Method and device for determining target function of full-waveform inversion

Abstract

The invention provides a full waveform inversion objective function determination method and device. The method comprises the following steps: carrying out nonlinear transformation on acquired seismic observation data and seismic synthesis data; constructing a distance matrix according to the seismic synthesis data, the seismic observation data and the seismic trace data after nonlinear transformation; determining an optimal permutation vector from the distance matrix; determining a single-channel data deviation corresponding to each seismic channel through a preset deviation calculation expression in combination with the optimal replacement vector; and summing all the single-channel data deviations to obtain a full-waveform inversion objective function. And optimal transmission under nonlinear transformation is used, so that a convex objective function is obtained, and the problem of cycle jump in full waveform inversion is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing of natural source earthquakes and artificial source earthquakes on land or in the ocean, and in particular to a method and device for determining an objective function of full waveform inversion. Background Art

[0002] Full waveform inversion is the most powerful imaging technology to date. Full waveform inversion relies on solving the wave equation to simulate the propagation of the wave field underground, and then compares the difference between the synthetic seismogram and the observed data. The error of the back-transmitted data forms a gradient, and the model is updated to reduce the data error. The new model is used as the initial model and it is iterated repeatedly until the algorithm converges to the optimal value. Usually, full waveform inversion uses the least squares waveform error, which not only fits the amplitude of the seismic signal, but also fits the phase of the seismic signal; so theoretically, the size that can be resolved by full waveform inversion can reach half a wavelength.

[0003] However, full waveform inversion requires an accurate initial model when solving underground medium parameters. Because the objective function is based on waveform comparison, when the initial value is significantly different from the observed data, cycle jumps are likely to occur, resulting in inaccurate inversion results. In actual production, it is not easy to provide an accurate initial model. Summary of the invention

[0004] The present invention provides a method and device for determining an objective function of full waveform inversion, which are used to obtain a relatively convex objective function by utilizing optimal transmission under nonlinear transformation.

[0005] In a first aspect, the present invention provides a method for determining an objective function of full waveform inversion, comprising:

[0006] Performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0007] Constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0008] determining an optimal permutation vector from the distance matrix;

[0009] Determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0010] The objective function of full waveform inversion is obtained by summing up all the single-channel data deviations.

[0011] Optionally, constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace time after nonlinear transformation includes:

[0012] Normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value;

[0013] Determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value;

[0014] Based on the normalized time difference value and the normalized amplitude difference value, matrix elements of the distance matrix are obtained, and the distance matrix is ​​constructed based on the matrix elements.

[0015] Optionally, determining an optimal permutation vector from the distance matrix comprises:

[0016] Sorting all the matrix elements of the distance matrix by a price-based ranking algorithm to obtain a sorting result;

[0017] The optimal replacement vector is determined according to the sorting result.

[0018] Optionally, the deviation calculation expression is specifically:

[0019] h=∑ ij c ij m ij ;

[0020] Where h is the deviation, c is ij is the distance matrix, m ij is the permutation matrix.

[0021] In a second aspect, the present invention provides a device for determining an objective function of full waveform inversion, comprising:

[0022] A transformation module, used for performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0023] A matrix construction module, used for constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0024] An optimal permutation vector determination module, used to determine an optimal permutation vector from the distance matrix;

[0025] A single-channel data deviation determination module is used to determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0026] The objective function determination module is used to sum all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0027] Optionally, the matrix building module includes:

[0028] A time difference normalization value determination submodule, used for normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data, to obtain a time difference normalization value;

[0029] A submodule for determining an amplitude difference normalized value, used to determine the amplitude difference of the seismic trace data after nonlinear transformation, and to perform normalization processing on the amplitude difference to obtain an amplitude difference normalized value;

[0030] A construction submodule is used to obtain matrix elements of the distance matrix based on the normalized time difference value and the normalized amplitude difference value, and to construct the distance matrix based on the matrix elements.

