Self-adaptive multi-frequency electrical prospecting system and geological anomalous body identification method

Abstract

The invention belongs to the technical field of geological prospecting, and discloses a self-adaptive multi-frequency electrical prospecting system and a geological anomalous body identification method, which are characterized in that an initial frequency is set, an electromagnetic signal is transmitted, a reflected signal is received, characteristic parameters are extracted, whether frequency modulation is needed is judged by adjusting a transmitting frequency index coefficient, and if the parameters exceed a preset range or do not meet a standard interval, the geological anomalous body is identified. According to the method, the signal quality is monitored in real time, the optimal frequency is automatically switched, the dynamic frequency is adjusted, invalid data acquisition is reduced, the geologic body anomaly is identified through multi-parameter fusion, the accuracy of the geologic body anomaly identification is improved, and the accuracy of the geologic body anomaly identification is improved. And the misjudgment rate is reduced by the multi-parameter fusion model.

Description

Technical Field

[0001] This invention belongs to the field of geological exploration technology, specifically relating to an adaptive multi-frequency electrical resistivity tomography system and a method for identifying geological anomalies. Background Technology

[0002] Electrical exploration is a geophysical method that uses differences in the electrical properties of underground media to explore geological structures and mineral resources.

[0003] Traditional electrical resistivity tomography (EPT) systems typically suffer from the following problems: 1. During exploration, electromagnetic signals are emitted at a fixed frequency. However, different geological bodies exhibit varying electromagnetic responses at different frequencies. Fixed-frequency exploration methods are ill-suited to complex and ever-changing geological environments, resulting in low exploration accuracy and limited ability to identify geological anomalies. 2. Geological body identification relies on parameters, which can easily lead to misjudgments. For example, carbonaceous shale (high polarization) may be mistaken for an ore body, and low-resistivity aquifers may be confused with metallic mineral responses. Therefore, this invention proposes an adaptive multi-frequency EPT system and a method for identifying geological anomalies. Summary of the Invention

[0004] The purpose of this invention is to provide an adaptive multi-frequency electrical resistivity tomography system and a method for identifying geological anomalies, thereby solving the aforementioned technical problems.

[0005] The objective of this invention can be achieved through the following technical solutions: An adaptive multi-frequency electrical resistivity tomography (EPT) exploration system, the system comprising a transmitting module, a receiving module, a data processing module, a data analysis module, and a control module; The transmitting module is used to transmit electromagnetic signals of different frequencies under the control of the control module, and can adaptively adjust the transmission frequency according to the signal fed back by the receiving module. The receiving module is used to receive the electromagnetic signals reflected by the geological formation and transmit them to the data processing module; The data processing module is used to process and analyze the received signal, extract feature parameters, determine whether frequency modulation is required based on the feature parameters, and feed the processing result back to the control module. The data analysis module is used to fuse multi-frequency data, calculate the geological anomaly identification coefficient, and classify and determine the anomaly type based on the geological anomaly identification coefficient value. The control module is used to coordinate the operation of the transmitting module, receiving module, and data processing module.

[0006] As a further description of the technical solution of the present invention, the transmitting module includes a frequency synthesis unit, a power amplification unit, and a transmitting electrode. The frequency synthesis unit is used to generate signals of different frequencies, the power amplification unit is used to amplify the generated signals, and the transmitting electrode is used to transmit the amplified signals underground.

[0007] As a further description of the technical solution of the present invention, the data processing module includes a data storage unit, a data analysis unit, and a data fusion unit. The data storage unit is used to store the received signal data, the data analysis unit is used to analyze and process the data, and the data fusion unit is used to fuse signal data at different frequencies.

[0008] A method for identifying geological anomalies in an adaptive multi-frequency electrical resistivity tomography system, the method comprising the following steps: Step S1: System initialization. The control module sets the initial transmission frequency, and the transmission module transmits electromagnetic signals at the corresponding frequency. Step S2: The receiving module receives the electromagnetic signals reflected by the geological formation and transmits them to the data processing module; Step S3: The data processing module processes the received signal data, extracts signal features, and feeds back the processing results to the control module. Step S4: The control module determines whether the transmission frequency needs to be adjusted based on the feedback result. If so, it controls the transmission module to adjust the transmission frequency and repeats steps S2-S3. If not, it proceeds to step S5. Step S5: The data processing module fuses signal data at different frequencies to obtain comprehensive data; Step S6: Perform feature analysis on the comprehensive data and identify geological anomalies by combining them with the geological model.

