Velocity model updating method and device based on seismic-logging data difference
By acquiring seismic and well logging data and updating the velocity model using the local similarity method, the problems of insufficient accuracy and geological consistency of the velocity model in the existing technology are solved, and a high-precision velocity model is constructed, which has significant effects, especially under complex geological conditions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2024-12-23
- Publication Date
- 2026-06-23
AI Technical Summary
Existing velocity model construction methods are inadequate in terms of the accuracy of automated seismic-well logging matching, the efficiency of velocity model updates, and geological consistency, especially under complex geological conditions.
By acquiring seismic and well logging data, local similarity is calculated using the Local Similarity Method (LSIM) to generate time offsets. Well logging velocities and seismic migration velocities are updated based on well logging velocities, and radial basis function weighting is combined to achieve smoothing of velocity information and geological consistency propagation.
It improves the accuracy and geological consistency of velocity models, solves the non-uniqueness problem in complex strata or anisotropic regions, and enhances the resolution of velocity models and the quality of seismic data processing.
Smart Images
Figure CN122260422A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of seismic image processing technology in petroleum seismic exploration, and more specifically, to a velocity model update method and apparatus based on the difference between seismic and well logging data. Background Technology
[0002] Seismic exploration technology, as an important tool for studying underground geological structures, focuses on inferring the distribution and properties of underground rock strata through the reflection characteristics of seismic waves. Velocity models are a crucial component in updating seismic velocity models based on the differences between seismic and well logging data, directly impacting the quality of seismic images and the accuracy of interpretation. Existing methods for constructing velocity models mainly include the following aspects:
[0003] Combining seismic and well logging data: While seismic data offers high spatial coverage, its resolution is relatively low; while well logging data, such as sonic logging, has high resolution but limited coverage. Therefore, combining the two through seismic-welltie matching to calibrate seismic images is a common method to improve the accuracy of velocity models.
[0004] Non-uniqueness of velocity models: During the construction of velocity models, due to the complexity of underground geological structures, there are often multiple velocity models that can satisfy the seismic data, which is the so-called non-uniqueness problem.
[0005] Injection of well logging data: In order to solve the problem of non-uniqueness, researchers have tried to inject well logging data into the construction of seismic migration velocity models to provide additional constraints.
[0006] Automated Seismic-Well Logging Matching Methods: To improve the efficiency and accuracy of seismic-well logging matching, several automated methods have been proposed. For example, Munoz and Hale [Munoz and Hale, 2012] used Dynamic Time Warping (DTW) to automatically align real and synthetic seismic maps. Herrera et al. [Herrera et al., 2014] demonstrated that the Local Similarity (LSIM) method can serve as an alternative to DTW, successfully calculating seismic-well logging matching.
[0007] However, despite the progress made in velocity model construction by existing technologies, several major problems remain, such as the accuracy of automated seismic-well logging matching, the efficiency of velocity model updates, and geological consistency. These issues limit the effectiveness of velocity models under complex geological conditions, necessitating a new technology to address them.
[0008] Therefore, how to solve the above problems is an urgent issue that needs to be addressed. Summary of the Invention
[0009] This application provides a velocity model update method and apparatus based on the difference between seismic and well logging data, aiming to improve the accuracy and geological consistency of the velocity model.
[0010] In a first aspect, this application provides a velocity model update method based on the difference between seismic and well logging data, the method comprising:
[0011] Acquire seismic and well logging data;
[0012] Seismic data was synthesized from the well logging data;
[0013] The local similarity between the model seismic data and the seismic data is calculated using the LSIM method to obtain the time offset;
[0014] Based on the time offset and the logging rate in the logging data, an updated logging rate is generated;
[0015] Obtain the initial seismic migration velocity;
[0016] An updated seismic migration velocity is generated based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and the updated seismic migration velocity is updated using the continuously updated logging velocity.
