Controllable source electromagnetic multi-parameter rapid inversion method, system and device for mineral exploration and storage medium

Abstract

The present application relates to the technical field of exploration, disclose a kind of mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method, system, equipment and storage medium, import field measurement data, calculate each parameter apparent resistivity, process the data of noise existence;Each inversion parameter is set, start the quick inversion of Okham based on analytical sensitivity;Assess the degree of data fitting, export multi-parameter inversion result, and carry out geological interpretation of mining area;The present application realizes the multi-parameter inversion of controllable source electromagnetic data considering the effect of induced polarization, provides more abundant geophysical basis for geological interpretation, greatly improves the accuracy and efficiency of sensitivity solution, enhances the practicality of multi-parameter inversion.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of exploration, in particular to a controlled source electromagnetic multi-parameter rapid inversion method, system, device and storage medium for mineral exploration. BACKGROUND

[0002] As a key means of mineral resource exploration, the frequency domain controlled source electromagnetic (CSEM) method has many advantages, such as being able to increase signal strength by increasing transmission power or field source size, being able to flexibly adjust device form according to the detection target, having high resolution, large exploration depth, wide observation range, high work efficiency and strong adaptability, and being widely used in resource investigation of oil and gas, geothermal, shale gas, metal mines and other resources, and playing an indispensable role in deep resource exploration; in the CSEM technology, the inversion method and technology are the core link connecting the geophysical data and the geological reality, and the one-dimensional inversion method with small calculation amount and fast speed is the key to the practical inversion software.

[0003] However, with the continuous improvement of fine geological exploration demand and the emergence of massive observation data, the existing technology exposes obvious defects and deficiencies:

[0004] Ignoring the influence of the induced polarization parameter reduces the accuracy of data interpretation: the frequency domain controlled source electromagnetic data collected in the actual complex geological background will be affected by the comprehensive action of multiple electrical parameters underground, at present, the field data inversion and interpretation mostly only consider the resistivity parameter, ignoring the influence of the polarization rate parameter, which greatly reduces the accuracy of inversion and interpretation, with the increasing complexity of exploration environment, it is urgent to develop a forward and inversion method and technology system considering the induced polarization effect and electromagnetic induction;

[0005] The sensitivity solving technology based on the perturbation method has limitations: the perturbation method is currently used to approximate the sensitivity matrix, which calculates the data response change to approximately solve the sensitivity matrix by applying a small perturbation to the model parameters, although parallel computing can improve efficiency, when multiple induced polarization parameters are introduced, it is still difficult to realize real-time imaging of field data, and with the increase of parameter quantity, field data quantity and the refinement of underground model parameter division, the parallel perturbation method has very high requirements for computer hardware, which seriously limits the further improvement of inversion speed. SUMMARY

[0006] The purpose of the present application is to solve the above problems, and a controlled source electromagnetic multi-parameter rapid inversion method and system for mineral exploration are designed to solve the problems of low inversion and interpretation accuracy and limited inversion speed in the prior art, considering the induced polarization effect and electromagnetic induction, realizing rapid and accurate inversion of multiple parameters, and providing more reliable geophysical basis for mineral exploration.

[0007] The first aspect of the application provides a controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration, which comprises the following steps:

[0008] Import field measurement data, calculate the apparent resistivity of each parameter, and process the data with noise;

[0009] Set each inversion parameter, including at least multi-thread parallel parameter, weight coefficient, initial model, and correlation constraint;

[0010] Start the Ocham rapid inversion based on analytical sensitivity;

[0011] Evaluate the degree of data fitting, export the multi-parameter inversion result, and carry out geological interpretation of the mining area.

[0012] Further, in the above controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration, the import field measurement data, calculation of the apparent resistivity of each parameter, and processing of the data with noise comprise:

[0013] Read the measurement data from the field measurement equipment, and calculate the apparent resistivity of each parameter using the measured electric field and magnetic field component data;

[0014] Process the data with noise, adopt the median filtering algorithm, scan the data with a certain window size, and take the median value of the data in the window as the new data value of the point to remove outliers and noise;

[0015] Use the Hanning window filtering method to filter the apparent resistivity data of different measurement points at the same frequency point.

[0016] Further, in the above controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration, setting each inversion parameter comprises:

[0017] Construct an initial geological model containing at least resistivity and polarization rate parameters, divide the underground into several horizontal strata according to the data frequency range and the detection depth requirement, determine the initial parameter value of each stratum, select the correlation constraint matrix, and determine the value of the correlation adjustment coefficient.

[0018] Further, in the above controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration, the start of the Ocham rapid inversion based on analytical sensitivity comprises:

[0019] According to the set initial model, calculate the theoretical electromagnetic response data using the fast Hankel transform algorithm;

[0020] Use the analytical sensitivity solving method to calculate the sensitivity of the underground medium and obtain the multi-parameter analytical sensitivity matrix.

