Near-surface transverse wave velocity modeling method and device based on continuous data of nodal instrument, equipment and medium
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA NAT PETROLEUM CORP
- Filing Date
- 2024-12-19
- Publication Date
- 2026-06-23
Smart Images
Figure CN122260446A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of oil and gas exploration technology, specifically to a method, apparatus, equipment, and medium for modeling near-surface shear wave velocities based on continuous data from a node instrument. Background Technology
[0002] As oil and gas exploration becomes increasingly challenging and geological targets become more complex, modeling and imaging complex media present significant challenges. Near-surface velocity modeling plays a crucial role in the entire seismic data processing process; its resolution directly impacts the accuracy of static correction, thus affecting velocity analysis and the final migration imaging quality. Currently, near-surface velocity modeling primarily focuses on establishing P-wave models. However, in geological areas where P-wave detection is insensitive, establishing S-wave velocity models becomes particularly important. In related technologies, environmental noise recorded over long periods by oil and gas exploration nodal instruments is often discarded, making it impossible to effectively establish S-wave velocity models and determine the corresponding static correction values for these areas. Therefore, determining converted wave static correction values using continuous data acquired by nodal instruments is a novel seismic data processing technique. Summary of the Invention
[0003] In view of this, the present invention provides a method, apparatus, device, and medium for modeling near-surface shear wave velocities based on continuous data from a nodal instrument, in order to solve the technical problem in related technologies of how to determine the static correction amount of converted waves using continuous data collected by a nodal instrument.
[0004] In a first aspect, the present invention provides a near-surface shear wave velocity modeling method based on continuous data from nodal instruments. The method includes: acquiring seismic data continuously collected by several nodal instruments; dividing the pseudo-surface channels corresponding to the nodal instruments into interval ranges based on the seismic data and the location of the nodal instruments, and determining the shear wave vertical velocity structure corresponding to each nodal instrument; constructing a three-dimensional shear wave velocity model of the target area based on all the shear wave vertical velocity structures; and determining the converted wave static correction amount of the target area based on the three-dimensional shear wave velocity model.
[0005] In conjunction with the first aspect, in one possible implementation of the first aspect, based on seismic data and the location of nodal points, the pseudo-surface channels corresponding to the nodal points are divided into interval ranges to determine the shear wave vertical velocity structure corresponding to each nodal point. This includes: selecting any nodal point as the central nodal point; determining the data filtering range based on the location of the central nodal point; filtering the seismic data corresponding to the filtering range to determine the continuous data to be filtered; determining the pseudo-surface channels and interval ranges corresponding to each other nodal point based on the filtered continuous data; determining the shear wave vertical velocity structure corresponding to the central nodal point based on the pseudo-surface channels and interval ranges corresponding to each other nodal point; and selecting any other nodal point again as the new central nodal point based on the correspondence between the virtual source shot gather and the nodal points, and looping back to the step of determining the data filtering range based on the location of the central nodal point, until all nodal points have been traversed.
[0006] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the pseudo-surface channel and interval range corresponding to the nodal instrument based on the filtered continuous data includes: convolving the first filtered continuous data corresponding to the central nodal instrument with the second filtered continuous data corresponding to each of the other nodal instruments to calculate the pseudo-surface channel corresponding to each of the other nodal instruments; determining the spacing between the central nodal instrument and each of the other nodal instruments based on the pseudo-surface channel; and dividing each of the other nodal instruments into intervals based on the preset channel spacing and each spacing to determine the interval range corresponding to each of the other nodal instruments.
[0007] In conjunction with the first aspect, in one possible implementation of the first aspect, the shear wave vertical velocity structure corresponding to the center node instrument is determined based on the pseudo-surface channels and interval ranges corresponding to each other node instrument. This includes: vertically superimposing pseudo-surface channels belonging to the same interval range and arranging the pseudo-surface channels in a preset order to form a virtual source shot gather; calculating the actual dispersion curve based on the virtual source shot gather; establishing an initial velocity model and determining the theoretical dispersion curve; and determining the shear wave vertical velocity structure corresponding to the center node instrument based on the actual dispersion curve, the theoretical dispersion curve, and the virtual source shot gather.
