Method and system for determining initial velocity model from seismic data inversion

Abstract

The application provides a method and system for determining an initial velocity model of seismic data inversion, and the method comprises the following steps: collecting seismic data and gravity data of a research area; obtaining a plurality of underground geological body velocity models through gravity data inversion and a preset lithology-velocity-density corresponding table; obtaining a plurality of forward seismic data according to the plurality of underground geological body velocity models, and determining a minimum velocity model of fitting difference between the forward seismic data and measured seismic data as the initial velocity model. The application can improve the efficiency and reliability of seismic data inversion.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geophysical inversion technology, and particularly relates to a method and system for determining an initial velocity model for seismic data inversion. BACKGROUND

[0002] The iterative inversion algorithm is the mainstream geophysical inversion algorithm at present, and the general steps are: data acquisition-given initial model-initial model forward calculation-calculation of data fitting difference-iterative update model, with the increase of the number of iterations, the model will be more and more close to the true model, and the data fitting difference will be smaller and smaller, until the fitting difference is smaller than a certain threshold or the number of iterations reaches the upper limit. As can be seen, when the given initial model is closer to the true model, the inversion algorithm can converge more quickly, and the dependence of the inversion result on the initial model is obvious.

[0003] In the prior art, there are also journals or patents discussing the importance of selecting the initial model of the inversion algorithm, for example, the paper 'Establishment of initial model in seismic wave impedance inversion' published by Wei Jia et al. proposes how to accurately give the initial model of seismic wave impedance inversion, but only introduces the concept and does not give the specific implementation. The patent CN108304618B mentions that starting from the uniform half-space model for the first inversion iteration, the error is accumulated in the subsequent iteration process, which affects the final result and even leads to non-convergence of the iteration process. The solution is to obtain another initial model of physical properties according to the relationship between the density and the resistivity obtained from the rock samples in the study area and the initial inversion result with good data quality. However, this method must collect a large number of rock samples in the study area, and generally the surface rock samples are easy to collect, but as the depth increases, the pressure and temperature increase, and the relationship between the physical properties obtained from the surface rock samples may not be applicable to the deep underground structure, which may cause large deviation of the inversion result. SUMMARY

[0004] An object of the present application is to provide a method for determining an initial velocity model for seismic data inversion, which improves the efficiency and reliability of seismic data inversion. Another object of the present application is to provide a server, a terminal, a computer device and a readable medium.

[0005] In order to achieve the above objects, one aspect of the present application discloses a method for determining an initial velocity model for seismic data inversion, comprising:

[0006] acquiring seismic data and gravity data of a study area;

[0007] obtaining a plurality of velocity models of underground geological bodies through gravity data inversion and a preset lithology-velocity-density correspondence table;

[0008] Forwarding according to the plurality of underground geological body velocity models obtains a plurality of forward seismic data, and a velocity model with minimum fitting difference between the forward seismic data and measured seismic data is determined as an initial velocity model.

[0009] Preferably, the plurality of underground geological body velocity models obtained by gravity data inversion and a preset lithology-velocity-density corresponding table specifically comprises:

[0010] Grid division is performed on the underground geological body.

[0011] A density model is obtained by gravity data inversion according to the seismic data and the gravity data.

[0012] A corresponding relationship of a plurality of velocity-density models is obtained according to the preset lithology-velocity-density corresponding table.

[0013] The plurality of underground geological body velocity models are obtained according to the density model and the corresponding relationship of the plurality of velocity-density models.

[0014] Preferably, the seismic data is travel time data, and the gravity data is residual gravity data.

[0015] Preferably, the algorithm of the gravity data inversion is a genetic algorithm, a neural network method or a simulated annealing method.

[0016] Preferably, the density model is a column vector composed of density values of each grid in the grid division.

[0017] Preferably, the lithology-velocity-density corresponding table comprises an exponential relationship and a polynomial relationship between the velocity and the density of rocks of different lithologies.

[0018] Preferably, the exponential relationship between the velocity and the density of rocks of different lithologies is a Gardner relationship, and the polynomial relationship between the velocity and the density of rocks of different lithologies is a Castagna relationship.