[0021] The Okham inversion algorithm is used to perform iterative calculation based on the constructed multi-parameter inversion objective function, in each iteration, according to the iterative update of the model parameters, the updated model parameters are calculated by using the current sensitivity matrix, observation data, forward prediction data and each constraint term, and the optimal solution is obtained through continuous iteration.

[0022] Further, in the above-mentioned mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method, the smooth constraint, reference model constraint and correlation constraint are used to optimize the objective function, and the Okham inversion algorithm is used to solve the optimal solution of the inverse problem, and the multi-parameter inversion objective function is constructed.

[0023] Further, in the above-mentioned mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method, the data fitting degree is evaluated, the multi-parameter inversion result is derived, and the mine area geological interpretation is carried out, including:

[0024] The model parameters obtained by inversion are substituted into the forward calculation again to obtain the theoretical electromagnetic response data of the inversion model;

[0025] The data is compared with the original observation data, and the data fitting difference is calculated, when the data fitting degree meets the pre-set threshold, the multi-parameter result obtained by inversion is derived;

[0026] Based on the derived multi-parameter inversion result, the mine area geological interpretation work is carried out.

[0027] Further, in the above-mentioned mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method, the multi-parameter result at least includes the resistivity and polarization rate parameter distribution of each stratum.

[0028] The second aspect of the present application provides a mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion system, which comprises:

[0029] The calculation module is used for importing field measurement data, calculating each parameter apparent resistivity, and processing data with noise;

[0030] The setting module is used for setting each inversion parameter, at least including multi-thread parallel parameter, weight coefficient, initial model and correlation constraint;

[0031] The inversion module is used for starting the Okham fast inversion based on analytical sensitivity;

[0032] The derivation module is used for evaluating the data fitting degree, deriving the multi-parameter inversion result, and carrying out the mine area geological interpretation.

[0033] The third aspect of the present application provides a mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device, the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device comprising a memory and at least one processor, the memory storing instructions; the at least one processor calling the instructions in the memory to enable the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device to perform the steps of the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method according to any one of the above.

[0034] The fourth aspect of the present application provides a computer readable storage medium, the computer readable storage medium storing instructions, the instructions being executed by a processor to implement the steps of the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method according to any one of the above.

[0035] In the technical solution provided by the present application, field measurement data is imported, each parameter apparent resistivity is calculated, and data with noise is processed; each inversion parameter is set, and the Ocham fast inversion based on analytical sensitivity is started; the data fitting degree is evaluated, the multi-parameter inversion result is exported, and the mine area geological interpretation is carried out; the present application aims at the problems that ignoring the effect of the induced polarization will increase the uncertainty of the frequency domain controllable source electromagnetic data inversion interpretation, and the multi-solution of the multi-parameter inversion is enhanced, the multi-parameter inversion objective function is constructed by referring to the model constraint and the correlation constraint, the multi-parameter inversion of the controllable source electromagnetic data considering the effect of the induced polarization is realized, and more abundant geophysical basis is provided for the geological interpretation; after considering the effect of the induced polarization, the number of inversion model parameters increases, the traditional inversion technology based on the perturbation method is greatly affected by the number of unknowns, and the inversion technology and system based on the analytical sensitivity greatly improve the accuracy and efficiency of the sensitivity solution and enhance the practicability of the multi-parameter inversion. BRIEF DESCRIPTION OF DRAWINGS

[0036] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments with reference made to the accompanying drawings. The drawings are for purposes of illustration only and are not considered as limiting the application.

[0037] Figure 1 The flowchart of the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method provided by the embodiments of the present application;

[0038] Figure 2 The model inversion result schematic diagram provided by the embodiments of the present application, wherein Figure 2 (a) is a fitting degree schematic diagram, Figure 2 (b) is an electrical conductivity inversion result schematic diagram, Figure 2 (c) is a charge rate inversion result schematic diagram, Figure 2 (d) is a frequency coefficient inversion result schematic diagram.

[0039] Figure 3 A structure schematic diagram of the controllable source electromagnetic multi-parameter rapid inversion system for mineral exploration provided by the embodiment of the present application is shown in the figure.

[0040] Figure 4 A structure schematic diagram of the controllable source electromagnetic multi-parameter rapid inversion system for mineral exploration provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0041] The terms "first", "second", "third", "fourth" and the like in the description and claims of the present application and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of these terms herein is to be construed to cover the embodiments of the application, unless otherwise indicated herein or understood by practice thereof. Furthermore, the terms "comprise", "comprising", "include", "including", and the like, as used herein, are specifically intended to be construed as open-ended terms (i.e., the terms do not exclude additional, unrecited elements). By way of example, the term "including" as used herein is specifically intended to be construed as meaning "including, but not limited to".

