A VTI medium accompanied state method and system for travel time multi-parameter tomography imaging

Abstract

The application relates to a VTI medium accompanying state method travel time multi-parameter tomography imaging method and system, which comprises the following steps: 1) acquiring observed initial travel time of original seismic data, determining an initial velocity and anisotropy parameter model and an observation system file; 2) calculating a single-shot theoretical travel time field, and determining a single-shot objective function and a single-shot accompanying field; 3) calculating a single-shot multi-parameter gradient of the VTI medium; 4) calculating a single-shot preconditioning illumination compensation operator; 5) obtaining a VTI multi-parameter tomography imaging result according to the objective function, the multi-parameter gradient and the preconditioning illumination compensation operator of all shots, and judging whether the VTI multi-parameter tomography imaging result meets the requirements; if yes, the VTI multi-parameter tomography imaging result is output; otherwise, the step 6) is entered; and 6) obtaining an updated velocity and anisotropy parameter model. The application can be widely applied in the field of near-surface anisotropy parameter modeling.

Description

Technical Field

[0001] This invention relates to the field of near-surface anisotropic parameter modeling, and in particular to a method and system for travel-time multiparameter tomography of VTI (transversely isotropic with a vertical axis of symmetry) media with accompanying state method. Background Technology

[0002] Subsurface rock strata generally exhibit anisotropic characteristics, and this anisotropy significantly impacts the kinematic and dynamic properties of seismic wave propagation. Therefore, constructing anisotropic parameter models is crucial for seismic data processing and imaging. In recent years, with the development of seismic exploration and observation methods such as wide-width and high-height seismographs, seafloor nodes (OBNs), and offshore seismometers (OBSs), the impact of anisotropy on seismic data with large offsets has become particularly prominent. First-arrival waves carry rich information on subsurface velocity and anisotropic parameters during their propagation in the near-surface medium. Therefore, using first-arrival information to establish subsurface velocity parameters and VTI anisotropic models is a common method in seismic exploration. Among these methods, travel-time information from first-arrival waves is the most robust and has the lowest dependence on the initial model, making travel-time tomography (LTT) frequently used to establish long-wavelength subsurface velocity and VTI anisotropic parameter models.

[0003] Based on different forward modeling engines, three main categories of travel time tomography methods have emerged: ray tomography based on ray tracing, wave equation travel time tomography or finite frequency travel time tomography based on wave equation simulation, and the adjoint state method travel time tomography based on the equation function to calculate travel time. These three types of travel time tomography methods all face a problem in VTI medium multi-parameter inversion that is different from the inversion of the first arrival travel time single velocity parameter in isotropic media. That is, the sensitivity of travel time information to different parameters changes with the angle, that is, the travel time information is not the same for multi-parameter angular illumination. This problem directly affects the iterative update of VTI medium multi-parameter travel time inversion.

[0004] In the multi-parameter inversion of travel time in VTI media using ray tomography and wave equations, some scholars have conducted preliminary research on the angle illumination problem. In the ray-tracing-based multi-parameter inversion method for VTI media, researchers, starting from the Christoffel matrix, were the first to derive the first derivatives of the stiffness coefficient with respect to phase velocity and group velocity. This theoretically reveals the characteristics of the sensitivity of first-arrival wave travel time information to multiple parameters in VTI media as a function of angle, providing theoretical analytical solutions for the sensitivity of qP, qSH, and qSV first-arrival wave travel time information to multiple parameters as a function of angle. Based on the qP wave group velocity or its approximate expression, an asymptotic approximate solution for the sensitivity of qP wave travel time information to the multi-parameter sensitive core of VTI media as a function of angle can also be obtained. Based on the acoustic qP wave wave equation in VTI media, expressions for the multi-parameter sensitive core of qP wave finite-frequency or wave equation travel time inversion in VTI media can be obtained. Then, by designing observation methods with different transmission angles, the sensitivity of multiple parameters at different transmission angles is numerically calculated and analyzed under illumination conditions. While the aforementioned methods have revealed the problem of non-uniform angular illumination, its adverse effects on inversion and how to compensate for angular illumination to improve inversion accuracy have not been thoroughly investigated. Unlike ray tomography and wave equation travel-time tomography, the AST method (travel-time multi-parameter tomography based on the adjoint state method) does not require ray tracing and Fréchet derivative matrix calculation, has low memory requirements, and is particularly suitable for parallel computing. It has been applied to joint transmission and reflection velocity modeling, regional velocity modeling, and VTI medium multi-parameter modeling.

