signal frequency band. The principle is based on the difference between the effective signal and noise in the frequency domain or spatial domain. The noise is separated and suppressed by the filtering algorithm, thereby highlighting the effective underground reflection phase axis. This allows the reflection wave groups corresponding to structural anomalies such as fault zones and joint zones (such as waveform disorder, phase axis misalignment, strong reflection interface, etc.) to be clearly displayed, laying the foundation for generating high-quality spatial distribution data of ground-penetrating radar.

[0030] Specifically, in step S4, the quantification model is as follows: calculate the comprehensive anomaly index CAI for each spatial unit, where CAI = f(E) × g(G), f(E) is the elemental anomaly function based on the content of gold mineralization indicator elements, and g(G) is the structural anomaly function based on the response characteristics of structural anomalies in ground-penetrating radar data.

[0031] In this embodiment, during the data fusion stage in step S4, a quantitative model called the Comprehensive Anomaly Index (CAI) is constructed and applied to mathematically fuse and enhance geochemical and geophysical anomalies. Its core expression is CAI = f(E) × g(G). First, the registered spatial region is divided into uniform regular grid cells. For each grid cell, the elemental anomaly function f(E) is quantified by calculating the weighted sum of the standardized anomaly values ​​of all selected gold mineralization indicator elements (such as As, Sb, Hg, Cu, etc.). f(E) = Σ[w_i × (C_i / C_{i0})], where C_i is the measured content of element i in the cell (from XRF data), C_{i0} is the background value of the element in the entire study area (usually the regional average or median), and w_i is a weighting coefficient pre-set based on the empirical correlation between the element and gold mineralization (e.g., giving higher weights to As and Sb); the principle of this function is to use the relative enrichment of element content to characterize the intensity of surface geochemical halo, and the weighted sum highlights the combined contribution of key indicator elements. Meanwhile, the structural anomaly function g(G) is used to quantify the degree of structural development revealed in the ground-penetrating radar profile below the unit. Its calculation is based on the envelope area of ​​the radar reflected wave amplitude within the target depth range (e.g., 5 to 20 meters below the surface). The principle is that structural anomalies such as fault zones and joint zones, due to the difference in dielectric constant between their internal infill materials and the surrounding rock, cause strong reflections of electromagnetic waves. The sum of the amplitude envelope areas of these reflected signals (or the integral of the difference between the reflected intensity and the background reflection intensity of the stable surrounding rock) directly reflects the scale of the structure and the degree of electrical difference between it and the surrounding rock. Finally, the CAI value is obtained by multiplying f(E) and g(G) of each grid cell. The underlying principle of the multiplication model is that it requires that the prospecting area must have both significant geochemical anomalies (high f(E) value) and obvious geological structural anomalies (high g(G) value). The absence of either aspect will cause the CAI value to drop sharply, thus effectively suppressing the false anomalies that may be generated by a single method. It greatly focuses and highlights those areas where "elemental anomalies and structural anomalies are spatially coupled". These high CAI value areas are scientifically delineated as primary prospecting target areas indicating the existence of concealed gold veins.

[0032] Specifically, the element anomaly function f(E) is the weighted sum of the standardized outliers of each indicator element, i.e., f(E) = Σ[w_i × (C_i / C_{i0})], where C_i is the measured content of element i, C_{i0} is the background value of element i, w_i is the weight coefficient of element i, and when C_i ≤ C_{i0}, let (C_i / C_{i0}) = 0; the constructed anomaly function g(G) is the integral of the difference between the envelope area of ​​the ground-penetrating radar reflected wave amplitude and the background reflection intensity within the target depth range.