[0042] For the convenience of understanding, the specific flow of the embodiment of the present application is described below, please refer to Figure 1 The flowchart of the controllable source electromagnetic multi-parameter rapid inversion system for mineral exploration provided by the embodiment of the present application, the method specifically includes the following steps:

[0043] Step 101, importing field measurement data, calculating each parameter apparent resistivity, processing data with noise;

[0044] In this embodiment, the measurement data is read from the field measurement equipment, the apparent resistivity of each parameter is calculated by using the measured electric field and magnetic field component data, the data with noise is processed, the median filtering algorithm is adopted to scan the data with a certain window size, the median value of the data in the window is taken as the new data value of the point, and the outlier noise is removed; the Hann window filtering method is used to filter the apparent resistivity data of different measurement points at the same frequency point.

[0045] Step 102, setting each inversion parameter, at least including multi-thread parallel parameter, weight coefficient, initial model, correlation constraint;

[0046] In this embodiment, the multi-thread parallel parameter setting: determine the number of threads participating in parallel computing, and reasonably allocate according to the core number and performance of the computer hardware to fully utilize the computing resources. Set the data sharing and synchronization mechanism between threads to ensure data consistency and calculation accuracy; weight coefficient setting: according to the importance of model smoothness, reference model and correlation constraint, determine the value of weight coefficient, which can be set preliminarily through multiple tests or according to experience value, and then adjusted and optimized according to the inversion effect; initial model setting: according to the existing geological data, prior information or previous exploration results in the survey area, an initial geological model containing resistivity, polarization rate and other parameters is constructed. According to the data frequency range and the detection depth requirement, the underground is divided into several horizontal strata, and the initial parameter value of each stratum is determined; correlation constraint setting: according to the geological conditions and research purposes, select the appropriate correlation constraint matrix P, and determine the value of correlation adjustment coefficient. If the spatial variation of induced polarization parameters such as polarization rate is expected to be similar to that of conductivity (high conductivity and high polarization), set the correlation adjustment coefficient = 1; if the opposite variation (low conductivity and high polarization) is expected, set the correlation adjustment coefficient = -1.

[0047] Step 103, start the rapid inversion of Ocham based on analytical sensitivity;

[0048] In this embodiment, according to the set initial model, the theoretical electromagnetic response data is calculated by using the fast Hankel transform algorithm; the sensitivity of the underground medium is calculated by using the analytical sensitivity solving method, and the multi-parameter analytical sensitivity matrix is obtained; the Ocham inversion algorithm is used to perform iterative calculation based on the constructed multi-parameter inversion objective function. In each iteration, according to the iterative update of the model parameters, the current sensitivity matrix, observation data, forward prediction data and each constraint term are used to calculate the updated model parameters, and the optimal solution is obtained through continuous iteration.

[0049] In this embodiment, the smoothness constraint, reference model constraint and correlation constraint are used to optimize the objective function, and the Ocham inversion algorithm is used to solve the optimal solution of the inverse problem to construct the multi-parameter inversion objective function.

[0050] In this embodiment, according to the initial model set, the CSEM forward response integral formula of one-dimensional layered stratum is solved by using the fast Hankel transform algorithm to obtain the theoretical electromagnetic response data of the entire exploration area under the current model; the theoretical electromagnetic response data represents the predicted data under the given model and exploration conditions, and is the basis for comparison of the inversion termination condition; the forward calculation can provide an important tool for subsequent inversion calculation; based on the complex resistivity model considering the induced polarization effect mentioned above, the analytical sensitivity is used to calculate the sensitivity of the underground medium; starting from the integral formula, the partial derivative formula of the complex resistivity with respect to each parameter is used, combined with the partial derivative formula of the model variable with respect to the electric field and magnetic field components, and the expression of the electromagnetic field components generated by the horizontal electric dipole in the cylindrical coordinate system, the partial derivative of the transfer function with respect to the model variable is solved through a series of derivation and calculation; then the Hankel numerical integral is used to obtain the partial derivative of the kernel function with respect to the model parameter; through the step-by-step back substitution, the partial derivative of the electromagnetic field with respect to the underground conductivity and other parameters is finally calculated, that is, the analytical sensitivity of the cole-cole model complex resistivity is obtained; then according to the derivative rule of the composite function, the analytical sensitivity of different underground parameters can be obtained; these analytical sensitivities are arranged and combined according to certain rules to form a multi-parameter sensitivity matrix; the matrix reflects the influence degree of the change of each underground parameter on the observed electromagnetic data on the ground, and provides a key basis for the model parameter update in the subsequent Ocham inversion algorithm; based on the multi-parameter inversion objective function constructed including the smoothing constraint, the reference model constraint and the correlation constraint, the Ocham inversion algorithm is started for iterative calculation; in each iteration process, according to the iterative update formula of the model parameter, the multi-parameter sensitivity matrix calculated at present, the actual observed data, the predicted data obtained by forward calculation, and the model smoothness constraint term, the reference model constraint term and the correlation constraint term are fully utilized; specifically, these data and constraint terms are substituted into the iterative update formula to calculate the updated model parameter value, and then the latest predicted data is calculated through forward calculation to determine whether it meets the iteration termination condition; by continuously repeating this iteration process, the model parameters gradually approach the optimal solution; during the iteration process, the Ocham inversion algorithm automatically adjusts the update direction and step of the model parameters according to the change of the objective function, so as to ensure that the fitting degree of the inversion result and the actual observed data is as high as possible under the premise of meeting various constraint conditions.