[0008] In conjunction with the first aspect, in one possible implementation of the first aspect, the vertical velocity structure of the shear wave corresponding to the center nodal instrument is determined based on the actual dispersion curve, the theoretical dispersion curve, and the virtual source shot gather. This includes: performing dispersion curve inversion based on the difference between the actual and theoretical dispersion curves to determine the initial shear wave velocity model; determining the first surface wave waveform of the initial layered velocity model using forward modeling of the elastic wave equation based on the initial shear wave velocity model; fitting the first surface wave waveform with the second surface wave waveform of the virtual source shot gather, and using least squares to determine the vertical velocity structure of the shear wave corresponding to the center nodal instrument.
[0009] In conjunction with the first aspect, in one possible implementation of the first aspect, based on the initial shear wave velocity model, the first surface wave waveform of the initial layered velocity model is determined using elastic wave forward modeling, including: The equation for elastic waves can be expressed by the following formula:
[0010] in, , Represents the velocity component. , , Represents stress components, Indicates density, , , , This represents the elastic constant of the medium.
[0011] In conjunction with the first aspect, in one possible implementation of the first aspect, based on a three-dimensional shear wave velocity model, the converted wave static correction amount for the target region is determined, including: The static correction amount of the converted wave in the target area is expressed by the following formula:
[0012] in, This represents the static correction amount for the target area. i Indicates the firing point. j Indicates the detector point. s This indicates the static correction amount at the shot point. g This indicates the static correction amount at the receiver point. Indicates the first k The residual dynamic correction time difference coefficient at each conversion point h Indicates the thickness of the bottom layer. y Indicates the dip angle at the twentieth position. k The static correction amount at each conversion point.
[0013] Secondly, the present invention provides a near-surface shear wave velocity modeling device based on continuous data from nodal instruments. The device includes: an acquisition module for acquiring seismic data continuously collected by several nodal instruments; a velocity structure determination module for dividing the pseudo-surface channels corresponding to each nodal instrument into interval ranges based on the seismic data and the location of the nodal instruments, and determining the vertical shear wave velocity structure corresponding to each nodal instrument; a velocity model construction module for constructing a three-dimensional shear wave velocity model of the target area based on all the vertical shear wave velocity structures; and a static correction determination module for determining the static correction amount of the target area based on the three-dimensional shear wave velocity model.
[0014] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the near-surface shear wave velocity modeling method based on nodal instrument continuous data as described in the first aspect or any corresponding embodiment.
[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the near-surface shear wave velocity modeling method based on nodal instrument continuous data according to the first aspect or any corresponding embodiment described above.
[0016] The technical solution of this invention has the following advantages: This invention provides a method, apparatus, device, and medium for near-surface shear wave velocity modeling based on continuous nodal instrument data. The method divides the seismic data acquired by the nodal instrument into intervals based on its location, and constructs a three-dimensional shear wave velocity model of the target area based on the correspondence between the nodal instruments, thereby determining the converted wave static correction for the target area. In this process, continuous seismic data is acquired by the nodal instrument, and the corresponding pseudo-surface channels are divided into intervals according to the nodal instrument's location. A corresponding shear wave velocity model is constructed for each nodal instrument point. Using each corresponding shear wave velocity model, a subsurface medium shear wave velocity model is constructed, thus completing the construction of the three-dimensional shear wave velocity model. Furthermore, the converted wave static correction is calculated using the established three-dimensional shear wave velocity model, achieving more accurate converted wave static correction and laying the foundation for more accurate anisotropic migration imaging. Attached Figure Description
[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0018] Figure 1 This is a flowchart illustrating a near-surface shear wave velocity modeling method based on continuous data from a nodal instrument, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the arrangement array of node instruments provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of vertical stacking of pseudo-surface channels according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a virtual source gun collection provided according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the spectrum curve provided according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the dispersion curve inversion result provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of a three-dimensional shear wave velocity model provided according to an embodiment of the present invention; Figure 8 This is a schematic diagram comparing the superimposed cross-sections before and after static correction of the converted wave according to an embodiment of the present invention; Figure 9 This is a structural block diagram of a near-surface shear wave velocity modeling device based on continuous data from a nodal instrument, according to an embodiment of the present invention. Figure 10 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0020] According to an embodiment of the present invention, a near-surface shear wave velocity modeling method based on continuous data from a node instrument is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.
