Deep Exploration Method, System and Storage Medium for Rare Earth Ore Based on Time-Frequency Electromagnetics

Abstract

The present invention discloses a deep exploration method, system and storage medium for rare earth ores based on time-frequency electromagnetic. The exploration method includes: identifying a target area in the area to be explored; collecting exploration data of the target area by using the time-frequency electromagnetic method to obtain first time-domain data and first frequency-domain data; calculating the apparent resistivity of the target area according to the first time-domain data, and calculating the total longitudinal conductance parameter based on the apparent resistivity; constructing an Occam inversion model related to the total longitudinal conductance parameter; performing dual-frequency phase calculation and dual-frequency amplitude calculation according to the first frequency-domain data to obtain a frequency parameter set of the target area; fitting the Occam inversion model and performing polarization rate inversion based on the frequency parameter set; and delineating deep geophysical exploration anomalies in the target area based on the polarization rate inversion result. The present invention can use time-frequency electromagnetic technology to identify deep rare earth ores, reduce the number of exploration drillings, lower the exploration cost, shorten the prospecting time, and improve the exploration efficiency of concealed rare earth ore deposits in thickly covered areas.

Description

Technical Field

[0001] The present invention relates to the technical field of mineral resource exploration, and particularly to a deep exploration method, system and storage medium for rare earth ores based on time-frequency electromagnetic. Background Art

[0002] With the development of the national economy, the social demand for rare earth resources is increasing significantly. However, the outcrop ores and the easily found shallow surface ores are becoming fewer and fewer. Especially in the Panxi rare earth metallogenic belt in Sichuan, which is more than 150 km long and 10 km wide, so far only 2 large-scale rare earth mines in operation (MaoNiuping Mine and Continental Trough Mine) have been discovered. There is a 100-km blank area between the MaoNiuping-Continental Trough mining area. Due to the deep topographic incision and thick Quaternary cover (>50 m), there are only a few ore spots and small and medium-sized mines.

[0003] From the perspective of the prospecting history in the Panxi rare earth metallogenic belt in Sichuan, since the 1960s, the prospecting work around the Panxi metallogenic belt has already started. Especially for the surface outcrops, almost all have been repeatedly explored by generations of geologists, and it is extremely difficult to find new outcrop ores. The surface is covered by a large amount of colluvial and alluvial deposits, so exploring deep and finding blind ores have become the focus of the prospecting work in this area. As a result, the prospecting difficulty has increased sharply, the exploration cost has soared, the exploration discovery rate has decreased significantly, and there is an urgent need for an efficient and low-cost method to guide the exploration of deep buried bodies in the process of mineral exploration. Therefore, exploring a suitable deep prospecting method for rare earth ores has important practical significance for finding deep buried bodies of the same type of rare earth ores in the future. Summary of the Invention

[0004] The embodiments of the present invention provide a deep exploration method, system and storage medium for rare earth ores based on time-frequency electromagnetic, which can use time-frequency electromagnetic technology to identify deep rare earth ores, reduce the number of exploration drillings, greatly reduce the exploration cost, shorten the ore prospecting time, and significantly improve the exploration efficiency of buried rare earth ore deposits in thickly covered areas.

[0005] An embodiment of the present invention provides a deep exploration method for rare earth ores based on time-frequency electromagnetic, including:

[0006] Identifying a target area in the to-be-explored area according to the regional characteristics of the to-be-explored area;

[0007] Collecting exploration data of the target area by using time-frequency electromagnetic method, preprocessing the exploration data to obtain first time-domain data and first frequency-domain data;

[0008] Calculating the apparent resistivity of the target area according to the first time-domain data, and calculating the total longitudinal conductance parameter based on the apparent resistivity;

[0009] Constructing an Occam inversion model related to the total longitudinal conductance parameter;

[0010] Perform dual-frequency phase calculation and dual-frequency amplitude calculation based on the first frequency-domain data to obtain a frequency parameter set of the target area;

[0011] Fit the Occam inversion model, and when the fitting result meets the preset error requirement, perform susceptibility inversion based on the frequency parameter set;

[0012] Based on the result of the susceptibility inversion, delineate deep geophysical anomaly bodies in the target area.

[0013] As an improvement to the above solution, the first time-domain data includes: angular frequency, magnetic permeability, electric field strength, and magnetic field strength;

[0014] The calculation of the apparent resistivity of the target area according to the first time-domain data and the calculation of the total longitudinal conductance parameter based on the apparent resistivity include:

[0015] Calculate the apparent resistivity through the following formula:

[0016]

[0017] In the formula, ρ is the apparent resistivity, ω is the angular frequency, μ is the magnetic permeability, E is the electric field strength in the first direction, H is the magnetic field strength in the second direction, where the first direction is perpendicular to the second direction;

[0018] Obtain an apparent resistivity curve based on the apparent resistivity, and calculate the total longitudinal conductance parameter through the following formula:

[0019]

[0020] In the formula, S is the total longitudinal conductance parameter, ρ min is the minimum value before the 45° elevation of the apparent resistivity curve, f min is the ρ min corresponding frequency.

[0021] As an improvement to the above solution, the construction of the Occam inversion model related to the total longitudinal conductance parameter includes:

[0022] For the Occam inversion model, construct the following objective function:

[0023]

[0024] In the formula, λ is the Lagrange multiplier, W is the error weighting matrix, S is the total longitudinal conductance parameter, m is the Occam inversion model parameter, G(m) is the forward operator, is the roughness matrix, △ is the first-order Laplace operator, t1 is the regularization parameter corresponding to the first-order Laplace operator, △2 is the second-order Laplacian operator, and t2 is the regularization parameter corresponding to the second-order Laplacian operator.