[0005] However, traditional AST methods define the objective function based on area integrals, resulting in adjoint equations that depend on the surface normal. This means that geophones can only be defined on the model surface and not inside the model. Consequently, AST methods are unsuitable for various observational data, such as inter-well, seafloor OBS, and vertical seismic profile (VSP) data, where geophones are located inside the model. In VTI media, numerical calculations of multi-parameter sensitive kernels also require geophones to be placed inside the model. Therefore, in VTI media, traditional AST methods cannot perform angular illumination analysis, let alone illumination compensation. Summary of the Invention

[0006] To address the aforementioned problems, the purpose of this invention is to provide a VTI medium-adjoint state method for travel-time multi-parameter tomography imaging and a system capable of performing angle illumination analysis and illumination compensation.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, it provides a VTI medium-accompanied state method for travel-time multi-parameter tomography, comprising:

[0008] 1) Obtain the first arrival travel time of the raw seismic data, determine the initial velocity and anisotropic parameter model, and the observation system file;

[0009] 2) Based on the velocity and anisotropic parameter model, calculate the theoretical travel time field of a single shot, and based on the observation system file, determine the target function and the adjoint field of a single shot according to the observed first arrival travel time;

[0010] 3) Calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model;

[0011] 4) Calculate the preconditioning illumination compensation operator for a single shot based on the observed first arrival travel time and the theoretical travel time field of a single shot;

[0012] 5) Sum the target functions, multi-parameter gradients, and preconditioning illumination compensation operators of all guns to obtain the VTI multi-parameter tomography results. Determine whether the VTI multi-parameter tomography results meet the requirements. If they do, output the VTI multi-parameter tomography results; otherwise, proceed to step 6).

[0013] 6) Based on the accompanying field of a single shot and the preconditioning illumination compensation operator of all shots, obtain the updated velocity and anisotropic parameter model, and proceed to step 2) until the VTI multiparameter tomography results meet the requirements.

[0014] Further, in step 2), the theoretical travel time field of a single shot is calculated based on the velocity and anisotropic parameter model, and the target function and adjoint field of a single shot are determined based on the observation system file and the observed first arrival travel time, including:

[0015] A fast scan algorithm is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model;

[0016] Based on the observation system file, the target function of a single shot is determined according to the observed first arrival travel time and the theoretical travel time field of a single shot;

[0017] Based on the observed first arrival travel time and the theoretical travel time field of a single shot, the accompanying field of a single shot is determined.

[0018] Furthermore, the theoretical travel time field T(x) of the single gun is calculated based on the following functional equation:

[0019]

[0020] Where F(v0,ε,δ,T) is the governing equation; x and z are the x and y coordinates of the point in the underground space, respectively; v0 is the velocity; and ε and δ are the Thomsen anisotropy parameters.

[0021] Furthermore, the determination of the single-shot target function based on the observation system file, according to the observed first arrival travel time and the theoretical travel time field of a single shot, includes:

[0022] Calculate the travel time difference between the observed first arrival travel time and the theoretical travel time field for a single shot;

[0023] Based on the observation system file and the travel time difference of a single shot, the single-shot target function J(v0,ε,δ) is obtained:

[0024]

[0025] Where, r i The position of the i-th detector point is represented by ; x represents any position within the computational region Ω′, using the δ function. Calculation of the objective function at the detector point within the control region Ω′; T(v0,ε,δ,x) is the theoretically calculated first arrival travel time.

[0026] Furthermore, by using the following adjoint state equation, the travel time difference of a single shot is back-projected into the subsurface multi-parameter model space to obtain the adjoint field λ(x) of a single shot:

[0027]

[0028]

[0029] Here, N(x) is the coefficient matrix of the adjoint field λ(x).

[0030] Further, in step 4), based on the observed first arrival travel time and the theoretical travel time field of a single shot, the preconditioning illumination compensation operator for a single shot is calculated, including:

[0031] Set the travel time difference of a single gun to a fixed constant;

[0032] Based on a fixed constant, the adjoint field at the detector location is initialized and an anti-propagation source is injected.

