Formation parameter determination method and apparatus, device, storage medium, and program product

Abstract

The present application relates to the technical field of seismic data acquisition and processing for petroleum exploration, and provides a formation parameter determination method and apparatus, a device, a storage medium, and a program product. The method comprises: acquiring an initial formation model; on the basis of the initial formation model and seismic exploration data, determining a target formation inversion function and an iterative residual vector, wherein the target formation inversion function is determined by means of a Scholte wave dispersion curve, and the iterative residual vector is determined by means of a Scholte wave partial-derivative dispersion curve; determining a formation parameter updating formula on the basis of the target formation inversion function and the iterative residual vector; iteratively updating the initial formation model on the basis of the formation parameter updating formula and a preset stratigraphic layering rule to determine a target formation model; and determining formation parameters on the basis of the target formation model, wherein the formation parameters comprise longitudinal wave velocity, transverse wave velocity, and formation medium density. The method of the present application effectively improves the accuracy and reliability of the Scholte wave technique in seismic exploration.

Description

Methods, apparatus, equipment, storage media and program products for determining formation parameters

[0001] This application claims priority to Chinese Patent Application No. 202411569523.8, filed on November 5, 2024, entitled “Method, Apparatus, Device, Storage Medium and Program Product for Determining Formation Parameters”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of seismic data acquisition and processing technology in petroleum exploration, and in particular to a method, apparatus, equipment, storage medium and program product for determining formation parameters. Background Technology

[0003] Currently, in the field of marine geological exploration, determining the sedimentary structure of seafloor strata is one of the main objectives of marine exploration and geological investigation. Traditional geological exploration methods often rely on surface observation and well sampling, which suffer from problems such as high cost, long cycle time, and limited coverage. In recent years, with the development of marine geophysical technology, stratigraphic exploration methods based on seafloor Scholte waves have gradually become a research hotspot.

[0004] However, existing geological studies using Scholte waves require knowledge of the number and thickness of strata, but the actual data on the number and thickness of strata are unknown. Therefore, these data need to be set manually based on experience, which greatly limits the use of Scholte waves in geological studies and makes it difficult to accurately reflect the true geological situation. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, storage medium, and program product for determining stratigraphic parameters, in order to solve the problem that the use of Scholte waves in geological research in the prior art is greatly limited and cannot accurately reflect the true geological situation.

[0006] Firstly, this application provides a method for determining stratigraphic parameters, including:

[0007] An initial stratigraphic model is obtained, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons that are uniformly distributed along the depth direction, where N is a positive integer.

[0008] Based on the initial stratigraphic model and the seismic exploration data, the target stratigraphic inversion function and the iterative residual vector are determined, wherein the target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection dispersion curve.

[0009] The formation parameter update formula is determined based on the target formation inversion function and the iterative residual vector.

[0010] The initial stratigraphic model is updated and iterated based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic strata distributed along the depth direction, where M is a positive integer and M is less than N.

[0011] Formation parameters are determined based on the target formation model, including P-wave velocity, S-wave velocity, and formation medium density.

[0012] In one possible design, determining the target stratigraphic inversion function and iterative residual vector based on the initial stratigraphic model and the seismic exploration data includes:

[0013] The initial Scholte wave dispersion curve and the initial Scholte wave deflector dispersion curve are determined based on the initial stratigraphic model.

[0014] The measured Scholte wave dispersion curve is determined based on the seismic exploration data, and the target stratum inversion function is established based on the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve.

[0015] The iterative residual vector is determined based on the target stratum inversion function and the initial Scholte wave deflection curve.

[0016] In one possible design, determining the initial Scholte wave deflection dispersion curve based on the initial formation model includes:

[0017] Based on the initial stratigraphic model, establish the Helmholtz equation for any of the aforementioned stratigraphic horizons;

[0018] The partial derivative differential equations are obtained by differentiating the Helmholtz equation with respect to formation parameters.

[0019] Solve the general solution of the partial derivative differential equation;

[0020] The displacement stress partial derivative vector of any stratum is determined based on the general solution.

[0021] Based on the displacement stress partial derivative vector, a recursive relationship is established to obtain the recursive relationship between the displacement stress partial derivative vector of the first stratum and the displacement stress partial derivative vector of the Nth stratum.

[0022] The Scholte wave partial guide dispersion equation is determined based on the recursive relationship.

[0023] Solve the Scholte wave partial-guide dispersion equation to obtain the initial Scholte wave partial-guide dispersion curve.

[0024] In one possible design, the target formation inversion function F(m) is expressed as: Among them, f c The initial Scholte wave dispersion curve, the To measure the dispersion curve of the Scholte wave.

[0025] In one possible design, the iterative residual vector d k Represented as: d k =-(G k T G k +α k I) -1 G k T f k , where d k Let G be the iterative residual vector of the k-th iteration. k Let I be the wave velocity partial derivative matrix of the k-th iteration, and the wave velocity partial derivative matrix is ​​obtained from the initial Scholte wave partial derivative dispersion curve, where I is the identity matrix and α is the wave velocity partial derivative matrix. k f is a positive real constant. k The calculated value of the k-th iteration of the target stratigraphic inversion function;

[0026] The formation parameter update formula m k+1 Represented as: m k+1 =m k +λ k d k , where m k Let m be the formation parameter vector matrix of the k-th iteration. k+1 Let λ be the formation parameter vector matrix for the (k+1)th iteration. k This is the step size calculated in the k-th iteration.

[0027] In one possible design, the step of updating and iterating the initial stratigraphic model based on the stratigraphic parameter update formula and preset stratigraphic stratification rules to determine the target stratigraphic model includes:

[0028] Obtain the updated formation parameters using the formation parameter update formula;

[0029] Based on the updated stratigraphic parameters, determine whether the difference in stratigraphic parameters between two adjacent stratigraphic horizons in the initial stratigraphic model is less than a first preset threshold.

[0030] If the difference in stratigraphic parameters between two adjacent stratigraphic layers is less than the first preset threshold, the two adjacent stratigraphic layers are merged to determine the target stratigraphic model.

[0031] Secondly, this application provides a formation parameter determination device, comprising:

[0032] The acquisition module is used to acquire an initial stratigraphic model, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons that are uniformly distributed along the depth direction, where N is a positive integer.

[0033] The determination module is used to determine the target stratum inversion function and the iterative residual vector based on the initial stratigraphic model and the seismic exploration data, wherein the target stratum inversion function is determined by the Scholte wave dispersion curve and the iterative residual vector is determined by the Scholte wave deflection dispersion curve.