[0009] As a further description of the technical solution of the present invention, the method for determining whether the transmission frequency needs to be adjusted in step S4 includes: At regular intervals, the electromagnetic signals reflected by the geological data received by the receiving module are extracted, including: the current signal-to-noise ratio, amplitude, phase, and frequency. The current signal-to-noise ratio, amplitude, phase, and frequency response time are compared with the corresponding standard ranges set by the system. If any parameter does not meet the corresponding standard range, the transmission frequency needs to be adjusted. If all parameters meet the corresponding standard ranges, it is further determined whether the transmission frequency needs to be adjusted.

[0010] As a further description of the technical solution of the present invention, the process of further determining whether the transmission frequency needs to be adjusted includes: Construct a calculation model for the coefficients of the adjusted transmission frequency index, with the following expression: ; In the formula, , , and These are the current signal-to-noise ratio, amplitude, phase, and frequency. , , and These are the reference values ​​for the current signal-to-noise ratio, amplitude, phase, and frequency set by the system. , , , These are the weighting coefficients corresponding to the current signal-to-noise ratio, amplitude, phase, and frequency, respectively. The transmission frequency index coefficient will be compared with the standard range set by the system. If the transmission frequency index coefficient does not meet the corresponding standard range, the transmission frequency needs to be adjusted.

[0011] As a further description of the technical solution of the present invention, the specific process of step S6 includes: Construct a model for calculating the identification coefficients of geological anomalies, with the following expression: ; In the formula, This refers to the apparent resistivity anomaly. The resistivity reference value set for the system. For the abnormal amplitude of polarizability, The reference value for polarization set for the system. Area of ​​gradient at the target volume boundary Total area of ​​the target body The standard deviation of noise. Standard deviation of the abnormal signal; Compare the geological anomaly identification coefficient with the threshold range set by the system. If > If so, the target body is determined to be strongly abnormal, and the abnormal body is a metallic ore body or a water-rich fault. like > If so, the target body is judged to be of medium anomaly, and the anomaly body is an alteration zone or a partially filled karst cave. like > If so, the target body is determined to be weakly anomaly, and the anomaly body is a thin-layer mineralized, porous aquifer. like If the target body is normal, it is determined that the target body is a uniform surrounding rock.

[0012] As a further description of the technical solution of the present invention, the process of obtaining the apparent resistivity anomaly amplitude includes: Within the test area, select a section without obvious anomalies and take the average resistivity. ; The Sobel operator was used to detect regions of abrupt changes in resistivity gradient and to locate the center value of anomalies. ; Calculate the apparent resistivity anomaly amplitude ; The process for obtaining the polarization anomaly amplitude includes: Background polarizability was obtained from measurements of surrounding rock samples or literature values. ; The anomalous polarizability is extracted by taking the average value of the delineated anomalous regions. ; Calculate the amplitude of polarization anomaly .

[0013] The beneficial effects of this invention are: This invention provides an adaptive multi-frequency electrical resistivity tomography (EPT) system and a method for identifying geological anomalies. The system sets an initial frequency, transmits electromagnetic signals, receives reflected signals, and extracts feature parameters. It determines whether frequency adjustment is needed by adjusting the transmission frequency index coefficient. If the parameters exceed a preset range or do not meet the standard interval, the frequency is adjusted. Multi-frequency data is fused, and a geological anomaly identification coefficient is calculated. Anomaly types are classified and determined based on the geological anomaly identification coefficient value. This application automatically switches to the optimal frequency by real-time monitoring of signal quality, and dynamic frequency adjustment reduces invalid data acquisition. Multi-parameter fusion is used to identify geological anomalies, and the multi-parameter fusion model reduces the false positive rate.

