Method and apparatus for determining anisotropic media for seismic exploration

Abstract

Embodiments of the present application provide a method and apparatus for determining anisotropic media for seismic exploration. The method comprises: determining seismic data for an area to be explored, wherein the seismic data includes wave velocity information corresponding to multiple underground depths; determining corresponding anisotropy parameters based on the wave velocity information corresponding to the multiple underground depths; inputting the anisotropy parameters and the multiple wave velocity information into an anisotropic medium prediction model to obtain a prediction result, which is used to indicate the seismic wavefield information of the area to be explored; and identifying and processing the seismic wavefield information to obtain the anisotropic medium in the area to be explored. This method maintains high stability even under strong anisotropy conditions, improving the accuracy of the processing results.

Description

Technical Field

[0001] The present application relates to the field of underground exploration technology, and in particular to a method for determining anisotropic media for seismic exploration, electronic equipment, storage medium, and program product. Background Art

[0002] Underground exploration refers to a professional activity that uses a variety of technical means to conduct comprehensive investigations and explorations of the earth's underground in order to identify underground geological structures, mineral resource distribution and their characteristics.

[0003] In existing technologies, seismic exploration technology is mainly used for underground exploration work, which is used to detect the underground medium structure through the propagation characteristics of seismic waves in the strata.

[0004] However, in existing underground exploration work, the accuracy obtained by existing technology is not accurate enough in some cases of strongly anisotropic media. Summary of the Invention

[0005] The embodiments of the present application provide a method for determining anisotropic media for seismic exploration, an electronic device, a storage medium, and a program product, so as to solve the problem of low accuracy of results obtained by seismic exploration technology in some strongly anisotropic media.

[0006] In a first aspect, an embodiment of the present application provides a method for determining an anisotropic medium for seismic exploration, the method comprising:

[0007] Determining seismic data of the area to be explored, wherein the seismic data includes: wave velocity information corresponding to multiple underground depths;

[0008] Determine corresponding anisotropy parameters based on wave velocity information corresponding to multiple underground depths;

[0009] Inputting the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, wherein the prediction result is used to indicate seismic wave field information of the area to be explored;

[0010] The seismic wave field information is identified and processed to obtain the anisotropic medium of the area to be explored.

[0011] In a possible implementation, determining corresponding anisotropy parameters according to wave velocity information corresponding to multiple underground depths includes:

[0012] For any one of the plurality of underground depths, determining a change between a plurality of wave velocities in the wave velocity information corresponding to the underground depth;

[0013] The anisotropy parameter is determined according to the change conditions corresponding to the multiple underground depths.

[0014] In one possible implementation, the seismic wavefield information includes: a high-precision imaging image of the anisotropic medium and a wavefield snapshot of the area to be explored, and the identifying and processing of the seismic wavefield information to obtain the anisotropic medium in the area to be explored includes:

[0015] Analyzing the high-precision imaging image to obtain anisotropic characteristics corresponding to the area to be explored;

[0016] determining an energy parameter corresponding to the area to be explored based on the wave field snapshot;

[0017] Based on the anisotropic characteristics and the energy parameters, an anisotropic medium corresponding to the area to be explored is determined.

[0018] In a possible implementation, before determining the seismic data of the area to be explored, the method further includes:

[0019] Determining historical seismic data of the explored area, the historical seismic data including: historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the explored area;

[0020] determining anisotropy parameters corresponding to the explored area based on a plurality of historical wave velocity information;

[0021] Inputting the anisotropy parameter of the explored area and the plurality of historical wave velocity information into a simulation model to obtain a simulation result, wherein the prediction result is used to indicate the historical seismic wave field information of the explored area;

[0022] determining a loss function of the simulation model according to the historical seismic wavefield information and the historical anisotropic medium information;

[0023] When the loss function meets a preset condition, the simulation model is determined as the anisotropic medium prediction model.

[0024] In a possible implementation, the method further includes:

[0025] When the loss function does not meet the preset condition, the model parameters of the simulation model are corrected based on the historical wave velocity information and the historical anisotropic medium information until the loss function of the corrected simulation model meets the preset condition.

[0026] In a possible implementation, before inputting the anisotropy parameter of the explored area and the plurality of historical wave velocity information into the simulation model to obtain the simulation results, the method further includes:

[0027] determining a coupled dispersion relation of qP waves and qSV waves in an anisotropic medium in the explored area;

[0028] Determining a P-wave independent dispersion relation based on the coupled dispersion relation;

[0029] Performing algebraic processing on the P-wave independent dispersion relation to obtain a P-wave independent dispersion relation including a pseudo-differential operator;

[0030] When the pseudo differential operator is within a preset value range, performing expansion processing on the pseudo differential operator to obtain an expansion result;

[0031] Based on a mapping relationship, performing conversion mapping processing on the expansion result to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain;

[0032] Based on the target result, the simulation model is constructed.

[0033] In a possible implementation, determining the loss function of the simulation model according to the historical seismic wavefield information and the historical anisotropic medium information includes:

[0034] performing data consistency processing on the simulation result and the historical anisotropic medium information;

[0035] The difference between the simulation result after data consistency processing and the historical anisotropic medium information is used as the loss function of the simulation model.