[0017] In one possible embodiment, the time offset satisfies:
[0018] LMin(t) = cor 2 (h k (t),r k (t+g k (t)));
[0019] Among them, h k (t) represents the seismic data of the model, r k (t) represents the earthquake data, g k (t) represents the time offset, cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
[0020] In one possible embodiment, generating an updated logging velocity based on the time offset and the logging velocity in the logging data includes:
[0021] Obtain the logging time corresponding to the current depth from the logging data;
[0022] An updated logging rate is generated based on the time offset, the logging rate, and the logging time.
[0023] In one possible embodiment, the updated logging rate satisfies:
[0024] v1(z)=v0(z)+g k (T0(z));
[0025] Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.
[0026] In one possible embodiment, the updated seismic migration velocity satisfies:
[0027]
[0028] Among them, v mig,0 Let v be the initial seismic migration velocity. mig,1 This indicates the updated seismic migration velocity.
[0029] In one possible embodiment, the method further includes:
[0030] The updated seismic migration velocities are propagated from well locations to the entire seismic dataset, and the velocity information is smoothed and geologically consistent through radial basis function weighting.
[0031] Secondly, this application provides a velocity model update device based on the difference between seismic and well logging data, the device comprising:
[0032] The first acquisition unit is used to acquire seismic data and well logging data;
[0033] The processing unit is used to synthesize model seismic data based on the well logging data;
[0034] The local similarity calculation unit is used to calculate the local similarity between the model seismic data and the seismic data using the LSIM method, and obtain the time offset;
[0035] The logging rate update unit is used to generate an updated logging rate based on the time offset and the logging rate in the logging data;
[0036] The second acquisition unit is used to acquire the initial seismic migration velocity;
[0037] The velocity model update unit is used to generate an updated seismic migration velocity based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and to update the updated seismic migration velocity using the continuously updated logging velocity.
[0038] In one possible embodiment, the time offset satisfies:
[0039] LMin(t) = cor 2 (h k (t),r k (t+g k (t)));
[0040] Among them, h k (t) represents the seismic data of the model, r k (t) represents the earthquake data, g k (t) represents the time offset, cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
[0041] In one possible embodiment, the logging velocity update unit is specifically used for:
[0042] Obtain the logging time corresponding to the current depth from the logging data;
[0043] An updated logging rate is generated based on the time offset, the logging rate, and the logging time.
[0044] In one possible embodiment, the updated logging rate satisfies:
[0045] v1(z)=v0(z)+g k (T0(z));
[0046] Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.
[0047] The present application provides a velocity model update method and apparatus based on the difference between seismic and well logging data. This method involves acquiring seismic and well logging data; synthesizing model seismic data from the well logging data; calculating the local similarity between the model seismic data and the seismic data using the LSIM method to obtain a time offset; generating an updated well logging velocity based on the time offset and the well logging velocity in the well logging data; obtaining an initial seismic migration velocity; and generating an updated seismic migration velocity based on the well logging velocity, the updated well logging velocity, and the initial seismic migration velocity. By quantifying misalignment and updating the seismic migration velocity through local similarity technology, this method achieves high accuracy and geological consistency in the velocity model. It not only improves the resolution of the velocity model but also helps solve the problem of constructing velocity models in complex strata or anisotropic regions, and has broad application prospects. Attached Figure Description
[0048] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0049] Figure 1 This is a schematic diagram of the structure of an electronic device provided in the first embodiment of this application;
[0050] Figure 2 A flowchart illustrating a velocity model update method based on seismic-well logging data differences, provided in the second embodiment of this application;
[0051] Figure 3 This is a schematic diagram of a traditional velocity model;
[0052] Figure 4 To adopt Figure 2 The diagram shows a velocity model updated using a velocity model update method based on the difference between seismic and well logging data.