[0025] As an improvement to the above solution, the double-frequency phase calculation and double-frequency amplitude calculation are performed based on the first frequency-domain data to obtain the frequency parameter set of the target area, including:

[0026] The double-frequency phase is calculated by the following formula:

[0027]

[0028] In the formula, DFP is the double-frequency phase, ω1 is the fundamental wave frequency collected, ω3 is the frequency of the third harmonic of ω1, and ω1 < ω3, is the phase of the fundamental wave, is the phase of the third harmonic;

[0029] The double-frequency amplitude is calculated by the following formula:

[0030]

[0031] In the formula, P_Amp is the double-frequency amplitude, A L is the low-frequency amplitude value, A H is the high-frequency amplitude value;

[0032] The double-frequency phase and the double-frequency amplitude of each frequency point are extracted to obtain the frequency parameter set.

[0033] As an improvement to the above solution, the polarizability inversion based on the frequency parameter set includes:

[0034] The polarizability inversion is performed by the following formula using the Cole-Cole model:

[0035]

[0036] In the formula, ρ’ is the result of the polarizability inversion, ρ is the apparent resistivity, DFP is the double-frequency phase, P_Amp is the double-frequency amplitude, i is the imaginary unit, ω is the angular frequency, τ is the time constant, and c is the distribution parameter of the Cole-Cole model.

[0037] As an improvement to the above solution, the identification of the target area in the to-be-explored area according to the area characteristics of the to-be-explored area includes:

[0038] Based on the area characteristics of the to-be-explored area, an initial working area is identified in the to-be-explored area, where the area characteristics include at least one of element characteristics, surface characteristics, and natural landscape characteristics;

[0039] Perform radioactive gamma measurement on the initial working area, and identify the target area according to the measurement results.

[0040] As an improvement to the above solution, the exploration data of the target area is collected by the time-frequency electromagnetic method, and the exploration data is preprocessed to obtain the first time-domain data and the first frequency-domain data, including:

[0041] Perform original signal analysis, data current normalization, and data denoising on the exploration data to obtain the first time-domain data;

[0042] Perform noise analysis, interference elimination, device coefficient normalization, current and frequency response normalization, and zero-channel and bad-point deletion on the exploration data to obtain the first frequency-domain data.

[0043] Another embodiment of the present invention correspondingly provides a deep exploration system for rare earth ores based on time-frequency electromagnetics, including:

[0044] A target area identification module for identifying a target area in the area to be explored according to the area characteristics of the area to be explored;

[0045] A data preprocessing module for collecting exploration data of the target area by the time-frequency electromagnetic method and preprocessing the exploration data to obtain the first time-domain data and the first frequency-domain data;

[0046] A time-domain analysis module for calculating the apparent resistivity of the target area according to the first time-domain data and calculating the total longitudinal conductance parameter based on the apparent resistivity;

[0047] A model calculation module for constructing an Occam inversion model related to the total longitudinal conductance parameter;

[0048] A frequency calculation module for performing dual-frequency phase calculation and dual-frequency amplitude calculation according to the first frequency-domain data to obtain a frequency parameter set of the target area;

[0049] A polarization rate inversion module for fitting the Occam inversion model and performing polarization rate inversion based on the frequency parameter set when the fitting result meets the preset error requirement;

[0050] A mineral identification module for delineating deep geophysical exploration anomalies in the target area based on the result of the polarization rate inversion.

[0051] Another embodiment of the present invention provides a deep exploration system for rare earth ores based on time-frequency electromagnetics, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the deep exploration method for rare earth ores based on time-frequency electromagnetics described in the above embodiment of the invention.

[0052] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method for deep exploration of rare earth ores based on time-frequency electromagnetic as described in the above-mentioned embodiment of the invention.

[0053] Compared with the prior art, in the embodiment of the present invention, first, through regional characteristics, target area identification is carried out in the area to be explored, narrowing the prospecting range; the time-frequency electromagnetic method is used to detect the target area, and the research and analysis of the profile anomaly characteristics are carried out through two aspects of the time domain and the frequency domain. Through the calculation of apparent resistivity and total longitudinal conductance parameters, an Occam inversion model is obtained, and then polarization rate inversion is carried out based on frequency data. Finally, an effective deep anomaly geological feature model is established as the basis for effectively delineating deep anomaly bodies; thus providing a basis for better arranging drilling projects, reducing the number of exploration drillings, greatly reducing the exploration cost, and at the same time being able to shorten the prospecting time and significantly improving the exploration efficiency of concealed rare earth ore deposits in thickly covered areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a schematic flow chart of a method for deep exploration of rare earth ores based on time-frequency electromagnetic provided by an embodiment of the present invention;

[0055] Figure 2 is a schematic diagram of an axial dipole device used in field construction provided by an embodiment of the present invention;

[0056] Figure 3 is a comprehensive geological-geophysical-drilling profile of Longjiagou P01 provided by an embodiment of the present invention;

[0057] Figure 4 is a schematic structural diagram of a deep exploration system for rare earth ores based on time-frequency electromagnetic provided by an embodiment of the present invention;

[0058] Figure 5 is a schematic structural diagram of a deep exploration system for rare earth ores based on time-frequency electromagnetic provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0059] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0060] See Figure 1, is a schematic flowchart of a deep exploration method for rare earth ores based on time-frequency electromagnetic provided by an embodiment of the present invention, including steps S101 to step S107:

[0061] S101. Identify the target area in the to-be-explored area according to the regional characteristics of the to-be-explored area;

[0062] Specifically, based on the basic geological data of the to-be-explored area, large-scale surface boulder mapping, large-scale surface geochemical exploration data, radioactive gamma measurement prospecting methods, etc., important surface mineralized areas can be initially delineated as the target area.

[0063] S102. Use the time-frequency electromagnetic method to collect exploration data of the target area, and preprocess the exploration data to obtain the first time-domain data and the first frequency-domain data;

[0064] Specifically, this embodiment proposes to use the time-frequency electromagnetic method (TFEM, Time-Frequency Electromagnetic Method) in the deep prospecting work of hard rock-type carbonate rare earth ores in deep overburden areas. Few geophysical deep methods have been used in rare earth ore exploration by predecessors, and only a small amount of experimental work has been done. The advantages of the time-frequency electromagnetic method compared with the conventional methods in the prior art include: (1) High-power excitation, which is more than a dozen times the power of the conventional electrical method, with strong anti-interference and high resolution; (2) Measuring the electric field and magnetic field components simultaneously, which compensates for the defect of low resolution of high-resistance thin layers caused by only observing single components, and multi-component inversion calculation reduces the non-uniqueness; (3) Measuring time-domain and frequency-domain information simultaneously; (4) Studying the resistivity and polarization anomalies of the target area simultaneously. In view of the above analysis, the deep exploration method for rare earth ores based on time-frequency electromagnetic provided by this embodiment can be used to solve the problems that the existing rare earth ore exploration methods cannot quickly and effectively penetrate thick overburden areas (floating soil thickness >  50 m) to delineate hidden abnormal bodies of deep rare earth ores, and have low prospecting success rate, high cost, and long cycle.