[0034] The determining module is also used to determine the formation parameter update formula based on the target formation inversion function and the iterative residual vector;

[0035] The model update module is used to update and iterate the initial stratigraphic model based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic strata distributed along the depth direction, where M is a positive integer and M is less than N.

[0036] The formation parameter determination module is used to determine formation parameters based on the target formation model. The formation parameters include P-wave velocity, S-wave velocity, and formation medium density.

[0037] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0038] The memory stores computer-executed instructions;

[0039] The processor executes computer execution instructions stored in the memory to implement the method as described in various possible designs of the first aspect.

[0040] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the methods described in various possible designs of the first aspect.

[0041] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in various possible designs of the first aspect.

[0042] The stratigraphic parameter determination method, apparatus, equipment, storage medium, and program product provided in this application involve: acquiring an initial stratigraphic model, which is constructed based on known seismic exploration data and includes N stratigraphic horizons uniformly distributed along the depth direction, where N is a positive integer; determining a target stratigraphic inversion function and an iterative residual vector based on the initial stratigraphic model and the seismic exploration data, wherein the target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection dispersion curve; determining a stratigraphic parameter update formula based on the target stratigraphic inversion function and the iterative residual vector; updating and iterating the initial stratigraphic model based on the stratigraphic parameter update formula and preset horizon stratification rules to determine the target stratigraphic model, which includes M stratigraphic horizons distributed along the depth direction, where M is a positive integer and M is less than N; and determining stratigraphic parameters based on the target stratigraphic model, including P-wave velocity, S-wave velocity, and stratigraphic medium density. The method of this application uses the dispersion curve of Scholte waves to determine the inversion function of the target stratum and the partial-guided dispersion curve of Scholte waves to determine the iterative residual vector. Then, the inversion function of the target stratum and the iterative residual vector are used to determine the stratum parameter update formula. The initial stratum model is then updated and iterated using the stratum parameter update formula and the preset stratigraphic layering rules, thereby obtaining a target stratum model with more accurate stratigraphic layers and thicknesses. The accurate stratum parameters are then determined from the target stratum model. The method of this application effectively improves the accuracy and reliability of Scholte wave technology in seismic exploration. Attached Figure Description

[0043] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0044] Figure 1 is an application scenario diagram corresponding to the formation parameter determination method provided in an embodiment of this application;

[0045] Figure 2 is a flowchart illustrating a method for determining formation parameters according to an embodiment of this application;

[0046] Figure 3 is a schematic diagram of an initial stratigraphic model provided in an embodiment of this application;

[0047] Figure 4 is a flowchart illustrating a method for determining formation parameters according to another embodiment of this application;

[0048] Figure 5 is a schematic diagram of the structure of a formation parameter determination device provided in an embodiment of this application;

[0049] Figure 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0050] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0053] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0054] In the field of marine geological exploration, accurately determining the sedimentary structure of seafloor strata is crucial for understanding marine geological evolution, resource exploration, and disaster prevention. Traditional geological exploration methods, such as surface observation and well sampling, while providing direct geological information, are limited by high costs, long cycles, and limited exploration ranges, making it difficult to meet the demands of large-scale, high-efficiency exploration. This is especially true in deep-sea areas, where the difficulty and cost of implementing these methods increase exponentially. In recent years, marine geophysical technologies have experienced rapid development. Among them, stratigraphic exploration methods based on seafloor Scholte waves have attracted considerable attention due to their efficiency and wide applicability. Scholte waves, as elastic waves propagating between the seafloor sediment-bedrock interface, have propagation characteristics closely related to stratigraphic structure, reflecting the physical properties of strata and interlayer interface information, providing a new direction for seafloor stratigraphic exploration. However, some technical challenges still exist in using Scholte waves for geological research. Specifically, accurate information on the number and thickness of stratigraphic layers is often difficult to obtain directly, yet these parameters are crucial for accurately interpreting Scholte wave signals and inverting stratigraphic structures. Existing methods largely rely on human experience to determine the number and thickness of stratigraphic layers, which not only increases the subjectivity and uncertainty of the research but also greatly limits the accuracy and reliability of Scholte wave technology in geological exploration.

[0055] Therefore, to improve the accuracy and reliability of Scholte waves in geological exploration, given the technical problems in existing technologies, it is first necessary to obtain an initial stratigraphic model with relatively accurate stratigraphic layer numbers and thicknesses. Then, an inversion process is performed from this model to obtain a final stratigraphic model with relatively accurate stratigraphic media, shear wave velocities, and p-wave velocities. Specifically, an initial stratigraphic model is first acquired from known seismic exploration data. Based on the initial stratigraphic model and seismic exploration data, the target stratigraphic inversion function and iterative residual vector are determined. The target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave partial-guide dispersion curve. A stratigraphic parameter update formula is determined based on the target stratigraphic inversion function and the iterative residual vector. The initial stratigraphic model is then updated iteratively based on the stratigraphic parameter update formula and preset layering rules to determine the target stratigraphic model. Finally, the p-wave velocity, shear wave velocity, and stratigraphic medium density are determined based on the target stratigraphic model.

[0056] Figure 1 illustrates an application scenario of the stratigraphic parameter determination method provided in an embodiment of this application. As shown in Figure 1, the application scenario of the stratigraphic parameter determination method provided in this embodiment includes a user terminal 11, a server 12, and a database 13. The database 13 stores an initial stratigraphic model and seismic exploration data, and the initial stratigraphic model is constructed based on known seismic exploration data. Specifically, when stratigraphic parameters need to be determined, the user sends a stratigraphic parameter determination request to the server 12 through the user terminal 11. After receiving the stratigraphic parameter determination request, the server 12 retrieves the initial stratigraphic model and seismic exploration data from the database 13. The server 12 determines the target stratigraphic inversion function and iterative residual vector using the initial stratigraphic model and seismic exploration data, and then determines the stratigraphic parameter update formula using the target stratigraphic inversion function and iterative residual vector. Thus, the target stratigraphic model is obtained by updating and iterating the initial stratigraphic model using the stratigraphic parameter update formula and preset stratigraphic stratification rules, and the precise stratigraphic parameters are then determined using the target stratigraphic model. Finally, the server 12 sends the target formation model and formation parameters to the user terminal 11, thereby achieving the purpose of determining the formation parameters.