[0053] Figure 5 A schematic diagram comparing the performance of a traditional velocity model with the velocity model provided in this application;
[0054] Figure 6 This is a schematic diagram of the functional modules of a velocity model update device based on the difference between seismic and well logging data, provided in the third embodiment of this application. Detailed Implementation
[0055] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0056] First embodiment:
[0057] Figure 1 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. In this application, it can be... Figure 1 The schematic diagram shown illustrates an example electronic device 100 for implementing the velocity model update method and apparatus based on seismic-well logging data differences according to embodiments of this application.
[0058] like Figure 1The diagram shows the structure of an electronic device 100. The electronic device 100 includes one or more processors 102, one or more storage devices 104, input devices 106, and output devices 108. These components are interconnected via a bus system and / or other forms of connection mechanisms (not shown). It should be noted that... Figure 1 The components and structure of the electronic device 100 shown are merely exemplary and not limiting; the electronic device may have, as needed. Figure 1 The components shown may also have Figure 1 Other components and structures not shown.
[0059] The processor 102 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 100 to perform desired functions.
[0060] It should be understood that the processor 102 in the embodiments of this application can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.
[0061] The storage device 104 may include one or more computer program products, which may include various forms of computer-readable storage media.
[0062] It should be understood that the storage device 104 in the embodiments of this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).
[0063] The computer-readable storage medium may store one or more computer program instructions, which the processor 102 may execute to implement the client functions (implemented by the processor) in the embodiments of this application described below, and / or other desired functions. Various applications and various data may also be stored in the computer-readable storage medium, such as various data used and / or generated by the applications.
[0064] The input device 106 may be a device used by a user to input commands, and may include one or more of the following: keyboard, mouse, microphone, and touch screen.
[0065] Second embodiment:
[0066] Reference Figure 2 The flowchart shown is a velocity model update method based on the difference between seismic and well logging data. The method specifically includes the following steps:
[0067] Step S201: Obtain seismic data and well logging data.
[0068] Step S202: Synthesize model seismic data based on the well logging data.
[0069] It should be noted that this embodiment does not limit the synthesis method, such as artificial synthesis.
[0070] Step S203: Calculate the local similarity between the model seismic data and the seismic data using the LSIM method to obtain the time offset.
[0071] Here, LSIM refers to the lsim function in Matlab. No specific limitations are specified here.
[0072] Optionally, the time offset satisfies:
[0073] LMin(t) = cor 2 (h k (t),r k (t+g k (t)));
[0074] Among them, h k (t) represents the seismic data (time profile) of the model, r k (t) represents the seismic data (time profile), g k (t) represents the time offset (i.e., the time offset corresponding to each moment in the seismic data), cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
[0075] Step S204: Generate an updated logging velocity based on the time offset and the logging velocity in the logging data.
[0076] As one implementation, step S204 includes: obtaining the logging time corresponding to the current depth in the logging data; and generating an updated logging speed based on the time offset, the logging speed, and the logging time.
[0077] Optionally, the updated logging rate satisfies:
[0078] v1(z)=v0(z)+g k (T0(z));
[0079] Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.
[0080] Step S205: Obtain the initial seismic migration velocity.
[0081] It is understandable that this initial seismic migration velocity is the migration velocity corresponding to the seismic data, i.e., the input initial velocity model.
[0082] Step S206: Generate an updated seismic migration velocity based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and update the updated seismic migration velocity using the continuously updated logging velocity.
[0083] Optionally, the updated seismic migration velocity satisfies:
[0084]
[0085] Among them, v mig,0 Let v be the initial seismic migration velocity. mig,1 This indicates the updated seismic migration velocity.
[0086] It should be noted that v mig,1 It can represent the updated seismic migration velocity, and can also be called a seismic migration velocity model.
[0087] In one possible embodiment, the method further includes: step S207, propagating the updated seismic migration velocity from the well location to the entire seismic dataset based on the local characteristics of the seismic structure, and achieving smooth and geologically consistent propagation of velocity information through radial basis function weighting.
