Cross-scale seismic wave attenuation and dispersion prediction method and related equipment

Abstract

The present disclosure provides a cross-scale seismic wave attenuation and dispersion prediction method and related equipment, which relate to the field of geophysical wave-induced fluid flow. The method comprises: determining a corrected solid bulk modulus based on a corrected solid dry bulk modulus and an average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling a spherical jet flow term to a skeleton dry modulus; determining a corrected rock dry bulk modulus based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure; determining a fast longitudinal wave velocity and an attenuation coefficient based on the corrected rock dry bulk modulus and the Biot elastic parameter, wherein the fast longitudinal wave velocity and the attenuation coefficient are used to represent seismic wave attenuation and dispersion. According to the embodiment of the present disclosure, macro-scale fluid flow and micro-spherical jet flow are taken into consideration to compensate for the limitations of conventional cross-scale attenuation and dispersion prediction methods, and effectively improve the prediction accuracy of seismic wave attenuation and dispersion in the medium.

Description

Technical Field

[0001] The present disclosure relates to the field of geophysical wave-induced fluid flow, and in particular to a cross-scale seismic wave attenuation and dispersion prediction method and related equipment. Background Art

[0002] Since the concept of wave-induced fluid flow was proposed, increasing attention has been paid to its research, and a large number of theoretical models for different media have been developed. Wave-induced fluid flow theory is categorized into macroscale, microscale, and mesoscale theories based on scale. At the macroscale, the pressure gradient generated between wave crests and troughs causes relative motion of the fluid relative to the solid, leading to the attenuation and dispersion of seismic waves. Mesoscale theory describes local fluid flow caused by the heterogeneous distribution of the medium. Microscale theory predicts jet flows generated by local pressure gradients between heterogeneous pores.

[0003] The macroscopic and microscopic cross-scale models in related technologies mainly consider the influence of two-dimensional jet flow, which is inconsistent with the actual underground situation and cannot accurately predict the attenuation and dispersion of seismic waves in porous media.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0005] The present disclosure provides a cross-scale seismic wave attenuation and dispersion prediction method and related equipment, which at least to a certain extent overcomes the problem that the macro and micro cross-scale models in the related technology mainly consider the influence of two-dimensional jet flow, which is inconsistent with the actual underground situation and cannot accurately predict the attenuation and dispersion of seismic waves in porous media.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0007] According to one aspect of the present disclosure, a cross-scale seismic wave attenuation and dispersion prediction method is provided, comprising:

[0008] The corrected solid bulk modulus is determined based on the corrected solid dry bulk modulus and the average pore pressure. The corrected solid dry bulk modulus is calculated by coupling the spherical jet term to the skeleton dry modulus.

[0009] Based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure, the corrected rock dry bulk modulus is determined;

[0010] The fast P-wave velocity and attenuation coefficient are determined based on the corrected rock bulk modulus and Biot elastic parameters. The fast P-wave velocity and attenuation coefficient are used to represent the attenuation and dispersion of seismic waves.

[0011] In one embodiment of the present disclosure, the method further includes:

[0012] Obtain rock physical parameters and fluid physical parameters;

[0013] Based on the rock physical parameters and fluid physical parameters, the pore pressure is calculated;

[0014] Based on the pore pressure, determine the average pore pressure.

[0015] In one embodiment of the present disclosure, the rock physical parameters include rock modulus and / or rock density.

[0016] In one embodiment of the present disclosure, the fluid physical property parameters include fluid viscosity and / or fluid density.

[0017] According to another aspect of the present disclosure, a cross-scale seismic wave attenuation and dispersion prediction device is provided, comprising:

[0018] A first calculation module is configured to determine a corrected solid bulk modulus based on the corrected solid dry bulk modulus and the average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling the spherical jet flow term to the skeleton dry modulus;

[0019] a second calculation module for determining a corrected rock dry bulk modulus based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure;

[0020] The prediction module is used to determine the fast P-wave velocity and attenuation coefficient based on the corrected rock bulk modulus and Biot elastic parameters. The fast P-wave velocity and attenuation coefficient are used to represent the attenuation and dispersion of seismic waves.

