A method for extracting polarizability from transient electromagnetic data based on frequency domain resistivity

Abstract

The present invention discloses a method for extracting polarizability from transient electromagnetic data based on frequency-domain resistivity. The method comprises the following steps: designing survey lines and conductor emission source locations in a test mine area, selecting observation parameters to collect field electromagnetic data, the field electromagnetic data comprising transient electromagnetic electric field data and frequency-domain electromagnetic electric field data; employing an Occam inversion algorithm to invert the measured frequency-domain electromagnetic electric field data to obtain resistivity characteristics at different measurement points, thereby obtaining resistivity distribution information; using the inverted resistivity distribution information as a constraint for inverting the transient electromagnetic electric field data, and performing transient electromagnetic polarizability inversion by analyzing the relationship between resistivity and time constant to extract polarizability. By analyzing and processing frequency-domain electromagnetic and time-domain electromagnetic data, the present invention can accurately extract resistivity and polarizability, achieve parameter separation, and overcome the coupling problem of traditional time-domain inversion.

Description

Technical Field

[0001] The present invention belongs to the technical field of geophysical exploration, and in particular relates to a method for extracting polarizability of transient electromagnetic data based on frequency domain resistivity. Background Art

[0002] Transient electromagnetic (TEM) methods, which exploit the significant electrical differences between target objects and surrounding rocks in mineral exploration, have been widely used in metal mineral exploration. Traditional TEM data interpretation methods primarily focus on resistivity inversion, often overlooking the influence of polarization on the electromagnetic response. Polaroids are ubiquitous in metal deposits, such as massive sulfide ore bodies, carbonaceous rocks, porphyry copper, pyrite, magnetite, and graphite. Due to the induced polarization (IP) effect of subsurface polaroids, measured TEM data contain not only electromagnetic responses related to resistivity but also IP responses related to information such as polarizability. The polarization properties (polarizability) of subsurface media are important indicators of mineral composition, pore structure, and saturated fluid type. The IP effect caused by polaroids can distort the TEM response, significantly increasing the difficulty of data processing and interpretation.

[0003] With the introduction of the Cole-Cole model, researchers began to try to simultaneously invert parameters such as resistivity and polarizability from electromagnetic responses. However, this method is computationally intensive and is only applicable to one-dimensional inversion. The most commonly used inversion algorithm currently uses early data that is less affected by the induced polarization effect to obtain the underground resistivity structure through three-dimensional inversion. Subsequently, the resistivity information obtained by inversion is used for three-dimensional forward simulation to obtain a pure electromagnetic response. By subtracting the pure electromagnetic response from the observed data, a pure induced polarization response can be obtained, which is further inverted to obtain information such as polarizability. However, this method requires multiple three-dimensional forward and inversions, which is computationally intensive and will cause error accumulation in the process, resulting in inaccurate resistivity results. In addition, early data measured in the field may also contain induced polarization responses, so this method is not suitable for the inversion of all underground structures.

[0004] To address the above problems, it is urgent to propose a method for extracting polarizability from transient electromagnetic data based on frequency domain resistivity. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a method for extracting polarizability from transient electromagnetic data based on frequency domain resistivity to solve the problems existing in the above prior art.

[0006] To achieve the above object, the present invention provides a method for extracting polarizability from transient electromagnetic data based on frequency domain resistivity, comprising the following steps:

[0007] Designing survey lines and conductor emission source locations in the test mine area, selecting observation parameters to collect field electromagnetic data, the field electromagnetic data including transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data;

[0008] The Occam inversion algorithm is used to invert the measured frequency domain electromagnetic electric field data to obtain the resistivity characteristics of different measuring points, and then obtain the resistivity distribution information;

[0009] The resistivity distribution information obtained by inversion is used as a constraint condition for the inversion of the transient electromagnetic method electric field data. By analyzing the relationship between resistivity and time constant, transient electromagnetic method polarizability inversion is performed to extract the polarizability.

[0010] Optionally, the selected observation parameters include at least transmission frequency, transmission current, observation frequency and measurement point spacing.