[0033] The fast scanning method is used to propagate the associated field at the receiver point to the underground model. Scanning is performed in different directions to calculate the associated field at each point in the entire underground model space, thus obtaining the preconditioning illumination compensation operator for a single shot.

[0034] Further, in step 6), based on the accompanying field of a single shot and the preconditioning illumination compensation operator for all shots, an updated velocity and anisotropy parameter model is obtained, and the process proceeds to step 2), until the VTI multiparameter tomography results meet the requirements, including:

[0035] Based on the accompanying field of a single shot and the preconditional illumination compensation operator of all shots, illumination compensation is performed on the original multi-parameter gradient to obtain the illumination-compensated gradient.

[0036] Based on the gradient after illumination compensation, the updated velocity and anisotropic parameter models are obtained, and the process proceeds to step 2) until the VTI multiparameter tomography results meet the requirements, thus obtaining the final VTI multiparameter tomography results.

[0037] Secondly, a VTI medium-accompanied state method travel-time multi-parameter tomography system is provided, comprising:

[0038] The data acquisition module is used to acquire the first arrival travel times of the raw seismic data, determine the initial velocity and anisotropic parameter model, and the observation system file;

[0039] The theoretical travel time field calculation module is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model, and to determine the target function and the adjoint field of a single shot based on the observation system file and the first arrival travel time of the observation.

[0040] The gradient calculation module is used to calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model.

[0041] The illumination compensation operator calculation module is used to calculate the precondition illumination compensation operator for a single shot based on the observed first arrival travel time and the theoretical travel time field of a single shot.

[0042] The judgment module is used to obtain the VTI multi-parameter tomography results based on the target function, multi-parameter gradient and preconditioning illumination compensation operator of all shots, and to determine whether the VTI multi-parameter tomography results meet the requirements. If they do, the VTI multi-parameter tomography results are output.

[0043] The illumination compensation module is used to obtain updated velocity and anisotropic parameter models based on the accompanying field of a single shot and the preconditional illumination compensation operators of all shots.

[0044] Thirdly, a processing device is provided, including computer program instructions, wherein when the computer program instructions are executed by the processing device, they are used to implement the steps corresponding to the above-described VTI medium-accompanied state method travel-time multi-parameter tomography method.

[0045] Fourthly, a computer-readable storage medium is provided, wherein computer program instructions are stored on the computer-readable storage medium, wherein when the computer program instructions are executed by a processor, they are used to implement the steps corresponding to the above-described VTI medium-accompanied state method for travel-time multiparameter tomography.

[0046] The present invention has the following advantages due to the adoption of the above technical solutions:

[0047] 1. This invention has low computational cost and high computational efficiency. It does not require forward modeling of the wave equation, nor does it require ray tracing and calculation of the Fréchet derivative matrix. Each iteration only requires solving the Eikonal equation and calculating the adjoint equation once.

[0048] 2. This invention has low memory usage, fast computation, and is easy to parallelize. Firstly, it saves a lot of computation time when solving the Eikonal equation compared to the simulation of the wave equation. Secondly, it has low memory usage and can easily achieve parallel computation in a single-shot cycle.

[0049] 3. This invention can easily apply preconditions, and only adds one calculation of the adjoint equation to obtain the precondition operator for angle illumination compensation, thus overcoming the problem of uneven illumination of multiple parameters in traditional methods and greatly improving the inversion accuracy.

[0050] This invention can be widely applied in the field of near-surface anisotropic parameter modeling. Attached Figure Description

[0051] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0052] Figure 1 This is a schematic diagram of a method flow provided in an embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of a real VTI multi-parameter model provided in an embodiment of the present invention, wherein, Figure 2 (a) is a schematic diagram of the parameter V0 model. Figure 2 (b) is a schematic diagram of the parameter ε model. Figure 2 (c) is a schematic diagram of the parametric δ model;

[0054] Figure 3 This is a schematic diagram of a VTI multi-parameter model inverted using a conventional method according to an embodiment of the present invention, wherein, Figure 3 (a) is a schematic diagram of the parameter v0 model. Figure 3 (b) is a schematic diagram of the parameter ε model. Figure 3 (c) is a schematic diagram of the parametric δ model;