[0014] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a partial flowchart of the geological anomaly identification method of the adaptive multi-frequency electrical resistivity tomography system 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 As shown, an adaptive multi-frequency electrical resistivity tomography (EPT) exploration system is provided, comprising a transmitting module, a receiving module, a data processing module, a data analysis module, and a control module. The transmitting module is connected to the control module and is used to transmit electromagnetic signals of different frequencies under the control of the control module. It can also adaptively adjust the transmission frequency according to the signal fed back by the receiving module. The receiving module is connected to the data processing module and is used to receive the electromagnetic signals reflected by the geological formation and transmit them to the data processing module. The data processing module is connected to the control module and is used to process and analyze the received signal, extract feature parameters, determine whether frequency modulation is needed based on the feature parameters, and feed the processing result back to the control module. The data analysis module is used to fuse multi-frequency data, calculate the geological anomaly identification coefficient, and classify and determine the anomaly type based on the geological anomaly identification coefficient value. The control module is used to coordinate the operation of the transmitting module, receiving module, and data processing module.

[0019] Through the above technical solution, this invention provides an adaptive multi-frequency electrical resistivity tomography (EPT) system and a method for identifying geological anomalies. An initial frequency (e.g., 10Hz) is set, electromagnetic signals are transmitted, reflected signals are received, and feature parameters (signal-to-noise ratio, amplitude, phase) are extracted. The system determines whether frequency modulation is needed by adjusting the transmission frequency index coefficient F. If the parameter (e.g., signal-to-noise ratio) exceeds a preset range or F does not meet the standard range, the frequency is adjusted. Multi-frequency data is fused, and the geological anomaly identification coefficient G is calculated. The anomaly type (strong / medium / weak anomaly) is determined based on the G value. This application automatically switches to the optimal frequency by real-time monitoring of signal quality (signal-to-noise ratio, phase stability, etc.). Dynamic frequency adjustment reduces invalid data acquisition. Geological anomaly identification is achieved through multi-parameter fusion, and the multi-parameter fusion model reduces the misjudgment rate.

[0020] As a further description of the technical solution of the present invention, the transmitting module includes a frequency synthesis unit, a power amplification unit, and a transmitting electrode. The frequency synthesis unit is used to generate signals of different frequencies, the power amplification unit is used to amplify the generated signals, and the transmitting electrode is used to transmit the amplified signals underground.

[0021] Through the above technical solution, this embodiment provides a detailed composition and working principle of the transmitting module. The core components are: a frequency synthesis unit, which generates high-precision, tunable multi-frequency electromagnetic signals (such as 0.1Hz–10kHz) to support frequency sweep or fixed-point transmission; a power amplification unit, which amplifies the weak synthesized signal to the kilowatt level (such as 100V–1kV) to ensure signal penetration depth; and a transmitting electrode, which injects the amplified current signal into the ground, optimizes signal coupling using an AB-MN device or dipole arrangement, and dynamically switches the output of the frequency synthesis unit according to feedback from the control module (such as insufficient signal-to-noise ratio).

[0022] As a further description of the technical solution of the present invention, the data processing module includes a data storage unit, a data analysis unit, and a data fusion unit. The data storage unit is used to store the received signal data, the data analysis unit is used to analyze and process the data, and the data fusion unit is used to fuse signal data at different frequencies.

[0023] Through the above technical solution, this embodiment provides a detailed description of the composition and working principle of the data processing module. The core components are: a data storage unit, which stores multi-band raw signals (including timestamps and frequency tags) in real time, supporting TB-level data management; and a data analysis unit. Extract signal features such as signal-to-noise ratio, amplitude, phase, and time delay, and calculate apparent resistivity and polarizability; The data fusion unit transforms different types of data into a unified standard for computation.

[0024] A method for identifying geological anomalies in an adaptive multi-frequency electrical resistivity tomography system, the method comprising the following steps: Step S1: System initialization. The control module sets the initial transmission frequency, and the transmission module transmits electromagnetic signals at the corresponding frequency. Step S2: The receiving module receives the electromagnetic signals reflected by the geological formation and transmits them to the data processing module; Step S3: The data processing module processes the received signal data, extracts signal features, and feeds back the processing results to the control module. Step S4: The control module determines whether the transmission frequency needs to be adjusted based on the feedback result. If so, it controls the transmission module to adjust the transmission frequency and repeats steps S2-S3. If not, it proceeds to step S5. Step S5: The data processing module fuses signal data at different frequencies to obtain comprehensive data; Step S6: Perform feature analysis on the comprehensive data and identify geological anomalies by combining them with the geological model.