[0033] In this embodiment, when calculating the Comprehensive Anomaly Index (CAI), the elemental anomaly function f(E) and the structural anomaly function g(G) are precisely defined and calculated mathematically. The elemental anomaly function f(E) is specifically implemented as f(E) = Σ[w_i × (C_i / C_{i0})], where first, the background value C_{i0} of each indicator element (such as As, Sb, Hg, Cu, etc.) needs to be determined. This value is usually obtained through systematic sampling statistics of the background area within the exploration area or by referencing regional geochemical background values. When calculating the f(E) value for each grid cell, the content of each element C_i and C_{i0} is first calculated. The ratio of C_i to C_{i0} is used, but the key point is that when C_i ≤ C_{i0}, (C_i / C_{i0}) is forced to be 0. The geochemical principle of this treatment is that only the anomalous content exceeding the background value has mineral exploration indication significance. This can effectively suppress background noise and highlight the real anomalous signal. Then, the standardized anomalous value of each element is multiplied by its corresponding weight coefficient w_i (the weight coefficient is determined based on the strength of the exclusive symbiotic relationship and migration ability of the element with gold mineralization, for example, As and Sb are assigned a weight of 0.3, Hg is assigned 0.2, and Cu is assigned 0.1). Finally, the sum is obtained to obtain the comprehensive elemental anomalous intensity. For the structural anomaly function g(G), its calculation is based on the processed ground-penetrating radar profile data. First, within the selected target depth range (e.g., 5-30 meters), the reflected wave amplitude sequence of each measuring point at the corresponding depth segment is extracted. Then, its Hilbert transform is calculated to obtain the amplitude envelope. The area enclosed by this envelope and the time axis (i.e., the depth axis) is the value of g(G). The geophysical principle is that the integral of the amplitude envelope area can comprehensively reflect the total energy of all structural reflection interfaces within the depth segment. Fault zones, joint zones, and other structurally developed areas often correspond to larger envelope areas. Another equivalent algorithm is to calculate the integral of the difference between the reflected wave amplitude and the background reflection intensity of the stable surrounding rock area within the depth segment, and highlight the anomaly response by subtracting the background value.

[0034] Specifically, the method also includes the following steps: S5. For the delineated primary mineral exploration target areas, X-ray fluorescence spectrometer is used for intensified measurement, and ground-penetrating radar is used for cross-line detection to form secondary mineral exploration target areas. S6. Drilling is conducted to verify the exploration within the secondary mineral exploration target area. S7. Based on the drilling results, compare the actual gold mineralization location with the elemental and structural anomalies in step S4, and optimize the target area delineation model by correcting the elemental background threshold, structural identification parameters and / or the quantification model, so as to guide subsequent exploration.

[0035] In this embodiment, after the primary prospecting target area is delineated, in step S5, a higher-precision exploration operation is deployed for the delineated primary target area: First, the spacing of the X-ray fluorescence spectrometer (XRF) grid is increased to 1 / 2 or 1 / 4 of the original scheme (e.g., from 20m × 40m to 10m × 10m). By increasing the number of measurement points per unit area, the spatial morphology and concentration center of surface element anomalies are finely characterized. At the same time, based on the original main survey line, cross survey lines perpendicular or oblique to it are added using ground-penetrating radar to form a gridded observation system. The principle is to use multi-directional detection and spatial intersection of structural anomalies revealed by profiles in different directions to constrain the true morphology, occurrence, and spatial distribution of underground structural anomalies (such as fault zone intersections and dense joint areas) in three dimensions. Finally, the densified element data and the cross radar data are fused to delineate a secondary prospecting target area with a smaller range and higher accuracy and reliability. In step S6, the drilling project is directly arranged in the above-mentioned secondary target area, especially at the coupling point where the element concentration center and the structure meet. Through drilling core sampling and subsequent geological logging and sample chemical analysis, the existence of gold (chemical) bodies underground and their specific location, thickness and grade are directly verified. This is the ultimate test of the geophysical-geochemical anomaly inference conclusion. In step S7, based on the "geological truth" revealed by drilling, key model feedback and optimization are performed: the spatial coordinates of the actual gold mineralization encountered are accurately superimposed and statistically compared with the corresponding CAI high value area, elemental anomaly intensity f(E), and structural anomaly intensity g(G) in step S4; if a stable correspondence is found between effective mineralization and specific elemental combinations (such as As-Cu-Ag) or specific structural radar response characteristics (such as strong reflection in a specific frequency range), the elemental background threshold (C_{i0}) is corrected accordingly to better distinguish between mineralized anomalies and non-mineralized anomalies, and structural identification parameters (such as reflected wave amplitude threshold and target depth range) are optimized to more accurately extract ore-controlling structures, and even the quantitative model is adjusted (such as modifying the weight coefficient w_i or the CAI calculation formula itself); the principle of this process is to establish a "quantitative prospecting model" based on the actual mineralized body and applicable to this exploration area.