[0021] This embodiment provides a near-surface shear wave velocity modeling method based on continuous nodal instrument data, such as... Figure 1 As shown, the method includes the following steps: S101. Acquire seismic data continuously collected by several nodal instruments.
[0022] Specifically, oil and gas seismic exploration uses nodal instruments to acquire seismic data. These nodal instruments operate continuously, constantly recording information about the subsurface geological structure; the acquired seismic data is also known as continuous nodal instrument data. For example... Figure 2 As shown, an exemplary array arrangement of nodal points is illustrated, where each triangle represents a nodal point, and the dashed circles represent the cross-correlation relationships of environmental noise data between nodal points.
[0023] In one alternative implementation, the method further includes: preprocessing the seismic data, the preprocessing including: removing the mean and linear trend to eliminate the instrument DC component and linear trend; bandpass filtering to suppress high-frequency noise; time-domain normalization to eliminate strong amplitude interference; and spectral whitening to make the noise approximate white noise.
[0024] S102. Based on seismic data and the location of nodal instruments, divide the pseudo-surface channels corresponding to the nodal instruments into interval ranges and determine the vertical velocity structure of the shear waves corresponding to each nodal instrument.
[0025] Specifically, based on seismic data and the location of nodal points, the pseudo-surface channels corresponding to the nodal points are divided into interval ranges. Determining the shear wave vertical velocity structure corresponding to each nodal point involves selecting any nodal point as the central nodal point and determining the continuous data to be filtered. This continuous data is then used to determine the pseudo-surface channels and interval ranges corresponding to each other nodal point. The shear wave vertical velocity structure corresponding to the central nodal point is further determined. Based on the correspondence between the virtual source shot gather and the nodal points, any other nodal point is selected again as the new central nodal point. This process is repeated until all nodal points have been traversed.
[0026] S103. Based on all shear wave vertical velocity structures, construct a three-dimensional shear wave velocity model for the target region.
[0027] Specifically, constructing a three-dimensional shear wave velocity model of the target area based on all shear wave vertical velocity structures refers to laterally interpolating the vertical velocity structures corresponding to all nodal instruments to establish a three-dimensional shear wave velocity model of the subsurface medium within the oil and gas seismic exploration area, such as... Figure 7 As shown.
[0028] S104. Based on the three-dimensional shear wave velocity model, determine the static correction amount of the converted wave in the target area.
[0029] Specifically, determining the converted wave static correction amount of the target area based on the three-dimensional shear wave velocity model means using the longitudinal wave static correction to determine the shot point static correction amount, using the three-dimensional shear wave velocity model to determine the receiver point static correction amount, and thus determining the converted wave static correction amount of the target area.
[0030] This invention provides a method, apparatus, device, and medium for near-surface shear wave velocity modeling based on continuous nodal instrument data. The method divides the seismic data acquired by the nodal instruments into intervals based on their locations, and constructs a three-dimensional shear wave velocity model of the target area based on the correspondence between the nodal instruments, thereby determining the converted wave static correction for the target area. In this process, based on the continuously acquired seismic data from the nodal instruments, the corresponding pseudo-surface channels are divided into intervals according to the nodal instrument locations. A corresponding shear wave velocity model is constructed for each nodal instrument location. Using each corresponding shear wave velocity model, a subsurface medium shear wave velocity model is constructed, thus completing the construction of the three-dimensional shear wave velocity model. Furthermore, the converted wave static correction is calculated using the established three-dimensional shear wave velocity model, achieving more accurate converted wave static correction and laying the foundation for more accurate anisotropic migration imaging.