[0055] Figure 4 This is a schematic diagram of a VTI multi-parameter model inverted using the present invention, provided in an embodiment of the present invention. Figure 4 (a) is a schematic diagram of the parameter v0 model. Figure 4 (b) is a schematic diagram of the parameter ε model. Figure 4(c) is a schematic diagram of the parametric δ model;

[0056] Figure 5 This is a schematic diagram of a VTI multi-parameter profile at x = 7 km obtained by inversion using the present invention, provided in an embodiment of the present invention. Figure 5 (a) is a schematic diagram of the parameter v0 model. Figure 5 (b) is a schematic diagram of the parameter ε model. Figure 5 (c) is a schematic diagram of the parametric δ model;

[0057] Figure 6 This is a schematic diagram of a line drawing obtained by inversion using the present invention, provided in an embodiment of the present invention, wherein, Figure 6 (a) is a schematic diagram of the velocity model drawing. Figure 6 (b) is a schematic diagram of the inversion ε model;

[0058] Figure 7 This is a schematic diagram of the initial model provided in an embodiment of the present invention and the RTM imaging results of the PAST inversion model of the present invention, wherein, Figure 7 (a) is a schematic diagram of the initial model. Figure 7 (b) is a schematic diagram of the RTM imaging results of the PAST inversion model of the present invention. Detailed Implementation

[0059] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0060] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0061] Although terms such as first, second, third, etc., may be used in this document to describe multiple elements, components, regions, layers, and / or segments, these elements, components, regions, layers, and / or segments should not be limited by these terms. These terms may be used only to distinguish one element, component, region, layer, or segment from another. Unless the context clearly indicates otherwise, terms such as "first," "second," and other numerical terms used herein do not imply order or sequence. Therefore, the first element, component, region, layer, or segment discussed below may be referred to as the second element, component, region, layer, or segment without departing from the teachings of the exemplary embodiments.

[0062] Anisotropy is prevalent in subsurface rock strata, and the anisotropy of the medium has a significant impact on the kinematic and dynamic properties of seismic wave propagation. Among them, VTI (Vascular Inertial Transient) media, which are transversely isotropic with a vertical axis of symmetry formed by geological processes such as sedimentation and compaction, are the most typical type of anisotropic media. VTI media are common in near-surface media, and their impact on large-offset seismic data from surface seismic exploration is particularly prominent. Multi-parameter travel-time inversion in VTI media faces the problem of sensitivity angle dependence. This angular illumination non-uniformity in multi-parameter travel-time inversion in VTI media seriously hinders the simultaneous and effective updating of multiple parameters, reducing the accuracy of anisotropic multi-parameter inversion.

[0063] The present invention provides a VTI medium accompanied state method travel time multi-parameter tomography imaging method and system. Firstly, it redefines the objective function of the AST method based on volume integrals, overcoming the limitations of traditional AST methods where the accompanying equation depends on the surface normal vector and the detector can only be defined on the model surface. This allows it to be applied to seismic data from various observation methods, including surface, well-to-well, seafloor, and VSP. Furthermore, the invention reveals the drawbacks of simultaneous AST multi-parameter inversion in VTI media, such as angular illumination inhomogeneity (dominant inversion region), ray density illumination inhomogeneity, and gradient singularities. To address the angular illumination problem, illumination compensation is achieved by applying a Hessian diagonal element approximation preconditioner to the gradient, thereby realizing multi-parameter angular illumination compensation and deep ray density compensation. This eliminates singularities in the original gradient and improves the accuracy of first-arrival travel time anisotropy multi-parameter inversion in VTI media.

[0064] Example 1

[0065] like Figure 1 As shown, this embodiment provides a VTI medium-accompanied state method for travel-time multi-parameter tomography, including the following steps:

[0066] 1) Set the number of loop iterations (LOOP).

[0067] 2) Data preprocessing: Obtaining the first arrival travel time T of the raw seismic data.obs The initial velocity and anisotropic parameter model (v0, ε, δ) and the observation system file were determined, where v0 is the velocity, ε and δ are the Thomsen anisotropic parameters, and the observation system file includes the total number of shots and receivers, as well as the position coordinates of each shot point and receiver point and the first arrival travel time T. obs .