[0031] Optionally, the optimal permutation vector determination module includes:

[0032] A sorting result determination submodule is used to sort all the matrix elements of the distance matrix by a bidding ranking algorithm to obtain a sorting result;

[0033] The optimal permutation vector determination submodule is used to determine the optimal permutation vector according to the sorting result. Optionally, the deviation calculation expression is specifically:

[0034] h=∑ ij c ij m ij ;

[0035] Where h is the deviation, c is ij is the distance matrix, m ij is the permutation matrix.

[0036] In a third aspect, the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method provided in the first aspect are performed.

[0037] In a fourth aspect, the present application provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the method provided in the first aspect are performed.

[0038] It can be seen from the above technical solutions that the present invention has the following advantages:

[0039] The present invention provides a method and device for determining the objective function of full waveform inversion, the method comprising: performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data; constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation; determining the best replacement vector from the distance matrix; determining the single-channel data deviation corresponding to each seismic trace by combining the best replacement vector with a pre-set deviation calculation expression; summing up all the single-channel data deviations to obtain the objective function of full waveform inversion. By using the optimal transmission under nonlinear transformation, a more convex objective function is obtained to solve the cycle jump problem in full waveform inversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 A flowchart of a first embodiment of a method for determining an objective function of full waveform inversion according to the present invention;

[0042] Figure 2 A flowchart of a second embodiment of a method for determining an objective function of full waveform inversion according to the present invention;

[0043] Figure 3 A flowchart of a third embodiment of a method for determining an objective function of full waveform inversion according to the present invention;

[0044] Figure 4 A flowchart of a fourth embodiment of a method for determining an objective function of full waveform inversion according to the present invention;

[0045] Figure 5 This is a schematic diagram of earthquake observation data;

[0046] Figure 6 This is a schematic diagram of earthquake synthetic data;

[0047] Figure 7 This is a schematic diagram of the real model;

[0048] Figure 8 This is a schematic diagram of the initial model;

[0049] Fig. 9 This is the initial data comparison chart;

[0050] Fig.10 is a schematic diagram of the inversion results;

[0051] Fig.11 This is a schematic diagram of the final synthetic data;

[0052] Fig.12 This is the final data comparison diagram;

[0053] Fig.13 The present invention is a structural block diagram of an embodiment of a device for determining an objective function of full waveform inversion according to the present invention. DETAILED DESCRIPTION

[0054] The embodiment of the present invention provides a method and device for determining an objective function of full waveform inversion, which is used to obtain a relatively convex objective function by optimizing transmission under nonlinear transformation.

[0055] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] For example, see Figure 1 , Figure 1 The flowchart of the first embodiment of the objective function determination method of the full waveform inversion of the present invention includes:

[0057] Step S101, performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0058] Step S102, constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0059] Step S103, determining the best replacement vector from the distance matrix;

[0060] Step S104, determining the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0061] Step S105, summing up all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0062] The present invention provides a method for determining the objective function of full waveform inversion, which performs nonlinear transformation on the acquired seismic observation data and seismic synthetic data; constructs a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation; determines the optimal replacement vector from the distance matrix; determines the single-channel data deviation corresponding to each seismic trace by combining the optimal replacement vector with a pre-set deviation calculation expression; and sums up all the single-channel data deviations to obtain the objective function of full waveform inversion. By using the optimal transmission under nonlinear transformation, a more convex objective function is obtained to solve the cycle jump problem in full waveform inversion.