[0031] In one optional implementation, based on seismic data and the location of the nodal instruments, the pseudo-surface channels corresponding to the nodal instruments are divided into interval ranges to determine the shear wave vertical velocity structure corresponding to each nodal instrument, including: Select any nodal instrument as the central nodal instrument. Based on the position of the central nodal instrument, determine the data filtering range. Filter the seismic data corresponding to the filtering range to determine the continuous data to be filtered. Based on the filtered continuous data, determine the pseudo-surface channels and interval ranges corresponding to each other nodal instrument. Based on the pseudo-surface channels and interval ranges corresponding to each other nodal instrument, determine the shear wave vertical velocity structure corresponding to the central nodal instrument. Based on the correspondence between the virtual source shot gather and the nodal instrument, select any other nodal instrument again as the new central nodal instrument, and repeat the process until all nodal instruments have been traversed.
[0032] Specifically, selecting any node instrument as the central node instrument, and determining the data filtering range based on the location of the central node instrument, refers to... Figure 2 In the array of node instruments shown, any one node instrument can be selected as the central node instrument, and a rectangular area with a preset length and preset width is constructed with the central node instrument as the center. The preset length and preset width can be set according to the actual working conditions. This embodiment does not make a specific limitation on this. The rectangular area composed of the preset length and preset width is the data filtering range.
[0033] Specifically, screening seismic data corresponding to the screening range, and determining the continuous data to be screened, means using the seismic data collected by the corresponding nodal instruments within the screening range as the continuous data to be screened.
[0034] Specifically, determining the pseudo-surface channel and interval range corresponding to the node instrument based on the filtered continuous data means calculating the pseudo-surface channel corresponding to each other node instrument based on the filtered continuous data, and determining the distance between the central node instrument and each other node instrument based on the pseudo-surface channel. Then, using the distance and the preset channel spacing, the interval is divided for each other node instrument, and the interval range corresponding to each other node instrument is determined.
[0035] Specifically, determining the shear wave vertical velocity structure corresponding to the center node instrument based on the pseudo-surface channels and interval ranges corresponding to each other node instrument means vertically superimposing pseudo-surface channels belonging to the same interval range, arranging the pseudo-surface channels in a preset order to form a virtual source shot gather, and using the virtual source shot gather to calculate the dispersion curve to determine the shear wave vertical velocity structure corresponding to the center node.
[0036] Specifically, the correspondence between virtual source shot sets and node instruments means that in the data acquisition array, a data acquisition instrument that has already served as a center node instrument has a corresponding virtual source shot set. The premise for selecting any other node instrument as a new center node instrument is that the node has not been selected and is called a center node. Therefore, if a node instrument does not have a corresponding virtual source shot set, then the node instrument can become a new center node instrument.
[0037] Specifically, selecting any other node as the new central node and looping back to the position of the central node to determine the data filtering range, until all nodes have been traversed, means selecting another node in the data acquisition array as the central node and repeating the process of looping back to the position of the central node to determine the data filtering range, determining the shear wave vertical velocity structure corresponding to that central node, until all nodes have the corresponding shear wave vertical velocity structure. It should be understood that the rectangular area of each central node is a rectangular area of a preset length and preset width formed around that central node.
[0038] In one optional implementation, determining the pseudo-surface channel and interval range corresponding to the nodal instrument based on filtering continuous data includes: The first-selected continuous data corresponding to the center node instrument is convolved with the second-selected continuous data corresponding to each of the other nodes to calculate the pseudo-surface channels corresponding to each of the other nodes; based on the pseudo-surface channels, the spacing between the center node instrument and each of the other nodes is determined; based on the preset channel spacing and each spacing, each of the other nodes is divided into intervals to determine the interval range corresponding to each of the other nodes.