[0068] 3) Set LOOP=1, enter the shot cycle, and use the fast scan algorithm to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model.

[0069] Specifically, taking a single shot as a unit, the theoretical travel time field T(x) of a single shot is calculated based on the following equation (1):

[0070]

[0071] Where F(v0,ε,δ,T) is the governing equation, i.e., the Eikonal equation; x and z are the x and y coordinates of the underground space points, respectively.

[0072] 4) Based on the observation system file, according to the observation first arrival travel time T obs Based on the theoretical travel time field of a single gun, the objective function of a single gun is determined as follows:

[0073] 4.1) Calculate the first arrival travel time T of a single shot. obs The time difference T(x) between (x) and the theoretical time field T(x) is T(x)-T obs (x).

[0074] 4.2) Based on the observation system file, according to the travel time difference of a single shot T(x)-T obs (x), thus obtaining the single-shot objective function J(v0,ε,δ):

[0075]

[0076] Where, r i The position of the i-th receiver point (there are N receiver points in total); x represents any position within the calculation region Ω′, using the δ function. Calculation of the objective function at the detector point within the control region Ω′; T(v0,ε,δ,x) is the theoretically calculated first arrival travel time.

[0077] 5) The adjoint state equation is adopted, based on the observed first arrival travel time T. obs Based on the theoretical travel time field of a single shot, the adjoint field λ(x) of the single shot is determined.

[0078] Specifically, using the adjoint state equations (3) and (4), the travel time difference T(x)-T of a single gun is expressed as follows: obs(x) is projected back onto the underground multi-parameter model space to obtain the adjoint field λ(x) of a single shot:

[0079]

[0080]

[0081] Where N(x) is the coefficient matrix of the adjoint field λ(x), and:

[0082]

[0083] 6) Calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model.

[0084] Specifically, the single-shot multi-parameter gradient of the VTI medium is calculated using the multi-parameter gradient formula in the VTI medium.

[0085]

[0086] 7) The adjoint state equation is adopted, based on the observed first arrival travel time T. obs Based on the theoretical travel time field of a single shot, the preconditioning illumination compensation operator for a single shot is calculated as follows:

[0087] 7.1) Within a single-shot cycle, the travel time difference of a single shot, T(x) - T obs (x) is set to a fixed constant T. const For example, the constant is set to 1.

[0088] 7.2) Based on a fixed constant T const The adjoint field λ at the location of the receiver point p (x) is initialized and the reverse propagation source is injected.

[0089] Specifically, the adjoint field λ at the receiver location is obtained using the following formula. p (x) Perform initial numerical calculations:

[0090]

[0091] 7.3) Using a fast scanning method, the adjoint field λ at the receiver location is obtained. p (x) propagates into the underground model, scans in different directions, and calculates the adjoint field λ at each point in the entire underground model space. p (x), that is, the preconditioning compensation operator λ for a single shot. p (x):

[0092]

[0093] 8) After the single-shot cycle ends, the VTI multi-parameter tomography results of all shots are summed, reduced, and accumulated to obtain the VTI multi-parameter tomography results, namely the target function value, multi-parameter gradient, and preconditioning illumination compensation operator.

[0094] 9) Determine whether the objective function value of this iteration meets the requirements. If not, proceed to step 10); if it does, end the iteration and output the VTI multi-parameter tomography results.

[0095] Specifically, determine whether the objective function value of this iteration has decreased compared to the objective function value of the previous iteration. If it has decreased, proceed to step 10; otherwise, end the iteration.

[0096] 10) Based on the adjoint field λ(x) of a single shot and the preconditioning illumination compensation operator for all shots, apply the original multi-parameter gradient obtained in step 6). Perform illumination compensation to obtain the gradient after illumination compensation.

[0097]

[0098] 11) Based on the gradient after illumination compensation, obtain the updated velocity and anisotropic parameter model, increment LOOP by 1, and proceed to step 3) until the objective function value meets the requirements, and obtain the final VTI multiparameter tomography result.

