Underground discontinuous geological anomalous body detection method and device

Abstract

The invention provides an underground discontinuous geological anomalous body detection method and device, and relates to the technical field of detection. Three-dimensional common offset seismic data of a research area can be acquired; according to each piece of frequency data of the three-dimensional common offset seismic data, determining a geological anomalous body effective signal component corresponding to each piece of frequency data by using a sparse-oriented optimal objective function; wherein the sparse-oriented optimization objective function is used for solving a convex optimization problem; and determining an underground discontinuous geological anomalous body detection result of the research area according to the effective signal component of the geological anomalous body corresponding to each frequency data. According to the underground discontinuous geological anomalous body detection method based on the sparse-oriented optimization objective function, effective signal components of the geological anomalous body in the three-dimensional common offset seismic data can be effectively estimated, non-effective signal interference is reduced, and therefore high-precision detection of the underground discontinuous geological anomalous body is achieved.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, and in particular to a method and device for detecting underground discontinuous geological anomalies. Background Art

[0002] Discontinuous underground geological anomalies have an important impact on the development and utilization of geothermal and mineral resources. Discontinuous underground geological anomalies can be used as storage space and migration channels for mineral resources such as coalbed methane, oil and natural gas, which are related to the selection of drilling locations, exploration and development of oil and gas resources, and safe mining of coal mines. Discontinuous underground geological anomalies are direct wave field responses of underground heterogeneous geological structures. This response can be used to accurately locate heterogeneous discontinuous geological bodies, provide stronger illumination of underground space, and realize accurate positioning and imaging of geological anomalies.

[0003] Traditional seismic exploration methods mainly use seismic reflection method. Due to the limitation of Rayleigh criterion, traditional seismic exploration methods are only applicable to the detection of large-scale smooth reflection interfaces, which is not conducive to the accurate imaging of underground discontinuous geological anomalies. Summary of the invention

[0004] The object of the present invention is to provide a method and device for detecting underground discontinuous geological anomalies, so as to achieve high-precision detection of underground discontinuous geological anomalies.

[0005] In a first aspect, the present invention provides a method for detecting underground discontinuous geological anomalies, comprising:

[0006] Acquire three-dimensional common-offset seismic data in the study area;

[0007] According to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined by using a sparse-oriented optimization objective function; wherein the sparse-oriented optimization objective function is used to solve the convex optimization problem;

[0008] According to the effective signal components of the geological anomaly corresponding to each frequency data, the detection results of the underground discontinuous geological anomaly in the study area are determined.

[0009] Furthermore, according to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined by using the sparse-oriented optimization objective function, including:

[0010] Perform Fourier transform on the three-dimensional common offset seismic data to obtain the target frequency domain data;

[0011] According to the diagonal matrix data corresponding to each frequency data in the target frequency domain data, the optimization objective function corresponding to each frequency data is constructed by using the expression of the sparse-oriented optimization objective function;

[0012] According to the optimization objective function corresponding to each frequency data, the optimal parameter matrix corresponding to each frequency data is determined; wherein the optimal parameter matrix is ​​obtained by iteratively updating each row element of the parameter matrix to be optimized in the corresponding optimization objective function based on the principle of dimensionality reduction;

[0013] According to the optimal parameter matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined.

[0014] Furthermore, according to the diagonal matrix data corresponding to each frequency data in the target frequency domain data, the optimization objective function corresponding to each frequency data is constructed using the expression of the sparse-oriented optimization objective function, including:

[0015] Perform a diagonal matrix transformation on each frequency data to obtain diagonal matrix data corresponding to each frequency data;

[0016] The diagonal matrix data corresponding to each frequency data is substituted into the expression of the sparse-oriented optimization objective function to obtain the optimization objective function corresponding to each frequency data.

[0017] Furthermore, the expression of the sparse-oriented optimization objective function includes:

[0018]

[0019] Where D represents the diagonal matrix data, R represents the parameter matrix to be optimized, α represents the preset weight balancing item parameter, q represents the number of rows in the parameter matrix, and R i Represents the i-th row element of the parameter matrix.