[0021] According to another aspect of the present disclosure, an electronic device is provided, including: a memory for storing instructions; and a processor for calling the instructions stored in the memory to implement the above-mentioned cross-scale seismic wave attenuation and dispersion prediction method.

[0022] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which computer instructions are stored. When the computer instructions are executed by a processor, the above-mentioned cross-scale seismic wave attenuation and dispersion prediction method is implemented.

[0023] According to another aspect of the present disclosure, a computer program product is provided. The computer program product stores instructions, which, when executed by a computer, enable the computer to implement the above-mentioned cross-scale seismic wave attenuation and dispersion prediction method.

[0024] According to yet another aspect of the present disclosure, there is provided a chip comprising at least one processor and an interface;

[0025] An interface for providing program instructions or data to at least one processor;

[0026] At least one processor is used to execute program instructions to implement the above-mentioned cross-scale seismic wave attenuation and dispersion prediction method.

[0027] The cross-scale seismic wave attenuation and dispersion prediction method and related equipment provided by the embodiments of the present disclosure couple fractures into solids, that is, couple the spherical jet term into the skeleton dry modulus. By changing the rock modulus, both macro-scale fluid flow and micro-scale spherical jet flow are considered simultaneously. Then, based on the propagation theory of elastic waves in fluid-saturated porous media, the fast longitudinal wave velocity and attenuation factor of the seismic wave are obtained. This can better predict the attenuation and dispersion of seismic waves, compensate for the limitations of conventional cross-scale attenuation and dispersion prediction methods, and effectively improve the prediction accuracy of seismic wave attenuation and dispersion in the medium.

[0028] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0030] Obviously, the drawings described below are only some embodiments of the present disclosure. A person skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0031] Figure 1 A conventional columnar jet flow model in the related art is shown;

[0032] Figure 2 A flow chart of a method for predicting cross-scale seismic wave attenuation and dispersion in an embodiment of the present disclosure is shown;

[0033] Figure 3 A flow chart of another cross-scale seismic wave attenuation and dispersion prediction method according to an embodiment of the present disclosure is shown;

[0034] Figure 4 shows a modified solid skeleton according to an embodiment of the present disclosure;

[0035] Figure 5 A three-dimensional spherical jet model according to an embodiment of the present disclosure is shown;

[0036] FIG6 shows a comparison of the fast longitudinal wave attenuation (a) and dispersion curve (b) predicted by the model (solid line) in the embodiment of the present disclosure and the conventional model (dashed line);

[0037] Figure 7 The figure shows the comparison of the velocity variation with pressure using the laboratory measured data (open circles), the model proposed in the present disclosure (solid line) and the conventional model (dashed line);

[0038] Figure 8 A schematic diagram of a cross-scale seismic wave attenuation and dispersion prediction device according to an embodiment of the present disclosure is shown;

[0039] Figure 9 A structural block diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0040] Example embodiments will be described more fully hereinafter with reference to the accompanying drawings.

[0041] It should be noted that example embodiments may be implemented in many forms and should not be construed as limited to the examples set forth herein.

[0042] When seismic waves propagate through fluid-saturated, porous media in the subsurface, pressure gradients develop between different regions, causing the fluid to flow relative to the solid. This fluid flow is known as wave-induced fluid flow. Wave-induced fluid flow causes attenuation and dispersion of the seismic waves propagating through the medium. Attenuation refers to the exponential decay of the wave's amplitude with distance, while dispersion refers to the change in its velocity with frequency. The study of fluid-related dissipation in oil and gas reservoir rocks, combined with attenuation and dispersion recorded from seismic data, can be used to estimate subsurface rock properties.

[0043] Since the concept of wave-induced fluid flow was proposed, increasing attention has been paid to its research, and a large number of theoretical models for different media have been developed. Wave-induced fluid flow theory is categorized into macroscale, microscale, and mesoscale theories based on scale. At the macroscale, the pressure gradient generated between wave crests and troughs causes relative motion of the fluid relative to the solid, leading to the attenuation and dispersion of seismic waves. Mesoscale theory describes local fluid flow caused by the heterogeneous distribution of the medium. Microscale theory predicts jet flows generated by local pressure gradients between heterogeneous pores.