[0039] Specifically, the first-selection continuous data corresponding to the center node instrument is convolved with the second-selection continuous data corresponding to each of the other node instruments. The calculation of the pseudo-surface channels corresponding to each of the other node instruments refers to convolving the continuous data of the node instrument at the center point of the rectangle with the continuous data of all other node instruments in the rectangular area, and calculating multiple pseudo-surface channels corresponding to each of the other node instruments.
[0040] Specifically, determining the distance between the center node instrument and other node instruments based on the pseudo-surface channel means calculating the distance between two points using the distance formula between two points, based on the vertical and horizontal coordinates of the two node instruments that generated the pseudo-surface channel.
[0041] Specifically, based on the preset trace spacing and various intervals, each other nodal instrument is divided into intervals. Determining the interval range corresponding to each other nodal instrument means dividing the distance between the nodal instrument at the center point of the rectangle and other nodal instruments within the rectangular area, using the preset trace spacing as the unit. Here, the preset trace spacing refers to the trace spacing determined by the oil and gas seismic exploration observation system, denoted as Δx. Then, the interval range corresponding to each nodal instrument can be expressed as: 0 times Δx to 1 times Δx; 1 times Δx to 2 times Δx; 2 times Δx to 3 times Δx; 3 times Δx to 4 times Δx; ... For example, if the distance between a certain node and the center node is 100 meters, and the track distance between the node and the center node is 60 meters, then the node belongs to the range of 1 to 2 times Δx.
[0042] In one alternative implementation, the shear wave vertical velocity structure corresponding to the center node instrument is determined based on the pseudo-surface wave channel and interval range corresponding to each other node instrument, including: The pseudo-surface channels belonging to the same interval range are vertically superimposed and arranged in a preset order to form a virtual source shot gather; based on the virtual source shot gather, the actual dispersion curve is calculated; an initial velocity model is established to determine the theoretical dispersion curve; based on the actual dispersion curve, the theoretical dispersion curve and the virtual source shot gather, the vertical velocity structure of the shear wave corresponding to the center node instrument is determined.
[0043] Specifically, vertically stacking pseudo-surface channels belonging to the same interval range means vertically stacking pseudo-surface channels with nodal spacing within the same interval range to form a single channel, such as... Figure 3 As shown.
[0044] Specifically, arranging the pseudo-surface channels in a preset order to form a virtual source shot gather refers to arranging all pseudo-surface channels according to the nodal point spacing in a preset order to form a virtual source shot gather. The preset order is usually from smallest to largest; this embodiment does not specifically limit this. Figure 4 As shown in the figure, a virtual source gun set is formed by arranging the sources from smallest to largest.
[0045] Specifically, based on the virtual source shot gather, calculating the actual dispersion curve refers to calculating the dispersion spectrum using any surface wave dispersion spectrum calculation method, such as the phase-shift method, frequency-wavenumber transform method, high-precision linear Randon transform method, or frequency-Bessel transform method, and extracting the dispersion curve. The extracted dispersion curve is as follows: Figure 5 As shown.
[0046] Specifically, establishing an initial velocity model and determining the theoretical dispersion curve means establishing an initial velocity model and calculating the theoretical dispersion curve corresponding to that model.
[0047] Specifically, determining the shear wave vertical velocity structure corresponding to the center nodal instrument based on the actual dispersion curve, theoretical dispersion curve, and virtual source shot gather involves using the difference between the actual and theoretical dispersion curves to perform dispersion curve inversion, determining the initial shear wave velocity model, and then determining the surface wave waveform of the initial layered velocity through elastic wave forward modeling. This surface wave waveform is then fitted to the surface wave waveform of the virtual source shot gather, and the shear wave vertical velocity structure corresponding to the center nodal instrument is determined using the least squares method. The dispersion curve inversion results for a single nodal instrument are shown below. Figure 6 As shown.