[0020] Furthermore, according to the optimization objective function corresponding to each frequency data, the optimal parameter matrix corresponding to each frequency data is determined, including:

[0021] Based on the principle of dimensionality reduction, the following formula is used in combination with the optimization objective function corresponding to each frequency data to iteratively update each row element of the parameter matrix until the parameter matrix converges to obtain the optimal parameter matrix corresponding to each frequency data:

[0022] R i =(1-α / ||k i ||2) * k i ;

[0023]

[0024] Among them, when 1-α / ||k i When ||2>0, (1-α / ||k i||2) * =1-α / ||k i ||2, otherwise (1-α / ||k i ||2) * =0; R i represents the i-th row element of the parameter matrix, α represents the preset weight balancing item parameter, k i represents an array sequence, D represents diagonal matrix data, D i′ represents the j-th column element of D, D l′ represents the l-th column element of D, R l Represents the l-th row element of the parameter matrix.

[0025] Furthermore, according to the optimal parameter matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined, including:

[0026] According to the non-zero row number of the optimal parameter matrix corresponding to each frequency data, a left multiplication operator matrix, a right multiplication operator matrix and an intersection operator matrix corresponding to each frequency data are constructed; wherein the left multiplication operator matrix is ​​composed of the m-th column elements in the diagonal matrix data corresponding to the corresponding frequency data, the right multiplication operator matrix is ​​composed of the m-th column elements after the diagonal matrix data corresponding to the corresponding frequency data is transposed, m is the non-zero row number of the corresponding optimal parameter matrix, and the intersection operator matrix is ​​composed of the intersection data of the left multiplication operator matrix and the right multiplication operator matrix;

[0027] According to the left multiplication operator matrix, right multiplication operator matrix and intersection operator matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is calculated.

[0028] Furthermore, according to the effective signal components of the geological anomaly corresponding to each frequency data, the detection results of the underground discontinuous geological anomaly in the study area are determined, including:

[0029] Perform inverse Fourier transform on the effective signal components of each geological anomaly to obtain the corresponding time domain signal components;

[0030] The migration algorithm is used to image each time domain signal component and obtain the detection results of underground discontinuous geological anomalies in the study area.

[0031] In a second aspect, the present invention further provides an underground discontinuous geological anomaly detection device, comprising:

[0032] A data acquisition module, used to acquire three-dimensional common offset seismic data of the study area;

[0033] The first determination module is used to determine the effective signal component of the geological anomaly body corresponding to each frequency data of the three-dimensional common offset seismic data by using a sparse-oriented optimization objective function; wherein the sparse-oriented optimization objective function is used to solve a convex optimization problem;

[0034] The second determination module is used to determine the detection result of the underground discontinuous geological anomaly in the study area according to the effective signal components of the geological anomaly corresponding to each frequency data.

[0035] In a third aspect, the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the underground discontinuous geological anomaly detection method of the first aspect is implemented.

[0036] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for detecting underground discontinuous geological anomalies of the first aspect is executed.

[0037] The underground discontinuous geological anomaly detection method and device provided by the embodiment of the present invention can obtain three-dimensional common offset seismic data of the study area; according to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly corresponding to each frequency data is determined by using the sparse-guided optimization objective function; wherein the sparse-guided optimization objective function is used to solve the convex optimization problem; according to the effective signal component of the geological anomaly corresponding to each frequency data, the detection result of the underground discontinuous geological anomaly in the study area is determined. This underground discontinuous geological anomaly detection method based on the sparse-guided optimization objective function can effectively estimate the effective signal component of the geological anomaly in the three-dimensional common offset seismic data, reduce the interference of ineffective signals, and thus achieve high-precision detection of underground discontinuous geological anomalies. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A schematic diagram of a flow chart of a method for detecting underground discontinuous geological anomalies provided by an embodiment of the present invention;

[0040] Figure 2 A schematic flow chart of another method for detecting underground discontinuous geological anomalies provided by an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of the structure of an underground discontinuous geological anomaly detection device provided by an embodiment of the present invention;

[0042] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Due to the limitation of Rayleigh criterion, traditional seismic exploration methods are only applicable to the detection of large-scale smooth reflection interfaces, which is not conducive to the accurate imaging of underground discontinuous geological anomalies. Based on this, an underground discontinuous geological anomaly detection method and device provided by an embodiment of the present invention can realize high-precision detection of underground discontinuous geological anomalies by constructing a sparse-guided optimization objective function.

[0045] To facilitate understanding of this embodiment, a method for detecting underground discontinuous geological anomalies disclosed in an embodiment of the present invention is first introduced in detail.