[0065] Specifically, the steps of collecting exploration data of the target area by the time-frequency electromagnetic method provided by this embodiment include the following three types:

[0066] (1) Adopt a long straight wire source excitation, combine frequency-domain sounding and time-domain sounding in one system, and different frequencies and different types of excitation waveforms can be selected according to the depth of the exploration target. It can not only provide resistivity information but also provide induced polarization information, so that while studying the electrical structure, high polarization rate abnormal bodies can be detected. The time-frequency electromagnetic method adopts a non-zero crossing square wave, which can have a variety of different combinations, continuously excite from high frequency to low frequency, and each frequency is excited several times repeatedly. The number of repetitions is set according to the frequency. The number of repetitions at high frequencies is more, and the number of repetitions at low frequencies is relatively reduced, and the data quality and reliability are relatively high.

[0067] (2) Adopt the working mode of multi-station array reception. Each station consists of an electrical acquisition station and a magnetic acquisition station. The signal reception system synchronously receives all signals repeatedly excited at each frequency through GPS. The time-frequency electromagnetic technology combines the advantages of the frequency-domain method and the time-domain method, enabling two processing means in data processing, namely the time domain and the frequency domain. By using multiple means to comprehensively utilize the characteristics of various fields to study various rock physical properties, the exploration accuracy is effectively improved.

[0068] (3) Refer to Figure 2 , when conducting field construction, the axial dipole device is adopted, which is divided into two parts: transmitting and receiving. The transmitting end consists of multiple parallel aluminum plates to form a horizontally finite-length grounding wire source. A high-power transmitter is used to send a series of right-angled pulse currents into the ground at different frequencies. The receiving end measures the electric field component E through electrodes grounded at two endpoints MN x .

[0069] S103. Calculate the apparent resistivity of the target area based on the first time-domain data, and calculate the total longitudinal conductance parameter based on the apparent resistivity;

[0070] Specifically, in electrical prospecting, the resistivity calculation method of a homogeneous half-space is extended and applied to a non-homogeneous half-space. The ρ solved is called the apparent resistivity. By analyzing the apparent resistivity - frequency section, the cross-section characteristics such as the electrical property distribution on the survey line, the undulation of the formation, the distribution of faults, and the division of electrical layers can be qualitatively understood. After static displacement correction such as single-point curve translation and spatial filtering method for the apparent resistivity curves of each survey line, the "hanging noodle" phenomenon of steep, dense, erratic, and disorderly isopotential lines can be seen to disappear from the apparent resistivity isopotential line section map.

[0071] S104. Construct an Occam inversion model related to the total longitudinal conductance parameter;

[0072] Specifically, in geophysical inversion, it is very difficult to use a simple layered model with very few parameters to describe the electrical property distribution of complex underground media, which is also inconsistent with the actual situation; the electrical properties of underground media should change continuously with depth, at least piecewise continuously. Occam inversion is a regularization inversion method. While pursuing the maximum fitting of the simulated data and the original measurement curve, it requires the model data to be the smoothest or roundest, so it is less affected by the initial model and can achieve stable convergence. Therefore, the Occam inversion model is adopted in this embodiment for time-domain data analysis.

[0073] S105. Conduct dual-frequency phase calculation and dual-frequency amplitude calculation based on the first frequency-domain data to obtain the frequency parameter set of the target area;

[0074] Specifically, when there is or is no polarization effect in the underground medium, the parameters measured by the time-frequency electromagnetic method are different. The comparison features are as follows: when there is a polarization effect in the underground medium, the real component and amplitude become higher, the imaginary component and phase become lower, and the phase even becomes negative at low frequencies. When there is a polarization effect, the calculated apparent resistivity will become larger, and these differences become more obvious at lower frequencies. Therefore, in this embodiment, dual-frequency phase calculation and dual-frequency amplitude calculation are performed on the first frequency domain data, so as to obtain accurate cross-section analysis data according to the frequency parameters.

[0075] S106. Fit the Occam inversion model, and when the fitting result meets the preset error requirement, perform polarization rate inversion based on the frequency parameter set;

[0076] Specifically, the excitation polarization information inversion method adopted in this embodiment is as follows: extract the amplitudes and phases of all frequency points in the first frequency domain data to form cross-section data, and then perform excitation polarization information inversion on the entire cross-section data to obtain the polarization rate inversion cross-section.

[0077] Specifically, in this embodiment, the Occam inversion model is first fitted before the polarization rate inversion, and the polarization rate inversion can be performed only when the fitting error of each measurement point meets the preset error requirement; among them, the calculation method of the fitting error is as follows:

[0078]

[0079] where, Re i is the fitting error of the i-th measurement point, U i obs is the observed value of the i-th measurement point, and U i is the fitting value of the Occam inversion model of the i-th measurement point.

[0080] Specifically, the preset error requirement can be less than 5%, 10%, 15%, etc., and the specific error requirement conditions can be set based on the actual exploration requirements, and this embodiment does not make specific limitations.

[0081] S107. Based on the polarization rate inversion result, delineate deep geophysical exploration anomalies in the target area.

[0082] Specifically, taking the Panxi rare earth metallogenic belt in Sichuan as an example, the dispersion degree of the apparent resistivity in the target area of this region is relatively large, the largest of which is nepheline pyroxene carbonatite, followed by light gray alkaline orthoclase, and the dispersion degrees of the remaining rocks (ores) are relatively small; while the overall dispersion degree of the apparent polarization rate is relatively small, the jump is small, and the data distribution is relatively uniform.

