Method and device for identifying seismic response rule of crack zone

Abstract

The invention discloses a method and a device for identifying a seismic response rule of a fractured zone, and relates to the technical field of oil and gas field exploration. Comprising the steps of obtaining seismic related data of a high-density seismic region; establishing fracture zone distribution models of different feature dimensions by using the seismic related data, and establishing an equivalent medium model by using the fracture zone distribution models of different feature dimensions; performing seismic wave field simulation based on the equivalent medium model to obtain a simulation result; and performing feature analysis on a simulation result and an actual seismic section to obtain seismic wave field response features. According to the method, the advantage of high resolution of high-density seismic data is fully utilized, and the underground inhomogeneous medium is described more flexibly and conveniently in combination with a Gaussian random medium modeling method. Besides, by defining the seismic wave field response characteristics of the random medium fracture zone in the work area, the recognition precision of the fracture-developed zone earthquake is remarkably improved, the fracture reservoir distribution of the target interval can be effectively predicted, and a reliable basis is provided for high-quality exploration and development of fractured oil and gas reservoirs.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas field exploration, and particularly relates to a method and device for identifying seismic response law of fracture zone. BACKGROUND

[0002] The reservoir space of carbonate rock is generally divided into three types: fracture type, fracture-cave type and pore-cave type. The reservoir composed of pores, fractures and caves generally has randomness in spatial distribution, and the occurrence and morphology of the reservoir change rapidly, making it more difficult to understand the reservoir, and it is more difficult to simulate such a reservoir. Unlike terrigenous clastic rock reservoir, carbonate rock reservoir has important practical value in oil and gas exploration and development. However, such reservoir is greatly affected by factors such as sedimentary environment, diagenesis and tectonic action, and the carbonate rock reservoir has many types of reservoir spaces, large secondary changes, strong reservoir heterogeneity, and stronger complexity and diversity in exploration.

[0003] In order to simulate the reservoir space of carbonate rock, previous researchers have conducted a lot of scientific research and established a geological and seismic reservoir model with certain equivalent approximation. However, in the carbonate rock reservoir, the petrophysical parameters (such as velocity, density, porosity, permeability, oil saturation, etc.) of the reservoir space composed of pores and fractures are discrete variables, and the existing method model is not good at understanding the seismic response characteristics of different types of fracture zones and the characteristics of the seismic wave field of small-scale fracture-type reservoirs in actual data, and the accuracy of seismic identification of fracture development zones is not high. SUMMARY

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a method and device for identifying seismic response law of fracture zone.

[0005] According to an aspect of an embodiment of the present application, a method for identifying seismic response law of fracture zone is provided, including obtaining seismic related data of a high-density seismic zone, wherein the seismic related data includes seismic data of the high-density seismic zone and geological data of the high-density seismic zone; establishing a fracture zone distribution model of different characteristic dimensions by using the seismic related data, and creating an equivalent medium model by using the fracture zone distribution model of different characteristic dimensions; performing seismic wave field simulation based on the equivalent medium model to obtain a simulation result; and performing characteristic analysis on the simulation result and actual seismic profile to obtain seismic wave field response characteristics.

[0006] Further, the use of the seismic correlation data to establish different characteristic dimension fracture zone distribution model, including from the seismic correlation data extraction high angle fracture corresponding first data set, mesh fracture corresponding second data set and horizontal fracture corresponding third data set;Using the first data set to build the high angle fracture corresponding fracture zone distribution model;Using the second data set to build the mesh fracture corresponding fracture zone distribution model;Using the third data set to build the horizontal fracture corresponding fracture zone distribution model.

[0007] Further, the use of different characteristic dimension fracture zone distribution model to create equivalent medium model, including based on different characteristic dimension fracture zone distribution model fracture zone equivalent to randomly distributed cracks, and randomly distributed cracks randomly crack into isotropic medium, get a plurality of equal probability model;The plurality of equal probability model is superimposed on the reservoir structure model, and the reservoir random model is obtained, and the equivalent medium model is constructed by using the reservoir random model.