[0046] The embodiment of the present invention provides a method for detecting underground discontinuous geological anomalies, which is executed by an electronic device with data processing capability. Figure 1 The flowchart of a method for detecting underground discontinuous geological anomalies is shown in FIG. 1 , and the method mainly includes the following steps S110 to S130:

[0047] Step S110, acquiring three-dimensional common-offset seismic data in the study area.

[0048] High-quality 3D common-offset seismic data can be obtained for the study area, where high quality means high signal-to-noise ratio. 3D common-offset seismic data refers to a data set in 3D seismic exploration where all seismic traces have the same source-receiver distance. This data set is common to a specific offset, meaning it is a subset of all records where the distance between the source and the receiver remains constant. In 3D common-offset seismic data, the vertical direction is the time detected by the receiver, and the horizontal direction is the distance between the source and the receiver.

[0049] Step S120, according to each frequency data of the three-dimensional common offset seismic data, using the sparse-guided optimization objective function to determine the effective signal component of the geological anomaly body corresponding to each frequency data; wherein the sparse-guided optimization objective function is used to solve the convex optimization problem.

[0050] The above-mentioned sparse-oriented optimization objective function means that in the optimization problem, the solution found not only satisfies certain constraints, but is also "sparse" in some aspects. Here, "sparse" means that the number of non-zero elements in the solution vector is small. The signal extraction problem of underground discontinuous geological anomalies can be regarded as a convex optimization problem, and the sparse-oriented optimization objective function can be used to solve the convex optimization problem. Among them, the convex optimization problem refers to a type of optimization problem in which the objective function is a convex function and the constraint set is a convex set.

[0051] In some possible embodiments, the above step S120 may include the following sub-steps:

[0052] Sub-step 121, performing Fourier transform on the three-dimensional common-offset seismic data to obtain target frequency domain data.

[0053] In order to facilitate subsequent data processing, the three-dimensional common-offset seismic data in the time domain can be first converted to the frequency domain through Fourier transform, so that the target frequency domain data can be decomposed into different frequency components, that is, different frequency data, each frequency component represents the amplitude and phase information of the original signal at that frequency.

[0054] Sub-step 122, based on the diagonal matrix data corresponding to each frequency data in the target frequency domain data, the optimization objective function corresponding to each frequency data is constructed using the expression of the sparse-oriented optimization objective function.

[0055] In order to simplify the calculation, improve efficiency and accelerate the convergence speed, each frequency data can be first transformed into a diagonal matrix to obtain the diagonal matrix data corresponding to each frequency data; then the diagonal matrix data corresponding to each frequency data is substituted into the expression of the sparse-guided optimization objective function to obtain the optimization objective function corresponding to each frequency data.

[0056] Optionally, the expression of the above sparse-oriented optimization objective function may include:

[0057]

[0058] Where D represents the diagonal matrix data, R represents the parameter matrix to be optimized, α represents the preset weight balancing item parameter, q represents the number of rows in the parameter matrix, and R i represents the i-th row element of the parameter matrix, |||| F Denotes the Frobenius norm (F-norm for short).

[0059] Sub-step 123, according to the optimization objective function corresponding to each frequency data, determine the optimal parameter matrix corresponding to each frequency data; wherein the optimal parameter matrix is ​​obtained by iteratively updating each row element of the parameter matrix to be optimized in the corresponding optimization objective function based on the principle of dimensionality reduction.

[0060] Based on the principle of dimensionality reduction, the following formula can be used in combination with the optimization objective function corresponding to each frequency data to iteratively update each row element of the parameter matrix until the parameter matrix converges to obtain the optimal parameter matrix corresponding to each frequency data:

[0061] R i =(1-α / ||k i || 2 ) * k i ;

[0062]

[0063] Among them, when 1-α / ||k i When ||2>0, (1-α / ||k i ||2) * =1-α / ||k i ||2, otherwise (1-α / ||k i ||2) * =0; R i represents the i-th row element of the parameter matrix, α represents the preset weight balancing item parameter, k i represents an array sequence, D represents diagonal matrix data, D i′ represents the j-th column element of D, D l′ represents the l-th column element of D, R l Represents the l-th row element of the parameter matrix.

[0064] Sub-step 124, determining the effective signal component of the geological anomaly body corresponding to each frequency data according to the optimal parameter matrix corresponding to each frequency data.