[0057] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0058] Figure 2 is a flowchart of a formation parameter determination method provided in an embodiment of this application. As shown in Figure 2, the execution subject of this embodiment is a formation parameter determination device. This formation parameter device can be implemented by a computer program, or by a medium storing a relevant computer program, such as a USB flash drive and / or optical disc; or it can be implemented by a physical device integrating or installing a relevant computer program, such as a chip or electronic device. The electronic device may be a computer or a server, etc. The formation parameter determination method provided in this embodiment includes the following steps:

[0059] S201. Obtain the initial stratigraphic model. The initial stratigraphic model is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons that are uniformly distributed along the depth direction, where N is a positive integer.

[0060] Specifically, an initial stratigraphic model is first obtained. This initial stratigraphic model is constructed from known seismic exploration data, and the stratigraphic horizons in this initial stratigraphic model are uniformly distributed along the depth direction. This facilitates subsequent updates to the initial stratigraphic model.

[0061] It should be noted that a stratigraphic model is an important concept in the field of geology. It abstracts and summarizes the distribution, morphology, properties, and interrelationships of underground rock strata, forming a visual representation. This helps to intuitively understand the structural characteristics of underground rock strata and provides important evidence for geological research, resource exploration, and development. The initial stratigraphic model includes not only N stratigraphic positions with the same thickness, but also initial stratigraphic parameters such as initial P-wave velocity, S-wave velocity, and formation medium density. Furthermore, the stratigraphic parameters are identical within the same stratigraphic position in the initial stratigraphic model.

[0062] Optionally, the value of N in the initial model can be taken with reference to the known number of actual strata, and the value of N can be set to be much larger than the number of actual strata. For example, if the number of actual strata is 100, then N can be 1000 or larger.

[0063] S202. Based on the initial stratigraphic model and seismic exploration data, determine the target stratigraphic inversion function and the iterative residual vector. The target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection curve.

[0064] Specifically, the target stratum inversion function and iterative residual vector are determined using the initial stratigraphic model and seismic exploration data, facilitating subsequent updates and iterations of the initial stratigraphic model. The target stratum inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave partial-guide dispersion curve. Since Scholte waves are highly sensitive to changes in stratigraphic structure, using the Scholte wave dispersion curve to determine the target stratum inversion function and the Scholte wave partial-guide dispersion curve to determine the iterative residual vector allows for a more accurate reflection of the strata's physical characteristics, such as density and wave velocity, thereby improving the accuracy of subsequent stratigraphic models.

[0065] The target stratigraphic inversion function is used to quantify the difference between the initial stratigraphic model prediction and the seismic exploration data. Mathematical methods are used to estimate and predict the structural characteristics of subsurface strata, such as solving wave equations and optimization algorithms.

[0066] The iterative residual vector is a mathematical representation of the difference between the initial stratigraphic model prediction and the actual observed seismic data in the current iteration step. More intuitively, in iterative inversion algorithms, a starting point is typically an initial stratigraphic model. The parameters of this initial model are continuously adjusted to minimize the difference between the simulated and observed seismic data. This difference is the iterative residual, and the iterative residual vector represents this difference in vector form.

[0067] Scholte waves are interfacial waves that propagate at liquid-solid interfaces. The Scholte wave dispersion curve shows the wave velocity as a function of frequency. The Scholte wave partial derivative dispersion curve shows the partial derivative of the wave velocity with respect to formation parameters as a function of frequency. By inverting the Scholte wave dispersion curve and its partial derivative dispersion curve, the internal structure of complex formations can be revealed more accurately, providing more reliable formation models for geological exploration and oil and gas development.

[0068] S203. Determine the formation parameter update formula based on the target formation inversion function and iterative residual vector.

[0069] Specifically, once the target formation inversion function and the iterative residual vector are determined, the formation parameter update formula is then derived from these two parameters. The formation parameters are then continuously adjusted using this update formula.

[0070] Among them, the formation parameter update formula is a mathematical formula used to update and calculate formation parameters.

[0071] S204. The initial stratigraphic model is updated and iterated based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic strata distributed along the depth direction, where M is a positive integer and M is less than N.

[0072] Specifically, once the formation parameter update formula is determined, the initial model is updated and iterated using the formation parameter update formula and the preset stratigraphic stratification rules to obtain the final target formation model.

[0073] Among them, the preset stratigraphic stratification rules are artificially set stratigraphic stratification rules or constraints, which are used to guide the re-division of stratigraphic strata in the initial stratigraphic model.

[0074] Optionally, when setting the number of stratigraphic positions N in the initial stratigraphic model, a value as large as possible should be chosen, making it significantly larger than the final number of stratigraphic positions M in the target stratigraphic model. Therefore, during iteration of the initial stratigraphic model, stratigraphic positions only need to be merged without further subdivision, simplifying the stratigraphic layering process. Furthermore, setting the number of stratigraphic positions N in the initial stratigraphic model to the largest possible value ensures higher accuracy of the target stratigraphic model after iteration.

[0075] Optionally, there are various methods for iterating the initial stratigraphic model, such as gradient descent, Newton's method, or conjugate gradient method, and this embodiment does not limit the method.

[0076] S205. Determine formation parameters based on the target formation model. Formation parameters include P-wave velocity, S-wave velocity, and formation medium density.

[0077] Specifically, once the target stratigraphic model is determined, it is used to further determine stratigraphic parameters by inversion, using a target stratigraphic model that more closely approximates the actual stratigraphic horizons and thickness distributions. This results in more accurate P-wave velocities, S-wave velocities, and formation medium density.

[0078] The P-wave velocity refers to the speed at which the P-wave (also known as the primary wave) propagates in the medium during a seismic event. The P-wave is the fastest-propagating type of seismic wave, causing compression and stretching vibrations in the medium's particles along the direction of wave propagation.

[0079] The transverse wave velocity refers to the speed at which transverse waves (also known as S-waves, secondary waves) propagate in a seismic medium. Transverse waves are another type of seismic wave that cause the particles in the medium to vibrate in a direction perpendicular to the wave's propagation.

[0080] Formation density refers to the mass of formation material per unit volume. It reflects the compactness and weight of the formation material.