[0036] In a second aspect, an embodiment of the present application provides a device for determining anisotropic media for seismic exploration, comprising:

[0037] An acquisition module is used to determine seismic data of the area to be explored, wherein the seismic data includes: wave velocity information corresponding to multiple underground depths;

[0038] A processing module, configured to determine corresponding anisotropy parameters based on wave velocity information corresponding to a plurality of underground depths;

[0039] The processing module is further configured to input the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, wherein the prediction result is used to indicate seismic wavefield information of the area to be explored;

[0040] The processing module is further configured to perform identification processing on the seismic wave field information to obtain the anisotropic medium of the area to be explored.

[0041] In a possible implementation, the acquisition module is further configured to determine, for any one of the plurality of underground depths, a change between a plurality of wave velocities in the wave velocity information corresponding to the underground depth;

[0042] The processing module is further configured to determine the anisotropy parameter according to changes corresponding to a plurality of underground depths.

[0043] In one possible implementation, the processing module is further configured to analyze the high-precision imaging image to obtain anisotropic characteristics corresponding to the area to be explored; determine energy parameters corresponding to the area to be explored based on the wave field snapshot; and determine the anisotropic medium corresponding to the area to be explored based on the anisotropic characteristics and the energy parameters.

[0044] In a possible implementation, the acquisition module is further configured to determine historical seismic data of the explored area, wherein the historical seismic data includes historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the explored area;

[0045] The processing module is further configured to determine anisotropy parameters corresponding to the explored area based on multiple pieces of historical wave velocity information; input the anisotropy parameters of the explored area and the multiple pieces of historical wave velocity information into a simulation model to obtain simulation results, wherein the prediction results are used to indicate historical seismic wavefield information of the explored area; determine a loss function of the simulation model based on the historical seismic wavefield information and the historical anisotropic medium information; and determine the simulation model as the anisotropic medium prediction model when the loss function meets a preset condition.

[0046] In one possible implementation, the processing module is further configured to, when the loss function does not meet the preset condition, correct the model parameters of the simulation model based on the historical wave velocity information and the historical anisotropic medium information, until the loss function of the corrected simulation model meets the preset condition.

[0047] In one possible implementation, the processing module is further used to determine the coupled dispersion relationship of qP waves and qSV waves in the anisotropic medium of the explored area; determine the independent dispersion relationship of P waves based on the coupled dispersion relationship; perform algebraic processing on the independent dispersion relationship of P waves to obtain an independent dispersion relationship of P waves containing a pseudo-differential operator; when the pseudo-differential operator is within a preset value range, perform expansion processing on the pseudo-differential operator to obtain an expansion result; based on a mapping relationship, perform conversion mapping processing on the expansion result to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain; and construct the simulation model based on the target result.

[0048] In a possible implementation, the processing module is further configured to perform data consistency processing on the simulation result and the historical anisotropic medium information; and use the difference between the simulation result after data consistency processing and the historical anisotropic medium information as the loss function of the simulation model.

[0049] In a third aspect, an embodiment of the present application provides a device for determining anisotropic media for seismic exploration, comprising:

[0050] Memory;

[0051] processor;

[0052] The memory stores computer-executable instructions;

[0053] The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method for determining anisotropic media for seismic exploration as described in the first aspect and various possible implementations of the first aspect.

[0054] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for determining anisotropic media for seismic exploration as described in the first aspect and various possible implementation methods of the first aspect.

[0055] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method for determining anisotropic media for seismic exploration as described in the first aspect and various possible implementations of the first aspect.

[0056] Embodiments of the present application provide a method, electronic device, storage medium, and program product for determining anisotropic media for seismic exploration. The method determines seismic data for the area to be explored, wherein the seismic data includes wave velocity information corresponding to multiple underground depths; determines corresponding anisotropy parameters based on the wave velocity information corresponding to the multiple underground depths; inputs the anisotropy parameters and the multiple wave velocity information into an anisotropic medium prediction model to obtain a prediction result, which is used to indicate the seismic wavefield information of the area to be explored; and identifies and processes the seismic wavefield information to obtain the anisotropic medium in the area to be explored. This method maintains high stability even under strong anisotropy conditions, improving the accuracy of the processing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0058] Figure 1 A schematic diagram of a method for determining anisotropic media for seismic exploration provided in this application Figure 1 ;

[0059] Figure 2 A schematic diagram of a method for determining anisotropic media for seismic exploration provided in this application Figure 2 ;

[0060] Figure 3 A schematic diagram of a method for determining anisotropic media for seismic exploration provided in this application Figure 3 ;

[0061] Figure 4 A schematic diagram of a method for determining anisotropic media for seismic exploration provided in this application Figure 4 ;

[0062] Figure 5 A schematic diagram of the structure of an anisotropic medium determination device for seismic exploration provided in this application Figure 1 ;

[0063] Figure 6 A schematic diagram of the structure of an anisotropic medium determination device for seismic exploration provided in this application Figure 1 .

[0064] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0065] The exemplary embodiments will be described in detail herein, with examples shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims. They are not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0066] The terms "first," "second," "third," "fourth," and so on (if any) in the description and claims of the present invention and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present invention described herein can, for example, be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, products, or apparatuses.

[0067] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described in this application as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0068] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and corresponding operation entrances must be provided for users to choose to authorize or refuse.