[0044] Many experts and scholars have done extensive research on cross-scale models that consider two-scale fluctuation-induced fluid flow. Among them, most of the attenuation and dispersion observed in the laboratory can be explained by cross-scale models that consider both macroscale and microscale. Currently, cross-scale models that consider both macroscale and microscale consider two-dimensional jet flows, such as Figure 1As shown, it is assumed that the jet flows only along the radial direction of the cylinder, which is inconsistent with the actual flow of fluid in complex underground media.

[0045] The macroscopic and microscopic cross-scale models in related technologies mainly consider the influence of two-dimensional jet flow, which is inconsistent with the actual underground situation and cannot accurately predict the attenuation and dispersion of seismic waves in porous media.

[0046] To address the above-mentioned issues, the disclosed embodiments provide a cross-scale seismic wave attenuation and dispersion prediction method and related equipment, coupling fractures into solids, that is, coupling the spherical jet term into the skeleton dry modulus. By varying the rock modulus, both macroscopic fluid flow and microscopic spherical jet flow are considered simultaneously. Then, based on the propagation theory of elastic waves in fluid-saturated porous media, the fast longitudinal wave velocity and attenuation factor of the seismic wave are calculated, enabling better prediction of seismic wave attenuation and dispersion. This method can effectively describe the seismic wave attenuation and dispersion caused by underground fluid flow, and better describe the complex porosity of the underground medium.

[0047] It should also be noted that the cross-scale seismic wave attenuation and dispersion prediction method of the embodiment of the present disclosure can be applied to electronic devices. The executor of the cross-scale seismic wave attenuation and dispersion prediction method can be at least one of the user terminals such as mobile phones, tablet computers, wearable devices, etc. that can be configured to execute the cross-scale seismic wave attenuation and dispersion prediction method provided by the embodiment of the present disclosure, or the executor of the method can also be the client itself that can execute the method.

[0048] This exemplary implementation is described in detail below with reference to the accompanying drawings and examples.

[0049] Figure 2 A flow chart of a cross-scale seismic wave attenuation and dispersion prediction method according to an embodiment of the present disclosure is shown. Figure 2 As shown, the cross-scale seismic wave attenuation and dispersion prediction method provided in the embodiment of the present disclosure includes steps S210-S230.

[0050] In S210, a corrected solid bulk modulus is determined based on the corrected solid dry bulk modulus and the average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling the spherical jet flow term to the skeleton dry modulus.

[0051] In some embodiments, the average pore pressure may be calculated as follows:

[0052] Obtain rock physical parameters and fluid physical parameters;

[0053] Based on the rock physical parameters and fluid physical parameters, the pore pressure is calculated;

[0054] Based on the pore pressure, determine the average pore pressure.

[0055] As an example, rock physical parameters may include rock modulus and / or rock density.

[0056] As an example, the fluid physical property parameters include fluid viscosity and / or fluid density.

[0057] In S220 , a corrected rock dry bulk modulus is determined based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure.

[0058] In S230, the fast P-wave velocity and attenuation coefficient are determined based on the corrected rock bulk modulus and Biot elastic parameters. The fast P-wave velocity and attenuation coefficient are used to represent seismic wave attenuation and dispersion.

[0059] The cross-scale seismic wave attenuation and dispersion prediction method provided by the embodiments of the present disclosure couples fractures into solids, that is, couples the spherical jet term into the skeleton dry modulus. By changing the rock modulus, both macro-scale fluid flow and micro-scale spherical jet flow are considered simultaneously. Then, based on the propagation theory of elastic waves in fluid-saturated porous media, the fast longitudinal wave velocity and attenuation factor of the seismic wave are obtained. This method can better predict the attenuation and dispersion of seismic waves, make up for the limitations of conventional cross-scale attenuation and dispersion prediction methods, and effectively improve the prediction accuracy of seismic wave attenuation and dispersion in the medium.