[0081] The method for determining stratigraphic parameters provided in this embodiment includes: acquiring an initial stratigraphic model, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons uniformly distributed along the depth direction, where N is a positive integer. Based on the initial stratigraphic model and the seismic exploration data, a target stratigraphic inversion function and an iterative residual vector are determined, wherein the target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection dispersion curve. A stratigraphic parameter update formula is determined based on the target stratigraphic inversion function and the iterative residual vector. The initial stratigraphic model is updated iteratively based on the stratigraphic parameter update formula and a preset stratigraphic layering rule to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic horizons distributed along the depth direction, where M is a positive integer and M is less than N. Based on the target stratigraphic model, stratigraphic parameters are determined, including P-wave velocity, S-wave velocity, and stratigraphic medium density. The method in this application utilizes the dispersion curve of Scholte waves to determine the inversion function of the target stratum and the partial derivative dispersion curve of Scholte waves to determine the iterative residual vector. Then, the inversion function of the target stratum and the iterative residual vector are used to determine the stratum parameter update formula, and the initial stratum model is updated iteratively using the stratum parameter update formula and preset stratigraphic rules. This results in a more accurate target stratum model with more precise stratigraphic horizons and thicknesses, from which accurate stratum parameters are then determined. The method in this application effectively improves the accuracy and reliability of Scholte wave technology in seismic exploration.

[0082] As an optional implementation, based on any of the above embodiments, the determination of the target stratum inversion function and iterative residual vector based on the initial stratigraphic model and seismic exploration data specifically includes the following steps: determining the initial Scholte wave dispersion curve and the initial Scholte wave deflection dispersion curve based on the initial stratigraphic model; determining the measured Scholte wave dispersion curve based on the seismic exploration data, and establishing the target stratum inversion function based on the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve; and determining the iterative residual vector based on the target stratum inversion function and the initial Scholte wave deflection dispersion curve.

[0083] Specifically, in determining the target stratum inversion function and iterative residual vector based on the initial stratigraphic model and seismic exploration data, the process is as follows: First, the initial Scholte wave dispersion curve and the initial Scholte wave deflection curve are determined using the initial stratigraphic model. Then, the measured Scholte wave dispersion curve is determined from the seismic exploration data, and the target stratum inversion function is established using the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve. Finally, the iterative residual vector is determined using the target stratum inversion function and the initial Scholte wave deflection curve. Thus, the target stratum inversion function and the iterative residual vector are obtained.

[0084] In the initial formation model, each formation level corresponds to a preset P-wave velocity, S-wave velocity, and formation medium density. By deriving formulas using these preset P-wave velocities, S-wave velocities, and formation medium density, the Scholte wave dispersion equation can be obtained. Based on this equation, the initial Scholte wave dispersion curve can be plotted. Similarly, by deriving formulas using the preset P-wave velocities, S-wave velocities, and formation medium density, the Scholte wave partial-guide dispersion equation can be obtained, which represents the partial derivatives of the Scholte wave with respect to the formation parameters. Based on this equation, the initial Scholte wave partial-guide dispersion curve can be plotted.

[0085] Optionally, the measured Scholte wave dispersion curve can be generated by numerical fitting based on seismic exploration data. This measured Scholte wave dispersion curve can reflect the true physical properties of the seafloor stratigraphic interface in the target area.

[0086] Optionally, in this embodiment, the difference between the initial Scholte wave dispersion curve and the measured Scholte wave dispersion curve is obtained by comparing the two, and a target stratum inversion function is constructed based on the difference between the two.

[0087] Optionally, the target formation inversion function is combined with the initial Scholte wave partial-guided dispersion curve to determine the iterative residual vector during the iteration process. The iterative residual vector reflects the difference between the current model predictions and measurements (i.e., the measured dispersion curve). In each iteration, the iterative residual vector is used to adjust the parameters of the formation model to reduce the difference between the predictions and measurements.

[0088] The stratigraphic parameter determination method provided in this embodiment determines the target stratigraphic inversion function and iterative residual vector based on the initial stratigraphic model and seismic exploration data. The initial Scholte wave dispersion curve and the initial Scholte wave deflection curve are determined using the initial stratigraphic model. The measured Scholte wave dispersion curve is determined using the seismic exploration data, and the target stratigraphic inversion function is established based on the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve. Then, the iterative residual vector is determined based on the target stratigraphic inversion function and the initial Scholte wave deflection curve. Therefore, subsequent stratigraphic parameters can be determined using the target stratigraphic inversion function and the iterative residual vector.

[0089] As an optional implementation, based on any of the above embodiments, the derivation process of the initial Scholte wave dispersion equation is as follows:

[0090] Figure 3 is a schematic diagram of the initial stratigraphic model. As shown in Figure 3, since the P-waves and S-waves are in the Roz plane, the initial stratigraphic model is set at layer j. and These are the longitudinal scalar potential function and the transverse vector potential function of the Scholte wave, respectively. and Satisfies the homogeneous Helmholtz equation:

[0091] In the formula, the operator in the cylindrical coordinate system Let be the wave vector of the longitudinal wave. V is the wave vector of the transverse wave. pj It is the propagation speed of longitudinal waves, V sj ω is the propagation speed of the transverse wave, and ω is the angular frequency of the wave.

[0092] set up in Let be the wave function of the longitudinal wave in the z-axis direction. The wave function of a transverse wave in the z-axis direction. Let r be the wave function of the longitudinal wave. Let be the r-direction wave function of the transverse wave. Then the z-direction wave function solutions of the homogeneous Helmholtz equations (1a) and (1b) are:

[0093] In the formula, and The undetermined coefficients of the longitudinal wave velocity potential function, and Let be the undetermined coefficients of the transverse wave velocity potential function, and e be a mathematical constant. Let be the wave number of the Scholte wave propagating at the seabed interface, and c be the wave velocity of the Scholte wave.

[0094] Define potential vector The displacement stress vector at the interface of the j-th medium layer is obtained from the continuity of displacement stress. With the interface displacement stress vector on the (j+1)th medium Recurrence relation:

[0095] In the formula, For radial displacement, For vertical displacement, For radial stress, The stress is vertical, and the superscript u indicates the upper interface of the stratum. Let be the recursive matrix of the j-th level, where

[0096] h j Let j be the thickness of the stratum.

[0097] μ j Let be the formation shear modulus of the j-th layer.

[0098] Given that the initial stratigraphic model has N stratigraphic layers, the recursive relationship of the displacement-stress vector between the 1st layer and the Nth layer is obtained from recursive formula (3):

[0099] In the formula,

[0100] As z→∞, the Nth layer of the initial stratigraphic model can be obtained from the wave field radiation condition. Since the first layer is a liquid layer, it can be obtained that... Then, given that the vertical displacement at the fluid interface (water surface) is 0, and the radial stress at the seabed interface (water-seabed stratum interface) is 0, a system of two linear homogeneous equations can be obtained using recursive formula (3), with the coefficient matrix as follows: The condition for this system of two linear homogeneous equations to have non-zero solutions is that the coefficient row and column are equal to zero, that is:

[0101] Equation (5) is called the Scholte wave dispersion equation. Solving equation (5) will yield the Scholte wave dispersion curve.