[0008] Further, the equivalent medium model is used to simulate the seismic wave field, and the simulation result is obtained, including using two-dimensional non-uniform isotropic elastic wave equation and its based on staggered grid finite difference wave equation to forward simulate the equivalent medium model;During forward simulation, the same parameters such as trace interval, minimum and maximum offset, sampling interval and wavelet main frequency in seismic correlation data are used to record shot gather, and the simulation result is obtained.

[0009] Further, the isotropic elastic wave equation is,

[0010]

[0011] Wherein: σ xx = σ xx (x,z,t), σ zz = σ zz (x,z,t), τ xz = τ xz (x,z,t) is stress tensor; ρ=ρ(x,z) is density; U=U(x,z,t), W=W(x,z,t) is the velocity component of medium in x, z two directions; λ=λ(x,z), μ=μ(x,z) is Lame coefficient, respectively, the particle velocity component U and W, respectively, the discrete value of particle stress component σ xx , σ zz and τ xz ; Δt represents time step; k is the discrete index of time domain; i represents the discrete in x axis direction; j represents the discrete in z axis direction; Δx and Δz respectively represent the space step in x direction and z direction.

[0012] Further, the feature analysis of the simulation result and the actual seismic profile to obtain the seismic wave field response feature comprises: performing feature analysis on the simulation result and the actual seismic profile according to dynamic characteristics and kinematic characteristics to obtain the seismic wave field response feature, wherein the kinematic characteristics at least include: waveform structure, external morphology, internal structure, and the dynamic characteristics at least include: amplitude, frequency and derived seismic attributes.

[0013] Further, the feature analysis of the simulation result and the actual seismic profile to obtain the seismic wave field response feature comprises:

[0014] According to another aspect of the embodiments of the present application, a device for identifying the seismic response law of a fracture zone is further provided, and the device comprises: an acquisition module, configured to acquire seismic related data of a high-density seismic zone, wherein the seismic related data comprises: seismic data of the high-density seismic zone and geological data of the high-density seismic zone; an establishment module, configured to establish a fracture zone distribution model of different characteristic dimensions by using the seismic related data, and create an equivalent medium model by using the fracture zone distribution model of different characteristic dimensions; a processing module, configured to perform seismic wave field simulation based on the equivalent medium model to obtain a simulation result; and a comparison module, configured to perform feature analysis on the simulation result and an actual seismic profile to obtain a seismic wave field response feature.

[0015] According to another aspect of the embodiments of the present application, a storage medium is further provided, and the storage medium comprises a stored program, and the program performs the steps described above when running.

[0016] According to another aspect of the embodiments of the present application, an electronic device is further provided, and the electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus; the memory is configured to store a computer program; and the processor is configured to perform the steps in the above method by running the program stored in the memory.

[0017] The embodiments of the present application further provide a computer program product comprising instructions which, when executed on a computer, cause the computer to perform the steps in the above method.

[0018] Compared with the prior art, the technical scheme provided by the embodiment of the present application has the following advantages: the method provided by the embodiment of the present application fully utilizes the advantage of high resolution of high-density seismic data, and is more flexible and convenient in describing the underground non-uniform medium in combination with the method of Gaussian-type random medium modeling. In addition, by explicitly defining the seismic wave field response characteristics of the random medium fracture zone in the work area, the identification accuracy of the fracture development zone is significantly improved, the distribution of the fracture reservoir in the target layer can be effectively predicted, and reliable basis is provided for high-quality exploration and development of the fractured oil and gas reservoir. BRIEF DESCRIPTION OF DRAWINGS

[0019] The drawings incorporated in the specification and constituting a part of the specification illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the present application.

[0020] In order to more clearly illustrate the technical scheme in the embodiments of the present application or the prior art, the drawings required to be used in the embodiment or the prior art description will be briefly introduced as follows, and obviously, other drawings can also be obtained by those skilled in the art without creative labor.

[0021] Figure 1 The flowchart of the method for identifying the seismic response law of the fracture zone provided by the embodiment of the present application.