[0083] The classification of apparent resistivity differences is relatively complex. In this embodiment, it is classified according to the characteristics that the apparent resistivity value less than 1000 is low resistivity, the resistivity of 1000 - 5000 is medium resistivity, and greater than 5000 is high resistivity. Generally, the lithologies with low resistivity are mainly gabbro, and the average resistivity of gabbro is about 97.77Ω. The lithologies with medium resistivity are mainly rhyolite, schist, granite, and light gray alkaline orthoclase. The average resistivity of light gray alkaline orthoclase is 3617.12Ωm, the average resistivity of granite is 1001.31Ωm, the average resistivity of rhyolite is 1949.73Ωm, and the average resistivity of schist is 1293.5Ωm. The lithologies with high resistivity are mainly vein - like ore bodies, rare earth ores, marble, and carbonatite containing aegirine - augite. The average resistivity of marble is 6751.48Ωm, the average resistivity of vein - like ore bodies is 6891.81Ωm, the average resistivity of carbonatite containing aegirine - augite is 6942.22Ωm, and the average resistivity of rare earth ores is 7266.71Ωm.

[0084] Refer to Table 1, which is a statistical table of the electrical properties of different rocks (ores). According to the differences in physical property parameters, the carbonatite rare earth ore body or the tectonic fracture zone containing carbonatite rare earth ore or the physical property characteristics are high resistivity and low polarizability (average 6751.48Ωm), and the orthoclase in the surrounding rock shows medium resistivity and low polarizability (average 3617.12Ωm); granite shows low resistivity and low polarizability (average 1001.31Ωm); in this area, the rare earth ore body mainly shows a high - resistivity anomaly, which is significantly different from the surrounding rock. Because the rare earth ore body contains a small amount of sulfides (i.e., pyrite and galena), the polarizability variation range is 0.46 - 1.49. Marble is relatively pure, and there are few sulfides in its strata, and its polarizability variation range is 0.15 - 1.48. Due to the increase or decrease of sulfide content, there is an overlap in polarizability between carbonatite rare earth ore and marble.

[0085] Table 1 Statistical table of the electrical properties of different rocks (ores)

[0086]

[0087]

[0088] In the specific implementation, according to the polarizability inversion results and the electrical property characteristic parameters of different rocks (ores), the rock (ore) types of different measuring points can be identified, so as to circle the area that meets the polarizability of rare earth ore as a deep geophysical exploration anomaly body, in order to carry out the drilling project in the next step to verify the ore - bearing property of the deep anomaly body.

[0089] In summary, the ore - prospecting method of this embodiment fully combines the geological background, deep geophysical exploration anomaly bodies, and can determine whether there is a rare earth mineralization zone in the deep part of this area, providing a reference basis for subsequent exploration work.

[0090] Refer to Figure 3This is a comprehensive geological, geophysical, and drilling profile of Longjiagou P01. Using this embodiment's time-frequency electromagnetic deep rare earth exploration method, deep rare earth prospecting was conducted in the thick overburden area of Longjiagou, outside the Maoniuping rare earth mine in Panxi. Building on existing research results and field geological surveys, the introduction of time-frequency electromagnetic deep measurement methods enabled the delineation of deep anomalous targets. Deep drilling engineering verification not only identified the distribution patterns of deep, concealed rare earth mineralization zones, but also established a new prospecting method combination for hard rock rare earth deposits in the area, successfully delineating the rare earth mineralization center in the thick overburden area of Longjiagou.

[0091] It can be seen that the rare earth mineral exploration method for thick cover areas (cover thickness > 50m) provided in this embodiment is based on the physical property differences between rock masses, uses time-frequency electromagnetic geophysical prospecting methods to delineate deep anomalies, and uses the physical property parameters of various rock types summarized in this area to distinguish and identify target anomalies, thereby improving the exploration efficiency of hidden rare earth deposits in thick cover areas.

[0092] In this embodiment, preferably, the first time domain data includes: angular frequency, magnetic permeability, electric field strength and magnetic field strength;

[0093] The apparent resistivity of the target area is calculated based on the first time domain data, and the total longitudinal conductivity parameters are calculated based on the apparent resistivity, including:

[0094] Calculate the apparent resistivity using the following formula:

[0095]

[0096] Where ρ is the apparent resistivity, ω is the angular frequency, μ is the magnetic permeability, E is the electric field intensity in the first direction, and H is the magnetic field intensity in the second direction, where the first direction is perpendicular to the second direction;

[0097] Based on the apparent resistivity, the apparent resistivity curve is obtained, and the total longitudinal conductivity parameter is calculated by the following formula:

[0098]

[0099] Where S is the total longitudinal conductance parameter, ρ min is the minimum value of the apparent resistivity curve before it rises 45°, f min is ρ min The corresponding frequency.

[0100] Specifically, when using Figure 2 When the axial dipole device is used for time-frequency electromagnetic acquisition during field construction, the above E is E x , that is, the electric field intensity in the x direction, at this time H is H y , that is, the magnetic field strength in the y direction.

[0101] Specifically, in this embodiment, the total longitudinal conductance of the measurement point is defined as the sum of the conductances from the surface to a certain depth, which can be expressed as:

[0102]

[0103] In the formula, σ(L) is the conductance value and L is the depth value.

[0104] The above formula shows that within the exploration depth range, the lower the resistivity, the greater the total longitudinal conductance, and at the same time, the thicker the low-resistivity formation, the greater the total longitudinal conductance. In geological interpretation, since the resistivity of sedimentary rocks is relatively low, it has an impact on the total longitudinal conductance, and the greater the thickness, the greater the impact; for the basement, theoretically, it can be considered that the resistivity tends to infinity and the conductance is 0, which has no impact on the S value. Therefore, the total longitudinal conductance is usually used to divide the thickness of the sedimentary rock cap layer and delineate the buried depth of the basement.