[0069] Underground exploration refers to a professional activity that uses a variety of technical means to conduct comprehensive investigations and explorations of the earth's underground in order to identify underground geological structures, mineral resource distribution and their characteristics. It is of great significance in resource discovery and development, geological disaster prevention and other aspects.

[0070] Seismic exploration technology is based on the fact that when seismic waves propagate underground, they will be emitted and refracted when they encounter the interface of rock layers with different medium properties. By receiving the reflected and refracted seismic waves, processing and interpreting these seismic waves, the properties and morphology of the underground rock layers can be inferred.

[0071] Seismic exploration technology mainly analyzes and processes seismic waves, obtains the dielectric properties of the underground medium based on the processing results, and infers the medium type of the area to be explored based on the dielectric properties.

[0072] In existing seismic exploration technology, when there is partially anisotropic media in the exploration area, the analysis and processing of seismic waves may cause amplitude distortion, that is, the processing of complex wave fields in the propagation direction is easily affected by numerical errors.

[0073] To address the above issues, this application provides a method for determining anisotropic media for seismic exploration. This method inputs seismic data and anisotropic parameters into an anisotropic medium prediction model to obtain prediction results. The prediction results are then analyzed and processed to determine the anisotropic media in the area to be explored. Because the processing method used in the anisotropic medium prediction model has high phase and kinematic accuracy, it remains stable under anisotropic conditions, improving the accuracy of the results.

[0074] Figure 1 The process of a method for determining anisotropic media for seismic exploration provided in an embodiment of the present application Figure 1 .like Figure 1 As shown, the method for determining anisotropic media for seismic exploration provided in this embodiment includes:

[0075] S101. Determine seismic data of a region to be explored, wherein the seismic data includes wave velocity information corresponding to multiple underground depths.

[0076] Among them, seismic data refers to various observations, detections, investigations and statistical data related to seismic activities, which mainly come from the capture and recording of seismic waves by seismic monitoring equipment. Seismic data includes but is not limited to seismic waveform data, which records the various characteristics of seismic waves during their propagation inside the earth, such as wave velocity, amplitude, spectrum, etc., and is of great significance in geological internal structure research, resource exploration and other aspects.

[0077] It can be understood that the wave velocity information corresponding to multiple underground depths reflects the propagation speed, propagation path and direction of seismic waves at different depths underground. A wave velocity information set can be established based on the wave velocity information corresponding to multiple underground depths, which is convenient for data storage and reading.

[0078] In this step, earthquake data can be obtained through earthquake monitoring networks, earthquake monitoring satellites, etc., and there is no limitation here.

[0079] S102: Determine corresponding anisotropy parameters according to wave velocity information corresponding to multiple underground depths.

[0080] Among them, anisotropy parameters are used to describe the characteristics of materials exhibiting different physical properties in different directions, and describe the influence of different directions on the propagation velocity of seismic waves in anisotropic media; they are mainly used to correct wave velocity deviations in seismic data, reduce errors in seismic imaging, and improve the resolution and accuracy of seismic imaging.

[0081] In this step, the corresponding anisotropic parameters are determined based on the wave velocity information corresponding to multiple underground depths. The corresponding anisotropic parameters can be solved by direct calculation method, iterative optimization method, and inversion method.

[0082] In one possible implementation, determining the corresponding anisotropy parameters may be achieved by an iterative optimization method, which includes:

[0083] Determine the propagation velocity data of seismic waves in different directions and establish a suitable physical model, wherein the physical model can describe the propagation behavior of seismic waves in the underground medium;

[0084] Setting an initial value of the anisotropy parameter, wherein the initial value may be an estimated value or an approximate value obtained by other means;

[0085] Constructing an objective function to measure the difference between the seismic wave velocity predicted by the physical model and the monitoring data, wherein the objective function can be constructed based on the least squares method, the maximum likelihood method or other optimization criteria;

[0086] Select an appropriate iterative optimization algorithm that continuously adjusts the value of the anisotropic parameter based on the gradient or higher-order derivative information of the objective function to minimize the objective function. Iterative optimization algorithms include the steepest descent method, Newton's method, conjugate gradient method, or genetic algorithm.

[0087] During the iteration process, reasonable constraints and restrictions are imposed on anisotropic parameters according to physical laws and actual geological conditions to accelerate the convergence of the iteration process.

[0088] The anisotropic parameters obtained by iterative optimization are introduced into the above model to obtain the prediction results, and the accuracy of the prediction results is verified.

[0089] S103: Input the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, where the prediction result is used to indicate seismic wave field information of the area to be explored.

[0090] Among them, the prediction model is constructed based on the historical seismic data of the explored area, and the prediction model is determined according to the loss function.

[0091] S104: Identify and process the seismic wave field information to obtain the anisotropic medium of the area to be explored.

[0092] The anisotropic medium is a medium whose physical properties have discovery characteristics; the seismic wave field information is identified and processed to obtain the anisotropic characteristics of the area to be explored, and the anisotropic medium of the area to be explored is obtained based on the anisotropic characteristics.