[0051] Step 104, evaluating the data fitting degree, deriving the multi-parameter inversion result, and developing the geological interpretation of the mining area.

[0052] In this embodiment, in each inversion iteration, the model parameters obtained by inversion are substituted into the forward calculation again to obtain the theoretical electromagnetic response data of the inversion model; the data are compared with the original observation data, the data fitting difference is calculated, and when the data fitting degree meets the pre-set threshold, the multi-parameter results obtained by inversion are derived; based on the derived multi-parameter inversion results, the mine area geological interpretation work is carried out.

[0053] In this embodiment, the multi-parameter results at least include the resistivity and polarizability parameter distribution of each stratum.

[0054] In this embodiment, the model parameters obtained through multiple iterations of inversion are again substituted into the forward algorithm to recompute the theoretical electromagnetic response data of the inversion model; this theoretical electromagnetic response data represents the electromagnetic signals generated by the subsurface geological bodies corresponding to the current inversion model; then, the theoretical electromagnetic response data is compared in detail with the original observation data, and the degree of data fitting is evaluated by calculating the fitting difference between the two; the commonly used fitting difference calculation indicators include mean square error, etc.; when calculating the mean square error, the square of the difference between the theoretical electromagnetic response data and the observation data at each data point is first calculated, then the sum of the square differences of all data points is calculated, and finally the total number of data points is divided to obtain the mean square error value; the calculated mean square error value is compared with the pre-set threshold to determine whether the degree of data fitting meets the requirements; if the mean square error value is less than or equal to the pre-set threshold, it indicates that the fitting degree of the inversion model and the actual observation data is good, and the inversion result is relatively reliable; otherwise, it is necessary to continue the inversion iteration calculation until the fitting requirements are met; when the degree of data fitting meets the pre-set threshold, it indicates that the inversion calculation has obtained a relatively ideal result; at this time, the multi-parameter results obtained through inversion are exported; these multi-parameter results contain the distribution of various electrical parameters such as resistivity and polarizability of each unit in the subsurface, and are stored and output in a certain data format, which is convenient for subsequent analysis and use; common data formats can be text files, database tables, etc., and the stratum position and specific value corresponding to each parameter will be clearly marked during output to ensure the accuracy and readability of the data; based on the exported multi-parameter inversion results, combined with the geological background knowledge of the mining area, the past geological exploration data and related geological theories, the geological interpretation work of the mining area is carried out; the geological interpretation personnel analyze the structure, structure and lithology change of the subsurface geological body according to the distribution characteristics of different parameters; for example, by observing the distribution of resistivity, the high-resistance and low-resistance regions can be determined, and the possible differences in rock types can be inferred; according to the distribution characteristics of the polarizability, the geological bodies with induced polarization effect are identified, and the possible mineral resource enrichment areas are inferred; at the same time, combined with the knowledge of geological structure, the relationship between the distribution of geological bodies and the structure is analyzed to determine whether there are geological structure conditions that are beneficial to the formation and storage of mineral resources; by comprehensively analyzing these information, geological profile maps, geological structure maps, etc. are drawn to provide intuitive and accurate geological information for mineral exploration and guide subsequent mineral exploration work, such as determining drilling locations, evaluating mineral resource reserves, etc.

[0055] The research shows that the actual rock generally exists the excitation polarization effect, the existing frequency domain CSEM inversion ignoring the excitation effect may lead to the wrong geological interpretation, in order to consider the excitation effect and the influence of electromagnetic induction on electromagnetic field data, the embodiment proposes to modify the original real resistivity in CSEM inversion to complex resistivity, thereby improving the precision and reliability of CSEM inversion, the embodiment proposes a method for solving analytical sensitivity, which can obtain the accurate sensitivity of underground medium, realize the accurate and fast solving of multi-parameter sensitivity matrix, effectively avoid the defects of conventional perturbation method, and greatly improve the calculation efficiency of multi-parameter inversion, in addition, in the inversion process, the Ocham inversion algorithm is used to realize the minimization of the objective function, and the reference model term and the spatial variation related term are introduced to constrain the solving of the inversion parameter, so as to ensure the stability of the inversion process and improve the reliability of the inversion result, in addition, for the data of different measuring points, the multi-thread parallel technology is used in the inversion process, combined with the foregoing analytical sensitivity method, the multi-parameter fast inversion of CSEM data can be realized.