[0105] In summary, after derivation in this embodiment, the following formula is obtained to calculate the total longitudinal conductance parameter:

[0106]

[0107] In this embodiment, preferably, an Occam inversion model related to the total longitudinal conductance parameter is constructed, including:

[0108] For the Occam inversion model, the following objective function is constructed:

[0109]

[0110] In the formula, λ is the Lagrange multiplier, W is the error weighting matrix, S is the total longitudinal conductance parameter, m is the Occam inversion model parameter, G(m) is the forward operator, is the roughness matrix, △ is the first-order Laplace operator, t1 is the regularization parameter corresponding to the first-order Laplace operator, △ 2 is the second-order Laplace operator, and t2 is the regularization parameter corresponding to the second-order Laplace operator.

[0111] Specifically, the free inversion result can reflect the macroscopic electrical property variation law, and the resistivity variation law in the horizontal direction is consistent with the actual formation undulation morphology. However, due to the volume effect in electrical prospecting, it cannot well meet the needs of deep interpretation in the working area. This embodiment selects the constrained inversion method.

[0112] Specifically, when establishing the inversion model, it is necessary to control the key geological layer boundaries. Therefore, this embodiment can also introduce the geological function K(x) to obtain the following new objective function:

[0113]

[0114] When the calculation results of U in two consecutive times are greater than the preset difference, it can be considered that the geological layer boundary has been reached. At this time, K(x) is assigned a value of 0; otherwise, K(x) is assigned a value of 1, making the geological layer boundary area show a steep curve.

[0115] Specifically, in the area of the non-geological layer boundary, it is necessary to make the curve of the objective function a smooth curve. Therefore, in this embodiment, the Laplace operator is also introduced to improve the smoothness of the curve in the non-geological boundary area.

[0116] In this embodiment, preferably, based on the first frequency domain data, dual-frequency phase calculation and dual-frequency amplitude calculation are performed to obtain a frequency parameter set of the target area, including:

[0117] The dual-frequency phase is calculated by the following formula:

[0118]

[0119] In the formula, DFP is the dual-frequency phase, ω1 is the fundamental wave frequency collected, ω3 is the frequency of the third harmonic of ω1, and ω1 < ω3, is the phase of the fundamental wave, is the phase of the third harmonic;

[0120] The dual-frequency amplitude is calculated by the following formula:

[0121]

[0122] In the formula, P_Amp is the dual-frequency amplitude, A L is the low-frequency amplitude value, A H is the high-frequency amplitude value;

[0123] The dual-frequency phase and dual-frequency amplitude of each frequency point are extracted to obtain the frequency parameter set.

[0124] Specifically, for the dual-frequency amplitude: the induced polarization effect has a capacitive characteristic, with a large low-frequency amplitude and a small high-frequency amplitude. Therefore, the induced polarization anomaly can be extracted by calculating the relative high- and low-frequency normalized amplitude difference in the near field area using the above formula.

[0125] Specifically, for the dual-frequency phase: the phase is also a parameter for evaluating the capacitive characteristic. A strong phase indicates a large capacitance, which means a strong polarization effect. The polarization effect can be extracted from the phase anomaly. In a specific implementation, to eliminate the influence of the induction field, similar to the dual-frequency amplitude difference processing method, trend filtering can also be performed.

[0126] In this embodiment, preferably, based on the frequency parameter set, polarizability inversion is performed, including:

[0127] The polarizability inversion is performed using the Cole-Cole model by the following formula:

[0128]

[0129] In the formula, ρ’ is the inversion result of the polarizability, ρ is the apparent resistivity, DFP is the dual-frequency phase, P_Amp is the dual-frequency amplitude, i is the imaginary unit, ω is the angular frequency, τ is the time constant, and c is the distribution parameter of the Cole-Cole model.

[0130] Specifically, the induced polarization information inversion technology first extracts the amplitudes and phases of all frequency points to form profile data. Then, the induced polarization information of the entire profile data is inverted to obtain the inversion section of the polarizability.

[0131] In this embodiment, preferably, according to the regional characteristics of the area to be explored, the target area is identified in the area to be explored, including:

[0132] Based on the regional characteristics of the area to be explored, the initial working area is identified in the area to be explored, where the regional characteristics include at least one of element characteristics, surface characteristics, and natural landscape characteristics;

[0133] Radioactive gamma measurement is carried out on the initial working area, and the target area is identified according to the measurement results.

[0134] Specifically, based on the area to be explored, the records of element combinations such as La, Ce, Y, Nb, Ba(Br), Th(U), Pb, Mo, F, etc. and the regional geological and mineral data in the database can be identified based on the 1:200,000 scale and 1:50,000 scale stream sediment measurement databases, so as to preferably select the range with more records of the above element combinations as the first working range.

[0135] Then, the images of the first working range are collected and compared with the 1:10,000 scale geological mapping. Through image recognition, the boulder data such as the particle size, roundness, and transportation distance of the boulders in the first working range are obtained, and the more preferable second working range is further identified in the first working range according to the boulder data. For example, the alkaline syenite-carbonate rock range is identified as the second working range.

[0136] For the reduced second working range, its natural landscape characteristics are obtained through image recognition, and the areas such as slope deposits, alluvial-proluvial deposits, residual deposits, and residual-slope deposits are divided in the above images according to the natural landscape characteristics. According to the preset division principle, the third working range is defined in the second working range; further, the surface of the third working range is scanned by surface gamma total measurement, and the target area is identified according to the measurement results.

[0137] In this embodiment, preferably, the exploration data of the target area is collected by the time-frequency electromagnetic method, and the exploration data is preprocessed to obtain the first time-domain data and the first frequency-domain data, including:

[0138] Perform original signal analysis, data current normalization, and data denoising on the exploration data to obtain the first time-domain data;

[0139] Perform noise analysis, interference elimination, device coefficient normalization, current and frequency response normalization, and zero-channel and bad-point deletion on the exploration data to obtain the first frequency-domain data.

[0140] Specifically, use a conversion program to convert the data collected in the field to obtain the corresponding current data file and received data file, then use a signal display program to playback and analyze the time-series signal, and finally obtain the relevant data in the time domain and frequency domain after a series of processing such as denoising and normalization.