[0019] Preferably, the determination of the velocity model with minimum fitting difference between the forward seismic data and the measured seismic data as the initial velocity model specifically comprises:

[0020] The fitting difference between the forward seismic data and the measured seismic data is calculated by a two-norm formula.

[0021] The velocity model with minimum fitting difference is taken as the initial velocity model of the seismic data inversion.

[0022] The application further discloses a seismic data inversion initial velocity model determination method, which comprises:

[0023] A data acquisition module is configured to acquire seismic data and gravity data of a research area.

[0024] The seismic model determining module is configured to obtain multiple underground geological body velocity models through gravity data inversion and a preset lithology-velocity-density correspondence table.

[0025] The initial velocity model determining module is configured to determine an initial velocity model by performing forward modeling on the multiple underground geological body velocity models to obtain multiple forward seismic data, and determining a velocity model with the least fitting difference between the forward seismic data and the measured seismic data as the initial velocity model.

[0026] Preferably, the seismic model determining module is specifically configured to perform grid division on the underground geological body, perform gravity data inversion on the seismic data and the gravity data to obtain a density model, obtain a corresponding relationship of multiple velocity-density models according to the preset lithology-velocity-density correspondence table, and obtain the multiple underground geological body velocity models according to the density model and the corresponding relationship of the multiple velocity-density models.

[0027] Preferably, the seismic data is travel time data, and the gravity data is residual gravity data.

[0028] Preferably, the algorithm of the gravity data inversion is a genetic algorithm, a neural network method or a simulated annealing method.

[0029] Preferably, the density model is a column vector composed of the density values of each grid in the grid division.

[0030] Preferably, the lithology-velocity-density correspondence table includes an exponential relationship and a polynomial relationship between the velocities and the densities of rocks with different lithologies.

[0031] Preferably, the exponential relationship between the velocities and the densities of the rocks with different lithologies is a Gardner relationship, and the polynomial relationship between the velocities and the densities of the rocks with different lithologies is a Castagna relationship.

[0032] Preferably, the initial velocity model determining module is specifically configured to calculate the fitting difference between the forward seismic data and the measured seismic data by using a two-norm formula, and determine the velocity model with the least fitting difference as the initial velocity model of the seismic data inversion.

[0033] The application further discloses a computer device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor,

[0034] The processor implements the method as described above when executing the program.

[0035] The application further discloses a computer readable medium, which stores a computer program,

[0036] The program is executed by the processor to implement the method as described above.

[0037] This invention provides a method for retrieving a density model of a subsurface geological body using gravity data. Then, based on empirical formulas relating rock properties, various velocity models for the subsurface geological body are obtained. Finally, the initial model for seismic inversion is determined by the magnitude of the fitting difference between the forward modeling results corresponding to these velocity models and measured seismic data. The velocity model provided by the density model in this invention closely approximates the actual model, effectively reducing the time required for iterative inversion calculations, improving computational efficiency, and preventing convergence of the iterative calculations. Furthermore, this invention does not require rock sample collection. By selecting the model with the smallest fitting difference between the forward modeling results and measured data based on various empirical formulas relating velocity and density, the effectiveness of the algorithm is ensured under different working areas and lithological conditions. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating a specific embodiment of the method for determining the initial velocity model in seismic data inversion according to the present invention is shown.

[0040] Figure 2 A flowchart illustrating a specific embodiment S200 of the method for determining the initial velocity model for seismic data inversion according to the present invention is shown.

[0041] Figure 3 A flowchart illustrating a specific embodiment S300 of the method for determining the initial velocity model for seismic data inversion according to the present invention is shown.

[0042] Figure 4 A flowchart illustrating a specific example of the method for determining the initial velocity model in seismic data inversion according to the present invention;

[0043] Figure 5 This diagram illustrates a specific example of the method for determining the initial velocity model in seismic data inversion according to the present invention, showing a subsurface grid partitioning and a schematic diagram of seismic receiver points and gravity measuring points;

[0044] Figure 6 This diagram illustrates a specific embodiment of the seismic data inversion initial velocity model determination system of the present invention.

[0045] Figure 7 A schematic diagram of a computer device suitable for implementing embodiments of the present invention is shown. Detailed Implementation

[0046] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application.