[0088] In one possible embodiment, the method further includes repeating steps 203-S207 to iteratively update the seismic migration velocity model until a predetermined number of iterations is reached or the model converges. This is to generate a high-resolution seismic migration velocity model consistent with the well logging data after the iterative process.
[0089] For example, such as Figures 3-5 As shown, the velocity model updated using the velocity model update method based on the difference between seismic and well logging data provided in this embodiment is significantly better than the traditional velocity model.
[0090] It is understood that the velocity model update method based on the differences between seismic and well logging data provided in this embodiment significantly improves the accuracy and geological consistency of the velocity model through iterative updates. Compared with traditional methods, this invention can more effectively integrate well logging data, reduce the non-uniqueness problem in complex strata or anisotropic regions, thereby improving the quality and efficiency of seismic data processing.
[0091] Third embodiment:
[0092] See Figure 6The illustrated velocity model update device based on the difference between seismic and well logging data includes: a first acquisition unit 510, a processing unit 520, a local similarity calculation unit 530, a well logging velocity update unit 540, a second acquisition unit 550, and a velocity model update unit 560. The specific functions of each unit are as follows:
[0093] The first acquisition unit 510 is used to acquire seismic data and well logging data;
[0094] Processing unit 520 is used to synthesize model seismic data based on the well logging data;
[0095] The local similarity calculation unit 530 is used to calculate the local similarity between the model seismic data and the seismic data using the LSIM method to obtain the time offset;
[0096] The logging rate update unit 540 is used to generate an updated logging rate based on the time offset and the logging rate in the logging data;
[0097] The second acquisition unit 550 is used to acquire the initial seismic migration velocity;
[0098] The velocity model update unit 560 is used to generate an updated seismic migration velocity based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and to update the updated seismic migration velocity using the continuously updated logging velocity.
[0099] Optionally, the time offset satisfies:
[0100] LMin(t) = cor 2 (h k (t),r k (t+g k (t)));
[0101] Among them, h k (t) represents the seismic data of the model, r k (t) represents the earthquake data, g k (t) represents the time offset, cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
[0102] Optionally, the logging rate update unit is specifically used to: obtain the logging time corresponding to the current depth in the logging data; and generate an updated logging rate based on the time offset, the logging rate, and the logging time.
[0103] Optionally, the updated logging rate satisfies:
[0104] v1(z)=v0(z)+g k (T0(z));
[0105] Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.
[0106] Optionally, the updated seismic migration velocity satisfies:
[0107]
[0108] Among them, v mig,0 Let v be the initial seismic migration velocity. mig,1 This indicates the updated seismic migration velocity.
[0109] In one possible embodiment, the velocity model update device based on seismic-well logging data discrepancies further includes: a velocity model propagation and interpolation unit, used for:
[0110] The updated seismic migration velocities are propagated from well locations to the entire seismic dataset, and the velocity information is smoothed and geologically consistent through radial basis function weighting.
[0111] In one possible embodiment, the velocity model update device based on the difference between seismic and well logging data further includes an iterative update unit, used to repeatedly control the local similarity calculation unit 530, the well logging velocity update unit 540, the second acquisition unit 550, the velocity model update unit 560, and the velocity model propagation and interpolation unit to perform corresponding steps, so as to iteratively update the seismic migration velocity model until a predetermined number of iterations is reached or the model converges. This facilitates the generation of a high-resolution seismic migration velocity model consistent with the well logging data after the iterative process.
[0112] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program. When the computer program is run by a processing device, it executes the steps of any of the velocity model update methods based on seismic-well logging data differences provided in Embodiment 2 above.
[0113] The computer program product of the velocity model update method and apparatus based on seismic-well logging data differences provided in this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.