[0141] After data collection, first analyze the signal. Through playback display, the data quality and noise level of the field records can be understood, and corresponding denoising processing can be performed. Then, a normalized database is obtained through spectral analysis, synchronous stacking, and program conversion. In addition, through spectral analysis, the spectral characteristics of the original signal and interference can be understood, and different processing methods can be adopted for different types of interference: for records with zero-bit drift or low-frequency electromagnetic interference, use linear interpolation method or correct by folding the positive and negative half-cycle signals; for electromagnetic interference with known frequencies, use filtering, and perform 50Hz filtering to remove noise while performing data format conversion and decoding; for medium-frequency electromagnetic interference and irregular pulse interference that are hopeless to improve the signal-to-noise ratio, delete them; effectively suppress high-frequency random interference through multiple signal stackings.

[0142] Furthermore, it also includes the processing of the transmitted signal, which is mainly for current normalization in later data processing. After obtaining the transmitted timing data, first playback the transmitted data, check whether the header information is correct, whether the current magnitude meets the requirements, whether the signal is stable, and whether the signals in each cycle are consistent. Then perform data stacking and FFT transformation. After obtaining the received timing data, first check the header information, mainly check whether the parameters such as MN distance, point number, and field source are correct, and then playback the timing data to check whether the data in each cycle is normal.

[0143] Specifically, after collection, the processing of time-domain data is divided into the following steps: original signal analysis, database establishment, data current normalization, data denoising processing, calculation of apparent resistivity and total longitudinal conductance. After the time-frequency electromagnetic method collection is completed, check the parameters such as AB length, excitation current, transceiver distance, MN length, and grounding resistance of the receiving electrode for the collected original data. After the check is completed, thin out the data. The principle of thinning is: based on the semi-cycle time axis displayed logarithmically, extract 20 sample points for each order of magnitude to participate in subsequent processing, so as to facilitate subsequent data calculation.

[0144] Field data not only reflects the overall electrical properties of the subsurface formation but also depends on the instrument's response characteristics, often interfering with various spectrums. Data preprocessing aims to eliminate or suppress the influence of these factors, ensuring that the signal truly reflects the subsurface electrical characteristics. Signal playback is used to assess the quality and noise level of the raw data. Signals with excessive noise or significantly poor data quality are directly deleted to prevent significant interference from affecting the data overlay. By measuring multiple channels of raw signal recordings over a single cycle, significant variations in noise levels can be observed between channels. To address this, the time series signals of each channel are selected, and signals with significant interference are removed. Spectral analysis is used to understand the spectral characteristics of the signal and noise. Based on the results of the spectral analysis, different filter parameters are selected to filter the signal and eliminate the influence of certain characteristic noise features.

[0145] A single cycle of square wave current transmitted by time-frequency electromagnetics consists of a negative DC current and a positive DC current. The received signal consists of a negative decay curve and a positive decay curve. If there is no interference, the sum of the positive and negative half-cycle signals should be zero. However, due to zero drift and low-frequency interference, this result is often not zero. Removing the interference value from the original recording corrects for zero drift and eliminates low-frequency interference. This summation of the positive and negative half-cycle signals is one of the unique noise reduction techniques of time-frequency electromagnetics.

[0146] Specifically, the main purpose of frequency domain data processing is to extract polarization information. It can be divided into the following steps:

[0147] (1) Noise analysis and suppression is to eliminate various interferences by analyzing the original signal and using processing techniques such as superposition, filtering, and smoothing; (2) Normalization of device coefficients is to eliminate the influence of device parameters and instrument systems; (3) Normalization of current and frequency response; (4) Browsing frequency domain data to delete zero channels and bad pixels.

[0148] In addition, repeated measurement points can be analyzed to evaluate the quality of the collected data and the data of repeated measurement points can be averaged.

[0149] In summary, in the embodiments of the present invention, the target area is first identified in the area to be explored through regional characteristics, thereby narrowing the prospecting scope; the target area is detected by using the time-frequency electromagnetic method, and the profile anomaly characteristics are studied and analyzed in both the time domain and the frequency domain. The Occam inversion model is obtained by calculating the apparent resistivity and total longitudinal conductivity parameters, and then the polarizability inversion is performed based on the frequency data. Finally, an effective deep anomaly geological characteristic model is established as a basis for effectively delineating deep anomalies; thereby providing a basis for better arrangement of drilling projects, reducing the number of exploration drilling wells, greatly reducing exploration costs, and at the same time shortening the prospecting time, significantly improving the exploration efficiency of hidden rare earth deposits in thick cover areas.

[0150] See Figure 4 , which is a schematic structural diagram of a deep exploration system for rare earth ores based on time-frequency electromagnetic fields provided by an embodiment of the present invention, including:

[0151] A target area identification module 201, configured to identify a target area in the area to be explored according to the area characteristics of the area to be explored;

[0152] A data preprocessing module 202, configured to collect exploration data of the target area by using the time-frequency electromagnetic method, preprocess the exploration data, and obtain first-time domain data and first-frequency domain data;

[0153] A time domain analysis module 203, configured to calculate the apparent resistivity of the target area according to the first-time domain data, and calculate the total longitudinal conductance parameter based on the apparent resistivity;

[0154] A model calculation module 204, configured to construct an Occam inversion model related to the total longitudinal conductance parameter;

[0155] A frequency calculation module 205, configured to perform dual-frequency phase calculation and dual-frequency amplitude calculation according to the first-frequency domain data, and obtain a frequency parameter set of the target area;

[0156] A polarization rate inversion module 206, configured to fit the Occam inversion model, and perform polarization rate inversion based on the frequency parameter set when the fitting result meets a preset error requirement;

[0157] A mineral identification module 207, configured to delineate a deep geophysical exploration anomaly body in the target area based on the polarization rate inversion result.