[0093] This embodiment provides a method for determining anisotropic media for seismic exploration. The method comprises determining seismic data for the area to be explored, wherein the seismic data includes wave velocity information corresponding to multiple underground depths; determining corresponding anisotropy parameters based on the wave velocity information corresponding to the multiple underground depths; inputting the anisotropy parameters and the multiple wave velocity information into an anisotropic medium prediction model to obtain a prediction result, which indicates seismic wavefield information for the area to be explored; and identifying and processing the seismic wavefield information to determine the anisotropic medium in the area to be explored. This method maintains high stability even under strong anisotropy conditions, improving the accuracy of the processing results.

[0094] Figure 2 The process of a method for determining anisotropic media for seismic exploration provided in an embodiment of the present application Figure 2 In this embodiment, the seismic wave field information includes: a high-precision imaging map of the anisotropic medium and a wave field snapshot of the area to be explored. Figure 1 Based on the embodiment, a possible implementation method for determining anisotropy parameters and identifying and processing seismic wave field information is explained. Figure 2 As shown, the method includes:

[0095] S201. For any one of the plurality of underground depths, determine a change between a plurality of wave velocities in the wave velocity information corresponding to the underground depth.

[0096] It can be understood that determining the change between multiple wave velocities in the wave velocity information corresponding to the underground depth can be used to calculate the wave velocity difference and analyze the change trend of the wave velocity.

[0097] S202: Determine the anisotropy parameter according to the changes corresponding to the multiple underground depths.

[0098] The determination of the anisotropy parameters is used to describe the fitting of wave velocities in different directions, thereby ensuring the accuracy of subsequent models.

[0099] In this step, the anisotropic parameters may be determined based on the changes corresponding to the multiple underground depths, for example, by establishing a suitable anisotropic medium model and utilizing a parameter inversion method.

[0100] S203: Input the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, where the prediction result is used to indicate seismic wave field information of the area to be explored.

[0101] Among them, step S203 is similar to the above step S103 and will not be repeated here.

[0102] S204: Analyze the high-precision imaging image to obtain anisotropic characteristics corresponding to the area to be explored.

[0103] Among them, high-precision imaging can reveal detailed information about the complex structure and properties of the underground, and the corresponding anisotropic characteristics can reflect the differences in the physical properties of the medium in different directions.

[0104] In this step, the high-precision imaging image is analyzed to obtain the anisotropic characteristics corresponding to the area to be explored. For example, the anisotropic characteristics, such as the differences in wave velocity, amplitude, phase, etc. in different directions, can be inferred by analyzing the propagation path and waveform changes of seismic waves in the area to be explored.

[0105] S205 : Determine energy parameters corresponding to the area to be explored based on the wave field snapshot.

[0106] Among them, the wave field snapshot is generated based on seismic wave data and through seismic wave forward simulation technology; the wave field snapshot is a visual representation of the propagation process of seismic waves in the medium, which can clearly show the shapes of different waveforms and the propagation laws of waves.

[0107] In this step, the energy parameters corresponding to the area to be explored are determined by the wave field snapshot, for example, by wave velocity and energy relationship, amplitude and energy relationship, reflection and transmission wave analysis, and other methods.

[0108] In a possible implementation, determining the energy parameter corresponding to the area to be explored may be achieved through a relationship between amplitude and energy. The method includes:

[0109] By observing the amplitude changes of different waveforms in the wave field snapshot, we can infer the energy in the area to be explored and calculate parameters such as total energy, energy density, and energy transfer efficiency. Among them, amplitude is an important parameter in seismic waves. It reflects the vibration intensity of seismic waves. The larger the amplitude, the greater the energy carried by the corresponding seismic waves.

[0110] S206: Determine the anisotropic medium corresponding to the area to be explored based on the anisotropic characteristics and the energy parameters.

[0111] In a possible implementation, based on the anisotropic characteristics and the energy parameter, determining the anisotropic medium corresponding to the area to be explored may be achieved by the following method, which includes:

[0112] Comparing the anisotropic characteristics and the energy parameters with known anisotropic media to preliminarily determine the type of anisotropic medium corresponding to the area to be explored;

[0113] Verify the preliminary results using geological data and obtain verification results;

[0114] The preliminarily determined medium type is revised based on the verification results to ensure the accuracy of the finally determined anisotropic medium.

[0115] This embodiment provides a method for determining anisotropic media for seismic exploration. For any one of multiple underground depths, the method determines the variation between multiple wave velocities in the wave velocity information corresponding to the underground depth; determines the anisotropy parameter based on the variation corresponding to the multiple underground depths; inputs the anisotropy parameter and the multiple wave velocity information into an anisotropic medium prediction model to obtain a prediction result, which is used to indicate the seismic wavefield information of the area to be explored; analyzes the high-precision imaging image to obtain the anisotropic characteristics corresponding to the area to be explored; determines the energy parameter corresponding to the area to be explored based on the wavefield snapshot; and determines the anisotropic medium corresponding to the area to be explored based on the anisotropic characteristics and the energy parameter. This method combines the anisotropic characteristics and the energy parameter to improve the accuracy of determining the anisotropic medium corresponding to the area to be explored.

[0116] Figure 3 The process of a method for determining anisotropic media for seismic exploration provided in an embodiment of the present application Figure 3 In this embodiment Figure 1 Based on the embodiment, a possible implementation method of the training process of the anisotropic medium prediction model is supplemented. Figure 3 As shown, the method includes:

[0117] S301: Determine historical seismic data of an explored area, where the historical seismic data includes historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the explored area.