[0102] Figure 4 is a flowchart of a formation parameter determination method provided in another embodiment of this application. As shown in Figure 4, as an optional implementation, based on any of the above embodiments, the formation parameter determination method provided in this embodiment specifically includes the following steps when determining the initial Scholte wave deflection curve based on the initial formation model:

[0103] S2021. Establish the Helmholtz equation for any stratigraphic level based on the initial stratigraphic model.

[0104] Specifically, the Helmholtz equation for any given stratigraphic level is shown in reference formulas (1a) and (1b). The Helmholtz equation is an elliptic partial differential equation describing wave phenomena such as electromagnetic waves.

[0105] S2022. Differentiate the Helmholtz equation with respect to formation parameters to obtain the partial derivative differential equation.

[0106] Specifically, formation parameters include P-wave velocity V p transverse wave velocity V s And the formation medium density ρ, let the formation parameter vector m of the qth layer in the initial formation model be... q =[V pq V sq ρ q ], where V pq V represents the longitudinal wave velocity of the q-th layer. sq ρ represents the transverse wave velocity of the q-th layer. q Let m represent the density of the formation medium in the q-th layer. qi m represents the formation parameter vector of the q-th layer. q The i-th formation parameter. Applying formulas (1a) and (1b) to m qi Taking the derivative, the partial derivative differential equation is:

[0107]

[0108] In the formula, For the solutions of formulas (1a) and (1b),

[0109] S2023. Solve the general solution of the partial derivative differential equation.

[0110] S2024. Determine the displacement stress partial derivative vector of any stratum based on the general solution.

[0111] Specifically, let the homogeneous solutions of formulas (6a) and (6b) be:

[0112] The homogeneous equation separated by variables is then:

[0113] In the formula, This is the derivative of the Scholte wave velocity c with respect to the formation parameters (called the Scholte wave velocity partial derivative). With R ψ (r) is the radial wave function of the partial derivative homogeneous differential equations (8a) to (8d) of the formation parameters.

[0114] Furthermore, since the problem has rotational symmetry about the z-axis, With R ψ The radial solution of (r) can be a zero-order Hankel function of the first kind. Superposition solution form and first-order Hankel function of the first kind The solution is in the form of a superposition, where, for The first derivative of is given by the wave function, which can then be written as:

[0115] The stress-displacement partial derivative can then be expressed as:

[0116] In the formula, This is the partial derivative of displacement stress, i.e., displacement stress with respect to formation parameter m. qi The partial derivatives, For the j-th layer of medium, the displacement in the r direction is... Let the displacement of the j-th medium layer in the z-direction be denoted as . For tangential stress, With vertical stress, μ j Let j be the formation shear modulus.

[0117] The general solutions to equations (8a) and (8c) are:

[0118] In the formula, A j B j C represents the undetermined coefficients of the longitudinal wave velocity potential function. j D j These are the undetermined coefficients of the transverse wave velocity potential function.

[0119] Define the wave velocity partial guide potential vector Define the displacement stress deflection quantity in the j-th layer of medium:

[0120] In the formula,

[0121] Then the time displacement stress partial derivative Γ j =[u rj u zj σ zrj σ zzj ] = S j R j (r)e -ωt Where t represents time,

[0122] Because the displacement and stress at the interfaces of vertically multi-layered strata are continuous, the equation still holds when the partial derivatives of the equations are taken with respect to the formation parameters. That is, the partial derivatives of displacement and stress at the formation interfaces are continuous, i.e., Γ... j =Γ j+1 At the interface between the j-th layer and the (j+1)-th medium, we have:

[0123] In the formula, z j Let z be the z-coordinate of the j-th layer interface.

[0124] Therefore, the partial derivative vector of the interface displacement stress on the j-th layer of medium is obtained. Partial derivative of the interface displacement stress vector on the (j+1)th medium Satisfies the recurrence relation:

[0125] In the formula, T j Let T be the recurrence matrix of the j-th level. j =m tj λ j n tj g j g j =diag[1,1,μ j+1 / μ j ,μ j+1 / μ j ],

[0126] In the formula, p j =γ pj kh j q j =γ sj kh j , For the j-th layer γ pj The derivative of the i-th formation parameter with respect to the q-th layer, For the j-th layer γ sj The derivative of the i-th formation parameter with respect to the q-th layer, μ j Let h be the formation shear modulus of the j-th layer. j Let j be the thickness of the stratum.

[0127] When q ≠ j (layers q and j are not in the same stratum), equations (8a) to (8d) are homogeneous equations. When q = j (i.e., layers q and j are in the same stratum), equations (8a) to (8d) are non-homogeneous equations, and their non-homogeneous functions... Let be the solutions to equations (1a) and (1b). Their intrinsic value is... Let be the wave number of the Scholte surface wave. The radial intrinsic function is... Therefore, equation (4) satisfies the condition that the determinant of the coefficient matrix is ​​zero, and its wave function can be any function. To find the partial derivative of the surface wave velocity with respect to the formation parameters corresponding to the point on the dispersion curve, we can select the basis functions of the solution to equation (1), the undetermined coefficients of equations (11a) and (11b) to construct a new fundamental solution, that is:

[0128] The wave function constructed in this way still satisfies equation (1). Substituting this wave function into equations (5a) and (5b) yields:

[0129] In the formula, Let the particular solutions of equations (16a) and (16b) be... and ψ * (z), then the general solution of equations (16a) and (16b) is:

[0130] S2025. Based on the displacement stress partial derivative vector, establish a recursive relationship to obtain the recursive relationship between the displacement stress partial derivative vector of the first stratum and the displacement stress partial derivative vector of the Nth stratum.

[0131] Specifically, the partial derivative vector of the interface displacement stress on the j=q layer of medium Partial derivative of the interface displacement stress vector on the (q+1)th medium There is a recurrence relation:

[0132] In the formula, T q =T j For a recursive matrix, Let u be the value of a particular solution of the displacement stress partial derivative vector at the upper interface of layer q, where the superscript u indicates the upper interface of the stratum.