[0099] The method of this invention has advantages over the traditional associated state method. The following detailed explanation of the VTI medium associated state method travel-time multi-parameter tomography imaging method of this invention uses the two-dimensional VTI-BP 2007 theoretical model as a real model as a specific embodiment:

[0100] like Figure 2 The diagram shown is a schematic of the two-dimensional VTI-BP 2007 theoretical model, where the actual models for the three parameters v0, ε, and δ are respectively as shown in the diagram. Figure 2 (a) Figure 2 (b) and Figure 2 (c) The initial velocity model v0 is a constant gradient velocity model, and the initial values ​​of the anisotropic parameter models ε and δ are both 0. It is evident that the initial models of the three parameters are far from the actual models. The grid number is nx = 801, nz = 116, and the grid spacing is dx = dz = 20m. 401 shot points and 801 geophones are uniformly distributed across the ground surface, with horizontal spacing of 40m and 20m between the shot points and geophones, respectively. The maximum offset is 6km. While employing the method of this invention, the traditional AST method is also applied simultaneously to highlight the effectiveness and superiority of this invention through comparison.

[0101] like Figure 3The image shows the inversion results of the traditional AST method. It can be seen that the traditional AST method has the following problems: (1) The dominant update ranges of the three parameters v0, ε, and δ are inconsistent. v0 is effectively updated in the shallow and middle regions, ε is updated more significantly in the middle region, and δ is only updated in the shallow region. (2) The traditional AST method clearly has insufficient updates in the middle and deep regions. (3) The δ parameter is significantly over-updated in the shallow region and under-updated in the deep region. (4) Due to the presence of a low-velocity interlayer in the velocity model, both v0 and ε of the medium below the low-velocity interlayer are over-updated. (5) The effective update depth of the ε parameter is greater. The above inversion results are due to the uneven angle illumination in the AST multi-parameter inversion, which leads to the problem of dominant inversion regions for the three parameters.

[0102] To address the problems existing in the traditional AST method inversion, the method of this invention is applied to this model to obtain new inversion results, such as... Figure 4 As shown, the VTI multi-parameter profile at x = 7 km from the inversion result is as follows: Figure 5 As shown. Compared with the inversion results of the traditional AST method, the inversion results using the method T of this invention have all three parameters effectively updated, and are closer to the real model, which demonstrates the effectiveness of the method of this invention in anisotropic media modeling.

[0103] The following uses actual data collected in the East China Sea as a specific example to illustrate the VTI medium-accompanied state method of travel-time multi-parameter tomography imaging of the present invention in detail:

[0104] The actual dataset contains 91 OBSs, distributed between 12km and 22km, with an interval of approximately 100m between them. After shot-detector reciprocity, the dataset used for the dataset contains 91 shots, with a maximum offset of 12km for each shot and a detector spacing of 35m.

[0105] After comparing with the known logging velocity curve at the x-coordinate of 18km in the model of the work area, as follows: Figure 6 As shown in (a), it can be observed that the inverted velocity values ​​not only fit well with the macroscopic background of the Vp logging curve, but also fit well with the Vp value calculated from Vp, Vs, and density using Backus averaging at that well. The ε value obtained from the inversion of the first arrival travel time is as follows: Figure 7 As shown in (b), it basically reflects the macroscopic trend of the theoretical ε value obtained by Backus averaging, proving that the reliability of Vp and ε parameters obtained by the first arrival wave travel time inversion is high.

[0106] like Figure 7 As shown, the RTM imaging results under the initial model and the VTI medium model inverted using the method of this invention are presented for comparison. Figure 7Figures (a) and (b) show that the imaging results of the inverted model have more continuous phase axes, clearer layers, and improved deep imaging quality. This also indicates that the VTI anisotropic multiparameter model obtained by the method of this invention is more reliable.

[0107] Example 2

[0108] This embodiment provides a VTI medium-accompanied state method travel-time multi-parameter tomography system, including:

[0109] The data acquisition module is used to acquire the first arrival travel time of the raw seismic data, determine the initial velocity and anisotropic parameter model, and the observation system file.

[0110] The theoretical travel time field calculation module is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model, and to determine the target function and the adjoint field of a single shot based on the observation system file and the first arrival travel time.

[0111] The gradient calculation module is used to calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model.