[0060] Figure 3 A flow chart of a cross-scale seismic wave attenuation and dispersion prediction method according to an embodiment of the present disclosure is shown. Figure 3 As shown in Figure 2, the pore pressure is calculated using rock and fluid physical parameters.

[0061] Based on the pore pressure, the average pore pressure is determined, and then combined with the corrected solid dry bulk modulus to determine the corrected solid bulk modulus.

[0062] The corrected rock dry bulk modulus is determined based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure. The fast P-wave velocity and attenuation coefficient are determined using the corrected rock dry bulk modulus and Biot elastic parameters.

[0063] The above calculation process is illustrated below through a specific example.

[0064] Dvorkin et al (1995) proposed a modified rock skeleton containing only hard pores, such as Figure 4 As shown. The corrected solid phase includes the real solid phase and cracks. Corrected bulk modulus K md The expression is:

[0065]

[0066] where Ks is the mineral bulk modulus, K ms is the corrected solid bulk modulus, K hp is the bulk modulus of the dry skeleton at critical high pressure.

[0067] In the modified rock, stress σ, skeleton deformation e and average pore pressure p av The relationship between them is:

[0068] dσ=K msd de-α c dp av (2)

[0069] Taking dσ as an example, d represents the differential symbol. K msd represents the corrected solid dry bulk modulus, α c =1-K ms / K s .

[0070] Corrected solid bulk modulus K ms The expression is as follows:

[0071]

[0072] According to equations (2) and (3), K ms It can be written as

[0073]

[0074] where K hp ,K msd and K s The numerical value of can be obtained through experimental measurement. It is only necessary to obtain the average pressure p av The relationship between the rock dry skeleton modulus K and the skeleton deformation e can be obtained. md .

[0075] We assume an ideal sphere with a radius of R0, and the jet flows along the radial direction of the sphere. The model is as follows Figure 5 The relationship between skeleton deformation, fracture porosity and pore pressure is shown in

[0076]

[0077] Among them For example, To find the sign of partial differential. is the fracture porosity, p is the pressure, and t is the time.

[0078] The compressibility of a fluid can be described as:

[0079]

[0080] Where c0 is the ultrasonic velocity in the fluid, ρ fl is the fluid density, and p is the fluid pressure in the soft pores.

[0081] According to the fluid flowing along the radial direction of the sphere, we can get the fluid mass conservation equation:

[0082]

[0083] where r is the radial distance of the sphere and w is the fluid displacement.

[0084] Substituting equations (5) and (6) into equation (7) yields

[0085]

[0086] The relationship between fluid velocity and pore pressure gradient can be obtained by Darcy's law:

[0087]

[0088] where κ is the permeability and η is the fluid viscosity.

[0089] Assuming these parameters are time harmonics:

[0090] exp(-iωt)(10)

[0091] Where exp represents the exponential function with the natural exponential as the base, ω is the circular frequency, and i is the imaginary unit.

[0092] Substituting equation (10) into equations (6) and (7) respectively, we can obtain

[0093]

[0094] in

[0095]

[0096] Based on equation (12), the fluid displacement in equation (11) can be replaced by the pressure p-related expression:

[0097]

[0098] At the boundary of the spherical jet fracture, the pore pressure is equal to 0, that is, The solution of equation (13) is

[0099]

[0100] where j0 is the zero-order spherical Bessel function,

[0101] The spherical Bessel function is converted into a cylindrical Bessel function, and the average pressure P(r) is obtained by integrating the pressure P(r). av :

[0102]

[0103] Among them J 1 / 2 is a 1 / 2 order cylindrical Bessel function, J 3 / 2 is a 3 / 2 order cylindrical Bessel function.