[0022] Figure 2 The equivalent medium model diagram of the fracture zone with different densities provided by the embodiment of the present application.

[0023] Figure 3 The seismic response characteristic diagram of the fracture zone with different types provided by the embodiment of the present application.

[0024] Figure 4 The block diagram of the device for identifying the seismic response law of the fracture zone provided by the embodiment of the present application.

[0025] Figure 5 The structural schematic diagram of the electronic device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are a part of the embodiments of the present application, rather than all the embodiments of the present application. The illustrative embodiments of the present application and the description thereof are used to explain the present application, and do not constitute an improper limitation on the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0027] It is to be noted that, in the present document, relational terms such as "first" and "second", and the like can be used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or 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 include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0028] The embodiment of the present application provides a method for identifying a seismic response law of a fracture zone. The method provided by the embodiment of the present application can be applied to any required electronic device, for example, a server, a terminal, and the like, which are not limited here, and for the convenience of description, are simply referred to as electronic devices hereinafter.

[0029] According to an aspect of the embodiment of the present application, a method for identifying a seismic response law of a fracture zone is provided. Figure 1 A flowchart of the method for identifying a seismic response law of a fracture zone provided by the embodiment of the present application is shown in Figure 1 The method comprises the following steps:

[0030] In step S11, seismic related data of a high-density seismic zone is acquired, including seismic data of the high-density seismic zone and geological data of the high-density seismic zone.

[0031] In the embodiment of the present application, the seismic related data of the high-density seismic zone comprises high-density seismic zone data and seismic data in a target research area. The high-density seismic zone data and the seismic data comprise all-directional seismic data and data such as imaging logging, drilling, testing, and core in a work area, which can be accurately completed in a subsequent modeling process.

[0032] In step S12, a fracture zone distribution model of different characteristic dimensions is established by using the seismic related data, and an equivalent medium model is created by using the fracture zone distribution model of different characteristic dimensions.

[0033] In the embodiment of the present application, the fracture zone distribution model of different characteristic dimensions is established by using the seismic related data, comprising:

[0034] extract a first data set corresponding to high-angle fractures, a second data set corresponding to network fractures and a third data set corresponding to horizontal fractures from the seismic related data, construct a fracture zone distribution model corresponding to high-angle fractures by using the first data set, construct a fracture zone distribution model corresponding to network fractures by using the second data set, and construct a fracture zone distribution model corresponding to horizontal fractures by using the third data set.

[0035] It should be noted that the single fracture zone distribution model of different types can be established according to the statistical characteristics of the parameters such as fracture length, width and angle of the research area from the seismic related data. That is, the first data set corresponding to high-angle fractures, the second data set corresponding to network fractures and the third data set corresponding to horizontal fractures can be extracted from the seismic related data, and then different types of single fracture zone distribution models can be constructed by using the first data set, the second data set and the third data set respectively.

[0036] For example, the main reservoir of the research area is a fracture type reservoir, the overall fracture is relatively developed, the porosity is small, and the filling is serious; through core observation and statistical analysis of logging data of typical wells in the research area, it can be known that the research area mainly develops high-angle fractures, network fractures and horizontal fractures, and the dip angles are mostly between 45° and 90°; among them, the high-angle fracture is the effective fracture type in the area, and the distribution range is the widest, and the subsequent embodiments of the application mainly design the fracture zone equivalent medium model mainly for high-angle fractures.

[0037] In the embodiments of the application, the process of creating an equivalent medium model by using a fracture zone distribution model with different characteristic dimensions is as follows: the fracture zone in the fracture type seismic geology model can be equivalent to randomly distributed fractures, and the length and diameter of each single fracture and the spatial arrangement and distribution of the fractures are random. Among them, the fractures in the fracture type seismic geology model can be simulated by the following process: by changing the r (roughness factor) in the mixed random medium autocorrelation function, r = 0 can obtain a Gaussian autocorrelation function:

[0038] x, y are the displacements in x and y directions, r is the roughness factor, a and b are the autocorrelation lengths in x and y directions. Using this elliptical autocorrelation function to describe the random medium, the autocorrelation lengths in x and z directions are used to reflect the scale of the non-uniformity of the medium in x and z directions, which can describe the isotropic non-uniformity, non-uniformity with elongation direction and even layered non-uniformity of the medium.