[0047] The components of the embodiments of the present application generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application.

[0048] Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0049] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0050] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the connection inside two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0051] According to one aspect of the present application, the embodiments disclose a method for determining initial velocity model of seismic data inversion. As shown in the figure, Figure 1 The method comprises the following steps:

[0052] S100: Collecting seismic data and gravity data of the study area. It should be noted that the seismic data S is travel time data, and the gravity data G is residual gravity data.

[0053] S200: Obtain a plurality of underground geological body velocity models by gravity data inversion and a preset lithology-velocity-density correspondence table.

[0054] S300: forward according to the plurality of subsurface geological body velocity model obtains a plurality of forward seismic data, determine the fitting difference minimum velocity model between forward seismic data and measured seismic data is initial velocity model.

[0055] The application provides a density model of a subsurface geological body by using gravity data inversion, and a plurality of velocity models of the subsurface geological body are obtained according to empirical formulas between rock physical properties, and the initial model of seismic inversion is determined according to the fitting difference between the corresponding forward results of the plurality of velocity models of the subsurface geological body and measured seismic data. The velocity model given according to the density model is close to the real model, the time of iterative calculation of inversion can be effectively reduced, the calculation efficiency is improved, and the iterative calculation does not converge. Moreover, the application does not need to collect rock samples, a model with the minimum fitting difference between the forward result and the measured data is selected according to a plurality of velocity-density empirical formulas, and the effectiveness of the algorithm under different working areas and different lithology conditions is ensured.

[0056] In the preferred embodiment, as shown in Figure 2 S200 can specifically include the following steps:

[0057] S210: grid division is performed on the subsurface geological body.

[0058] S220: a density model is obtained by gravity data inversion according to the seismic data and the gravity data.

[0059] S230: a corresponding relationship of a plurality of velocity-density models is obtained according to a preset lithology-velocity-density corresponding table.

[0060] S240: a plurality of velocity models of the subsurface geological body are obtained according to the density model and the corresponding relationship of the plurality of velocity-density models.

[0061] Preferably, one of a genetic algorithm, a neural network method and a simulated annealing method is used to invert the gravity data, and a density model M G of the subsurface geological body in the research area is obtained. The M G obtained by inversion is a column vector composed of the density values of each grid in the grid division.

[0062] The preset lithology-velocity-density corresponding table includes an exponential relationship and a polynomial relationship between the velocity and the density of rocks with different lithologies. Preferably, the exponential relationship between the velocity and the density of rocks with different lithologies is a Gardner relationship, and the polynomial relationship between the velocity and the density of rocks with different lithologies is a Castagna relationship. Specifically, the general expression of the Gardner relationship is The general expression of the Castagna relationship is wherein ρ is the density, v pFor speed, a, b, c, d and e are coefficients, Table 1 shows a specific example of the coefficient value table of different lithology, the specific value of the coefficient can be obtained by pre-experiment or taking an empirical value, the present application does not make limitation to this.

[0063] Table 1

[0064] Lithology a b c d e Shale 1.75 0.265 -0.0261 0.373 1.458 Sandstone 1.66 0.261 -0.0115 0.261 1.515 Limestone 1.50 0.225 -0.0296 0.461 0.963 Dolomite 1.74 0.252 -0.0235 0.390 1.242

[0065] In a preferred embodiment, as shown in Figure 3 The S300 determines the minimum velocity model of the fitting difference between the forward seismic data and the measured seismic data as the initial velocity model, which specifically can include:

[0066] S310: Calculate the fitting difference between the forward seismic data and the measured seismic data by the two norm formula.

[0067] S320: Take the velocity model with the minimum fitting difference as the initial velocity model of the seismic data inversion.

[0068] In one specific example, the two norm formula is R i =‖S i -S‖ 2 , wherein i=1, 2, 3…, N. The fitting difference can be calculated by the two norm formula.