[0118] Among them, historical anisotropic medium information involves the study and recording of different physical properties of underground internal media in different directions, mainly including information such as seismic wave velocity anisotropy and geological structure analysis. It is of great significance in understanding the internal geological structure, seismic imaging, resource exploration, geological research, etc.; historical wave velocity information includes seismic wave velocity, historical change trend of seismic wave velocity and other information.

[0119] In this step, historical anisotropic medium information can be obtained through methods such as seismic wave analysis, rock physical measurements, geological and structural analysis, geophysical measurements, and numerical simulations.

[0120] In a possible implementation, the historical anisotropic medium information of the explored area can be determined, for example, by analyzing the conversion of seismic waves on discontinuities between the crust and the mantle in a seismic wave analysis method to extract the anisotropic medium information.

[0121] S302: Determine anisotropy parameters corresponding to the explored area according to multiple historical wave velocity information.

[0122] Wherein, based on a plurality of historical wave velocity information, the anisotropy parameter corresponding to the exploration area is determined to express the historical variation trend of the wave velocity of the explored area.

[0123] In this step, determining the anisotropy parameters corresponding to the explored area can be achieved, for example, by an inversion method, a machine learning method, etc.

[0124] In a possible implementation, the anisotropy parameter corresponding to the explored area may be determined by the following method, which includes:

[0125] removing noise and outliers from the historical wave velocity information to ensure data quality;

[0126] According to the regional geological characteristics, select the appropriate anisotropic model and define the anisotropic parameters that need to be inverted;

[0127] Use the initial model to perform forward simulation of seismic wave transmission and calculate the theoretical wave velocity;

[0128] According to the difference between the measured wave velocity and the theoretical wave velocity, an anisotropic parameter is adjusted using an optimization algorithm to optimize the model;

[0129] Validate the model, evaluate the impact of anisotropy parameters on the model output, identify key parameters, and provide confidence intervals for anisotropy parameter estimates, wherein model validation can be performed using independent data sets or cross-datasets;

[0130] The anisotropy parameters corresponding to the explored area are determined based on the regional geological characteristics, the confidence interval of the anisotropy parameter estimation, and the consistency judgment between the model output results and the detection results.

[0131] S303: Input the anisotropy parameters of the explored area and the plurality of historical wave velocity information into a simulation model to obtain a simulation result, wherein the prediction result is used to indicate the historical seismic wave field information of the explored area.

[0132] The simulation model is established based on the seismic wave propagation characteristics and the anisotropic medium characteristics, and the simulation model can reflect the influence of the anisotropy of the medium on the seismic wave propagation.

[0133] S304: Determine a loss function of the simulation model according to the historical seismic wavefield information and the historical anisotropic medium information.

[0134] Among them, the loss function is a function that maps the model's prediction results to a non-negative real value, which represents the "risk" or "loss" between the predicted results and the actual results. The loss function of the simulation model is mainly used to quantify the difference between the simulation results and the actual detection results; it is used to evaluate model performance, guide model training, and model selection and tuning.

[0135] In a possible implementation, determining the loss function of the simulation model according to the historical seismic wavefield information and the historical anisotropic medium information may be achieved in the following manner, including:

[0136] Select an appropriate loss function type based on the requirements of seismic wavefield simulation, where loss function types include mean square error, absolute error, etc.

[0137] According to the difference between the target value and the predicted value, a loss function is designed, in which the historical wave field information is used as the target value and the wave field predicted by the model is used as the predicted value. In the loss function, the importance of different components of seismic waves and the influence of the anisotropy of the medium on the wave field need to be considered.

[0138] In a possible implementation, data consistency processing may be performed on the simulation result and the historical anisotropic medium information first, and then the difference between the simulation result after data consistency processing and the historical anisotropic medium information is used as the loss function.

[0139] It can be understood that if the value of the loss function is large, it means that the difference between the simulation results and the historical anisotropic medium information is large, that is, the simulation results deviate from the actual results, and the simulation accuracy of the simulation model is low;

[0140] If the value of the loss function is large, it indicates that the difference between the simulation results and the historical anisotropic medium information is large, that is, the simulation results deviate from the actual results, and the simulation accuracy of the simulation model is low.

[0141] If the value of the loss function is small, it indicates that the difference between the simulation results and the historical anisotropic medium information is small, that is, the simulation results are closer to the actual results, and the simulation accuracy of the simulation model is higher; if the value of the loss function is too small, the simulation model will be overfitted, resulting in poor generalization ability of the simulation model for new data.

[0142] S305: When the loss function meets a preset condition, the simulation model is determined as the anisotropic medium prediction model.

[0143] Among them, the preset conditions of the loss function are equivalent to the stopping criteria of model training, which are used to improve the accuracy of the model and enhance the generalization ability of the model.

[0144] In this step, the preset conditions of the loss function may be, for example, the loss function value reaching a threshold, the loss function convergence, the target accuracy or recall rate, and other preset conditions, which are not limited here.

[0145] In a possible implementation, when the loss function does not meet the preset condition, the model parameters of the simulation model are corrected based on the historical wave velocity information and the historical anisotropic medium information until the loss function of the corrected simulation model meets the preset condition.