[0039] Secondly, the threshold intercept method is used to determine the center point position (x0, y0) of the fracture distribution, Wherein, n is the number of fracture zones. Then at the center point position, the Gaussian simulation method is selected to simulate the fractures according to the dip angle, length and width of the fracture zone.

[0040] The crack type seismic geological model can be equivalent to an isotropic medium by Gassmann equation, that is, embedded into an isotropic medium by multi-scale random cracks, a plurality of equal probability models are established by changing simulation parameters, and are superimposed in the reservoir structure model, so as to obtain an equivalent medium model of superimposed cracks, that is, a fine reservoir random model.

[0041] The equivalent medium model of superimposed cracks is based on a multi-scale random medium model, and has the following form:

[0042]

[0043] wherein may be a Gaussian autocorrelation function or an exponential autocorrelation function, x, a i respectively, are displacement and autocorrelation length of the autocorrelation function, ω i are weights of random disturbances of different scales. The equivalent medium model of superimposed crack zones is shown in FIG. 1. Figure 2

[0044] In step S13, the seismic wave field simulation is performed based on the equivalent medium model, and a simulation result is obtained.

[0045] In the embodiment of the present application, the seismic wave field simulation is performed based on the equivalent medium model, and a simulation result is obtained, including: using a two-dimensional non-uniform isotropic elastic wave equation and a staggered grid finite difference wave equation based on the equation to perform forward modeling on the equivalent medium model, in the forward modeling process, using the same parameters such as trace interval, minimum and maximum offset, sampling interval and wavelet main frequency in the seismic related data to record shot gathers, and obtaining a simulation result, the isotropic elastic wave equation is:

[0046]

[0047] wherein: σ xx = σ xx (x,z,t), σ zz = σ zz (x,z,t), τ xz = τ xz (x,z,t) is a stress tensor, ρ = ρ(x,z) is a density, U = U(x,z,t), W = W(x,z,t) is a velocity component of the medium in x and z directions, λ = λ(x,z), μ = μ(x,z) is a Lame coefficient, respectively, are particle velocity components U and W, respectively, are particle stress components σ xx , σ zz and τ xz ​wherein, Δt represents a time step, k is a discrete index in the time domain, i represents a discrete in the x-axis direction, j represents a discrete in the z-axis direction, Δx and Δz represent a spatial step in the x-axis direction and the z-axis direction respectively.

[0048] It should be noted that, in order to make the simulation process closer to the actual seismic acquisition process, wave propagation process and processing process, the same trace interval, minimum and maximum offset, sampling interval, wavelet main frequency and other parameters as the actual seismic data acquisition are used to record the forward simulation of shot gather. In addition, in order to reduce the influence of errors in processing on the migration results, the model velocity is directly used for pre-stack depth migration processing and converted to the time domain; then the data is processed and analyzed based on Focus and GeoDepth software.

[0049] In step S14, the simulation results are analyzed with the actual seismic profile to obtain the seismic wave field response characteristics, including analyzing the simulation results and the actual seismic profile according to the dynamic characteristics and the kinematic characteristics respectively to obtain the seismic wave field response characteristics.

[0050] In the embodiments of the present application, the simulation results are analyzed with the actual seismic profile to obtain the seismic wave field response characteristics, including: analyzing the simulation results and the actual seismic profile according to the dynamic characteristics and the kinematic characteristics respectively to obtain the seismic wave field response characteristics, wherein the kinematic characteristics at least include: waveform structure, external morphology, internal structure, and the dynamic characteristics at least include: amplitude, frequency and derived seismic attributes.