[0011] Optionally, the process of inverting the measured frequency domain electromagnetic method electric field data using the Occam inversion algorithm includes:

[0012] Based on the Occam inversion algorithm, the nonlinear electromagnetic inversion problem is transformed into an iterative linear solution process, and the model correction is obtained through iterative calculation;

[0013] In each iteration, a dual optimization objective function including data fitting term and model smoothing term is established, and an adjustable balance parameter is introduced to dynamically adjust the weight relationship between the data fitting term and the model smoothing term.

[0014] Automatically select the optimal balance parameters during the iterative optimization process, so that the inversion results can simultaneously meet the best match between simulated data and measured data and the simplest smoothness of the inversion model;

[0015] When the preset number of iterations is reached, the final inversion result is output.

[0016] Alternatively, the calculation formula of the Occam inversion algorithm is as follows:

[0017] F(m k +△m)≈F(m k )+J(m k )△m,

[0018] Among them, m k is the model parameter vector of the kth iteration, Δm is the model correction amount, J(m k ) is the Jacobian matrix.

[0019] Alternatively, the calculation formula for extracting the polarizability is as follows:

[0020]

[0021] Where Δρ is the resistivity change and ρ0 is the base resistivity.

[0022] Optionally, after extracting the polarizability, the method further includes:

[0023] Collect existing geological models in the area and compare the extracted resistivity and polarizability information with the existing geological models to ensure that the existing geological models and the extracted resistivity and polarizability data are spatially corresponding.

[0024] The present invention also provides a system for extracting polarizability from transient electromagnetic data based on frequency domain resistivity, which is used to implement the method described above and comprises: a data acquisition module, a data inversion module and a polarizability extraction module;

[0025] The data acquisition module is used to design the survey line and the conductor emission source position in the test mine area, select observation parameters to collect field electromagnetic data, and the field electromagnetic data includes transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data;

[0026] The data inversion module is used to invert the measured frequency domain electromagnetic method electric field data using the Occam inversion algorithm to obtain the resistivity characteristics of different measuring points and further obtain the resistivity distribution information;

[0027] The polarizability extraction module is used to use the resistivity distribution information obtained by inversion as the constraint condition for the inversion of the transient electromagnetic method electric field data, and to perform transient electromagnetic method polarizability inversion and extract polarizability by analyzing the relationship between resistivity and time constant.

[0028] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0029] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0030] The present invention also provides a computer program product, comprising a computer program, which implements the steps of the method when executed by a processor.

[0031] Compared with the prior art, the present invention has the following advantages and technical effects:

[0032] (1) The present invention can accurately extract resistivity and polarizability by analyzing and processing frequency-domain electromagnetic and time-domain electromagnetic data, achieve parameter separation, and break through the traditional time-domain inversion coupling problem;

[0033] (2) Using frequency domain analysis and optimized inversion algorithms, the step-by-step inversion strategy reduces the number of simultaneous inversion parameters and computational complexity, making it suitable for rapid analysis of large-scale geological data;

[0034] (3) The present invention can be applied to various underground structure types such as metal minerals, oil and gas, etc., overcoming the limitations of traditional methods under specific conditions and expanding the scope of application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0036] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of electric field data measured by the frequency domain electromagnetic method according to an embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of electric field data measured by the transient electromagnetic method according to an embodiment of the present invention;

[0039] Figure 4 This is a frequency electromagnetic resistivity cross-section diagram of an embodiment of the present invention;

[0040] Figure 5 This is a cross-sectional diagram of the transient electromagnetic method polarizability of an embodiment of the present invention. DETAILED DESCRIPTION

[0041] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0042] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0043] Example 1

[0044] Regarding the extraction of polarizability from transient electromagnetic data, the existing technology has the following problems:

[0045] (1) Influence of IP effect on transient electromagnetic response: IP effect caused by polarized bodies will lead to distortion of transient electromagnetic response, seriously increasing the difficulty of transient electromagnetic inversion and interpretation;

[0046] (2) Traditional inversion methods are inefficient and have poor accuracy: Traditional inversion methods require large amounts of computation and are unable to quickly process large-scale geological data. Furthermore, a large amount of error will accumulate during the inversion process, making it difficult to ensure the accuracy of the inversion results.