[0056] The technical scheme of the embodiment is:

[0057] (1) The solving of multi-parameter analytical sensitivity, in the CSEM method forward and inversion, the resistivity of underground medium is generally considered as a real number and does not change with frequency, that is, only the conductivity of rock is considered, however, the actual rock generally exists the excitation polarization effect, and the resistivity (the reciprocal of conductivity) shows a complex number changing with frequency, Pelton et al. found that the resistivity changing with frequency caused by excitation effect can be represented by Cole-Cole model through rock sample measurement in the 1970s, and the expression is as follows:

[0058]

[0059] The four parameters ρ0, m, c and τ contained in the above formula respectively represent the zero frequency resistivity (i.e. the resistivity usually said), the charging rate, the frequency correlation coefficient and the time constant, and i is the imaginary unit. ω is the angular frequency, and ρ(iω) represents that the resistivity is a complex number changing with frequency.

[0060] At this time, the resistivity in the controlled source electromagnetic response equation is replaced by the Cole-Cole complex resistivity model. In the inversion, the main calculation time consumption is the calculation of the sensitivity matrix, generally the perturbation method is used to obtain. For example, for a certain parameter of a certain stratum underground, a small perturbation is made on the basis of the original value, the change of electromagnetic response is obtained, and then the approximate sensitivity of the data to the parameter is obtained, however, with the current demand for fine geological exploration, when multiple electrical parameters, more underground layers and frequency numbers are involved, the calculation efficiency of the perturbation method cannot meet the demand of fast inversion interpretation.

[0061] To solve this problem, the present scheme proposes an analytical solution of the sensitivity matrix. First, taking the electric field as an example, the accurate derivative of the electric field response data obtained on the ground surface with respect to each model parameter of the underground can be expressed as:

[0062]

[0063] In the above formula, E is the electric field response data, and p j is the complex resistivity of the jth layer, and the remaining parameters are the induced polarization parameters shown in formula (1). The partial derivative of the complex resistivity with respect to the four parameters can be easily obtained by differentiating formula (1). To solve the partial derivative of the surface observation data with respect to the resistivity parameter of each layer, only the partial derivative of the electric field and magnetic field components with respect to the model variable is required, taking the horizontal component of the electric field E x and the horizontal component of the magnetic field H y as examples:

[0064]

[0065] In the above formula, the field source is placed at the origin by default, the field source direction is the x-axis direction, is the angle between the connecting line of the measuring point and the x-axis. E r , H r are the electric field and magnetic field of the measuring point in the radial direction of the cylindrical coordinate system, are the electric field and magnetic field of the measuring point in the tangential direction of the cylindrical coordinate system. In the cylindrical coordinate system, the electromagnetic field components generated by the horizontal electric dipole on the ground surface are expressed as:

[0066]

[0067] In the formula, I4, I5, I6, I7, and I8 are integral kernel functions, all of which are in integral form, and the specific expressions can be referred to the book "Controlled Source Audio Frequency Magnetotelluric Method and Its Application". P E is the electric dipole moment, i is the imaginary unit, ω is the angular frequency, μ is the vacuum permeability, r is the transmitter-receiver distance, p j is the complex resistivity of the jth layer. The integral kernel function contains m1, R, R * , which are related to the model parameters in the underground medium, but m1 is only related to the resistivity of the first layer, that is m is called the spatial frequency, which has the dimension of the inverse of the distance. R, R * are transfer functions. Therefore, the derivative of the kernel function can be divided into two cases, and the partial derivative is as follows (taking I4 as an example):

[0068]

[0069] In the formula, J1 is the first-order Bessel function.

[0070] The rest of the kernel function derivation is similar to the above formula, which is not described here. As can be seen from the above formula, only the transfer function R needs to be solved, and the partial derivative of the transfer function with respect to the model variable can be obtained by the following formula: * Partial derivative of model variable The partial derivative of the kernel function with respect to the model parameter can be obtained by Hankel numerical integration, and the partial derivative of the transfer function with respect to the model variable can be obtained by the following formula:

[0071]

[0072] In the formula The transfer functions of the 1st, 2nd, and j-1th layers are respectively. Therefore, only the following needs to be solved And The transfer function recursive formula is:

[0073]

[0074] h j The thickness of the stratum is From the above formula, we can get:

[0075]

[0076]

[0077] The same method can be used to solve Therefore, only the following needs to be calculated by the above formula Then, back-substitute to formula (6), formula (5), formula (4) and formula (3) step by step, the partial derivative of the electromagnetic field with respect to the underground conductivity parameter, i.e. the analytical sensitivity, can be obtained. The above integral formula is solved by fast Hankel numerical integration, and then the accurate sensitivity of the electromagnetic field component with respect to different parameters can be obtained by formula (2). The analytical sensitivity is derived from the integral formula, and does not need to perturb the underground model layer by layer. The calculation time of the analytical sensitivity is about 1 to 2 times the forward calculation time, which is much smaller than the calculation time of the perturbation method.