[0158] Further, the first-time domain data includes: angular frequency, magnetic permeability, electric field strength, and magnetic field strength;

[0159] Calculating the apparent resistivity of the target area according to the first-time domain data, and calculating the total longitudinal conductance parameter based on the apparent resistivity, including:

[0160] Calculating the apparent resistivity through the following formula:

[0161]

[0162] In the formula, ρ is the apparent resistivity, ω is the angular frequency, μ is the magnetic permeability, E is the electric field strength in the first direction, H is the magnetic field strength in the second direction, where the first direction is perpendicular to the second direction;

[0163] Obtaining an apparent resistivity curve based on the apparent resistivity, and calculating the total longitudinal conductance parameter through the following formula:

[0164]

[0165] Wherein, S is the total longitudinal conductance parameter, ρ min is the minimum value before the apparent resistivity curve rises by 45°, f min is the ρ min corresponding frequency.

[0166] Furthermore, an Occam inversion model related to the total longitudinal conductance parameter is constructed, including:

[0167] For the Occam inversion model, the following objective function is constructed:

[0168]

[0169] Wherein, λ is the Lagrange multiplier, W is the error weighting matrix, S is the total longitudinal conductance parameter, m is the Occam inversion model parameter, G(m) is the forward operator, is the roughness matrix, △ is the first-order Laplacian operator, t1 is the regularization parameter corresponding to the first-order Laplacian operator, △ 2 is the second-order Laplacian operator, t2 is the regularization parameter corresponding to the second-order Laplacian operator.

[0170] Furthermore, based on the first frequency domain data, double-frequency phase calculation and double-frequency amplitude calculation are performed to obtain the frequency parameter set of the target area, including:

[0171] The double-frequency phase is calculated by the following formula:

[0172]

[0173] Wherein, DFP is the double-frequency phase, ω1 is the fundamental wave frequency collected, ω3 is the frequency of the 3rd harmonic of ω1, and ω1 < ω3, is the phase of the fundamental wave, is the phase of the 3rd harmonic;

[0174] The double-frequency amplitude is calculated by the following formula:

[0175]

[0176] Wherein, P_Amp is the double-frequency amplitude, A L is the low-frequency amplitude value, A H is the high-frequency amplitude value;

[0177] The double-frequency phase and double-frequency amplitude of each frequency point are extracted to obtain the frequency parameter set.

[0178] Furthermore, based on the frequency parameter set, polarizability inversion is performed, including:

[0179] The polarizability inversion is performed by the following formula using the Cole-Cole model:

[0180]

[0181] In the formula, ρ’ is the inversion result of the polarizability, ρ is the apparent resistivity, DFP is the dual-frequency phase, P_Amp is the dual-frequency amplitude, i is the imaginary unit, ω is the angular frequency, τ is the time constant, and c is the distribution parameter of the Cole-Cole model.

[0182] Furthermore, according to the regional characteristics of the area to be explored, the target area is identified in the area to be explored, including:

[0183] Based on the regional characteristics of the area to be explored, the initial working area is identified in the area to be explored, where the regional characteristics include at least one of element characteristics, surface characteristics, and natural landscape characteristics;

[0184] Radioactive gamma measurement is carried out on the initial working area, and the target area is identified according to the measurement results.

[0185] Furthermore, the exploration data of the target area is collected by the time-frequency electromagnetic method, and the exploration data is preprocessed to obtain the first time-domain data and the first frequency-domain data, including:

[0186] The exploration data is subjected to original signal analysis, data current normalization, and data denoising processing to obtain the first time-domain data;

[0187] The exploration data is subjected to noise analysis, interference elimination, device coefficient normalization, current and frequency response normalization, and zero-channel and bad-point deletion to obtain the first frequency-domain data.

[0188] In summary, in the embodiment of the present invention, the target area is first identified in the area to be explored through regional characteristics, narrowing the prospecting range; the time-frequency electromagnetic method is used to detect the target area, and the profile anomaly characteristics are studied and analyzed from two aspects of the time domain and the frequency domain. Through the calculation of the apparent resistivity and the total longitudinal conductance parameters, the Occam inversion model is obtained, and then the polarizability inversion is carried out based on the frequency-domain data. Finally, an effective deep anomaly geological feature model is established as the basis for effectively delineating deep anomaly bodies; thus providing a basis for better arranging drilling projects, reducing the number of exploration drillings, greatly reducing the exploration cost, and at the same time being able to shorten the prospecting time and significantly improve the exploration efficiency of concealed rare earth deposits in thickly covered areas.

[0189] See Figure 5, which is a schematic diagram of a deep exploration system for rare earth ores based on time-frequency electromagnetic provided by an embodiment of the present invention. The deep exploration system for rare earth ores based on time-frequency electromagnetic in this embodiment includes: a processor 1, a memory 2, and a computer program stored in the memory 2 and executable on the processor, such as a deep exploration program for rare earth ores based on time-frequency electromagnetic. When the processor 1 executes the computer program, the steps in each of the above embodiments of the deep exploration method for rare earth ores based on time-frequency electromagnetic are implemented. Alternatively, when the processor 1 executes the computer program, the functions of each module / unit in each of the above device embodiments are implemented.

[0190] Exemplarily, the computer program can be divided into one or more modules / units. One or more modules / units are stored in the memory and executed by the processor to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the deep exploration system for rare earth ores based on time-frequency electromagnetic.

[0191] The deep exploration system for rare earth ores based on time-frequency electromagnetic may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the schematic diagram is only an example of the deep exploration system for rare earth ores based on time-frequency electromagnetic, and does not constitute a limitation on the deep exploration system for rare earth ores based on time-frequency electromagnetic. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the deep exploration system for rare earth ores based on time-frequency electromagnetic may also include input / output devices, network access devices, CAN buses, etc.

[0192] The embodiment of the present invention correspondingly provides a computer-readable storage medium, which is characterized in that the computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the deep exploration method for rare earth ores based on time-frequency electromagnetic as in Embodiment 1 of the present invention.

[0193] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the deep exploration system for rare earth ores based on time-frequency electromagnetics, and connects various parts of the entire deep exploration system for rare earth ores based on time-frequency electromagnetics through various interfaces and circuits.