[0047] (3) Insufficient applicability of existing methods: Existing methods have poor applicability to different underground structures, resulting in the inability to obtain accurate polarizability under special geological conditions.

[0048] To address the current difficulties faced by traditional methods in processing transient electromagnetic data affected by the induced polarization effect, this embodiment proposes a method for extracting polarizability from transient electromagnetic data based on frequency-domain resistivity. Frequency-domain resistivity inversion results are less susceptible to interference from the induced polarization effect. Using this as a constraint to extract polarizability information from transient electromagnetic data can improve the efficiency and accuracy of the inversion. Specifically, the method includes the following steps:

[0049] Designing survey lines and conductor emission source locations in the test mine area, selecting observation parameters to collect field electromagnetic data, the field electromagnetic data including transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data;

[0050] The Occam inversion algorithm is used to invert the measured frequency domain electromagnetic electric field data to obtain the resistivity characteristics of different measuring points, and then obtain the resistivity distribution information;

[0051] The resistivity distribution information obtained by inversion is used as a constraint condition for the inversion of the transient electromagnetic method electric field data. By analyzing the relationship between resistivity and time constant, transient electromagnetic method polarizability inversion is performed to extract the polarizability.

[0052] As a specific implementation method, the following steps are specifically included:

[0053] Step 1: Conduct a preliminary survey of the test mine area based on the geological conditions and target area, design the survey line and the transmitter location, and select appropriate observation parameters (such as transmission frequency, transmission current, observation frequency, and measurement point spacing) for field electromagnetic data collection. Arrange the transmitter at the designed location, set up receiving electrodes at the selected measurement points, use the deployed transmitter to transmit a step current, and use the receiver to receive transient electromagnetic method (TEM) and frequency domain electromagnetic method electric field data;

[0054] Step 2: After data acquisition is completed, the Occam inversion algorithm is used to invert the measured frequency domain electromagnetic data to obtain the resistivity characteristics of different measurement points and extract the resistivity distribution information. The specific process includes:

[0055] (1) Linearization processing:

[0056] Occam inversion requires the maximum fit between the simulated data and the measured data, and also requires the model data to be as smooth as possible. Based on Taylor's theorem and the idea of ​​local linearization, the Occam algorithm converts nonlinear problems into linear problems:

[0057] F(m k +△m)≈F(m k )+J(m k )△m,

[0058] Among them, m k is the model parameter vector of the kth iteration, Δm is the model correction amount, J(m k ) is the Jacobian matrix.

[0059] The expression of each component is:

[0060]

[0061] (2) Multi-objective optimization:

[0062] The Occam inversion algorithm pursues two goals simultaneously:

[0063] Optimal data fitting: minimize the residuals between simulated data and measured data;

[0064] Smoothest model: by minimizing model roughness Avoid overfitting.

[0065] (3) Regularization solution:

[0066] Construct an objective function including the regularization parameter μ:

[0067]

[0068] Among them, W d is the data weight matrix, and μ controls the balance between goodness of fit and model smoothness.

[0069] (4) Parameter optimization:

[0070] Calculate the candidate model m by a series of μ values k+1 (μ), is selected to simultaneously satisfy: minimum data fitting error, lowest model roughness and optimal regularization parameter μ.

[0071] (5) Iteration convergence:

[0072] The above process is repeated until the fitting error meets the standard or the upper limit of the number of iterations is reached, and finally an inversion result that takes into account both data matching and geological rationality is obtained.

[0073] Step 3: Use the inverted resistivity results as constraints for the inversion of transient electromagnetic electric field data (TEM). Use an appropriate algorithm (such as the Occam algorithm) to analyze the relationship between resistivity and time constant, perform transient electromagnetic polarizability inversion, and extract the polarizability (α):

[0074]

[0075] Where Δρ is the resistivity change and ρ0 is the base resistivity.