[0036] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0037] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A rapid location method for gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar, characterized in that: Includes the following steps: S1, deploying survey lines within the pre-selected survey area; S2. Along the same survey line, X-ray fluorescence spectrometry is used to measure the content of gold mineralization indicator elements in the surface or shallow medium, and the location information of the measurement points is recorded simultaneously to generate spatial distribution data of element content; gold mineralization indicator elements include at least one of arsenic (As), antimony (Sb), and mercury (Hg); S3, along the same survey line, uses ground-penetrating radar to detect and obtain reflected wave signals of the underground medium, and simultaneously records the location information of the detection points. Through data processing, it identifies geological structural anomalies such as fault zones and joint zones, and generates ground-penetrating radar spatial distribution data. S4. Spatial registration is performed between the spatial distribution data of elemental content generated in step S2 and the spatial distribution data of ground-penetrating radar generated in step S3. The comprehensive anomaly index is calculated through a quantitative model, and the spatial distribution of the index is used to delineate the areas where elemental geochemical anomalies and geological structural anomalies are spatially coupled, which serve as primary mineral exploration target areas.

2. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 1, characterized in that: In step S2, the X-ray fluorescence spectrometer is used in either continuous scanning mode or equidistant fixed-point measurement mode.

3. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 2, characterized in that: In step S2, the X-ray fluorescence spectrometer is calibrated using a standard sample before measurement; and / or, location information is obtained via GPS or BeiDou positioning system.

4. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 1, characterized in that: In step S2, the gold mineralization indicator elements also include one or more of copper (Cu), lead (Pb), zinc (Zn), silver (Ag), and sulfur (S).

5. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 1, characterized in that: In step S3, the ground-penetrating radar selects antennas with different center frequencies according to the exploration depth requirements; 100MHz-500MHz antennas are used for shallow fine structure detection, and 25MHz-100MHz antennas are used for medium-deep structural detection.

6. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 5, characterized in that: In step S3, data processing includes one or more of the following: time zero-point correction, gain recovery, and background denoising.

7. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 1, characterized in that: In step S4, the quantification model is as follows: calculate the comprehensive anomaly index CAI for each spatial unit, where CAI = f(E) × g(G), f(E) is the elemental anomaly function based on the content of gold mineralization indicator elements, and g(G) is the structural anomaly function based on the response characteristics of structural anomalies in ground-penetrating radar data.

8. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 7, characterized in that: The element anomaly function f(E) is the weighted sum of the standardized outliers of each indicator element, i.e., f(E) = Σ[w_i × (C_i / C_{i0})], where C_i is the measured content of element i, C_{i0} is the background value of element i, w_i is the weight coefficient of element i, and when C_i ≤ C_{i0}, let (C_i / C_{i0}) = 0; the constructed anomaly function g(G) is the integral of the difference between the envelope area of ​​the ground-penetrating radar reflected wave amplitude and the background reflection intensity within the target depth range.

9. The method for rapid location of gold veins using X-ray fluorescence spectrometry combined with ground-penetrating radar according to claim 1, characterized in that: The method also includes the following steps: S5. For the delineated primary mineral exploration target areas, X-ray fluorescence spectrometer is used for intensified measurement, and ground-penetrating radar is used for cross-line detection to form secondary mineral exploration target areas. S6. Drilling is conducted to verify the exploration within the secondary mineral exploration target area. S7. Based on the drilling results, compare the actual gold mineralization location with the elemental and structural anomalies in step S4, and optimize the target area delineation model by correcting the elemental background threshold, structural identification parameters and / or the quantification model, so as to guide subsequent exploration.

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