[0025] Through the above technical solution, this embodiment provides a geological anomaly identification method based on an adaptive multi-frequency electrical resistivity tomography (EPT) system. It achieves efficient and accurate anomaly detection through dynamic adjustment of the transmission frequency, multi-frequency data fusion, and intelligent analysis. First, the control module sets the initial transmission frequency (e.g., 10Hz), and the transmitting module begins transmitting electromagnetic signals. Then, the receiving module collects the reflected signals and extracts key parameters: signal-to-noise ratio (SNR) to evaluate signal quality; amplitude (A) and phase (φ) to reflect differences in the electrical properties of the subsurface medium; and frequency response to analyze signal attenuation characteristics at different frequency bands. Then, dynamic frequency adjustment is performed; if any parameter (SNR, amplitude, phase) is not adjusted, the anomaly detection method will be implemented. If a parameter exceeds a preset threshold, frequency adjustment is immediately triggered. For example, if the signal-to-noise ratio is low, the frequency is reduced (to reduce electromagnetic coupling noise); if the phase is unstable, interference frequency bands are avoided (such as 50Hz harmonics); if the amplitude attenuation is large, the power is increased or the device type is switched. If no parameter exceeds the threshold, the frequency adjustment requirement is quantified by adjusting the transmission frequency index coefficient (F). Finally, the geological anomaly identification coefficient is calculated, and geological anomalies are identified based on the coefficient. Through closed-loop adaptive control, the signal quality is fed back in real time to dynamically adjust the frequency to optimize data acquisition efficiency, reduce invalid exploration time, and significantly reduce the false anomaly misjudgment rate by combining parameters such as resistivity, polarizability, and boundary morphology.

[0026] As a further description of the technical solution of the present invention, the method for determining whether the transmission frequency needs to be adjusted in step S4 includes: At regular intervals, the electromagnetic signals reflected by the geological data received by the receiving module are extracted, including: the current signal-to-noise ratio, amplitude, phase, and frequency. The current signal-to-noise ratio, amplitude, phase, and frequency response time are compared with the corresponding standard ranges set by the system. If any parameter does not meet the corresponding standard range, the transmission frequency needs to be adjusted. If all parameters meet the corresponding standard ranges, it is further determined whether the transmission frequency needs to be adjusted.

[0027] As a further description of the technical solution of the present invention, the process of further determining whether the transmission frequency needs to be adjusted includes: Construct a calculation model for the coefficients of the adjusted transmission frequency index, with the following expression: ; In the formula, , , and These are the current signal-to-noise ratio, amplitude, phase, and frequency. , , and These are the reference values ​​for the current signal-to-noise ratio, amplitude, phase, and frequency set by the system. , , , These are the weighting coefficients corresponding to the current signal-to-noise ratio, amplitude, phase, and frequency, respectively. The transmission frequency index coefficient will be compared with the standard range set by the system. If the transmission frequency index coefficient does not meet the corresponding standard range, the transmission frequency needs to be adjusted.

[0028] Through the above technical solution, this embodiment provides an intelligent decision-making module for frequency adjustment in an adaptive multi-frequency electrical resistivity tomography (EPT) exploration system. By real-time monitoring and quantitative evaluation of multiple parameters, it achieves dynamic optimization of the transmission frequency. The following signal characteristics are periodically collected: signal-to-noise ratio (SNR), reflecting the signal's anti-interference capability; amplitude, characterizing signal strength attenuation; phase, revealing the electromagnetic properties of the medium; and frequency response time, evaluating signal penetration efficiency. All parameters are compared with standards; if any parameter exceeds the limit, frequency adjustment is immediately triggered without further calculation, making it suitable for sudden strong interference. If no parameter exceeds the limit, frequency adjustment is achieved using a formula... Calculate the overall transmission frequency index coefficient, where, The degree of signal-to-noise ratio degradation , Signal amplitude and phase distortion Frequency offset compensation compares the adjusted transmission frequency index coefficient with the standard range set by the system. If the entire transmission frequency index coefficient does not meet the corresponding standard range, the transmission frequency needs to be adjusted. This is suitable for adaptive weight adjustment in the exploration stage. Through the dual protection of threshold and model, it avoids system oscillation caused by over-adjustment.