[0069] The present application will be further described by a specific example. In this embodiment, a certain work area mainly composed of limestone is taken as an example to introduce the initial model giving method of the present application in detail. Figure 4 The flow chart of the method for determining the initial velocity model of the seismic data inversion in this embodiment is shown in Figure 5 The schematic diagram of the underground grid dissection and the seismic detection point and the gravity measurement point in this embodiment is shown in FIG. 2, the vertical downward is the depth direction, the study area is dissectioned into 50m×50m, a total of 10×10 grids, Figure 5 The geological target body (i.e. the abnormal body) in the middle is a plate-shaped model with a depth of 100m and a size of 200m×100m, the inverted triangle in the figure is the seismic detection point and the gravity measurement point (both are repeated), which is located on the ground surface, the point distance is 50m, and the seismic shot point and the detection point are coincident.

[0070] The method for determining the initial velocity model of the seismic data inversion in this embodiment includes the following steps:

[0071] S1: Collect seismic data S and gravity data G in the study area simultaneously. The seismic data is travel time data, and the gravity data is residual gravity data. The seismic data S is a column vector of travel time data, and the gravity data G is a column vector of residual gravity data. For example, in this example, S = [s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] and G = [g1, g2, g3, g4, g5, g6, g7, g8, g9, g10]. Wherein s1-s10 are travel time data of 10 measuring points, and g1-g10 are residual gravity data of 10 measuring points.

[0072] S2: Grid division is performed on the underground geological body, and the study area is divided into 50m x 50m, a total of 10 x 10 grids.

[0073] S3: Use one of genetic algorithm, neural network method or simulated annealing method to invert the gravity data to obtain the density model M of the underground geological body in the study area G ; M G is a column vector composed of the density values of each grid in step S2, MG = [p1, p2, p3, …, p100], p1, p2, p3, …, p100 are the density values in the first to the 100th grid, respectively.

[0074] S4: Determine the velocity-density model N corresponding relationship according to the lithology-velocity-density corresponding table, N is a positive integer. The lithology-velocity-density corresponding table includes the exponential and polynomial relationship between the velocity and density of different rocks of different lithologies. The exponential relationship between the velocity and density of different rocks of different lithologies is Gardner relationship, and the polynomial relationship between the velocity and density of different rocks of different lithologies is Castagna relationship. The general expression of the Gardner relationship is The general expression of the Castagna relationship is Where p is the density, v p is the velocity, a, b, c, d and e are coefficients. In this example, there are 8 corresponding relationships between velocity and density, which are as follows:

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] S5: according to the M G and the velocity-density model corresponding relationship, 8 underground geological body velocity models M S1 , M S2 , …, M S8 .

[0084] S6: using the 8 underground geological body velocity models to perform forward, 8 forward seismic data S1, S2, … S8 are obtained. Wherein, S1=[s11, s12, s13, …, s110]; S2=[s21, s22, s23, …, s210]; … S8=[s81, s82, s83, …, s810].

[0085] S7: calculate the fitting difference R1, R2, … R8 between the forward seismic data S1, S2, … S8 and the measured seismic data S, using the two norm formula R i =‖S i -S‖ 2 to calculate the fitting difference, wherein i=1, 2, 3, …, 8. Wherein, R1=(s 11 -s1) 2 +(s 12 -s2) 2 +…+(s 110 -s 10 ) 2 , R2, … R8 are similar.

[0086] S8: compare R1, R2, … R N , in this example, finally R7 is minimum, the velocity model with the minimum fitting difference is taken as the initial velocity model of seismic data inversion, that is, the velocity model calculated by the formula is taken as the initial velocity model of seismic data inversion.

[0087] In order to illustrate the technical effect of the present application, eight models are used for inversion test respectively, and the calculation efficiency and calculation accuracy are shown in table 2.

[0088] Table 2 initial model inversion time consumption and fitting difference comparison table

[0089]

[0090] From the table, it can be concluded that the model 7 has the least inversion time and the smallest fitting error, indicating that the inversion efficiency and accuracy are relatively improved.

[0091] Based on the same principle, the embodiment also discloses a method for determining an initial velocity model in seismic data inversion. Figure 6 As shown in the figure, in the embodiment, the system comprises a data acquisition module 11, a seismic model determination module 12, and an initial velocity model determination module 13.

[0092] The data acquisition module 11 is configured to acquire seismic data and gravity data of a study area.

[0093] The seismic model determination module 12 is configured to obtain a plurality of velocity models of underground geological bodies by gravity data inversion and a preset lithology-velocity-density correspondence table.