[0146] This embodiment provides a method for determining anisotropic media for seismic exploration. The method determines historical seismic data for an already explored area, the historical seismic data including historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information for the explored area. Based on the multiple historical wave velocity information, anisotropic parameters corresponding to the explored area are determined. The anisotropic parameters and the multiple historical wave velocity information for the explored area are input into a simulation model to obtain simulation results, which are used to indicate the historical seismic wavefield information for the explored area. Based on the historical seismic wavefield information and the historical anisotropic medium information, a loss function for the simulation model is determined. When the loss function meets a preset condition, the simulation model is determined as the anisotropic medium prediction model. This method utilizes historical seismic data and preset conditions to train the simulation model, thereby improving the accuracy and versatility of the simulation model.

[0147] Figure 4 The process of a method for determining anisotropic media for seismic exploration provided in an embodiment of the present application Figure 4 In this embodiment Figure 1Based on the embodiment, a possible implementation method of the anisotropic medium prediction model construction process is supplemented. Figure 4 As shown, the method includes:

[0148] S401: Determine the coupling dispersion relationship between qP waves and qSV waves in the anisotropic medium of the explored area.

[0149] Anisotropic media are materials that exhibit different physical properties in different directions. qP waves are quasi-longitudinal waves in anisotropic media, and qSV waves are quasi-perpendicular shear waves in anisotropic media. The coupled dispersion relation of qP and qSV waves in anisotropic media describes the mutual influence and behavior of qP and qSV waves as they propagate through the medium, revealing how the velocity, path, and vibration characteristics of these two waves are affected by the anisotropic characteristics of the medium when propagating through the medium. The coupled dispersion relation of qP and qSV waves in anisotropic media is determined by the following formula:

[0150]

[0151] in, is the angular frequency, is the longitudinal wave velocity along the axis of symmetry, is the P-wave velocity along the axis of symmetry, is the P-wave velocity perpendicular to the symmetry axis, is the qP wave correction velocity, and is the Thomsen anisotropy parameter, and is the number of waves in different directions along the coordinate axis.

[0152] S402: Determine a P-wave independent dispersion relation according to the coupled dispersion relation.

[0153] The P-wave independent dispersion relation is obtained by decomposing the coupled dispersion relation expression of qP wave and qSV wave in anisotropic media to obtain the corresponding P-wave independent dispersion relation. The P-wave independent dispersion relation is as follows:

[0154]

[0155] in, and It can be expressed as:

[0156]

[0157] In the decomposition of the coupled dispersion relation for qP and qSV waves, the squared angular frequency is considered as a whole and a linear equation is solved to obtain the independent dispersion relation for P waves. This relation accurately describes the dispersion relation for pure qP waves in anisotropic media and does not include artifacts from the simulated S-wave wavefield.

[0158] S403: Perform algebraic processing on the P-wave independent dispersion relation to obtain a P-wave independent dispersion relation including a pseudo-differential operator.

[0159] The P-wave independent dispersion relation is processed algebraically to obtain the following expression of the P-wave independent dispersion relation including the pseudo differential operator:

[0160]

[0161] In this step, the algebraic processing is to extract the common part of the P-wave independent dispersion relation and obtain the P-wave independent dispersion relation expression containing the pseudo-differential operator.

[0162] Where W is the pseudo-differential operator in the P-wave independent dispersion relation expression, which is expressed as follows:

[0163]

[0164] S404 : When the pseudo differential operator is within a preset value range, perform expansion processing on the pseudo differential operator to obtain an expansion result.

[0165] Among them, when and When the pseudo differential operator is within the preset value range, the pseudo differential operator is expanded by using the Padé first-order expansion approximation to expand the pseudo differential operator, and k x With k z The expression of is processed by the square root operator to obtain the following expression:

[0166]

[0167] Among them, the Padé first-order expansion approximation for the part containing the pseudo-differential operator is as follows:

[0168]

[0169] In this step, Padé approximation is a rational function approximation method for function approximation, which approximates a given function by a rational function (i.e., a ratio of polynomials), providing better convergence and stability than polynomial approximation.

[0170] S405 . Perform conversion mapping processing on the expanded result based on a mapping relationship to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain.

[0171] The expansion result is converted and mapped to obtain the target result as follows:

[0172]

[0173] The mapping relationship between the time-space domain and the frequency-wavenumber domain is to obtain the target result by taking the high-order derivative between the velocity along the symmetry axis and the velocity perpendicular to the symmetry axis. The expression of P is:

[0174]

[0175] In this expression, Q can be discretized by finite differences to obtain the partial differential equation and solved using sparse matrix solving techniques.

[0176] S406: Construct the simulation model based on the target result.

[0177] It can be understood that the simulation model is constructed based on target results and processing methods for processing and analyzing seismic data.

[0178] This embodiment provides a method for determining anisotropic media for seismic exploration. The method comprises determining the coupled dispersion relationship of qP waves and qSV waves in the anisotropic media of the explored area; determining the independent dispersion relationship of P waves based on the coupled dispersion relationship; performing algebraic processing on the independent dispersion relationship of P waves to obtain an independent dispersion relationship of P waves containing a pseudo-differential operator; performing an expansion process on the pseudo-differential operator when the pseudo-differential operator is within a preset value range to obtain an expansion result; performing a conversion mapping process on the expansion result based on a mapping relationship to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain; and constructing a simulation model based on the target result. This method overcomes the disadvantage of amplitude distortion in strongly anisotropic media, resulting in more accurate calculation results.