[0029] As a further description of the technical solution of the present invention, the specific process of step S6 includes: Construct a model for calculating the identification coefficients of geological anomalies, with the following expression: ; In the formula, This refers to the apparent resistivity anomaly. The resistivity reference value set for the system. For the abnormal amplitude of polarizability, The reference value for polarization set for the system. Area of ​​gradient at the target volume boundary Total area of ​​the target body The standard deviation of noise. Standard deviation of the abnormal signal; Compare the geological anomaly identification coefficient with the threshold range set by the system. If > If so, the target body is determined to be strongly abnormal, and the abnormal body is a metallic ore body or a water-rich fault. like > If so, the target body is judged to be of medium anomaly, and the anomaly body is an alteration zone or a partially filled karst cave. like > If so, the target body is determined to be weakly anomaly, and the anomaly body is a thin-layer mineralized, porous aquifer. like If the target body is normal, it is determined that the target body is a uniform surrounding rock.

[0030] As a further description of the technical solution of the present invention, the process of obtaining the apparent resistivity anomaly amplitude includes: Select sections within the measurement area that show no obvious anomalies (at least 10×10 measurement points) and take the average resistivity. ; The Sobel operator was used to detect regions of abrupt changes in resistivity gradient and to locate the center value of anomalies. ; Calculate the apparent resistivity anomaly amplitude ; The process for obtaining the polarization anomaly amplitude includes: Background polarizability was obtained from measurements of surrounding rock samples or literature values. ; The anomalous polarizability is extracted by taking the average value of the delineated anomalous regions. ; Calculate the amplitude of polarization anomaly .

[0031] Through the above technical solution, this embodiment uses a multi-parameter fusion-based geological anomaly classification and identification model. By quantitatively calculating the anomaly identification coefficient (G value), it achieves accurate classification of geological targets, and through the formula... Calculate the identification coefficient of geological anomalies, where, Indicating differences in physical properties, Indicates the sharpness of the boundary. To indicate data reliability and suppress false anomalies in low-quality data, the identification coefficient of geological anomalies is compared with a threshold range set by the system. > If so, the target body is determined to be strongly abnormal, and the abnormal body is a metallic ore body or a water-rich fault. like > If so, the target body is judged to be of medium anomaly, and the anomaly body is an alteration zone or a partially filled karst cave. like > If so, the target body is determined to be weakly anomaly, and the anomaly body is a thin-layer mineralized, porous aquifer. like If the target body is normal, it is determined that the target body is a uniform surrounding rock.

[0032] It should be noted that the formulas in this application are all dimensionless and numerical calculations. The formulas are obtained by software simulation based on a large amount of data and are the closest to the real situation. The thresholds, standard values ​​and weight coefficients involved in this application are all empirical values ​​and are selected by those skilled in the art according to the actual situation.

[0033] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in the claims, they should all fall within the protection scope of the present invention.

Claims

1. An adaptive multi-frequency electrical resistivity tomography (EPT) exploration system, characterized in that, The system includes a transmitting module, a receiving module, a data processing module, a data analysis module, and a control module; The transmitting module is used to transmit electromagnetic signals of different frequencies under the control of the control module, and can adaptively adjust the transmission frequency according to the signal fed back by the receiving module. The receiving module is used to receive the electromagnetic signals reflected by the geological formation and transmit them to the data processing module; The data processing module is used to process and analyze the received signal, extract feature parameters, determine whether frequency modulation is required based on the feature parameters, and feed the processing result back to the control module. The data analysis module is used to fuse multi-frequency data, calculate the geological anomaly identification coefficient, and classify and determine the anomaly type based on the geological anomaly identification coefficient value. The control module is used to coordinate the operation of the transmitting module, receiving module, and data processing module.

2. The adaptive multi-frequency electrical resistivity tomography system according to claim 1, characterized in that, The transmitting module includes a frequency synthesis unit, a power amplification unit, and a transmitting electrode. The frequency synthesis unit is used to generate signals of different frequencies, the power amplification unit is used to amplify the generated signals, and the transmitting electrode is used to transmit the amplified signals underground.