[0078] (2) Construction of multi-parameter inversion objective function: smooth constraint, reference model constraint and correlation constraint are used to optimize the objective function, and the optimal solution of the inverse problem is solved by using the Ockham inversion algorithm. In the multi-parameter inversion considering the induced polarization effect, due to the increase of parameters, the coupling among the four parameters will appear underdetermined problem, therefore, the embodiment proposes to consider smooth constraint, reference model constraint and correlation constraint in the objective function at the same time, so as to improve the stability of inversion. In order to solve the minimization problem, the objective function formed by the Lagrange multiplier is:

[0079] PRmP 2 +αPm-m * P 2 ​+ βPP(m - θm σ )P 2 + λ -1 PW(d - F(m))P 2 (11)

[0080] The first term on the right side of the above formula is a model smoothness constraint, the second term is a reference model constraint, the third term is a correlation constraint term, and the fourth term is a data fitting term. In the formula, m is an inversion model parameter, R is a first-order gradient operator, m * is an initial model or a prior model; P is a correlation constraint matrix (which can be a gradient operator), m σ is a conductivity model parameter, and the correlation between parameters can be adjusted by setting the P matrix to ensure the correlation of the spatial variation of different parameters; α and β are weight coefficients to measure the proportion of the reference model constraint term and the correlation constraint term in the objective function; θ is a correlation adjustment coefficient, θ equal to 1 is positively correlated, representing that the spatial variation of the polarizability and other induced polarization parameters is similar to the spatial variation of the conductivity (i.e., high conductivity and high polarization), and θ equal to -1 is negatively correlated (i.e., low conductivity and high polarization); λ is a Lagrange multiplier, which is obtained by using the golden section method in Ocham inversion; d is the observed data, F(m) is the forward predicted data; W is a data diagonal line weighting matrix, which can be represented as the inverse of the standard deviation std i of the data (here i represents the ith observation data, i = 1, 2, …, M, and M is the number of data):

[0081] W = diag{1 / std1, 1 / std2, …, 1 / std M}(12)

[0082] By Taylor expansion of the objective function and ignoring high-order terms, the iterative update formula of the model parameter can be obtained as:

[0083]

[0084] wherein

[0085]

[0086] wherein I is a unit matrix, all diagonal elements of which are 1 and all other elements are 0, m k is the model parameter obtained by the kth inversion, J k is the sensitivity matrix of the kth iteration, which is solved by the aforementioned analytical method, including the sensitivity of the underground induced polarization parameters (zero-frequency resistivity, chargeability, frequency coefficient, and time constant).

[0087] In each inversion iteration, the following steps are involved:

[0088] (1) Calculate the predicted data of the current obtained model parameter by the forward method;

[0089] (2) evaluate the fitting degree of the predicted data obtained by the current model and the observed data, if the requirement is not met, go to step (3), otherwise end the inversion;

[0090] (3) solve the sensitivity matrix by using the analytical sensitivity method, and update iteratively by using the Occam method, and return to step (1).

[0091] The inversion system proposed in this embodiment has strong applicability and can meet the needs of traditional resistivity inversion. Arbitrary parameter combinations can also be set, for example, the sensitivity of the time constant is low, so this parameter can be selected to be fixed, and the remaining three parameters are inverted synchronously. When multiple measurement points are involved in the observed data, the multi-thread parallel technology based on OpenMP is still used to speed up the inversion calculation of different measurement points. Combined with the aforementioned analytical sensitivity method, the inversion technology and system proposed in this scheme can greatly improve the efficiency of the existing technology and support the imaging of multiple parameters of the underground model, thereby improving the accuracy of the controlled source electromagnetic inversion.

[0092] In this embodiment, the middle 200m of the real model is set as a low-resistance high-polarization layer, the field source length is set as 100m, the current is set as 1A, the transmitting-receiving distance is set as 8km, and 60 receiving frequencies are uniformly distributed in 1Hz to 10000Hz. The electric field x component E x is regarded as the field observation data, and multi-parameter inversion and single-parameter inversion calculation are performed. In the inversion process, a / β / θ are all set as 1. The number of layers of the underground grid is set as 74, and the resistivity, charge rate, frequency coefficient and time constant of the initial model are set as 100 / 0.1 / 0.1 / 1 respectively. Since the time constant has small sensitivity to the data, the parameter can be fixed in the inversion, such as Figure 2 (a-d) show the results of single-parameter inversion and multi-parameter inversion, Figure 2 (a) is a data fitting error reduction curve, the horizontal coordinate is the number of iterations, and the vertical coordinate is the root mean square error, which is used to evaluate the fitting degree of the inversion predicted data and the real observed data; (b) is the root mean square error between the observed data and the final predicted data. After 9 iterations of inversion, both single-parameter inversion and multi-parameter inversion can obtain a lower data fitting result, which shows the multi-solution of CSEM data, that is, similar electromagnetic response results can be obtained by different models; Figure 2 (b) is the comparison result of the conductivity, the results of single-parameter inversion and multi-parameter inversion are similar, and both can better reflect the position of the middle high-conductivity layer (low-resistance layer); however, the conductivity value of single-parameter inversion deviates from the real model, and the conductivity obtained by multi-parameter inversion has higher accuracy. Figure 2 (c), Figure 2(d) the inversion results of the charge rate and the frequency coefficient, respectively, the horizontal coordinate is the formation depth, and the vertical coordinate is the value of each parameter, and these figures are used to show the distribution of the finally obtained inversion parameters in the underground layers; according to the inversion results, it is shown that the multi-parameter inversion of the scheme can better restore the real model parameters, and the multi-parameter inversion also provides more abundant geophysical basis for geological interpretation.