[0133] From the recursive formula (18), the recursive relationship between the 1st layer and the Nth layer is:

[0134] In the formula, Q = T N T N-1 …T1.

[0135] S2026. Determine the Scholte wave partial guide dispersion equation based on the recursive relationship.

[0136] Specifically, from the wave field radiation conditions, the Nth layer of the initial stratigraphic model has... Level 1 The stress at the sea surface is zero, and the shear stress at the seabed is zero. Therefore, the corresponding vertical and radial stress partial derivatives are zero, i.e., σ... zz | z＝0 =0, Since the undetermined coefficients of the particular solutions in equations (17a) and (17b) are chosen from those of equations (11a) and (11b), equation (19) remains a system of two linear homogeneous equations, which is a nonlinear function of the Scholte wave velocity partial derivative c′. zz | z＝0 =0, or Substituting into equation (19), we obtain the Scholte wave partial-guide dispersion equation: E(c′,f)=0 (20)

[0137] S2027. Solve the Scholte wave partial guide dispersion equation to obtain the initial Scholte wave partial guide dispersion curve.

[0138] Specifically, through calculation and drawing The curve showing the change with frequency f yields the Scholte wave deflection curve.

[0139] The formation parameter determination method provided in this embodiment, when determining the initial Scholte wave partial-guided dispersion curve based on an initial formation model, includes: establishing the Helmholtz equation for any formation horizon based on the initial formation model; differentiating the Helmholtz equation with respect to formation parameters to obtain partial derivative differential equations; solving the general solution of the partial derivative differential equations; determining the displacement stress partial derivative vector for any formation horizon based on the general solution; establishing a recursive relationship based on the displacement stress partial derivative vector to obtain the recursive relationship between the displacement stress partial derivative vector of the first formation horizon and the displacement stress partial derivative vector of the Nth formation horizon; determining the Scholte wave partial-guided dispersion equation based on the recursive relationship; and solving the Scholte wave partial-guided dispersion equation to obtain the initial Scholte wave partial-guided dispersion curve. The method of this application derives the Scholte wave partial-guided dispersion equation through formula derivation. Compared to existing techniques that calculate Scholte wave velocity partial derivatives based on the numerical difference quotient of the Scholte wave dispersion equation, the Scholte wave velocity partial derivative calculated using the method in this application can be calculated more accurately. This ensures the accuracy of subsequent data derived from the Scholte wave velocity partial derivative.

[0140] As an optional implementation, based on any of the above embodiments, the target formation inversion function F(m) is expressed as: Among them, f c The initial Scholte wave dispersion curve, To measure the dispersion curve of the Scholte wave. Iterative residual vector d k Represented as: d k =-(G k T G k +α k I) -1 G k T f k , where d k Let G be the iterative residual vector of the k-th iteration. k Let I be the wave velocity partial derivative matrix of the k-th iteration, obtained from the initial Scholte wave partial derivative dispersion curve, where I is the identity matrix and α is the wave velocity partial derivative matrix. k f is a positive real constant. k This represents the calculated value of the target formation inversion function in the kth iteration. The formation parameter update formula is m. k+1 Represented as: m k+1 =m k +λ k d k , where m k Let m be the formation parameter vector matrix of the k-th iteration. k+1 Let λ be the formation parameter vector matrix for the (k+1)th iteration. k This is the step size calculated in the k-th iteration.

[0141] Specifically, in this embodiment, the target formation inversion function F(m) is expressed as: The difference between the data calculated from the initial Scholte wave dispersion curve and the Scholte wave dispersion curve extracted from the actual observation data is measured by the norm.

[0142] Specifically, set Contains M t There are 1 observation data point, m = [m1, ..., m2]. q ,…,m Nz ], m q =[V pq V sq ρ q ], m q Let be the formation parameter vector of the q-th layer. In this embodiment, the iterative residual vector d k Represented as: d k =-(G k T Gk +α k I) -1 G k T f k G k Let be the wave velocity partial derivative matrix of the k-th iteration, and let be obtained from the initial Scholte wave partial derivative dispersion curve. For G k The transpose of . Specifically, G is represented as:

[0143] α k It is a positive real constant, and α k The value of f ranges from 1 to 2. k Let be the calculated value of the k-th iteration of the target stratigraphic inversion function. Further, to simplify the calculation, take...

[0144] Optionally, the iterative residual vector d k It can also be expressed as:

[0145] Specifically, the formation parameter update formula m k+1 Represented as: m k+1 =m k +λ k d k , λ k Let be the step size calculated in the k-th iteration, where λ k It is pre-set by humans, and its specific values ​​can be adjusted according to the results of each experiment.

[0146] The formation parameter determination method provided in this embodiment uses the target formation inversion function F(m) as follows: Among them, f c The initial Scholte wave dispersion curve, To measure the Scholte wave dispersion curve; iterate the residual vector d. k Represented as: d k =-(G k T G k +α k I) -1 G k T f k Where, d k Let G be the iterative residual vector of the k-th iteration. k Let I be the wave velocity partial derivative matrix of the k-th iteration, obtained from the initial Scholte wave partial derivative dispersion curve, where I is the identity matrix and α is the wave velocity partial derivative matrix. k f is a positive real constant. kThis represents the calculated value of the target formation inversion function in the kth iteration. The formation parameter update formula is m. k+1 Represented as: m k+1 m k +λ k d k , where m k Let m be the formation parameter vector matrix of the k-th iteration. k+1 Let λ be the formation parameter vector matrix for the (k+1)th iteration. k This represents the step size for the k-th iteration. In this embodiment, the formation parameters can be updated progressively using the determined target formation inversion function, iterative residual vector, and formation parameter update formula.

[0147] As an optional implementation, based on any of the above embodiments, the initial stratigraphic model is updated iteratively according to the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model, including:

[0148] Obtain the updated formation parameters using the formation parameter update formula.

[0149] Based on the updated stratigraphic parameters, determine whether the difference in stratigraphic parameters between two adjacent stratigraphic layers in the initial stratigraphic model is less than a first preset threshold.

[0150] If the difference in stratigraphic parameters between two adjacent stratigraphic layers is less than a first preset threshold, the two adjacent stratigraphic layers are merged to determine the target stratigraphic model.