3. The adaptive multi-frequency electrical resistivity tomography system according to claim 1, characterized in that, The data processing module includes a data storage unit, a data analysis unit, and a data fusion unit. The data storage unit is used to store the received signal data, the data analysis unit is used to analyze and process the data, and the data fusion unit is used to fuse signal data at different frequencies.

4. A method for identifying geological anomalies based on the adaptive multi-frequency electrical resistivity tomography system according to any one of claims 1-3, characterized in that, The method includes the following steps: Step S1: System initialization. The control module sets the initial transmission frequency, and the transmission module transmits electromagnetic signals at the corresponding frequency. Step S2: The receiving module receives the electromagnetic signals reflected by the geological formation and transmits them to the data processing module; Step S3: The data processing module processes the received signal data, extracts signal features, and feeds back the processing results to the control module. Step S4: The control module determines whether the transmission frequency needs to be adjusted based on the feedback result. If so, it controls the transmission module to adjust the transmission frequency and repeats steps S2-S3. If not, it proceeds to step S5. Step S5: The data processing module fuses signal data at different frequencies to obtain comprehensive data; Step S6: Perform feature analysis on the comprehensive data and identify geological anomalies by combining them with the geological model.

5. The adaptive multi-frequency electrical resistivity tomography system and geological anomaly identification method according to claim 4, characterized in that, The method for determining whether the transmission frequency needs to be adjusted in step S4 includes: At regular intervals, the electromagnetic signals reflected by the geological data received by the receiving module are extracted, including: the current signal-to-noise ratio, amplitude, phase, and frequency. The current signal-to-noise ratio, amplitude, phase, and frequency response time are compared with the corresponding standard ranges set by the system. If any parameter does not meet the corresponding standard range, the transmission frequency needs to be adjusted. If all parameters meet the corresponding standard ranges, it is further determined whether the transmission frequency needs to be adjusted.

6. The adaptive multi-frequency electrical resistivity tomography system and geological anomaly identification method according to claim 5, characterized in that, The further process of determining whether the transmission frequency needs to be adjusted includes: Construct a calculation model for the coefficients of the adjusted transmission frequency index, with the following expression: ； In the formula, , , and These are the current signal-to-noise ratio, amplitude, phase, and frequency. , , and These are the reference values ​​for the current signal-to-noise ratio, amplitude, phase, and frequency set by the system. , , , These are the weighting coefficients corresponding to the current signal-to-noise ratio, amplitude, phase, and frequency, respectively. The transmission frequency index coefficient will be compared with the standard range set by the system. If the transmission frequency index coefficient does not meet the corresponding standard range, the transmission frequency needs to be adjusted.

7. The adaptive multi-frequency electrical resistivity tomography system and geological anomaly identification method according to claim 5, characterized in that, The specific process of step S6 includes: Construct a model for calculating the identification coefficients of geological anomalies, with the following expression: ； In the formula, This refers to the apparent resistivity anomaly. The resistivity reference value set for the system. For the abnormal amplitude of polarizability, The reference value for polarization set for the system. Area of ​​gradient at the target volume boundary Total area of ​​the target body The standard deviation of noise. Standard deviation of the abnormal signal; Compare the geological anomaly identification coefficient with the threshold range set by the system. If > If so, the target body is determined to be strongly abnormal, and the abnormal body is a metallic ore body or a water-rich fault. like > If so, the target body is judged to be of medium anomaly, and the anomaly body is an alteration zone or a partially filled karst cave. like > If so, the target body is determined to be weakly anomaly, and the anomaly body is a thin-layer mineralized, porous aquifer. like If the target body is normal, it is determined that the target body is a uniform surrounding rock.

8. The adaptive multi-frequency electrical resistivity tomography system and geological anomaly identification method according to claim 7, characterized in that, The process for obtaining the apparent resistivity anomaly amplitude includes: Within the test area, select a section without obvious anomalies and take the average resistivity. ; The Sobel operator was used to detect regions of abrupt changes in resistivity gradient and to locate the center value of anomalies. ; Calculate the apparent resistivity anomaly amplitude ; The process for obtaining the polarization anomaly amplitude includes: Background polarizability was obtained from measurements of surrounding rock samples or literature values. ; The anomalous polarizability is extracted by taking the average value of the delineated anomalous regions. ; Calculate the amplitude of polarization anomaly .

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