[0076] Step 4: Collect existing geological models for the region, including information on strata, ore body distribution, and lithologic characteristics. Validate the extracted resistivity and polarizability information and compare it with existing geological models or other measurement results. Evaluate the accuracy and reliability of the model to ensure spatial alignment between the existing model and the extracted resistivity and polarizability data. Interpret the model within the geological context and analyze the geological significance of the extracted results based on information such as the regional geological structure, ore body characteristics, and stratum type.

[0077] Example 2

[0078] according to Figure 1 As shown, this embodiment provides a method for extracting polarizability from transient electromagnetic data based on frequency-domain resistivity. The Yemaquan skarn-type iron-polymetallic deposit in Qinghai Province is used as an example. The mining area is located in the Eastern Kunlun Orogenic Belt. The ore body occurs within skarns in the outer contact zone between intermediate-acidic intrusive rocks and carbonate rocks of the Qimantag Group and Di'aosu Formation. The skarns are primarily ferromagnesian, followed by calcicmagnesian and manganese skarns, and are strictly controlled by skarns and fault structures. Quaternary aeolian and diluvial deposits are widespread in the mining area. According to drill hole data and outcrop observations, the strata, from oldest to youngest, include the Ordovician Qimantag Group, the Upper Devonian Maoniushan Formation, the Upper Carboniferous Di'aosu Formation, the Lower-Middle Permian Dachaigou Formation, and the Quaternary. The main rock types include granodiorite, biotite-quartz monzodiorite, and monzogranite, with minor amounts of monzodiorite.

[0079] Based on the known data and the latest physical property measurement results, a statistical table of physical properties of the mining area is obtained, as shown in Table 1 below.

[0080] Table 1

[0081] Lithology Resistivity / Ωm Polarization rate / % limestone 719 0.9 carbonaceous limestone 48 39.2 marble 1057 0.6 granodiorite 1420 1.1 Mineralized skarn 367.6 6.7 Galena magnetite 179 18.3 Sphalerite magnetite ore 13.7 17.6 Brass magnetite 12.7 9.3 magnetite 10.3 14.9

[0082] The resistivity of monzogranite in the study area is the highest, exhibiting a distinct high-resistivity characteristic. Mineralized skarn has a medium resistivity, while carbonaceous limestone and carbonaceous limestone have the lowest resistivity. The polarizability of mineralized rock masses and carbonaceous surrounding rock is high, while the polarizability of non-carbonaceous surrounding rock and rock masses is very low. Significant differences in resistivity and polarizability exist between the various lithologies in the study area, particularly between ore bodies and surrounding rock. Transient electromagnetic and frequency domain electromagnetic surveys were conducted in the mining area, and polarizability information was extracted from representative survey lines.

[0083] Figure 2 and Figure 3 The electric field data measured by frequency domain electromagnetic method and transient electromagnetic method are shown respectively. It can be seen that frequency domain data is not easily affected by induced polarization effect, while transient electromagnetic method is greatly affected by induced polarization effect, and the late data is seriously distorted. First, the least squares method is used to invert the frequency domain data to obtain the resistivity model. Figure 4 This is the resistivity profile obtained by inverting frequency-domain data using the least squares method. The profile is divided into two main regions based on the distribution of electrical properties. The resistivity between the 960-2400m and 2400-3660m regions is significantly different, with a sudden interface between the high-resistance (red) and low-resistance (blue).

[0084] Then Figure 4 The resistivity inversion results are used as constraints, and the Bayesian algorithm is used to extract the polarizability of transient electromagnetic data. Figure 5 This is a transient electromagnetic polarizability profile. The high-resistance and low-polarizability areas at the 1200-2600m measuring point correspond to the granodiorite body, the low-resistance and high-polarizability shallow areas correspond to the carbonaceous strata, and the high-low-resistance transition area corresponds well to the known skarn belt. The entire section clearly reflects the deep spatial characteristics of each geological body, and the rock interface is consistent with the actual interface of the exploration line. The iron-polymetallic ore body is located in the high-low-resistance transition area, indicating that this method can effectively extract the transient electromagnetic polarizability information and demarcate the main deep geological bodies and the contact boundary between the rock body and the stratum.