[0094] The initial velocity model determination module 13 is configured to obtain a plurality of forward seismic data by forward calculation according to the plurality of velocity models of underground geological bodies, and determine a minimum fitting error velocity model between the forward seismic data and the measured seismic data as the initial velocity model.

[0095] In the preferred embodiment, the seismic model determination module 12 is specifically configured to perform grid division on the underground geological bodies, obtain a density model by gravity data inversion according to the seismic data and the gravity data, obtain a corresponding relationship of a plurality of velocity-density models according to the preset lithology-velocity-density correspondence table, and obtain the plurality of velocity models of underground geological bodies according to the density model and the corresponding relationship of the plurality of velocity-density models.

[0096] In the preferred embodiment, the seismic data is travel time data, and the gravity data is residual gravity data.

[0097] In the preferred embodiment, the algorithm of the gravity data inversion is a genetic algorithm, a neural network method, or a simulated annealing method.

[0098] In the preferred embodiment, the density model is a column vector composed of density values of each grid in the grid division.

[0099] In the preferred embodiment, the lithology-velocity-density correspondence table comprises an exponential relationship and a polynomial relationship between the velocity and the density of rocks of different lithologies.

[0100] In the preferred embodiment, the exponential relationship between the velocity and the density of rocks of different lithologies is a Gardner relationship, and the polynomial relationship between the velocity and the density of rocks of different lithologies is a Castagna relationship.

[0101] In the preferred embodiment, the initial velocity model determination module 13 is specifically configured to calculate the fitting difference between the forward seismic data and the measured seismic data by using the two-norm formula; and the velocity model with the minimum fitting difference is taken as the initial velocity model of the seismic data inversion.

[0102] Since the principle of solving problems of the system is similar to the above method, the implementation of the system can refer to the implementation of the method, which will not be repeated here.

[0103] The system, device, module or unit illustrated in the above embodiments can be specifically implemented by a computer chip or entity, or by a product with certain functions. A typical implementation device is a computer device, specifically, the computer device may, for example, be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0104] In a typical example, the computer device specifically includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method as described above when executing the program.

[0105] The following refers to Figure 7 which shows a structural schematic diagram of a computer device 600 suitable for being used to implement the embodiments of the present application.

[0106] As shown in Figure 7 , the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate operations and processes according to programs stored in a read-only memory (ROM) 602 or programs loaded into a random access memory (RAM) 603 from a storage portion 608. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0107] The following components are connected to the I / O interface 605: an input part 606 including a keyboard, a mouse, etc.; an output part 607 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 608 including a hard disk, etc.; and a communication part 609 including a network interface card such as a LAN card, a modem, etc. The communication part 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as necessary. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 610 as necessary, so that a computer program read out therefrom is installed in the storage part 608 as necessary.

[0108] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program tangibly embodied on a machine readable medium, the computer program comprising program code for executing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication part 609, and / or installed from the removable medium 611.

[0109] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media such as modulated data signals and carriers.

[0110] For the convenience of description, the above apparatus is described in various units by function. Of course, the functions of each unit can be implemented in the same or more software and / or hardware when implementing the present application.

[0111] The embodiments of the present application are described with reference to the flowchart illustrations and / or block diagrams of the methods, apparatus (systems) and computer program products according to the embodiments of the present application. It is understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0112] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0114] It should also be noted that the terms "comprising," "including," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0115] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, and the like) embodying computer readable program code.

[0116] The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in local and remote computer storage media including memory storage devices.

[0117] The various embodiments in the specification are described progressively, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, the system embodiments are described simply because they are basically similar to the method embodiments, and the relevant parts can be referred to the description of the method embodiments.

[0118] The above only describes the embodiments of the present application and is not intended to limit the present application. The present application can have various changes and modifications for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the scope of claims of the present application.