[0048] In one optional implementation, the vertical velocity structure of the shear wave corresponding to the center node instrument is determined based on the actual dispersion curve, the theoretical dispersion curve, and the virtual source shot gather, including: Based on the difference between the actual dispersion curve and the theoretical dispersion curve, dispersion curve inversion is performed to determine the initial shear wave velocity model. Based on the initial shear wave velocity model, the first surface wave waveform of the initial layered velocity model is determined by forward modeling using the elastic wave equation. The first surface wave waveform is fitted with the second surface wave waveform of the virtual source shot gather, and the vertical velocity structure of the shear wave corresponding to the center node instrument is determined by least squares.
[0049] Specifically, based on the difference between the actual and theoretical dispersion curves, dispersion curve inversion is performed to determine the initial shear wave velocity model. This involves subtracting the actual and theoretical dispersion curves and using a least-squares local optimization algorithm or a global optimization algorithm such as a genetic algorithm to invert the dispersion curve, iteratively updating the velocity structure. The final result is the subsurface shear wave velocity structure model at a single point at the center of the rectangle, thus determining the initial shear wave velocity model. The result of the dispersion curve inversion is as follows: Figure 6 As shown.
[0050] Specifically, based on the initial shear wave velocity model, the first surface wave waveform of the initial layered velocity model is determined by using forward modeling of the elastic wave equation. This means establishing an initial layered model of equal thickness based on the initial shear wave velocity model, and using forward modeling of the elastic wave equation with the finite difference method to solve it, thereby determining the surface wave waveform of the forward modeled initial layered velocity model, i.e., the first surface wave waveform.
[0051] Specifically, fitting the first surface wave waveform with the second surface wave waveform of the virtual source shot collection and using least squares to determine the shear wave vertical velocity structure corresponding to the center node instrument means fitting the forward modeled surface wave waveform with the surface wave waveform in the virtual source shot collection formed by convolution superposition, using the least squares algorithm to continuously reduce the waveform error between the two, iterating and updating the velocity model in multiple rounds to obtain the optimal subsurface medium shear wave velocity structure at the rectangular center point, that is, determining the shear wave vertical velocity structure corresponding to the center node instrument. Among them, the least squares algorithm is represented by formula (1): (1) in, Let the objective function of the least squares algorithm be represented. This represents the surface wave waveform data from the forward model. This represents the surface wave waveform in a continuous data virtual source shot set.
[0052] Specifically, when the surface wave waveform error reaches its minimum, the velocity model obtained at this point is the final velocity model, which is the transverse wave vertical velocity structure corresponding to the center node instrument.
[0053] In one optional implementation, based on the initial shear wave velocity model, the first surface wave waveform of the initial layered velocity model is determined using forward modeling of the elastic wave equation, including: The elastic wave equation can be expressed by the following formula (2): (2) in, , Represents the velocity component. , , Represents stress components, Indicates density, , , , This represents the elastic constant of the medium.
[0054] In one optional implementation, the converted wave static correction amount for the target region is determined based on a three-dimensional shear wave velocity model, including: The static correction amount of the converted wave in the target area is expressed by the following formula (3): (3) in, This represents the static correction amount of the converted wave in the target area. i Indicates the firing point. j Indicates the detector point. s This indicates the static correction amount at the shot point. g This indicates the static correction amount at the receiver point. Indicates the first k The residual dynamic correction time difference coefficient at each conversion point h Indicates the thickness of the bottom layer. y Indicates the dip angle at the twentieth position. k The static correction amount at each conversion point.