[0085] Example 3

[0086] This embodiment also provides a system for extracting polarizability from transient electromagnetic data based on frequency domain resistivity, which is used to implement the method described above, and includes: a data acquisition module, a data inversion module, and a polarizability extraction module;

[0087] The data acquisition module is used to design the survey line and the conductor emission source position in the test mine area, select observation parameters to collect field electromagnetic data, and the field electromagnetic data includes transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data;

[0088] The data inversion module is used to invert the measured frequency domain electromagnetic method electric field data using the Occam inversion algorithm to obtain the resistivity characteristics of different measuring points and further obtain the resistivity distribution information;

[0089] The polarizability extraction module is used to use the resistivity distribution information obtained by inversion as the constraint condition for the inversion of the transient electromagnetic method electric field data, and to perform transient electromagnetic method polarizability inversion and extract polarizability by analyzing the relationship between resistivity and time constant.

[0090] Example 4

[0091] This embodiment further provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0092] Example 5

[0093] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0094] Example 6

[0095] This embodiment also provides a computer program product, including a computer program, which implements the steps of the method when executed by a processor.

[0096] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for extracting polarizability from transient electromagnetic data based on frequency domain resistivity, characterized in that: The following steps are involved: Designing survey lines and conductor emission source locations in the test mine area, selecting observation parameters to collect field electromagnetic data, the field electromagnetic data including transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data; The Occam inversion algorithm is used to invert the measured frequency domain electromagnetic electric field data to obtain the resistivity characteristics of different measuring points, and then obtain the resistivity distribution information; The resistivity distribution information obtained by inversion is used as a constraint condition for the inversion of the transient electromagnetic method electric field data. By analyzing the relationship between resistivity and time constant, transient electromagnetic method polarizability inversion is performed to extract the polarizability.

2. The method according to claim 1, characterized in that The selected observation parameters include at least the emission frequency, emission current, observation frequency and measurement point spacing.

3. The method according to claim 1, characterized in that The process of inverting the measured frequency domain electromagnetic electric field data using the Occam inversion algorithm includes: Based on the Occam inversion algorithm, the nonlinear electromagnetic inversion problem is transformed into an iterative linear solution process, and the model correction is obtained through iterative calculation; In each iteration, a dual optimization objective function including data fitting term and model smoothing term is established, and an adjustable balance parameter is introduced to dynamically adjust the weight relationship between the data fitting term and the model smoothing term. Automatically select the optimal balance parameters during the iterative optimization process, so that the inversion results can simultaneously meet the best match between simulated data and measured data and the simplest smoothness of the inversion model; When the preset number of iterations is reached, the final inversion result is output.

4. The method according to claim 3, characterized in that The calculation formula of the Occam inversion algorithm is as follows: F(m k +△m)≈F(m k )+J(m k )△m, Among them, m k is the model parameter vector of the kth iteration, Δm is the model correction amount, J(m k ) is the Jacobian matrix.

5. The method according to claim 1, wherein The calculation formula for extracting the polarizability is as follows: Where Δρ is the resistivity change and ρ0 is the base resistivity.

6. The method according to claim 1, characterized in that After extracting the polarizability, it also includes: Collect existing geological models in the area and compare the extracted resistivity and polarizability information with the existing geological models to ensure that the existing geological models and the extracted resistivity and polarizability data are spatially corresponding.

7. A system for extracting polarizability from transient electromagnetic data based on frequency domain resistivity, characterized in that: Used to implement the method according to any one of claims 1 to 6, comprising: a data acquisition module, a data inversion module and a polarizability extraction module; The data acquisition module is used to design the survey line and the conductor emission source position in the test mine area, select observation parameters to collect field electromagnetic data, and the field electromagnetic data includes transient electromagnetic method electric field data and frequency domain electromagnetic method electric field data; The data inversion module is used to invert the measured frequency domain electromagnetic method electric field data using the Occam inversion algorithm to obtain the resistivity characteristics of different measuring points and further obtain the resistivity distribution information; The polarizability extraction module is used to use the resistivity distribution information obtained by inversion as the constraint condition for the inversion of the transient electromagnetic method electric field data, and to perform transient electromagnetic method polarizability inversion and extract polarizability by analyzing the relationship between resistivity and time constant.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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