[0114] In summary, the velocity model update method and apparatus based on seismic-well logging data differences provided in this application acquires seismic data and well logging data; synthesizes model seismic data from the well logging data; calculates the local similarity between the model seismic data and the seismic data using the LSIM method to obtain a time offset; generates an updated well logging velocity based on the time offset and the well logging velocity in the well logging data; obtains an initial seismic migration velocity; and generates an updated seismic migration velocity based on the well logging velocity, the updated well logging velocity, and the initial seismic migration velocity. Thus, by quantifying misalignment and updating the seismic migration velocity through local similarity technology, high accuracy and geological consistency of the velocity model are achieved. This not only improves the resolution of the velocity model but also helps solve the problem of constructing velocity models in complex strata or anisotropic regions, and has broad application prospects.
[0115] It should be noted that the above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.
[0116] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.
[0117] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.
[0118] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0120] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0121] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components 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 through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0122] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0123] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0124] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
Claims
1. A velocity model update method based on the difference between seismic and well logging data, characterized in that, The method includes: Acquire seismic and well logging data; Seismic data was synthesized from the well logging data; The local similarity between the model seismic data and the seismic data is calculated using the LSIM method to obtain the time offset; Based on the time offset and the logging rate in the logging data, an updated logging rate is generated; Obtain the initial seismic migration velocity; An updated seismic migration velocity is generated based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and the updated seismic migration velocity is updated using the continuously updated logging velocity.
2. The method according to claim 1, characterized in that, The time offset satisfies: LMin(t)=cor 2 (h k (t),r k (t+g k (t))); Among them, h k (t) represents the seismic data of the model, r k (t) represents the earthquake data, g k (t) represents the time offset, cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
3. The method according to claim 2, characterized in that, Based on the time offset and the logging velocity in the logging data, an updated logging velocity is generated, including: Obtain the logging time corresponding to the current depth from the logging data; An updated logging rate is generated based on the time offset, the logging rate, and the logging time.
4. The method according to claim 3, characterized in that, The updated logging rate satisfies: v1(z)=v0(z)+g k (T0(z)); Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.
5. The method according to claim 4, characterized in that, The updated seismic migration velocity satisfies: Among them, v mig,0 Let v be the initial seismic migration velocity. mig,1 This indicates the updated seismic migration velocity.
6. The method according to any one of claims 1-5, characterized in that, The method further includes: The updated seismic migration velocities are propagated from well locations to the entire seismic dataset, and the velocity information is smoothed and geologically consistent through radial basis function weighting.
7. A velocity model update device based on the difference between seismic and well logging data, characterized in that, The device includes: The first acquisition unit is used to acquire seismic data and well logging data; The processing unit is used to synthesize model seismic data based on the well logging data; The local similarity calculation unit is used to calculate the local similarity between the model seismic data and the seismic data using the LSIM method, and obtain the time offset; The logging rate update unit is used to generate an updated logging rate based on the time offset and the logging rate in the logging data; The second acquisition unit is used to acquire the initial seismic migration velocity; The velocity model update unit is used to generate an updated seismic migration velocity based on the logging velocity, the updated logging velocity, and the initial seismic migration velocity, and to update the updated seismic migration velocity using the continuously updated logging velocity.
8. The apparatus according to claim 7, characterized in that, The time offset satisfies: LMin(t)=cor 2 (h k (t),r k (t+g k (t))); Among them, h k (t) represents the seismic data of the model, r k (t) represents the earthquake data, g k (t) represents the time offset, cor 2 It is a cross-correlation operation, where t represents the logging time in the seismic data.
9. The apparatus according to claim 8, characterized in that, The logging velocity update unit is specifically used for: Obtain the logging time corresponding to the current depth from the logging data; An updated logging rate is generated based on the time offset, the logging rate, and the logging time.
10. The apparatus according to claim 9, characterized in that, The updated logging rate satisfies: v1(z)=v0(z)+g k (T0(z)); Where v0(z) represents the logging rate, T0(z) represents the logging time corresponding to the current depth, and v1(z) is the updated logging rate.