[0104] Substituting equation (15) into equation (4), we can obtain

[0105]

[0106] Finally, based on Biot (1956), the longitudinal wave velocity V can be obtained p The expression of attenuation coefficient α is:

[0107]

[0108]

[0109] Among them, Im represents the imaginary part, Re represents the real part,

[0110] B=ω 2 (2ρ a Q-ρ1R-ρ2P)-ibω(2Q+P+R),

[0111]

[0112] ρ1=(1-φ)ρ s +ρ a ,ρ2=φρ f +ρ a , ρ a is the additional coupling density, b=ηφ 2 / κ,

[0113]

[0114] Q=φ(α-φ) / β, R=φ 2 / β,μ md is the modified shear modulus, and φ is the porosity.

[0115] As shown in FIG6 , the spherical jet model proposed in the embodiment of the present disclosure is compared with the traditional two-dimensional jet model. It can be found that the jet attenuation characteristic frequency of the present model is higher than that of the two-dimensional jet model. This is because the spherical jet has a larger spray range and the fluid is easier to relax.

[0116] like Figure 7 A comparison between the laboratory measured data, the prediction results of the model proposed in the embodiment of the present disclosure, and the prediction results of the conventional model is shown. It can be found that the embodiment of the present disclosure can better predict the change of fast longitudinal wave velocity with pressure than the conventional model, which proves the correctness and rationality of the embodiment of the present disclosure.

[0117] Furthermore, although the steps of the methods of the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in this particular order, or that all illustrated steps must be performed to achieve desired results.

[0118] In some embodiments, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0119] Based on the same inventive concept, the presently disclosed embodiments also provide a device for predicting cross-scale seismic wave attenuation and dispersion, as described in the following embodiments. Because the principles underlying the problems solved by this device embodiment are similar to those of the aforementioned method embodiment, the implementation of this device embodiment can be referenced to the implementation of the aforementioned method embodiment, and any repetitions will not be repeated.

[0120] Figure 8 A schematic diagram of a cross-scale seismic wave attenuation and dispersion prediction device according to an embodiment of the present disclosure is shown. Figure 8 As shown, the cross-scale seismic wave attenuation and dispersion prediction device 800 includes:

[0121] A first calculation module 802 is configured to determine a corrected solid bulk modulus based on the corrected solid dry bulk modulus and the average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling the spherical jet term to the skeleton dry modulus;

[0122] A second calculation module 804 is configured to determine a corrected rock dry bulk modulus based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure;

[0123] The prediction module 806 is used to determine the fast P-wave velocity and attenuation coefficient based on the corrected rock bulk modulus and Biot elastic parameters. The fast P-wave velocity and attenuation coefficient are used to represent the attenuation and dispersion of seismic waves.

[0124] In some embodiments, the apparatus may further include:

[0125] Data acquisition module, used to obtain rock physical parameters and fluid physical parameters;

[0126] Pressure calculation module, used to calculate pore pressure based on rock physical parameters and fluid physical parameters;

[0127] The data processing module is used to determine the average pore pressure based on the pore pressure.

[0128] In some embodiments, rock physical parameters may include rock modulus and / or rock density.

[0129] In some embodiments, the fluid physical property parameters may include fluid viscosity and / or fluid density.

[0130] The concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0131] Regarding the cross-scale seismic wave attenuation and dispersion prediction device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the cross-scale seismic wave attenuation and dispersion prediction method, and will not be elaborated here.

[0132] In summary, in the cross-scale seismic wave attenuation and dispersion prediction device provided in the embodiment of the present application, the cracks are coupled to the solid, that is, the spherical jet flow term is coupled to the skeleton dry modulus. Through the change of the rock modulus, the macroscale fluid flow and the microscopic spherical jet flow are considered at the same time. Then, based on the propagation theory of elastic waves in fluid-saturated porous media, the fast longitudinal wave velocity and attenuation factor of the seismic wave are obtained, which can better predict the attenuation and dispersion of seismic waves, make up for the limitations of conventional cross-scale attenuation and dispersion prediction methods, and effectively improve the prediction accuracy of seismic wave attenuation and dispersion in the medium.

[0133] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, such division is not mandatory.

[0134] In fact, according to the embodiment of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0135] Some of the blocks shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0136] Refer to the following Figure 9 To describe the electronic device provided by the embodiment of the present disclosure. Figure 9The electronic device 900 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0137] Figure 9 FIG. 1 shows a schematic diagram of the architecture of an electronic device 900 provided by an embodiment of the present invention. Figure 9 As shown, the electronic device 900 includes but is not limited to: at least one processor 910 and at least one memory 920.