[0065] First, according to the non-zero row number of the optimal parameter matrix corresponding to each frequency data, the left multiplication operator matrix, the right multiplication operator matrix and the intersection operator matrix corresponding to each frequency data can be constructed; then, according to the left multiplication operator matrix, the right multiplication operator matrix and the intersection operator matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is calculated. Among them, the left multiplication operator matrix is ​​composed of the m-th column elements in the diagonal matrix data corresponding to the corresponding frequency data, the right multiplication operator matrix is ​​composed of the m-th column elements after the diagonal matrix data corresponding to the corresponding frequency data is transposed, m is the non-zero row number of the corresponding optimal parameter matrix, and the intersection operator matrix is ​​composed of the intersection data of the left multiplication operator matrix and the right multiplication operator matrix. It should be noted that the non-zero row number can be one or more.

[0066] Optionally, the effective signal component S of the above geological anomaly body can be calculated by the following formula:

[0067] S = WGV;

[0068] Among them, W represents the left multiplication operator matrix, G represents the intersection operator matrix, and V represents the right multiplication operator matrix.

[0069] Step S130, determining the detection result of the underground discontinuous geological anomaly in the study area according to the effective signal components of the geological anomaly corresponding to each frequency data.

[0070] The effective signal components of each geological anomaly can be inversely transformed by Fourier to obtain the corresponding time domain signal components; then the migration algorithm is used to image each time domain signal component to obtain the detection results of the underground discontinuous geological anomaly in the study area. Among them, the migration algorithm can be set according to actual needs and is not limited here. For example, the migration algorithm specifically adopts the Kirchhoff migration algorithm.

[0071] The underground discontinuous geological anomaly detection method provided by the embodiment of the present invention can obtain three-dimensional common offset seismic data of the study area; according to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly corresponding to each frequency data is determined by using the sparse-guided optimization objective function; wherein the sparse-guided optimization objective function is used to solve the convex optimization problem; according to the effective signal component of the geological anomaly corresponding to each frequency data, the detection result of the underground discontinuous geological anomaly in the study area is determined. This underground discontinuous geological anomaly detection method based on the sparse-guided optimization objective function can effectively estimate the effective signal component of the geological anomaly in the three-dimensional common offset seismic data, reduce the interference of the ineffective signal, and thus realize the high-precision detection of the underground discontinuous geological anomaly.

[0072] For ease of understanding, the above-mentioned underground discontinuous geological anomaly detection method is introduced in detail below. Figure 2Another method for detecting underground discontinuous geological anomalies is shown in the flowchart, the method comprising the following steps S210 to S270:

[0073] Step S210, obtaining three-dimensional common offset seismic data D in the study area 0 .

[0074] Step S220, for D 0 The target frequency domain data D obtained after Fourier transform F For each frequency component in, generate corresponding diagonal matrix data D.

[0075] D=H(D F );

[0076] Where H represents the diagonal matrix transformation.

[0077] Step S230, using the data D, constructing a sparse-oriented optimization objective function to solve the optimization parameter matrix.

[0078] The problem of underground anomaly signal extraction can be regarded as a convex optimization problem. The expression of the sparse-oriented optimization objective function is as follows:

[0079]

[0080] Among them, R represents the parameter matrix to be optimized, R i represents the i-th row element of the parameter matrix, α represents the preset weight balancing item parameter, and q represents the number of rows of the parameter matrix, which is the same as the number of rows of D.

[0081] Step S240, based on the principle of dimensionality reduction, iteratively update each row element of the parameter matrix until the parameter matrix converges to obtain the optimal parameter matrix.

[0082] The update formula of the parameter matrix is ​​as follows:

[0083] R i =(1-α / ||k i ||2) * k i ;

[0084] Among them, when 1-α / ||k i When ||2>0, (1-α / ||k i ||2) * =1-α / ||k i ||2, otherwise (1-α / ||k i ||2) * =0; k i Represents an array sequence, which can be expressed as:

[0085]

[0086] Among them, D i′ represents the j-th column element of D, D l′ represents the l-th column element of D, R l Represents the l-th row element of the parameter matrix.

[0087] Specifically, during each iterative update of the parameter matrix, each row element of the parameter matrix can be updated in turn, and when the current row elements are updated, the elements of other current rows will be used; after completing one update of the parameter matrix, the objective function value can be calculated based on the optimization objective function, and based on the objective function value, it can be judged whether the parameter matrix has converged; if not, the iteration continues; if it has converged, the iteration can be stopped and the current parameter matrix can be used as the optimal parameter matrix.