[0063] For example 2, please refer to Figure 2 , Figure 2 The flowchart of Embodiment 2 of a method for determining an objective function of waveform inversion of the present invention includes:

[0064] Step S201, performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0065] Step S202, normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value;

[0066] Step S203, determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value;

[0067] Step S204, obtaining matrix elements of the distance matrix based on the normalized time difference value and the normalized amplitude difference value, and constructing the distance matrix based on the matrix elements;

[0068] Step S205, determining the best replacement vector from the distance matrix;

[0069] Step S206, determining the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0070] Step S207, summing up all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0071] For example 3, please refer to Figure 3 , Figure 3 The flowchart of the third embodiment of the objective function determination method of full waveform inversion of the present invention includes:

[0072] Step S301, performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0073] Step S302, constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0074] Step S303, sorting all the matrix elements of the distance matrix by a bidding ranking algorithm to obtain a sorting result;

[0075] Step S304, determining the optimal replacement vector according to the sorting result;

[0076] Step S305, determining the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0077] Step S306, summing up all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0078] Example 4, please refer to Figure 4 , Figure 4 The flowchart of Embodiment 4 of the objective function determination method of full waveform inversion of the present invention comprises:

[0079] Step S401, performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0080] It should be noted that full waveform inversion is to compare the relationship between seismic synthetic data and seismic observation data, while in actual observation records, seismic observation data and seismic synthetic data are both discrete.

[0081] In the embodiment of the present invention, it is assumed that the single channel data of the seismic observation data is j When d j , the observation single channel data of seismic synthetic data is T i When u i Nonlinear transformation can effectively balance the amplitude differences between different seismic events. For example, applying TANH to land data can effectively enhance the strength of body waves, which is important for improving the contribution of surface waves and obtaining deep structures.

[0082] Step S402, normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value;

[0083] Step S403, determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value;

[0084] Step S404, obtaining matrix elements of the distance matrix based on the normalized time difference value and the normalized amplitude difference value, and constructing the distance matrix based on the matrix elements;

[0085] In the embodiment of the present invention, the seismic trace after nonlinear transformation is denoted as

[0086] Among them, α and β are two constants to prevent the situation that the data calculation exceeds the range of computer expression. Then we can construct a distance matrix c as follows: ij , as shown below:

[0087]

[0088] Among them, T is the total observed reality, A is the maximum value of the observed data, and η is the user input parameter.

[0089] Step S405, sorting all the matrix elements of the distance matrix by a paid ranking algorithm to obtain a sorting result;

[0090] Step S406, determining the optimal replacement vector according to the sorting result;

[0091] Step S407, determining the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0092] Specifically, the deviation calculation expression is:

[0093] h=∑ ij c ij m ij ;

[0094] Where h is the deviation, c is ij is the distance matrix, m ij is a permutation matrix, which is obtained by permuting the rows and columns of the unit matrix. The permutation matrix is ​​equivalent to the permutation vector; in other words, the permutation matrix can be represented by a vector: j = σ i .

[0095] In the embodiment of the present invention, after constructing the distance matrix, the best replacement vector is quickly obtained through a bidding ranking algorithm, and then the data deviation corresponding to each seismic channel is determined by combining the best replacement vector with a pre-set deviation calculation expression.

[0096] Step S408, summing up all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0097] In the embodiment of the present invention, the sum of all single-channel data deviations is the objective function required for the entire full waveform inversion.

[0098] See also Figure 5 and Figure 6 , Figure 5 For Figure 7 The seismic observation data generated from the real model, namely the seismic shot collection, Figure 6 For Figure 8 The synthetic seismic data generated by the initial model are compared with Figure 5 and Figure 6 ,get Fig. 9 The initial data comparison diagram shown in FIG. 1 shows that the letter O represents the observed data and the letter S represents the synthetic data. It can be seen that the data difference is large and the cycle jump phenomenon is serious. The inversion result obtained by the determination method of the objective function proposed in the embodiment of the present invention is as follows: Fig.10 As shown in Figure 1, because the objective function is relatively convex, the velocity structure can be well inverted. On this basis, the final synthetic data schematic diagram and the final data comparison schematic diagram are shown in Figure 1. Fig.11 and Fig.12 As shown, it can be seen that the entire seismic signal is fitted.

[0099] The present invention provides a method for determining the objective function of full waveform inversion, which determines the optimal permutation vector through the constructed distance matrix, and then determines the single-channel data deviation corresponding to each seismic channel, and then obtains the objective function of full waveform inversion. By using the optimal transmission under nonlinear transformation, a more convex objective function is obtained to solve the cycle jump problem in full waveform inversion.