[0151] Specifically, when updating and iterating the initial stratigraphic model based on the stratigraphic parameter update formula and preset stratigraphic stratification rules to determine the target stratigraphic model, the following steps are taken: First, the updated stratigraphic parameters are obtained using the updated formula. When the difference in stratigraphic parameters between two adjacent stratigraphic positions in the updated initial stratigraphic model is less than a first preset threshold, these two positions are considered to be very similar in physical properties, and thus belong to the same stratigraphic position. In this case, the two stratigraphic positions are merged. Conversely, when the difference in stratigraphic parameters between two adjacent stratigraphic positions in the updated initial stratigraphic model is greater than or equal to the first preset threshold, these two adjacent stratigraphic positions are considered not to belong to the same stratigraphic position, and are not merged. This process is repeated to determine the division of all stratigraphic positions in the initial model, thereby determining the target stratigraphic model.

[0152] The formation parameters include P-wave velocity, S-wave velocity, and formation medium density.

[0153] The first preset threshold is set manually. This first preset threshold is an empirical value obtained after multiple experiments, and no specific value is specified here.

[0154] Optionally, an initial stratigraphic model update stopping criterion can be set so that updates cease once the initial stratigraphic model meets the criterion. Further, there are various ways to set the update stopping criterion, such as a preset number of iterations (i.e., stopping updates when the initial stratigraphic model has been updated to the preset number of iterations), or a residual vector threshold (i.e., stopping updates when the value of the iterated residual vector is less than the set residual vector threshold). In this embodiment, the update stopping criterion is not specifically limited, as long as it can achieve the goal of stopping the update of the initial stratigraphic model.

[0155] The stratigraphic parameter determination method provided in this embodiment updates and iterates an initial stratigraphic model based on a stratigraphic parameter update formula and preset stratigraphic stratification rules to determine a target stratigraphic model. The method includes: obtaining the stratigraphic parameters updated using the stratigraphic parameter update formula; determining whether the difference in stratigraphic parameters between two adjacent stratigraphic strata in the initial stratigraphic model is less than a first preset threshold based on the updated stratigraphic parameters; and merging the two adjacent stratigraphic strata if the difference is less than the first preset threshold to determine the target stratigraphic model. This method, through iterative optimization of the stratigraphic parameter update formula, ensures more accurate stratigraphic parameters. It automatically merges stratigraphic strata using preset stratigraphic stratification rules to achieve the purpose of re-dividing the stratigraphic strata of the initial stratigraphic model. This results in a target stratigraphic model that more closely approximates the actual stratigraphic strata distribution for subsequent research applications.

[0156] As an optional implementation, based on any of the above embodiments, once the target stratigraphic model is determined—that is, the stratigraphic horizons and thicknesses of the target stratigraphic model more closely resemble the actual stratigraphic horizon distribution—the stratigraphic parameters are then determined through inversion using the aforementioned target stratigraphic model, target stratigraphic inversion function, iterative residual vector, and stratigraphic parameter update formula. This yields more accurate stratigraphic parameters for subsequent research and applications.

[0157] Figure 5 shows a formation parameter determination device provided in an embodiment of this application. As shown in Figure 5, the formation parameter determination device provided in this embodiment is located in an electronic device. The formation parameter determination device 30 provided in this embodiment includes: an acquisition module 31, a determination module 32, a model update module 33, and a formation parameter determination module 34.

[0158] Specifically, module 31 is used to acquire an initial stratigraphic model, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons uniformly distributed along the depth direction, where N is a positive integer. Module 32 is used to determine the target stratigraphic inversion function and iterative residual vector based on the initial stratigraphic model and seismic exploration data. The target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection dispersion curve. Module 32 is also used to determine the stratigraphic parameter update formula based on the target stratigraphic inversion function and the iterative residual vector. Module 33 is used to update and iterate the initial stratigraphic model based on the stratigraphic parameter update formula and preset stratigraphic layering rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic horizons distributed along the depth direction, where M is a positive integer and M is less than N. Module 34 is used to determine the stratigraphic parameters based on the target stratigraphic model. The stratigraphic parameters include P-wave velocity, S-wave velocity, and stratigraphic medium density.

[0159] Optionally, module 32, when determining the target stratum inversion function and iterative residual vector based on the initial stratigraphic model and seismic exploration data, is specifically used for: determining the initial Scholte wave dispersion curve and the initial Scholte wave deflection dispersion curve based on the initial stratigraphic model; determining the measured Scholte wave dispersion curve based on the seismic exploration data, and establishing the target stratum inversion function based on the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve; and determining the iterative residual vector based on the target stratum inversion function and the initial Scholte wave deflection dispersion curve.

[0160] Optionally, module 32, when determining the initial Scholte wave partial-guided dispersion curve based on the initial stratigraphic model, is specifically used for: establishing the Helmholtz equation for any stratigraphic level based on the initial stratigraphic model; differentiating the Helmholtz equation with respect to stratigraphic parameters to obtain the partial derivative differential equation; solving the general solution of the partial derivative differential equation; determining the displacement stress partial derivative vector for any stratigraphic level based on the general solution; establishing a recursive relationship based on the displacement stress partial derivative vector to obtain the recursive relationship between the displacement stress partial derivative vector of the first stratigraphic level and the displacement stress partial derivative vector of the Nth stratigraphic level; determining the Scholte wave partial-guided dispersion equation based on the recursive relationship; and solving the Scholte wave partial-guided dispersion equation to obtain the initial Scholte wave partial-guided dispersion curve.

[0161] Optionally, the target formation inversion function F(m) is expressed as: Among them, f c The initial Scholte wave dispersion curve, To measure the dispersion curve of the Scholte wave.

[0162] Optionally, the iterative residual vector d k Represented as: d k =-(G k T G k +α k I) -1 G k T f k , where d k Let G be the iterative residual vector of the k-th iteration. k Let I be the wave velocity partial derivative matrix of the k-th iteration, obtained from the initial Scholte wave partial derivative dispersion curve, where I is the identity matrix and α is the wave velocity partial derivative matrix. k f is a positive real constant. k This represents the calculated value of the target formation inversion function in the kth iteration. The formation parameter update formula is m. k+1 Represented as: m k+1 =m k +λ k d k , where m k Let m be the formation parameter vector matrix of the k-th iteration. k+1 Let λ be the formation parameter vector matrix for the (k+1)th iteration. k This is the step size calculated in the k-th iteration.

[0163] Optionally, the model update module 33, when updating and iterating the initial stratigraphic model based on the stratigraphic parameter update formula and preset stratigraphic stratification rules to determine the target stratigraphic model, specifically performs the following steps: Obtaining the stratigraphic parameters updated by the stratigraphic parameter update formula; determining whether the difference in stratigraphic parameters between two adjacent stratigraphic layers in the initial stratigraphic model is less than a first preset threshold based on the updated stratigraphic parameters; and merging the two adjacent stratigraphic layers to determine the target stratigraphic model if the difference in stratigraphic parameters between two adjacent stratigraphic layers is less than the first preset threshold.