[0088] Step S250, constructing a left multiplication operator matrix W using the non-zero row numbers of the optimal parameter matrix.

[0089] If the i-th row element of the optimal parameter matrix R is a non-zero vector, the i-th column element of the data D is used to construct the left multiplication operator matrix W.

[0090] Step S260, through the transposition operation of D, a right multiplication operator matrix and an intersection operator matrix are constructed based on the non-zero row numbers of the optimal parameter matrix to restore the effective signal of the geological anomaly body.

[0091] By transposing the original data D, the rows and columns of the data can be interchanged, thereby realizing the selection of the row elements of the data, constructing the corresponding right multiplication operator matrix V, taking the intersection data of the matrix W and V to construct the intersection operator matrix G, and then recovering the effective signal component S of the geological anomaly.

[0092] S=WGV.

[0093] Step S270, imaging the effective signal data through iterative calculation of frequency components combined with Kirchhoff migration algorithm to obtain high-precision detection results of underground discontinuous geological anomalies.

[0094] Iterative calculation is performed on each frequency component of the original data to obtain the effective signal components of the geological anomaly of all frequency components. Combined with the migration algorithm, high-precision imaging of underground discontinuous geological bodies can be achieved.

[0095] This discontinuous geological body imaging method based on sparse-guided optimization objective function can effectively estimate the discontinuous geological body signal components in seismic data, which is conducive to the high-precision detection of underground discontinuous geological anomalies. This method can effectively extract effective signals of underground anomalies and reduce the interference of ineffective signals. It is suitable for geological exploration, seismic monitoring and engineering safety assessment, and has important scientific research and application value.

[0096] Corresponding to the above-mentioned underground discontinuous geological anomaly detection method, the embodiment of the present invention also provides an underground discontinuous geological anomaly detection device. Figure 3 The schematic diagram of the structure of a device for detecting underground discontinuous geological anomalies is shown, and the device comprises:

[0097] Data acquisition module 301, used to acquire three-dimensional common offset seismic data of the study area;

[0098] The first determination module 302 is used to determine the effective signal component of the geological anomaly body corresponding to each frequency data of the three-dimensional common offset seismic data by using a sparse-oriented optimization objective function; wherein the sparse-oriented optimization objective function is used to solve a convex optimization problem;

[0099] The second determination module 303 is used to determine the detection result of the underground discontinuous geological anomaly in the study area according to the effective signal components of the geological anomaly corresponding to each frequency data.

[0100] The underground discontinuous geological anomaly detection device provided by the embodiment of the present invention can obtain three-dimensional common offset seismic data of the study area; according to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly corresponding to each frequency data is determined by using the sparse-guided optimization objective function; wherein the sparse-guided optimization objective function is used to solve the convex optimization problem; according to the effective signal component of the geological anomaly corresponding to each frequency data, the detection result of the underground discontinuous geological anomaly in the study area is determined. This underground discontinuous geological anomaly detection method based on the sparse-guided optimization objective function can effectively estimate the effective signal component of the geological anomaly in the three-dimensional common offset seismic data, reduce the interference of ineffective signals, and thus realize the high-precision detection of underground discontinuous geological anomalies.

[0101] Furthermore, the above-mentioned first determination module 302 is specifically used for: performing Fourier transform on the three-dimensional common offset seismic data to obtain target frequency domain data; according to the diagonal matrix data corresponding to each frequency data in the target frequency domain data, constructing the optimization objective function corresponding to each frequency data using the expression of the sparse-guided optimization objective function; according to the optimization objective function corresponding to each frequency data, determining the optimal parameter matrix corresponding to each frequency data; wherein the optimal parameter matrix is ​​obtained by iteratively updating each row element of the parameter matrix to be optimized in the corresponding optimization objective function based on the principle of dimensionality reduction; according to the optimal parameter matrix corresponding to each frequency data, determining the effective signal component of the geological anomaly corresponding to each frequency data.

[0102] Furthermore, the above-mentioned first determination module 302 is also used to: perform a diagonal matrix transformation on each frequency data to obtain the diagonal matrix data corresponding to each frequency data; substitute the diagonal matrix data corresponding to each frequency data into the expression of the sparse-guided optimization objective function to obtain the optimization objective function corresponding to each frequency data.