[0138] The memory 920 is used to store instructions.

[0139] In some embodiments, the memory 920 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 9201 and / or a cache memory unit 9202 , and may further include a read-only memory unit (ROM) 9203 .

[0140] In some embodiments, the memory 920 may also include a program / utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0141] In some embodiments, the memory 920 may store an operating system, which may be a real-time operating system (RTX), LINUX, UNIX, WINDOWS, or OS X.

[0142] In some embodiments, data may also be stored in the memory 920 .

[0143] As an example, the processor 910 may read data stored in the memory 920 . The data may be stored at the same storage address as the instruction, or the data may be stored at a different storage address than the instruction.

[0144] The processor 910 is configured to call instructions stored in the memory 920 to implement the steps described in the "Exemplary Method" section above according to various exemplary embodiments of the present disclosure. For example, the processor 910 may perform the following steps of the aforementioned method embodiment:

[0145] The corrected solid bulk modulus is determined based on the corrected solid dry bulk modulus and the average pore pressure. The corrected solid dry bulk modulus is calculated by coupling the spherical jet term to the skeleton dry modulus.

[0146] Based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure, the corrected rock dry bulk modulus is determined;

[0147] The fast P-wave velocity and attenuation coefficient are determined based on the corrected rock bulk modulus and Biot elastic parameters. The fast P-wave velocity and attenuation coefficient are used to represent the attenuation and dispersion of seismic waves.

[0148] It should be noted that the processor 910 may be a general-purpose processor or a dedicated processor. The processor 910 may include one or more processing cores, and the processor 910 executes various functional applications and data processing by running instructions.

[0149] In some embodiments, the processor 910 may include a central processing unit (CPU) and / or a baseband processor.

[0150] In some embodiments, the processor 910 may determine an instruction according to the priority identifier and / or function category information carried in each control instruction.

[0151] In the present disclosure, the processor 910 and the memory 920 may be provided separately or integrated together.

[0152] As an example, the processor 910 and the memory 920 may be integrated on a single board or a system on chip (SOC).

[0153] like Figure 9 As shown, the electronic device 900 is implemented as a general-purpose computing device. The electronic device 900 may further include a bus 930 .

[0154] Bus 930 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0155] The electronic device 900 may also communicate with one or more external devices 940 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 900, and / or any device that enables the electronic device 900 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 950.

[0156] Furthermore, the electronic device 900 can also communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through the network adapter 960 .

[0157] like Figure 9 As shown, the network adapter 960 communicates with other modules of the electronic device 900 via the bus 930 .

[0158] It should be understood that although not shown in the figures, other hardware and / or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0159] It is understood that the structure shown in the embodiment of the present disclosure does not constitute a specific limitation on the electronic device 900. In other embodiments of the present disclosure, the electronic device 900 may include Figure 9 More or fewer components may be shown, or some components may be combined or separated, or the components may be arranged differently. Figure 9 The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0160] The present disclosure also provides a computer-readable storage medium having computer instructions stored thereon. When the computer instructions are executed by a processor, the cross-scale seismic wave attenuation and dispersion prediction method described in the above method embodiment is implemented.

[0161] The computer-readable storage medium in the embodiments of the present disclosure is a computer instruction that can be sent, propagated or transmitted for use by or in conjunction with an instruction execution system, apparatus or device.

[0162] As an example, computer readable storage media are non-volatile storage media.

[0163] In some embodiments, more specific examples of computer-readable storage media in the present disclosure may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, a USB flash drive, a mobile hard disk, or any suitable combination of the foregoing.

[0164] In the embodiments of the present disclosure, the computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer instructions (readable program codes).

[0165] Such a propagated data signal may take any of a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0166] In some examples, computing instructions contained on a computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0167] The embodiments of the present disclosure also provide a computer program product, which stores instructions. When the instructions are executed by a computer, the computer implements the cross-scale seismic wave attenuation and dispersion prediction method described in the above method embodiment.