[0051] Specifically, the simulation results and the actual seismic profile are analyzed according to the dynamic characteristics and the kinematic characteristics respectively to obtain the seismic wave field response characteristics, for example, referring to Figure 3 The strength of the seismic response of the fracture zone is positively correlated with the length, width and density of the fracture zone, and is negatively correlated with the spatial development angle of the fracture zone and the velocity difference with the surrounding rock: when the length, width and density of the fracture zone increase, the chaotic reflection energy of the seismic profile is enhanced and the phase axis distortion is intensified; when the spatial development angle of the fracture zone increases, the abnormal reflection energy on the seismic profile is obviously weakened, the larger the angle, the lower the energy; when the velocity difference between the filling velocity of the fracture zone and the surrounding rock velocity increases, the chaotic reflection energy of the earthquake is enhanced, and the overall reflection characteristics are short-axis strong amplitude.

[0052] The method provided in the embodiments of the present application compares and analyzes the model migration results and the actual seismic profile, combines the seismic attribute analysis, and summarizes the seismic wave field response characteristics of the fracture type reservoir from the kinematics (waveform structure, external morphology, internal structure) and the dynamics (amplitude, frequency and derived seismic attributes), so as to ensure the identification accuracy of the seismic response law of the fracture zone.

[0053] The method provided by the embodiments of the present application fully utilizes the advantage of high resolution of high-density seismic data, and is more flexible and convenient in describing the underground non-uniform medium in combination with the method of Gaussian-type random medium modeling. In addition, by explicitly defining the seismic wave field response characteristics of the random medium fracture zone in the work area, the identification accuracy of the fracture development zone is significantly improved, and the distribution of the fracture reservoir in the target layer can be effectively predicted, thereby providing a reliable basis for high-quality exploration and development of the fractured oil and gas reservoir.

[0054] Figure 4 A block diagram of a fracture zone seismic response rule identification device provided by the embodiments of the present application is shown in FIG. 1. The device can be realized as part or all of an electronic device by software, hardware or a combination of both. As shown in FIG. 1, the fracture zone seismic response rule identification device comprises: Figure 4

[0055] The acquisition module 41 is configured to acquire seismic related data of the high-density seismic area, wherein the seismic related data comprises seismic data of the high-density seismic area and geological data of the high-density seismic area.

[0056] The establishment module 42 is configured to establish a fracture zone distribution model of different characteristic dimensions by using the seismic related data, and create an equivalent medium model by using the fracture zone distribution model of different characteristic dimensions.

[0057] The processing module 43 is configured to perform seismic wave field simulation based on the equivalent medium model to obtain a simulation result.

[0058] The comparison module 44 is configured to perform characteristic analysis on the simulation result and an actual seismic profile to obtain a seismic wave field response characteristic.

[0059] In the embodiments of the present application, the establishment module 42 is configured to extract a first data set corresponding to high-angle fractures, a second data set corresponding to network fractures and a third data set corresponding to horizontal fractures from the seismic related data; construct a fracture zone distribution model corresponding to the high-angle fractures by using the first data set; construct a fracture zone distribution model corresponding to the network fractures by using the second data set; and construct a fracture zone distribution model corresponding to the horizontal fractures by using the third data set.

[0060] In the embodiments of the present application, the establishment module 42 is configured to embed random fractures in an isotropic medium based on the fractures of the fracture zone distribution model of different characteristic dimensions being randomly distributed, to obtain a plurality of equiprobable models; superimpose the plurality of equiprobable models on a reservoir structure model to obtain a reservoir random model, and construct an equivalent medium model by using the reservoir random model.

[0061] ​In this embodiment of the application, the processing module 43 is used to perform forward modeling of the equivalent medium model using the two-dimensional non-uniform isotropic elastic wave equation and its staggered grid finite difference wave equation; during the forward modeling process, the same parameters such as trace spacing, minimum and maximum offset, sampling interval, and wavelet dominant frequency are collected from the seismic related data to record the shot collection and obtain the simulation results.