[0055] Specifically, the shot point static correction quantity s i The static correction at the receiver point of the converted wave is obtained from the static correction of the longitudinal wave. g i The static correction for the converted wave, calculated using a three-dimensional shear wave velocity model, is more accurate. Furthermore, this correction can be used to improve anisotropic migration imaging results. When the terrain is relatively flat, the static correction at the receiver point... g i Much greater than the remaining normal time difference Time difference with structural dip angle y k sum. like Figure 8 As shown, an exemplary schematic diagram of the superimposed cross-sections before and after converted wave static correction is presented. It should be understood that the left side is the image corresponding to the converted wave before static correction, and the right side is the image corresponding to the converted wave after static correction.
[0056] This embodiment also provides a near-surface shear wave velocity modeling device based on continuous data from a nodal instrument. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.
[0057] This embodiment provides a near-surface shear wave velocity modeling device based on continuous data from a nodal instrument, such as... Figure 9 As shown, it includes: The acquisition module 201 is used to acquire seismic data continuously collected by several nodal instruments. For details, please refer to the description of step S101 in the above embodiments, which will not be repeated here. The velocity structure determination module 201 is used to divide the pseudo-surface wave channels corresponding to each nodal instrument into interval ranges based on seismic data and the location of the nodal instruments, and to determine the vertical velocity structure of the shear waves corresponding to each nodal instrument. For details, please refer to the relevant description of step S102 in the above embodiments, which will not be repeated here. The velocity model construction module 203 is used to construct a three-dimensional shear wave velocity model of the target region based on all shear wave vertical velocity structures. For details, please refer to the description of step S103 in the above embodiments, which will not be repeated here. The static correction determination module 204 is used to determine the converted wave static correction amount for the target region based on the three-dimensional shear wave velocity model. For details, please refer to the description of step S104 in the above embodiments, which will not be repeated here.
[0058] In this embodiment, the near-surface shear wave velocity modeling device based on continuous data from the node instrument is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.
[0059] This invention also provides a computer device having the above-described features. Figure 9 The diagram shows a near-surface shear wave velocity modeling device based on continuous nodal data. Please refer to [link / reference]. Figure 10 , Figure 10 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 10 As shown, the computer device includes one or more processors 301, memory 302, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 10 Take processor 301 as an example.
[0060] Processor 301 may be a central processing unit, a network processor, or a combination thereof. Processor 301 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.
[0061] The memory 302 stores instructions executable by at least one processor 301 to cause the at least one processor 301 to perform the method shown in the above embodiments.
[0062] Memory 302 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, memory 302 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 302 may optionally include memory remotely located relative to processor 301, and this remote memory may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0063] The memory 302 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 302 may also include combinations of the above types of memory. The computer device also includes a communication interface 303 for communicating with other devices or communication networks.
[0064] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.
[0065] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.
Claims
1. A method for modeling near-surface shear wave velocities based on continuous nodal instrument data, characterized in that, The method includes: Acquire seismic data continuously collected by several nodal instruments; Based on the seismic data and the location of the nodal instruments, the pseudo-surface channels corresponding to the nodal instruments are divided into interval ranges to determine the vertical velocity structure of the shear waves corresponding to each nodal instrument. Based on all the described shear wave vertical velocity structures, a three-dimensional shear wave velocity model of the target region is constructed. Based on the three-dimensional shear wave velocity model, the converted wave static correction amount for the target region is determined.
2. The method according to claim 1, characterized in that, Based on the seismic data and the location of the nodal instruments, the pseudo-surface channels corresponding to the nodal instruments are divided into interval ranges to determine the shear wave vertical velocity structure corresponding to each nodal instrument, including: Select any node instrument as the central node instrument, and determine the data filtering range based on the position of the central node instrument; Filter the earthquake data corresponding to the filtering range to determine the continuous data to be filtered; Based on the filtered continuous data, determine the pseudo-surface channel and interval range corresponding to each other node instrument; Based on the pseudo-surface wave channel and interval range corresponding to each other node instrument, the shear wave vertical velocity structure corresponding to the central node instrument is determined. Based on the correspondence between the virtual source gun set and the node instrument, any other node instrument is selected as the new central node instrument, and the process is repeated until the step of determining the data filtering range based on the position of the central node instrument is completed, until all the node instruments are traversed.