[0179] Figure 5 The present application provides a device for determining anisotropic media for seismic exploration. Figure 5 As shown, an embodiment of the present application provides a device 500 for determining anisotropic media for seismic exploration, including:

[0180] An acquisition module 501 is configured to determine seismic data of a region to be explored, wherein the seismic data includes: wave velocity information corresponding to a plurality of underground depths;

[0181] The processing module 502 is used to determine corresponding anisotropy parameters according to the wave velocity information corresponding to the multiple underground depths;

[0182] The processing module 502 is further configured to input the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, wherein the prediction result is used to indicate seismic wavefield information of the area to be explored;

[0183] The processing module 502 is further configured to perform identification processing on the seismic wave field information to obtain the anisotropic medium of the area to be explored.

[0184] In a possible implementation, the acquisition module 501 is further configured to determine, for any one of the multiple underground depths, a change between multiple wave velocities in the wave velocity information corresponding to the underground depth;

[0185] The processing module 502 is further configured to determine the anisotropy parameter according to changes corresponding to multiple underground depths.

[0186] In one possible implementation, the processing module 502 is further configured to analyze the high-precision imaging image to obtain anisotropic characteristics corresponding to the area to be explored; determine energy parameters corresponding to the area to be explored based on the wave field snapshot; and determine the anisotropic medium corresponding to the area to be explored based on the anisotropic characteristics and the energy parameters.

[0187] In a possible implementation, the acquisition module 501 is further configured to determine historical seismic data of an already explored area, wherein the historical seismic data includes historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the already explored area;

[0188] The processing module 502 is further configured to determine anisotropy parameters corresponding to the explored area based on multiple pieces of historical wave velocity information; input the anisotropy parameters of the explored area and the multiple pieces of historical wave velocity information into a simulation model to obtain simulation results, wherein the prediction results are used to indicate historical seismic wavefield information of the explored area; determine a loss function of the simulation model based on the historical seismic wavefield information and the historical anisotropic medium information; and determine the simulation model as the anisotropic medium prediction model when the loss function meets a preset condition.

[0189] In one possible implementation, the processing module 502 is further used to correct the model parameters of the simulation model based on the historical wave velocity information and the historical anisotropic medium information when the loss function does not meet the preset condition, until the loss function of the corrected simulation model meets the preset condition.

[0190] In one possible implementation, the processing module 502 is further used to determine the coupled dispersion relationship of qP waves and qSV waves in the anisotropic medium of the explored area; determine the independent dispersion relationship of P waves based on the coupled dispersion relationship; perform algebraic processing on the independent dispersion relationship of P waves to obtain the independent dispersion relationship of P waves containing a pseudo-differential operator; when the pseudo-differential operator is within a preset value range, perform expansion processing on the pseudo-differential operator to obtain an expansion result; based on a mapping relationship, perform conversion mapping processing on the expansion result to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain; and construct the simulation model based on the target result.

[0191] In a possible implementation, the processing module 502 is further configured to perform data consistency processing on the simulation result and the historical anisotropic medium information; and use the difference between the simulation result after data consistency processing and the historical anisotropic medium information as the loss function of the simulation model.

[0192] The present embodiment provides a device for determining anisotropic media for seismic exploration, which can execute the method for determining anisotropic media for seismic exploration provided in the above method embodiment. The implementation principles and technical effects are similar and are not described in detail in this embodiment.

[0193] Figure 6 This is a schematic diagram of a device for determining anisotropic media for seismic exploration provided by this application. Figure 6 As shown, the anisotropic medium determination device 600 for seismic exploration provided by the present application includes: a receiver 601 , a transmitter 602 , a processor 603 and a memory 604 .

[0194] Transmitter 602, used to send instructions and data;

[0195] Memory 604, for storing computer-executable instructions;

[0196] The processor 603 is configured to execute computer-executable instructions stored in the memory 604 to implement the steps of the method for determining anisotropic media for seismic exploration in the above embodiment. For details, please refer to the relevant description in the embodiment of the method for determining anisotropic media for seismic exploration.

[0197] Optionally, the memory 604 may be independent or integrated with the processor 603 .

[0198] When the memory 604 is independently provided, the electronic device further includes a bus for connecting the memory 604 and the processor 603 .

[0199] The present application also provides a computer-readable storage medium, which stores computer-executable instructions. When a processor executes the computer-executable instructions, the method for determining anisotropic media for seismic exploration performed by the above-mentioned device for determining anisotropic media for seismic exploration is implemented.

[0200] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the aforementioned method for determining anisotropic media for seismic exploration. For details, please refer to the relevant description in the aforementioned embodiment of the method for determining anisotropic media for seismic exploration.

[0201] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0202] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0203] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0204] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0205] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0206] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0207] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0208] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0209] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0210] 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.