[0168] The above instructions may be program codes. In specific implementation, the program codes may be written in any combination of one or more programming languages.

[0169] Programming languages ​​include object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages.

[0170] The program code may execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0171] Where a remote computing device is involved, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0172] The embodiment of the present disclosure further provides a chip, comprising at least one processor and an interface;

[0173] An interface for providing program instructions or data to at least one processor;

[0174] At least one processor is used to execute program instructions to implement the cross-scale seismic wave attenuation and dispersion prediction method described in the above method embodiment.

[0175] In some embodiments, the chip may further include a memory for storing program instructions and data, and the memory may be located inside or outside the processor.

[0176] Those skilled in the art will appreciate that all or part of the steps for implementing the above embodiments may be implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software, which may be collectively referred to herein as a "circuit," "module," or "system."

[0177] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein.

[0178] This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the appended claims.

Claims

1. A cross-scale seismic wave attenuation and dispersion prediction method, characterized in that: include: Determining a corrected solid bulk modulus based on the corrected solid dry bulk modulus and the average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling the spherical jet flow term to the skeleton dry modulus; Determining a corrected rock dry bulk modulus based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure; Determining a fast P-wave velocity and an attenuation coefficient based on the corrected rock bulk modulus and Biot elastic parameters, wherein the fast P-wave velocity and the attenuation coefficient are used to represent seismic wave attenuation and dispersion; The corrected solid bulk modulus is calculated using the following formula: ； in, represents the corrected solid bulk modulus, represents the corrected solid dry bulk modulus, represents the average pressure change, represents the solid skeleton deformation, represents the corrected Biot coefficient.

2. The method according to claim 1, characterized in that The method further comprises: Obtain rock physical parameters and fluid physical parameters; Calculating pore pressure based on the rock physical parameters and the fluid physical parameters; Based on the pore pressures, an average pore pressure is determined.

3. The method according to claim 2, characterized in that The rock physical parameters include rock modulus and / or rock density.

4. The method according to claim 2, characterized in that The fluid physical property parameters include fluid viscosity and / or fluid density.

5. A cross-scale seismic wave attenuation and dispersion prediction device, characterized in that: include: A first calculation module is configured to determine a corrected solid bulk modulus based on the corrected solid dry bulk modulus and the average pore pressure; wherein the corrected solid dry bulk modulus is calculated by coupling the spherical jet flow term to the skeleton dry modulus; a second calculation module, configured to determine a corrected rock dry bulk modulus based on the corrected solid bulk modulus and the rock dry bulk modulus under high pressure; A prediction module, configured to determine a fast P-wave velocity and an attenuation coefficient based on the corrected rock bulk modulus and Biot elastic parameters, wherein the fast P-wave velocity and the attenuation coefficient are used to represent seismic wave attenuation and dispersion; The first calculation module is used to calculate the corrected solid bulk modulus using the following formula: ； in, represents the corrected solid bulk modulus, represents the corrected solid dry bulk modulus, represents the average pressure change, represents the solid skeleton deformation, represents the corrected Biot coefficient.

6. The device according to claim 5, characterized in that The device further comprises: Data acquisition module, used to obtain rock physical parameters and fluid physical parameters; A pressure calculation module, configured to calculate the pore pressure based on the rock physical parameters and the fluid physical parameters; A data processing module is used to determine an average pore pressure based on the pore pressure.

7. An electronic device, characterized in that: include: a memory for storing instructions; A processor is used to call the instructions stored in the memory to implement the cross-scale seismic wave attenuation and dispersion prediction method according to any one of claims 1 to 4.

8. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the cross-scale seismic wave attenuation and dispersion prediction method described in any one of claims 1 to 4 is implemented.

9. A chip, characterized in that: comprising at least one processor and an interface; The interface is configured to provide program instructions or data to the at least one processor; The at least one processor is used to execute the program instructions to implement the cross-scale seismic wave attenuation and dispersion prediction method as described in any one of claims 1-4.

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