[0100] For example 5, please refer to Fig.13 , Fig.13 The structure block diagram of an embodiment of a device for determining a target function of full waveform inversion of the present invention comprises:

[0101] Transformation module 501, used for performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0102] A matrix construction module 502, for constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0103] An optimal replacement vector determination module 503, used to determine the optimal replacement vector from the distance matrix;

[0104] The single-channel data deviation determination module 504 is used to determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0105] The objective function determination module 505 is used to sum all the single-channel data deviations to obtain the objective function of full waveform inversion.

[0106] In an optional embodiment, the matrix construction module 502 includes:

[0107] A time difference normalization value determination submodule, used for normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data, to obtain a time difference normalization value;

[0108] A submodule for determining an amplitude difference normalized value, used to determine the amplitude difference of the seismic trace data after nonlinear transformation, and to perform normalization processing on the amplitude difference to obtain an amplitude difference normalized value;

[0109] A construction submodule is used to obtain matrix elements of the distance matrix based on the normalized time difference value and the normalized amplitude difference value, and to construct the distance matrix based on the matrix elements.

[0110] In an optional embodiment, the optimal permutation vector determination module 503 includes:

[0111] A sorting result determination submodule is used to sort all the matrix elements of the distance matrix by a bidding ranking algorithm to obtain a sorting result;

[0112] The optimal permutation vector determination submodule is used to determine the optimal permutation vector according to the sorting result. In an optional embodiment, the deviation calculation expression is specifically:

[0113] h=∑ ij c ij m ij ;

[0114] Where h is the deviation, c is ij is the element in the i-th row and j-th column of the distance matrix, m ij is the element in the i-th row and j-th column of the corresponding permutation vector.

[0115] Embodiment 6. The embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor performs the steps of a method for determining an objective function of full waveform inversion, including:

[0116] Performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0117] Constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0118] determining an optimal permutation vector from the distance matrix;

[0119] Determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0120] The objective function of full waveform inversion is obtained by summing up all the single-channel data deviations.

[0121] In an optional embodiment, a distance matrix is ​​constructed according to the seismic synthetic data, the seismic observation data, and the seismic trace time after nonlinear transformation, including:

[0122] Normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value;

[0123] Determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value;

[0124] Based on the normalized time difference value and the normalized amplitude difference value, matrix elements of the distance matrix are obtained, and the distance matrix is ​​constructed based on the matrix elements.

[0125] In an optional embodiment, determining the best permutation vector from the distance matrix comprises:

[0126] Sorting all the matrix elements of the distance matrix by a price-based ranking algorithm to obtain a sorting result;

[0127] The optimal replacement vector is determined according to the sorting result.

[0128] In an optional embodiment, the deviation calculation expression is specifically:

[0129] h=∑ ij c ij m ij ;

[0130] Where h is the deviation, c is ij is the element in the i-th row and j-th column of the distance matrix, m ij is the element in the i-th row and j-th column of the corresponding permutation vector.

[0131] Embodiment 7, the embodiment of the present invention further provides a computer storage medium, on which a computer program is stored, and when the computer program is executed by the processor, the steps of implementing a method for determining an objective function of full waveform inversion include:

[0132] Performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data;

[0133] Constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation;

[0134] determining an optimal permutation vector from the distance matrix;

[0135] Determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression;

[0136] The objective function of full waveform inversion is obtained by summing up all the single-channel data deviations.

[0137] In an optional embodiment, a distance matrix is ​​constructed according to the seismic synthetic data, the seismic observation data, and the seismic trace time after nonlinear transformation, including:

[0138] Normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value;

[0139] Determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value;

[0140] Based on the normalized time difference value and the normalized amplitude difference value, matrix elements of the distance matrix are obtained, and the distance matrix is ​​constructed based on the matrix elements.