[0093] Then, the calculation time and memory consumption (iteration 1 time) of the multi-parameter inversion are compared, and the sensitivity matrix is solved by using the perturbation method and the analytical method respectively; the memory required by the two methods in one iteration of the Occam inversion is basically the same, however, the calculation speed of the analytical sensitivity method is obviously better than that of the perturbation method, and the acceleration ratio reaches 13.8. Since the perturbation method needs to perturb and solve each frequency and each model parameter, the calculation speed is slow, while the analytical sensitivity technology directly and quickly obtains the sensitivity value of all frequency data to all parameters in the underground through integration, which greatly improves the inversion speed.

[0094] In the embodiment, ignoring the influence of the induced polarization effect will exacerbate the uncertainty of the frequency domain controlled source electromagnetic data inversion interpretation, and at the same time, the multi-solution of the inversion will be sharply enhanced, the scheme adopts the reference model constraint and the correlation constraint to construct the multi-parameter inversion objective function, can realize the multi-parameter inversion of the controlled source electromagnetic data considering the induced polarization effect, and provides more abundant geophysical basis for geological interpretation; the inversion model parameters considering the induced polarization effect will be several times of the original, the inversion technology based on the perturbation method is seriously affected by the number of unknown model parameters, while the inversion technology and system based on the analytical sensitivity of the scheme will greatly improve the accuracy and efficiency of the sensitivity solution, and then improve the practicability of the multi-parameter inversion.

[0095] Please refer to Figure 3 The structure schematic diagram of the controlled source electromagnetic multi-parameter fast inversion system for mineral exploration provided by the embodiment of the present application, the system comprises:

[0096] The calculation module is used for importing field measurement data, calculating the apparent resistivity of each parameter, and processing the data with noise;

[0097] The setting module is used for setting each inversion parameter, and at least includes multi-thread parallel parameters, weight coefficients, initial models, and correlation constraints;

[0098] The inversion module is used for starting the Occam fast inversion based on the analytical sensitivity;

[0099] The export module is used for evaluating the data fitting degree, exporting the multi-parameter inversion results, and developing the geological interpretation of the mining area.

[0100] Figure 4is a structural schematic view of a mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device provided by an embodiment of the present application. The mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device 600 can have a large difference due to different configurations or performances, and can include one or more processors (central processing units, CPUs) 610 (for example, one or more processors) and a memory 620, one or more storage media 630 (for example, one or more mass storage devices) storing application programs 633 or data 632. The memory 620 and the storage media 630 can be temporary storage or persistent storage. The programs stored in the storage media 630 can include one or more modules (not shown in the figure), and each module can include a series of instruction operations in the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device 600. Further, the processor 610 can be configured to communicate with the storage media 630 and execute a series of instruction operations in the storage media 630 on the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device 600 to implement the method provided by the above embodiment.

[0101] The mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device 600 can further include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input / output interfaces 660, and / or one or more operating devices 631, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art can understand that the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device 600 can include more or fewer components than those shown, or combine certain components, or arrange different components. Figure 4 The mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion device structure shown does not constitute a limitation on the computer device provided by the present application, and can include more or fewer components than those shown, or combine certain components, or arrange different components.