[0062] In this embodiment of the application, the isotropic elastic wave equation is:

[0063]

[0064] Where: σ xx =σ xx (x,z,t), σ zz =σ zz (x,z,t),τ xz =τ xz (x,z,t) is the stress tensor; ρ = ρ(x,z) is the density; U = U(x,z,t) and W = W(x,z,t) are the velocity components of the medium in the x and z directions; λ = λ(x,z) and μ = μ(x,z) are the Lamé coefficients. These are the particle velocity components U and W, respectively. These are the particle stress components σ xx σ zz and τ xz The discrete values; Δt represents the time step; k is the time domain discretization exponent; i represents discretization in the x-axis direction; j represents discretization in the z-axis direction; Δx and Δ z These represent the spatial step sizes in the x and z directions, respectively.

[0065] In this embodiment of the application, the comparison module 44 is used to perform feature analysis on the simulation results and the actual seismic profile according to the dynamic features and kinematic features respectively, so as to obtain the seismic wavefield response features. The kinematic features include at least: waveform structure, external morphology and internal structure, and the dynamic features include at least: amplitude, frequency and derived seismic attributes.

[0066] In this embodiment, the simulation results and actual seismic profiles are analyzed according to dynamic and kinematic characteristics to obtain seismic wavefield response characteristics, including...

[0067] This application also provides an electronic device, such as... Figure 5 As shown, the electronic device may include: a processor 1501, a communication interface 1502, a memory 1503, and a communication bus 1504, wherein the processor 1501, the communication interface 1502, and the memory 1503 communicate with each other through the communication bus 1504.

[0068] a memory 1503, configured to store a computer program,

[0069] a processor 1501, configured to execute the computer program stored in the memory 1503, and thereby implement the steps of the above embodiments.

[0070] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0071] The communication interface is configured to communicate between the above terminal and other devices.

[0072] The memory can include a Random Access Memory (RAM) and can also include a non-volatile memory, such as at least one disk memory. Optionally, the memory can also be at least one storage device located away from the aforementioned processor.

[0073] The processor mentioned above can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc., and can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0074] In another embodiment provided in the present application, a computer readable storage medium is also provided, and the computer readable storage medium stores instructions, and when the instructions run on a computer, the computer executes the method of any one of the above embodiments.

[0075] In another embodiment provided in the present application, a computer program product containing instructions is also provided, and when the instructions run on a computer, the computer executes the method of any one of the above embodiments.

[0076] In the embodiments described above, all or some of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or some of the embodiments can be implemented in the form of a computer program product storing computer program instructions. The computer program instructions are executed in a computer to implement the procedures or functions according to the embodiments of the present application. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatuses. The computer program instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center through wired (for example, coaxial cable, optical fiber, digital subscriber line) or wireless (for example, infrared, wireless, microwave, etc.) manner. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, etc. containing one or more available media. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a Solid State Disk), etc.

[0077] The preferred embodiments of the present application have been described above with the aid of a number of drawings. These embodiments are illustrative only and not intended to limit the scope of the present application. Other embodiments of the application, readily ascertainable by one skilled in the art, and modifications made thereto and equivalents thereof, are to be included within the scope of the present application.

[0078] The specific embodiments described above have been shown by way of example, and any modifications of the above-described modes of practice that are within the fair scope of the teaching of this application are to be considered within the scope of the application. What is desired to be secured by Letters Patent is the subject matter as follows:

Claims

1. A method for identifying a rule of seismic response of a fracture zone, characterized in that, The method comprises the following steps: obtaining seismic related data of a high-density seismic area, wherein the seismic related data comprises seismic data of the high-density seismic area and geological data of the high-density seismic area; establishing fracture zone distribution models of different characteristic dimensions by using the seismic related data, and creating an equivalent medium model by using the fracture zone distribution models of different characteristic dimensions; performing seismic wave field simulation based on the equivalent medium model to obtain a simulation result; performing characteristic analysis on the simulation result and an actual seismic profile to obtain seismic wave field response characteristics.