[0211] If a function is implemented as 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, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0212] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0213] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for determining anisotropic media for seismic exploration, characterized in that: include: Determining historical seismic data of the explored area, the historical seismic data including: historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the explored area; determining anisotropy parameters corresponding to the explored area based on a plurality of historical wave velocity information; determining a coupled dispersion relation of qP waves and qSV waves in an anisotropic medium in the explored area; Determining a P-wave independent dispersion relation based on the coupled dispersion relation; Performing algebraic processing on the P-wave independent dispersion relation to obtain a P-wave independent dispersion relation including a pseudo-differential operator; When the pseudo differential operator is within a preset value range, performing expansion processing on the pseudo differential operator to obtain an expansion result; Based on a mapping relationship, performing conversion mapping processing on the expansion result to obtain a target result, wherein the mapping relationship is a mapping relationship between the time-space domain and the frequency-wavenumber domain; constructing a simulation model based on the target results; Inputting the anisotropy parameter of the explored area and the plurality of historical wave velocity information into the simulation model to obtain a simulation result, wherein the simulation result is used to indicate the historical seismic wave field information of the explored area; determining a loss function of the simulation model according to the simulation results and the historical anisotropic medium information; When the loss function meets a preset condition, determining the simulation model as the anisotropic medium prediction model; Determining seismic data of the area to be explored, wherein the seismic data includes: wave velocity information corresponding to multiple underground depths; Determine corresponding anisotropy parameters based on wave velocity information corresponding to multiple underground depths; Inputting the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, wherein the prediction result is used to indicate seismic wave field information of the area to be explored; The seismic wave field information is identified and processed to obtain the anisotropic medium of the area to be explored.

2. The method according to claim 1, characterized in that The determining of corresponding anisotropy parameters according to the wave velocity information corresponding to the multiple underground depths includes: For any one of the plurality of underground depths, determining a change between a plurality of wave velocities in the wave velocity information corresponding to the underground depth; The anisotropy parameter is determined according to the change conditions corresponding to the multiple underground depths.

3. The method according to claim 1, characterized in that The seismic wavefield information includes: a high-precision imaging image of the anisotropic medium and a wavefield snapshot of the area to be explored. The identification and processing of the seismic wavefield information to obtain the anisotropic medium of the area to be explored includes: Analyzing the high-precision imaging image to obtain anisotropic characteristics corresponding to the area to be explored; determining an energy parameter corresponding to the area to be explored based on the wave field snapshot; Based on the anisotropic characteristics and the energy parameters, an anisotropic medium corresponding to the area to be explored is determined.

4. The method according to claim 3, characterized in that The method further comprises: When the loss function does not meet the preset condition, the model parameters of the simulation model are corrected based on the historical wave velocity information and the historical anisotropic medium information until the loss function of the corrected simulation model meets the preset condition.

5. The method according to claim 1, wherein determining the loss function of the simulation model based on the historical seismic wavefield information and the historical anisotropic medium information comprises: performing data consistency processing on the simulation result and the historical anisotropic medium information; The difference between the simulation result after data consistency processing and the historical anisotropic medium information is used as the loss function of the simulation model.

6. A device for determining anisotropic media for seismic exploration, characterized in that: include: An acquisition module is used to determine historical seismic data of an explored area, wherein the historical seismic data includes historical wave velocity information corresponding to multiple underground depths and historical anisotropic medium information of the explored area; a processing module, configured to determine anisotropy parameters corresponding to the explored area based on multiple historical wave velocity information; input the anisotropy parameters of the explored area and the multiple historical wave velocity information into a simulation model to obtain simulation results, wherein the simulation results are used to indicate historical seismic wavefield information of the explored area; determine a loss function of the simulation model based on the historical seismic wavefield information and the historical anisotropic medium information; and determine the simulation model as the anisotropic medium prediction model if the loss function meets a preset condition; The processing module is further configured to determine a coupled dispersion relationship between qP waves and qSV waves in the anisotropic medium of the explored area; determine a P-wave independent dispersion relationship based on the coupled dispersion relationship; perform algebraic processing on the P-wave independent dispersion relationship to obtain a P-wave independent dispersion relationship including a pseudo-differential operator; perform expansion processing on the pseudo-differential operator when the pseudo-differential operator is within a preset value range to obtain an expansion result; perform conversion mapping processing on the expansion result based on a mapping relationship to obtain a target result, wherein the mapping relationship is a mapping relationship between a time-space domain and a frequency-wavenumber domain; and construct the simulation model based on the target result; The acquisition module is further configured to determine seismic data of the area to be explored, wherein the seismic data includes: wave velocity information corresponding to multiple underground depths; The processing module is further configured to determine corresponding anisotropy parameters based on wave velocity information corresponding to a plurality of underground depths; The processing module is further configured to input the anisotropy parameter and the plurality of wave velocity information into an anisotropic medium prediction model to obtain a prediction result, wherein the prediction result is used to indicate seismic wavefield information of the area to be explored; The processing module is further configured to perform identification processing on the seismic wave field information to obtain the anisotropic medium of the area to be explored.

7. A device for determining anisotropic media for seismic exploration, characterized in that: include: Memory; processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method for determining anisotropic media for seismic exploration according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for determining anisotropic media for seismic exploration according to any one of claims 1 to 5.

9. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method for determining anisotropic media for seismic exploration according to any one of claims 1 to 5.

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