[0112] The illumination compensation operator calculation module is used to calculate the precondition illumination compensation operator for a single shot based on the observed first arrival travel time and the theoretical travel time field of a single shot.

[0113] The judgment module is used to obtain the VTI multi-parameter tomography results based on the target function, multi-parameter gradient and preconditioning illumination compensation operator of all shots, and to determine whether the VTI multi-parameter tomography results meet the requirements. If they do, the VTI multi-parameter tomography results are output.

[0114] The illumination compensation module is used to obtain updated velocity and anisotropic parameter models based on the accompanying field of a single shot and the preconditional illumination compensation operators of all shots.

[0115] The system provided in this embodiment is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0116] Example 3

[0117] This embodiment provides a processing device corresponding to the VTI medium-accompanied state method travel-time multi-parameter tomography method provided in Embodiment 1. The processing device can be applied to client processing devices, such as mobile phones, laptops, tablets, desktop computers, etc., to execute the method of Embodiment 1.

[0118] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to enable communication between them. The memory stores a computer program that can run on the processing device. When the processing device runs the computer program, it executes the VTI medium-accompanied state method travel-time multi-parameter tomography method provided in Embodiment 1.

[0119] In some implementations, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0120] In other implementations, the processor can be any type of general-purpose processor, such as a central processing unit (CPU) or a digital signal processor (DSP), and there is no limitation here.

[0121] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0122] Those skilled in the art will understand that the structure of the above-described computing device is only a partial structure related to the solution of this application and does not constitute a limitation on the computing device to which the solution of this application is applied. A specific computing device may include more or fewer components, or combine certain components, or have different component arrangements.

[0123] Example 4

[0124] This embodiment provides a computer program product corresponding to the VTI medium-accompanied state method travel-time multiparameter tomography method provided in Embodiment 1. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the VTI medium-accompanied state method travel-time multiparameter tomography method described in Embodiment 1 are loaded.

[0125] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0126] The computer-readable storage medium provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0127] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0128] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0129] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0130] The above embodiments are only used to illustrate the present invention. The structure, connection method and manufacturing process of each component can be varied. All equivalent transformations and improvements made on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A VTI medium-adjoint state method for travel-time multi-parameter tomography, characterized in that, include: 1) Obtain the first arrival travel time of the raw seismic data, determine the initial velocity and anisotropic parameter model, and the observation system file; 2) Calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model, and determine the target function and adjoint field of a single shot based on the observation system file and the first arrival travel time. 3) Calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model; 4) Calculate the preconditioning illumination compensation operator for a single shot based on the observed first arrival travel time and the theoretical travel time field of a single shot; 5) Based on the target function, multi-parameter gradient, and preconditioning illumination compensation operator of all shots, obtain the VTI multi-parameter tomography results, and determine whether the VTI multi-parameter tomography results meet the requirements. If they do, output the VTI multi-parameter tomography results; otherwise, proceed to step 6). 6) Based on the accompanying field of a single shot and the preconditioning illumination compensation operator of all shots, obtain the updated velocity and anisotropy parameter model, and proceed to step 2) until the VTI multiparameter tomography results meet the requirements; In step 2), the theoretical travel time field of a single shot is calculated based on the velocity and anisotropic parameter model. Then, based on the observation system file and the observed first arrival travel times, the target function and the adjoint field of the single shot are determined, including: A fast scan algorithm is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model; Based on the observation system file, the target function of a single shot is determined according to the observed first arrival travel time and the theoretical travel time field of a single shot; Based on the observed first arrival travel time and the theoretical travel time field of a single shot, the accompanying field of a single shot is determined; The method for determining the single-shot target function based on the observation system file, according to the observed first arrival travel time and the theoretical travel time field of a single shot, includes: Calculate the travel time difference between the observed first arrival travel time and the theoretical travel time field for a single shot; Based on the observation system files and the travel time difference of a single gun, the target function of a single gun is obtained. : in, Indicates the first The location of each detector point; Represents the computational region Use at any position within function Control Area Calculation of the objective function at the internal detector point; This is the initial arrival time calculated theoretically.

2. The VTI medium-adjoint state method for travel-time multi-parameter tomography as described in claim 1, characterized in that, The theoretical travel time field of the single gun Calculate based on the following functional equation: in, For the governing equations; and These are the x and y coordinates of a point in the underground space, respectively. For speed; and For Thomsen anisotropy parameters.