[0164] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0165] Figure 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. As shown in Figure 6, the electronic device 40 provided in this embodiment includes: a processor 41 and a memory 42 that is communicatively connected to the processor.

[0166] The memory 42 stores computer execution instructions; the processor 41 executes the computer execution instructions stored in the memory 42 to implement the formation parameter determination method provided in any of the above embodiments.

[0167] The program may include program code, which includes computer-executable instructions. Memory 42 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0168] In this embodiment, the memory 42 and the processor 41 are connected via a bus 43. The bus 43 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus 43 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only a single straight line is used in Figure 6, but this does not indicate that there is only one bus or one type of bus 43.

[0169] This application also provides a computer-readable storage medium, including computer-executable instructions stored therein. When executed by a processor, these instructions are used to implement the formation parameter determination method provided in any of the above embodiments. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device. The non-transitory computer-readable storage medium may be any available medium or data storage device that can be accessed by a processor, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO), etc.), optical memory (e.g., CD, DVD, BD, HVD, etc.), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD), etc.).

[0170] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the formation parameter determination method provided in any of the above embodiments.

[0171] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0172] The modules described as separate components may or may not be physically separate. The components shown as modules 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 the modules can be selected to implement the solution of this embodiment according to actual needs.

[0173] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0174] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0175] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the disclosed method can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0176] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0177] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0178] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage 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 storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0179] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0180] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to 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; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0181] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for determining formation parameters, characterized in that, include: An initial stratigraphic model is obtained, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons that are uniformly distributed along the depth direction, where N is a positive integer. Based on the initial stratigraphic model and the seismic exploration data, the target stratigraphic inversion function and the iterative residual vector are determined, wherein the target stratigraphic inversion function is determined by the Scholte wave dispersion curve, and the iterative residual vector is determined by the Scholte wave deflection dispersion curve. The formation parameter update formula is determined based on the target formation inversion function and the iterative residual vector. The initial stratigraphic model is updated and iterated based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic strata distributed along the depth direction, where M is a positive integer and M is less than N. Formation parameters are determined based on the target formation model, including P-wave velocity, S-wave velocity, and formation medium density.

2. The method according to claim 1, characterized in that, The determination of the target stratigraphic inversion function and iterative residual vector based on the initial stratigraphic model and the seismic exploration data includes: The initial Scholte wave dispersion curve and the initial Scholte wave deflector dispersion curve are determined based on the initial stratigraphic model. The measured Scholte wave dispersion curve is determined based on the seismic exploration data, and the target stratum inversion function is established based on the measured Scholte wave dispersion curve and the initial Scholte wave dispersion curve. The iterative residual vector is determined based on the target stratum inversion function and the initial Scholte wave deflection curve.

3. The method according to claim 1 or 2, characterized in that, The determination of the initial Scholte wave deflection profile based on the initial stratigraphic model includes: Based on the initial stratigraphic model, establish the Helmholtz equation for any of the aforementioned stratigraphic horizons; The partial derivative differential equations are obtained by differentiating the Helmholtz equation with respect to formation parameters. Solve the general solution of the partial derivative differential equation; The displacement stress partial derivative vector of any stratum is determined based on the general solution. Based on the displacement stress partial derivative vector, a recursive relationship is established to obtain the recursive relationship between the displacement stress partial derivative vector of the first stratum and the displacement stress partial derivative vector of the Nth stratum. The Scholte wave partial guide dispersion equation is determined based on the recursive relationship. Solve the Scholte wave partial-guide dispersion equation to obtain the initial Scholte wave partial-guide dispersion curve.

4. The method according to any one of claims 1-3, characterized in that, The target formation inversion function F(m) is expressed as: Among them, f c The initial Scholte wave dispersion curve, the To measure the dispersion curve of the Scholte wave.

5. The method according to any one of claims 1-4, characterized in that, The iterative residual vector d k Represented as: d k =-(G k T G k +α k I) -1 G k T f k Where, d k Let G be the iterative residual vector of the k-th iteration. k Let I be the wave velocity partial derivative matrix of the k-th iteration, and the wave velocity partial derivative matrix is ​​obtained from the initial Scholte wave partial derivative dispersion curve, where I is the identity matrix and α is the wave velocity partial derivative matrix. k f is a positive real constant. k The calculated value of the k-th iteration of the target stratigraphic inversion function; The formation parameter update formula m k+1 Represented as: m k+1 =m k +λ k d k , where m k Let m be the formation parameter vector matrix of the k-th iteration. k+1 Let λ be the formation parameter vector matrix for the (k+1)th iteration. k This is the step size calculated in the k-th iteration.

6. The method according to any one of claims 1-5, characterized in that, The step of updating and iterating the initial stratigraphic model based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model includes: Obtain the updated formation parameters using the formation parameter update formula; Based on the updated stratigraphic parameters, determine whether the difference in stratigraphic parameters between two adjacent stratigraphic horizons in the initial stratigraphic model is less than a first preset threshold. If the difference in stratigraphic parameters between two adjacent stratigraphic layers is less than the first preset threshold, the two adjacent stratigraphic layers are merged to determine the target stratigraphic model.

7. A formation parameter determination device, characterized in that, include: The acquisition module is used to acquire an initial stratigraphic model, which is constructed based on known seismic exploration data. The initial stratigraphic model includes N stratigraphic horizons that are uniformly distributed along the depth direction, where N is a positive integer. The determination module is used to determine the target stratum inversion function and the iterative residual vector based on the initial stratigraphic model and the seismic exploration data, wherein the target stratum inversion function is determined by the Scholte wave dispersion curve and the iterative residual vector is determined by the Scholte wave deflection dispersion curve. The determining module is also used to determine the formation parameter update formula based on the target formation inversion function and the iterative residual vector; The model update module is used to update and iterate the initial stratigraphic model based on the stratigraphic parameter update formula and the preset stratigraphic stratification rules to determine the target stratigraphic model. The target stratigraphic model includes M stratigraphic strata distributed along the depth direction, where M is a positive integer and M is less than N. The formation parameter determination module is used to determine formation parameters based on the target formation model. The formation parameters include P-wave velocity, S-wave velocity, and formation medium density.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-6.

9. 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 as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-6.

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