[0102] The present application also provides a computer readable storage medium, which can be a non-volatile computer readable storage medium or a volatile computer readable storage medium. The computer readable storage medium has instructions stored therein, and when the instructions run on a computer, the computer executes the steps of the mineral exploration-oriented controllable source electromagnetic multi-parameter fast inversion method provided by the above embodiments.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described device or apparatus, unit can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0104] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0105] The basic principles, main features and advantages of the present application are shown and described above. Those skilled in the art should understand that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only preferred examples of the present application and are not intended to limit the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for mineral exploration controlled source electromagnetic multi-parameter fast inversion, characterized in that, The method comprises the following steps: Import field measurement data, calculate the apparent resistivity of each parameter, process data with noise, process data with noise, use median filtering algorithm, scan data with a certain window size, take the median of the data in the window as the new data value of the point, remove outliers and noise, use Hanning window filtering method to filter the apparent resistivity data of different measuring points at the same frequency point; Set each inversion parameter, including at least multi-thread parallel parameter, weight coefficient, initial model, correlation constraint; Start the rapid inversion of Occam based on analytical sensitivity; Evaluate the degree of data fitting, export the multi-parameter inversion result, and carry out geological interpretation of the mining area; The start of the rapid inversion of Occam based on analytical sensitivity comprises: According to the set initial model, use the fast Hankel transform algorithm to calculate the theoretical electromagnetic response data; Use the analytical sensitivity solving method to calculate the sensitivity of the underground medium to obtain the multi-parameter analytical sensitivity matrix; Use the Occam inversion algorithm to perform iterative calculation based on the constructed multi-parameter inversion objective function, in each iteration, according to the iterative update of the model parameters, use the current sensitivity matrix, observation data, forward prediction data and each constraint term to calculate the updated model parameters, and through continuous iteration, the optimal solution is obtained; Smooth constraint, reference model constraint and correlation constraint are used to optimize the objective function, and the Occam inversion algorithm is used to solve the optimal solution of the inverse problem to construct the multi-parameter inversion objective function.

2. The method according to claim 1, wherein, The import of field measurement data, the calculation of the apparent resistivity of each parameter, and the processing of data with noise comprise: Read the measurement data from the field measurement equipment, calculate the apparent resistivity of each parameter using the measured electric field and magnetic field component data.

3. The method of claim 1, wherein, The setting of each inversion parameter comprises: Construct an initial geological model containing at least resistivity and polarization rate parameters, divide the underground into several horizontal strata according to the data frequency range and the detection depth requirement, and determine the initial parameter value of each stratum; Select the correlation constraint matrix and determine the value of the correlation adjustment coefficient.

4. The method of claim 1, wherein, The evaluation of the degree of data fitting, the export of the multi-parameter inversion result, and the geological interpretation of the mining area comprise: Substitute the model parameters obtained by inversion into the forward calculation again to obtain the theoretical electromagnetic response data of the inversion model; Compare the data with the original observation data, calculate the data fitting difference, and when the data fitting degree meets the pre-set threshold, export the multi-parameter result obtained by inversion; Based on the exported multi-parameter inversion result, carry out the geological interpretation of the mining area.

5. The method of claim 4, wherein the method is a multi-parameter fast inversion method for mineral exploration controlled source electromagnetic. The multi-parameter result at least includes the resistivity and polarization rate parameter distribution of each stratum.

6. A mineral exploration oriented controlled source electromagnetic multi-parameter fast inversion system, characterized in that, The system comprises: A calculation module for importing field measurement data, calculating the apparent resistivity of each parameter, processing data with noise, processing data with noise, using a median filtering algorithm, scanning data with a certain window size, taking the median of the data in the window as the new data value of the point, removing outliers and noise, and using a Hanning window filtering method to filter the apparent resistivity data of different measuring points at the same frequency point; The setting module is configured to set inversion parameters, including at least multi-thread parallel parameters, weight coefficients, initial models, and correlation constraints. The inversion module is configured to start the Ocham rapid inversion based on analytical sensitivity: calculate theoretical electromagnetic response data by using a rapid Hankel transform algorithm according to the set initial model; calculate the sensitivity of the underground medium by using an analytical sensitivity solving method to obtain a multi-parameter analytical sensitivity matrix; perform iterative calculation based on the constructed multi-parameter inversion objective function by using the Ocham inversion algorithm, in each iteration, calculate the updated model parameters by using the current sensitivity matrix, observation data, forward prediction data, and each constraint term according to the iterative update of the model parameters, obtain the optimal solution by continuous iteration; optimize the objective function by using the smoothing constraint, reference model constraint, and correlation constraint, and solve the optimal solution of the inverse problem by using the Ocham inversion algorithm to construct the multi-parameter inversion objective function; The exporting module is configured to evaluate the fitting degree of data, export the multi-parameter inversion result, and develop geological interpretation of the mining area.

7. A mineral exploration oriented controlled source electromagnetic multi-parameter fast inversion device, characterized in that, The controllable source electromagnetic multi-parameter rapid inversion equipment for mineral exploration includes a memory and at least one processor, and the memory stores instructions; the at least one processor calls the instructions in the memory to enable the controllable source electromagnetic multi-parameter rapid inversion equipment for mineral exploration to perform each step of the controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration according to any one of claims 1-5.

8. A computer-readable storage medium having stored thereon instructions, the computer-readable storage medium comprising: The instructions are executed by the processor to implement each step of the controllable source electromagnetic multi-parameter rapid inversion method for mineral exploration according to any one of claims 1-5.

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