Claims

1. A method for determining the initial velocity model in seismic data inversion, characterized in that, include: Collect seismic and gravity data for the study area; Multiple velocity models of underground geological bodies were obtained by gravity data inversion and by using a pre-defined lithology-velocity-density correspondence table. Multiple forward modeling seismic data were obtained by performing forward modeling on the multiple underground geological body velocity models. The velocity model with the smallest fitting difference between the forward modeling seismic data and the measured seismic data was determined as the initial velocity model. The specific methods for obtaining velocity models of multiple underground geological bodies through gravity data inversion and a preset lithology-velocity-density correspondence table include: Grid subdivision of underground geological bodies; A density model is obtained by gravity data inversion based on the earthquake data and gravity data. The correspondence between multiple velocity-density models is obtained based on the pre-set lithology-velocity-density correspondence table; Based on the correspondence between the density model and multiple velocity-density models, multiple velocity models of underground geological bodies are obtained.

2. The method for determining the initial velocity model for seismic data inversion according to claim 1, characterized in that, The earthquake data is travel time data, and the gravity data is residual gravity data.

3. The method for determining the initial velocity model for seismic data inversion according to claim 1, characterized in that, The algorithm for gravity data inversion is a genetic algorithm, a neural network method, or a simulated annealing method.

4. The method for determining the initial velocity model for seismic data inversion according to claim 1, characterized in that, The density model is a column vector consisting of the density values ​​of each grid cell in the mesh.

5. The method for determining the initial velocity model for seismic data inversion according to claim 1, characterized in that, The lithology-velocity-density correspondence table includes exponential and polynomial relationships between velocity and density for rocks of different lithologies.

6. The method for determining the initial velocity model for seismic data inversion as described in claim 5, characterized in that, The exponential relationship between velocity and density of rocks of different lithologies is the Gardner relation; the polynomial relationship between velocity and density of rocks of different lithologies is the Castagna relation.

7. The method for determining the initial velocity model for seismic data inversion as described in claim 5, characterized in that, The initial velocity model that minimizes the fitting difference between forward-modeled seismic data and measured seismic data specifically includes: The fitting difference between forward modeled seismic data and measured seismic data is calculated using the L2 norm formula; The velocity model with the smallest fitting difference is used as the initial velocity model for seismic data inversion.

8. A system for determining the initial velocity model in seismic data inversion, characterized in that, include: The data acquisition module is used to collect seismic and gravity data for the study area. The earthquake model determination module is used to obtain velocity models of multiple underground geological bodies through gravity data inversion and a preset lithology-velocity-density correspondence table. The initial velocity model determination module is used to perform forward modeling based on the velocity models of the multiple underground geological bodies to obtain multiple forward modeling seismic data, and to determine the velocity model with the smallest fitting difference between the forward modeling seismic data and the measured seismic data as the initial velocity model; The earthquake model determination module is specifically used to perform grid subdivision of underground geological bodies; to obtain a density model by gravity data inversion based on the earthquake data and gravity data; to obtain the correspondence between multiple velocity-density models based on a preset lithology-velocity-density correspondence table; and to obtain multiple velocity models of underground geological bodies based on the density model and the correspondence between multiple velocity-density models.

9. The system for determining the initial velocity model for seismic data inversion according to claim 8, characterized in that, The earthquake data is travel time data, and the gravity data is residual gravity data.

10. The system for determining the initial velocity model for seismic data inversion according to claim 8, characterized in that, The algorithm for gravity data inversion is a genetic algorithm, a neural network method, or a simulated annealing method.

11. The system for determining the initial velocity model for seismic data inversion according to claim 8, characterized in that, The density model is a column vector consisting of the density values ​​of each grid cell in the mesh.

12. The system for determining the initial velocity model for seismic data inversion according to claim 8, characterized in that, The lithology-velocity-density correspondence table includes exponential and polynomial relationships between velocity and density for rocks of different lithologies.

13. The system for determining the initial velocity model for seismic data inversion as described in claim 12, characterized in that, The exponential relationship between velocity and density of rocks of different lithologies is the Gardner relation; the polynomial relationship between velocity and density of rocks of different lithologies is the Castagna relation.

14. The system for determining the initial velocity model for seismic data inversion as described in claim 8, characterized in that, The initial velocity model determination module is specifically used to calculate the fitting difference between forward modeled seismic data and measured seismic data using the L2 norm formula; and to use the velocity model with the smallest fitting difference as the initial velocity model for seismic data inversion.

15. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1-7.

16. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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