[0194] The memory can be used to store computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory, and invoking the data stored in the memory, the processor realizes various functions of the deep exploration system for rare earth ores based on time-frequency electromagnetics. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.), etc. In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

[0195] Among them, when the modules / units integrated in the deep exploration system of rare earth ores based on time-frequency electromagnetics are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0196] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0197] The above are the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A method for deep exploration of rare earth mines based on time-frequency electromagnetics, characterized in that: include: identifying a target area in the area to be explored based on regional characteristics of the area to be explored; collecting exploration data of the target area using a time-frequency electromagnetic method, and preprocessing the exploration data to obtain first time domain data and first frequency domain data; calculating the apparent resistivity of the target area according to the first time domain data, and calculating a total longitudinal conductance parameter based on the apparent resistivity; constructing an Occam inversion model related to the total longitudinal conductance parameter; Performing dual-frequency phase calculation and dual-frequency amplitude calculation according to the first frequency domain data to obtain a frequency parameter set of the target area; Fitting the Occam inversion model, and performing polarizability inversion based on the frequency parameter set when the fitting result meets a preset error requirement; Based on the results of the polarizability inversion, deep geophysical anomalies are delineated in the target area.

2. The method for deep exploration of rare earth mines based on time-frequency electromagnetics according to claim 1, characterized in that: The first time domain data includes: angular frequency, magnetic permeability, electric field strength and magnetic field strength; Calculating the apparent resistivity of the target area according to the first time domain data, and calculating the total longitudinal conductivity parameter based on the apparent resistivity, includes: The apparent resistivity is calculated by the following formula: Wherein, ρ is the apparent resistivity, ω is the angular frequency, μ is the magnetic permeability, E is the electric field intensity in the first direction, and H is the magnetic field intensity in the second direction, wherein the first direction is perpendicular to the second direction; An apparent resistivity curve is obtained based on the apparent resistivity, and the total longitudinal conductivity parameter is calculated by the following formula: Where S is the total longitudinal conductance parameter, ρ min is the minimum value of the apparent resistivity curve before the 45° rise, f min is ρ min The corresponding frequency.

3. The deep exploration method for rare earth mines based on time-frequency electromagnetics according to claim 2, characterized in that: The constructing of an Occam inversion model related to the total longitudinal conductance parameter includes: For the Occam inversion model, the following objective function is constructed: Where λ is the Lagrange multiplier, W is the error weighting matrix, S is the total longitudinal conductivity parameter, m is the Occam inversion model parameter, G(m) is the forward operator, is the roughness matrix, △ is the first-order Laplace operator, t1 is the regularization parameter corresponding to the first-order Laplace operator, △ 2 is a second-order Laplace operator, and t2 is a regularization parameter corresponding to the second-order Laplace operator.

4. The deep exploration method for rare earth mines based on time-frequency electromagnetics according to claim 3, characterized in that: The performing dual-frequency phase calculation and dual-frequency amplitude calculation based on the first frequency domain data to obtain the frequency parameter set of the target area includes: The dual-frequency phase is calculated by the following formula: Where DFP is the dual-frequency phase, ω1 is the fundamental frequency of the acquisition, ω3 is the frequency of the third harmonic of ω1, and ω1<ω3, is the phase of the fundamental wave, is the phase of the third harmonic; The dual-frequency amplitude is calculated by the following formula: Where, P_Amp is the dual-frequency amplitude, A L is the low-frequency amplitude value, A H is the high frequency amplitude value; The dual-frequency phase and the dual-frequency amplitude of each frequency point are extracted to obtain the frequency parameter set.

5. The deep exploration method for rare earth mines based on time-frequency electromagnetics according to claim 4, characterized in that: The performing polarizability inversion based on the frequency parameter set includes: The polarizability inversion is performed using the Cole-Cole model using the following formula: Wherein, ρ' is the result of the polarizability inversion, ρ is the apparent resistivity, DFP is the dual-frequency phase, P_Amp is the dual-frequency amplitude, i is the imaginary unit, ω is the angular frequency, τ is the time constant, and c is the distribution parameter of the Cole-Cole model.

6. The deep exploration method for rare earth mines based on time-frequency electromagnetics according to claim 1, characterized in that: The step of identifying a target area in the area to be explored based on the area characteristics of the area to be explored includes: identifying an initial working area in the area to be explored based on regional characteristics of the area to be explored, wherein the regional characteristics include at least one of element characteristics, surface characteristics, and natural landscape characteristics; Performing radioactive gamma measurement on the initial working area, and identifying the target area based on the measurement result.

7. The method for deep exploration of rare earth mines based on time-frequency electromagnetics according to claim 1, characterized in that: The method of collecting exploration data of the target area by using a time-frequency electromagnetic method and preprocessing the exploration data to obtain first time domain data and first frequency domain data includes: Performing raw signal analysis, data current normalization, and data denoising on the exploration data to obtain the first time domain data; The exploration data is subjected to noise analysis, interference elimination, device coefficient normalization, current and frequency response normalization, and zero trace and bad pixel deletion to obtain the first frequency domain data.

8. A rare earth mine deep exploration system based on time-frequency electromagnetic, characterized in that: include: A target area identification module is used to identify a target area in the area to be explored according to the area characteristics of the area to be explored; a data preprocessing module, configured to collect exploration data of the target area using a time-frequency electromagnetic method, and preprocess the exploration data to obtain first time domain data and first frequency domain data; a time domain analysis module, configured to calculate the apparent resistivity of the target area according to the first time domain data, and calculate a total longitudinal conductance parameter based on the apparent resistivity; A model calculation module, used for constructing an Occam inversion model related to the total longitudinal conductance parameter; a frequency calculation module, configured to perform dual-frequency phase calculation and dual-frequency amplitude calculation based on the first frequency domain data to obtain a frequency parameter set of the target area; a polarizability inversion module, configured to fit the Occam inversion model and, when the fitting result meets a preset error requirement, perform polarizability inversion based on the frequency parameter set; A mineral identification module is used to delineate deep geophysical anomalies in the target area based on the results of the polarizability inversion.

9. A rare earth mine deep exploration system based on time-frequency electromagnetic, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for deep exploration of rare earth minerals based on time-frequency electromagnetics as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the deep exploration method for rare earth mines based on time-frequency electromagnetics as described in any one of claims 1 to 7.

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