3. The VTI medium-adjoint state method for travel-time multi-parameter tomography as described in claim 1, characterized in that, Using the following adjoint state equation, the travel time difference of a single shot is back-projected into the subsurface multi-parameter model space to obtain the adjoint field of the single shot. : in, For accompanying field The coefficient matrix.

4. The VTI medium-adjoint state method for travel-time multi-parameter tomography as described in claim 1, characterized in that, In step 4), the preconditioning illumination compensation operator for a single shot is calculated based on the observed first arrival travel time and the theoretical travel time field of the single shot, including: Set the travel time difference of a single gun to a fixed constant; Based on a fixed constant, the adjoint field at the detector location is initialized and an anti-propagation source is injected. The fast scanning method is used to propagate the associated field at the receiver point to the underground model. Scanning is performed in different directions to calculate the associated field at each point in the entire underground model space, thus obtaining the preconditioning illumination compensation operator for a single shot.

5. The VTI medium-associated state method for travel-time multi-parameter tomography as described in claim 1, characterized in that, In step 6), based on the accompanying field of a single shot and the preconditioning illumination compensation operator for all shots, the updated velocity and anisotropy parameter model is obtained, and the process proceeds to step 2) until the VTI multiparameter tomography results meet the requirements, including: Based on the accompanying field of a single shot and the preconditional illumination compensation operator of all shots, illumination compensation is performed on the original multi-parameter gradient to obtain the illumination-compensated gradient. Based on the gradient after illumination compensation, the updated velocity and anisotropic parameter models are obtained, and the process proceeds to step 2) until the VTI multiparameter tomography results meet the requirements, thus obtaining the final VTI multiparameter tomography results.

6. A VTI medium-accompanied state method travel-time multi-parameter tomography system, characterized in that, include: The data acquisition module is used to acquire the first arrival travel times of the raw seismic data, determine the initial velocity and anisotropic parameter model, and the observation system file; The theoretical travel time field calculation module is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model, and to determine the target function and the adjoint field of a single shot based on the observation system file and the first arrival travel time of the observation. The gradient calculation module is used to calculate the single-shot multi-parameter gradient of the VTI medium based on the velocity and anisotropic parameter model. The illumination compensation operator calculation module is used to calculate the precondition illumination compensation operator for a single shot based on the observed first arrival travel time and the theoretical travel time field of a single shot. The judgment module is used to obtain the VTI multi-parameter tomography results based on the target function, multi-parameter gradient and preconditioning illumination compensation operator of all shots, and to determine whether the VTI multi-parameter tomography results meet the requirements. If they do, the VTI multi-parameter tomography results are output. The illumination compensation module is used to obtain the updated velocity and anisotropy parameter models based on the accompanying field of a single shot and the preconditional illumination compensation operators of all shots. The process involves calculating the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model, and determining the target function and adjoint field of a single shot based on the observation system file and the first arrival travel time. A fast scan algorithm is used to calculate the theoretical travel time field of a single shot based on the velocity and anisotropic parameter model; Based on the observation system file, the target function of a single shot is determined according to the observed first arrival travel time and the theoretical travel time field of a single shot; Based on the observed first arrival travel time and the theoretical travel time field of a single shot, the accompanying field of a single shot is determined; The method for determining the single-shot target function based on the observation system file, according to the observed first arrival travel time and the theoretical travel time field of a single shot, includes: Calculate the travel time difference between the observed first arrival travel time and the theoretical travel time field for a single shot; Based on the observation system files and the travel time difference of a single gun, the target function of a single gun is obtained. : in, Indicates the first The location of each detector point; Represents the computational region Use at any position within function Control Area Calculation of the objective function at the internal detector point; This is the initial arrival time calculated theoretically.

7. A processing device, characterized in that, It includes computer program instructions, wherein when executed by a processing device, the computer program instructions are used to implement the steps corresponding to the VTI medium-accompanied state method of travel-time multiparameter tomography imaging method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, wherein when the computer program instructions are executed by a processor, they are used to implement the steps corresponding to the VTI medium-accompanied state method travel-time multiparameter tomography method according to any one of claims 1-5.

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