[0103] Furthermore, the expression of the above sparse-oriented optimization objective function includes:

[0104]

[0105] Where D represents the diagonal matrix data, R represents the parameter matrix to be optimized, α represents the preset weight balancing item parameter, q represents the number of rows in the parameter matrix, and R i Represents the i-th row element of the parameter matrix.

[0106] Furthermore, the first determination module 302 is further used to iteratively update each row element of the parameter matrix based on the principle of dimensionality reduction by using the following formula in combination with the optimization objective function corresponding to each frequency data until the parameter matrix converges to obtain the optimal parameter matrix corresponding to each frequency data:

[0107] R i =(1-α / ||k i ||2) * k i ;

[0108]

[0109] Among them, when 1-α / ||k i When ||2>0, (1-α / ||k i ||2) * =1-α / ||k i ||2, otherwise (1-α / ||k i ||2) * =0; R i represents the i-th row element of the parameter matrix, α represents the preset weight balancing item parameter, k i represents an array sequence, D represents diagonal matrix data, D i′ represents the j-th column element of D, D l′ represents the l-th column element of D, R l Represents the l-th row element of the parameter matrix.

[0110] Furthermore, the first determination module 302 is also used to: construct a left multiplication operator matrix, a right multiplication operator matrix and an intersection operator matrix corresponding to each frequency data according to the non-zero row number of the optimal parameter matrix corresponding to each frequency data; wherein the left multiplication operator matrix is ​​composed of the m-th column elements in the diagonal matrix data corresponding to the corresponding frequency data, the right multiplication operator matrix is ​​composed of the m-th column elements of the diagonal matrix data corresponding to the corresponding frequency data after transposition operation, m is the non-zero row number of the corresponding optimal parameter matrix, and the intersection operator matrix is ​​composed of the intersection data of the left multiplication operator matrix and the right multiplication operator matrix; according to the left multiplication operator matrix, the right multiplication operator matrix and the intersection operator matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is calculated.

[0111] Furthermore, the second determination module 303 is specifically used to: perform inverse Fourier transform on the effective signal components of each geological anomaly to obtain corresponding time domain signal components; and use an offset algorithm to image each time domain signal component to obtain the detection results of underground discontinuous geological anomalies in the study area.

[0112] The underground discontinuous geological anomaly detection device provided in this embodiment has the same implementation principle and technical effects as those of the aforementioned underground discontinuous geological anomaly detection method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the underground discontinuous geological anomaly detection device, reference may be made to the corresponding contents in the aforementioned underground discontinuous geological anomaly detection method embodiment.

[0113] like Figure 4 As shown, an electronic device 400 provided in an embodiment of the present invention includes: a processor 401, a memory 402 and a bus, the memory 402 stores a computer program that can be run on the processor 401, when the electronic device 400 is running, the processor 401 and the memory 402 communicate through the bus, and the processor 401 executes the computer program to implement the above-mentioned underground discontinuous geological anomaly detection method.

[0114] Specifically, the memory 402 and the processor 401 can be general-purpose memories and processors, which are not specifically limited here.

[0115] The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the underground discontinuous geological anomaly detection method in the above method embodiment is executed. The computer-readable storage medium includes: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a RAM, a magnetic disk or an optical disk, and other media that can store program codes.

[0116] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0117] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limiting, and thus other examples of the exemplary embodiments may have different values.

[0118] The flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and a part of a module, a program segment or a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of the boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules 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 communication interfaces, and the indirect coupling or communication connection of devices or modules can be electrical, mechanical or other forms.

[0120] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0121] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting underground discontinuous geological anomalies, characterized in that: include: Acquire three-dimensional common-offset seismic data in the study area; According to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined by using a sparse-oriented optimization objective function; wherein the sparse-oriented optimization objective function is used to solve a convex optimization problem; The detection result of the underground discontinuous geological anomaly in the study area is determined according to the effective signal components of the geological anomaly corresponding to each of the frequency data.