[0141] In an optional embodiment, determining the best permutation vector from the distance matrix comprises:

[0142] Sorting all the matrix elements of the distance matrix by a price-based ranking algorithm to obtain a sorting result;

[0143] The optimal replacement vector is determined according to the sorting result.

[0144] In an optional embodiment, the deviation calculation expression is specifically:

[0145] h=∑ ij c ij m ij ;

[0146] Where h is the deviation, c is ij is the element in the i-th row and j-th column of the distance matrix, m ij is the element in the i-th row and j-th column of the corresponding permutation vector.

[0147] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0148] In the several embodiments provided in the present application, it should be understood that the methods, devices, electronic devices and storage media disclosed in the present invention can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0149] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0150] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0151] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a readable storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned readable storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0152] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the objective function of full waveform inversion, characterized in that: include: Performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data; Constructing a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation; determining an optimal permutation vector from the distance matrix; Determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression; The objective function of full waveform inversion is obtained by summing up all the single-channel data deviations.

2. The objective function determination method of full waveform inversion according to claim 1, characterized in that: A distance matrix is ​​constructed according to the seismic synthetic data, the seismic observation data, and the seismic trace time after nonlinear transformation, including: Normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data to obtain a normalized time difference value; Determining the amplitude difference of the seismic trace data after nonlinear transformation, and normalizing the amplitude difference to obtain a normalized amplitude difference value; Based on the normalized time difference value and the normalized amplitude difference value, matrix elements of the distance matrix are obtained, and the distance matrix is ​​constructed based on the matrix elements.

3. The objective function determination method of full waveform inversion according to claim 1 is characterized in that: Determining an optimal permutation vector from the distance matrix includes: Sorting all the matrix elements of the distance matrix by a price-based ranking algorithm to obtain a sorting result; The optimal replacement vector is determined according to the sorting result.

4. The objective function determination method of full waveform inversion according to claim 1 is characterized in that: The deviation calculation expression is specifically: h=∑ ij c ij m ij ; Where h is the deviation, c is ij is the distance matrix, m ij is the permutation matrix.

5. A device for determining the objective function of full waveform inversion, characterized in that: include: A transformation module, used for performing nonlinear transformation on the acquired seismic observation data and seismic synthetic data; A matrix construction module, used to construct a distance matrix according to the seismic synthetic data, the seismic observation data, and the seismic trace data after nonlinear transformation; An optimal permutation vector determination module, used to determine an optimal permutation vector from the distance matrix; A single-channel data deviation determination module is used to determine the single-channel data deviation corresponding to each seismic channel by combining the optimal replacement vector with a preset deviation calculation expression; The objective function determination module is used to sum all the single-channel data deviations to obtain the objective function of full waveform inversion.

6. The objective function determination device for full waveform inversion according to claim 5, characterized in that: The matrix building module includes: A time difference normalization value determination submodule, used for normalizing the time difference between the synthetic single-channel data of all the seismic synthetic data and the observed single-channel data corresponding to the seismic observation data, to obtain a time difference normalization value; A submodule for determining an amplitude difference normalized value, used to determine the amplitude difference of the seismic trace data after nonlinear transformation, and to perform normalization processing on the amplitude difference to obtain an amplitude difference normalized value; A construction submodule is used to obtain matrix elements of the distance matrix based on the normalized time difference value and the normalized amplitude difference value, and to construct the distance matrix based on the matrix elements.

7. The objective function determination device for full waveform inversion according to claim 5, characterized in that: The optimal permutation vector determination module comprises: A sorting result determination submodule is used to sort all the matrix elements of the distance matrix by a bidding ranking algorithm to obtain a sorting result; The optimal replacement vector determination submodule is used to determine the optimal replacement vector according to the sorting result.

8. The objective function determination method of full waveform inversion according to claim 5, characterized in that: The deviation calculation expression is specifically: h=∑ ij c ij m ij ; Where h is the deviation, c is ij is the distance matrix, m ij is the permutation matrix.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 4 is executed.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is executed.

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