2. The method of claim 1, wherein, The step of establishing fracture zone distribution models of different characteristic dimensions by using the seismic related data comprises the following steps: extracting a first data set corresponding to high-angle fractures, a second data set corresponding to network fractures and a third data set corresponding to horizontal fractures from the seismic related data; constructing a fracture zone distribution model corresponding to the high-angle fractures by using the first data set; constructing a fracture zone distribution model corresponding to the network fractures by using the second data set; constructing a fracture zone distribution model corresponding to the horizontal fractures by using the third data set.

3. The method of claim 2, wherein, The step of creating an equivalent medium model by using the fracture zone distribution models of different characteristic dimensions comprises the following steps: based on the fracture zone distribution models of different characteristic dimensions, equivalent random distribution fractures are obtained, and the random distribution fractures are embedded into an isotropic medium to obtain a plurality of equiprobable models; the plurality of equiprobable models are superimposed on a reservoir structure model to obtain a reservoir random model, and the reservoir random model is used to construct the equivalent medium model.

4. The method of claim 1, wherein, The step of performing seismic wave field simulation based on the equivalent medium model to obtain a simulation result comprises the following steps: forward modeling is performed on the equivalent medium model by using a two-dimensional non-uniform isotropic elastic wave equation and a staggered grid finite difference wave equation; in the process of forward modeling, shot gathers are recorded by using the same parameters such as trace interval, minimum and maximum offset, sampling interval and wavelet main frequency in the seismic related data to obtain the simulation result.

5. The method of claim 4, wherein, The isotropic elastic wave equation is as follows: where: σ xx = σ xx (x, z, t), σ zz = σ zz (x, z, t), τ xz = τ xz (x, z, t) are the stress tensors; p = p(x, z) is the density; U = U(x, z, t), W = W(x, z, t) are the velocity components of the medium in the x, z directions; l = l(x, z), m = m(x, z) are the Lame coefficients, are respectively the discrete values of the particle velocity components U and W, are respectively the discrete values of the particle stress components σ xx , σ zz and τ xz ; At represents the time step; k is the discrete index in the time domain; i represents the discretization in the x-axis direction; j represents the discretization in the z-axis direction; Ax and Az represent respectively the spatial steps in the x and z directions.

6. The method of claim 1, wherein, The step of performing characteristic analysis on the simulation result and an actual seismic profile to obtain seismic wave field response characteristics comprises the following steps: the simulation result and the actual seismic profile are analyzed according to dynamic characteristics and kinematic characteristics to obtain seismic wave field response characteristics, wherein the kinematic characteristics at least include waveform structure, external morphology and internal structure, and the dynamic characteristics at least include amplitude, frequency and derived seismic attributes.

7. A device for identifying the seismic response pattern of fracture zones, characterized in that, The method comprises the following steps: a obtaining module is configured to obtain seismic related data of a high-density seismic area, wherein the seismic related data comprises seismic data of the high-density seismic area and geological data of the high-density seismic area; an establishing module is configured to establish fracture zone distribution models of different characteristic dimensions by using the seismic related data, and create an equivalent medium model by using the fracture zone distribution models of different characteristic dimensions; a processing module is configured to perform seismic wave field simulation based on the equivalent medium model to obtain a simulation result; a comparison module is configured to perform characteristic analysis on the simulation result and an actual seismic profile to obtain seismic wave field response characteristics.

8. The device for identifying a rule of seismic response of a fracture zone according to claim 7, characterized in that, The establishing module is configured to extract a first data set corresponding to high-angle fractures, a second data set corresponding to network fractures, and a third data set corresponding to horizontal fractures from the seismic correlation data; construct a fracture zone distribution model corresponding to the high-angle fractures by using the first data set; construct a fracture zone distribution model corresponding to the network fractures by using the second data set; and construct a fracture zone distribution model corresponding to the horizontal fractures by using the third data set.

9. A storage medium, characterized by The storage medium comprises a stored program, wherein the program performs the method of any one of claims 1 to 6 when executed.

10. An electronic device, comprising: The device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus; wherein: The memory is configured to store a computer program. The processor is configured to perform the method of any one of claims 1 to 6 by running the program stored in the memory.

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