2. The method according to claim 1, characterized in that The method of determining the effective signal component of the geological anomaly body corresponding to each frequency data of the three-dimensional common offset seismic data by using a sparse-oriented optimization objective function comprises: Performing Fourier transformation on the three-dimensional common offset seismic data to obtain target frequency domain data; According to the diagonal matrix data corresponding to each frequency data in the target frequency domain data, the optimization objective function corresponding to each frequency data is constructed using the expression of the sparse-oriented optimization objective function; According to the optimization objective function corresponding to each of the frequency data, determine the optimal parameter matrix corresponding to each of the frequency data; wherein the optimal parameter matrix is ​​obtained by iteratively updating each row element of the parameter matrix to be optimized in the corresponding optimization objective function based on the principle of dimensionality reduction; According to the optimal parameter matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is determined.

3. The method according to claim 2, characterized in that The step of constructing the optimization objective function corresponding to each frequency data according to the diagonal matrix data corresponding to each frequency data in the target frequency domain data using the expression of the sparse-oriented optimization objective function comprises: Performing a diagonal matrix transformation on each of the frequency data to obtain diagonal matrix data corresponding to each of the frequency data; The diagonal matrix data corresponding to each of the frequency data is substituted into the expression of the sparse-oriented optimization objective function to obtain the optimization objective function corresponding to each of the frequency data.

4. The method according to claim 2, characterized in that: The expression of the sparse-oriented optimization objective function includes: Where D represents the diagonal matrix data, R represents the parameter matrix to be optimized, α represents the preset weight balancing item parameter, q represents the number of rows in the parameter matrix, and R i Represents the i-th row element of the parameter matrix.

5. The method according to claim 2, characterized in that: Determining the optimal parameter matrix corresponding to each frequency data according to the optimization objective function corresponding to each frequency data includes: Based on the principle of dimensionality reduction, the following formula is used in combination with the optimization objective function corresponding to each of the frequency data to iteratively update each row element of the parameter matrix until the parameter matrix converges to obtain the optimal parameter matrix corresponding to each of the frequency data: R i =(1-α / ||k i ||2) * k i ; Among them, when 1-α / ||k i When ||2>0, (1-α / ||k i ||2) * =1-α / ||k i ||2, otherwise (1-α / ||k i ||2) * =0; R i represents the i-th row element of the parameter matrix, α represents the preset weight balancing item parameter, k i represents an array sequence, D represents diagonal matrix data, D i′ represents the j-th column element of D, D l′ represents the l-th column element of D, R l Represents the l-th row element of the parameter matrix.

6. The method according to claim 2, characterized in that Determining the effective signal component of the geological anomaly body corresponding to each frequency data according to the optimal parameter matrix corresponding to each frequency data includes: According to the non-zero row sequence number of the optimal parameter matrix corresponding to each of the frequency data, a left multiplication operator matrix, a right multiplication operator matrix and an intersection operator matrix corresponding to each of the frequency data are constructed; wherein the left multiplication operator matrix is ​​composed of the m-th column elements in the diagonal matrix data corresponding to the corresponding frequency data, the right multiplication operator matrix is ​​composed of the m-th column elements after the diagonal matrix data corresponding to the corresponding frequency data is transposed, m is the non-zero row sequence number of the corresponding optimal parameter matrix, and the intersection operator matrix is ​​composed of the intersection data of the left multiplication operator matrix and the right multiplication operator matrix; According to the left multiplication operator matrix, the right multiplication operator matrix and the intersection operator matrix corresponding to each frequency data, the effective signal component of the geological anomaly body corresponding to each frequency data is calculated.

7. The method according to claim 1, characterized in that Determining the detection result of the underground discontinuous geological anomaly in the study area according to the effective signal components of the geological anomaly corresponding to each of the frequency data includes: Performing inverse Fourier transform on the effective signal components of each geological anomaly body to obtain corresponding time domain signal components; The time domain signal components are imaged using a migration algorithm to obtain the detection results of underground discontinuous geological anomalies in the study area.

8. An underground discontinuous geological anomaly detection device, characterized in that: include: A data acquisition module, used to acquire three-dimensional common offset seismic data of the study area; A first determination module is used to determine, according to each frequency data of the three-dimensional common offset seismic data, the effective signal component of the geological anomaly body corresponding to each frequency data by using a sparse-oriented optimization objective function; wherein the sparse-oriented optimization objective function is used to solve a convex optimization problem; The second determination module is used to determine the detection result of the underground discontinuous geological anomaly body in the study area according to the effective signal components of the geological anomaly body corresponding to each of the frequency data.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the method for detecting underground discontinuous geological anomalies according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for detecting underground discontinuous geological anomalies according to any one of claims 1 to 7 is executed.

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