3. The method according to claim 2, characterized in that, The step of determining the pseudo-surface channel and interval range corresponding to each other node instrument based on the filtered continuous data includes: The first selected continuous data corresponding to the central node instrument is convolved with the second selected continuous data corresponding to each other node instrument to calculate the pseudo-surface channel corresponding to each other node instrument. Based on the pseudo-surface wave channel, the spacing between the central node instrument and each of the other node instruments is determined; Based on the preset track spacing and the aforementioned intervals, each other node instrument is divided into intervals to determine the interval range corresponding to each other node instrument.
4. The method according to claim 2, characterized in that, The determination of the shear wave vertical velocity structure corresponding to the center node instrument based on the pseudo-surface wave channel and interval range corresponding to each other node instrument includes: The pseudo-surface channels belonging to the same interval range are vertically superimposed and arranged in a preset order to form a virtual source shot collection. Based on the virtual source gun set, calculate the actual dispersion curve; Establish an initial velocity model and determine the theoretical dispersion curve; Based on the actual dispersion curve, the theoretical dispersion curve, and the virtual source shot collection, the transverse wave vertical velocity structure corresponding to the center node instrument is determined.
5. The method according to claim 4, characterized in that, The determination of the transverse wave vertical velocity structure corresponding to the center node instrument based on the actual dispersion curve, the theoretical dispersion curve, and the virtual source shot gather includes: Based on the difference between the actual dispersion curve and the theoretical dispersion curve, dispersion curve inversion is performed to determine the initial shear wave velocity model. Based on the initial shear wave velocity model, the first surface wave waveform of the initial layered velocity model is determined by using forward modeling of the elastic wave equation. The waveform of the first surface wave is fitted with the waveform of the second surface wave of the virtual source shot collection, and the vertical velocity structure of the transverse wave corresponding to the center node instrument is determined by least squares.
6. The method according to claim 5, characterized in that, The determination of the first surface wave waveform of the initial layered velocity model based on the initial shear wave velocity model, using forward modeling of the elastic wave equation, includes: The equation for elastic waves can be expressed by the following formula: in, , Represents the velocity component. , , Represents stress components, Indicates density, , , , This represents the elastic constant of the medium.
7. The method according to claim 1, characterized in that, The determination of the converted wave static correction amount for the target region based on the three-dimensional shear wave velocity model includes: The static correction amount of the converted wave in the target area is expressed by the following formula: in, This represents the static correction amount of the converted wave in the target area. i Indicates the firing point. j Indicates the detector point. s This indicates the static correction amount at the shot point. g This indicates the static correction amount at the receiver point. Indicates the first k The residual dynamic correction time difference coefficient at each conversion point h Indicates the thickness of the bottom layer. y Indicates the dip angle at the twentieth position. k The static correction amount at each conversion point.
8. A near-surface shear wave velocity modeling device based on continuous data from a nodal instrument, characterized in that, The device includes: The acquisition module is used to acquire seismic data continuously collected by several nodal instruments; The velocity structure determination module is used to divide the pseudo-surface wave channel corresponding to the nodal instrument into interval ranges based on the seismic data and the position of the nodal instrument, and determine the vertical velocity structure of the shear wave corresponding to each nodal instrument. The velocity model construction module is used to construct a three-dimensional shear wave velocity model of the target region based on all the shear wave vertical velocity structures described above. The static correction determination module is used to determine the converted wave static correction amount of the target region based on the three-dimensional shear wave velocity model.
9. A computer device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the near-surface shear wave velocity modeling method based on continuous nodal instrument data as described in any one of claims 1 to 7 by executing the computer instructions.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the near-surface shear wave velocity modeling method based on continuous nodal instrument data as described in any one of claims 1 to 7.