Seismic wave velocity dispersion and attenuation prediction method, device, equipment and medium

Abstract

The present disclosure provides a seismic wave velocity dispersion and attenuation prediction method, device, equipment and medium, and relates to the field of seismic rock physics. The method comprises: obtaining logging data and / or laboratory measurement data of a seismic rock; determining a corrected wet framework bulk modulus and a shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data; determining an equivalent plane wave modulus of a saturated rock using a boundary average dynamic effective medium model based on the corrected wet framework bulk modulus and the shear modulus; and determining a seismic wave P-wave velocity and attenuation based on the equivalent plane wave modulus of the saturated rock. According to the present disclosure, the seismic wave dispersion and attenuation in the seismic frequency band can be reasonably and stably predicted without determining the micro-fracture type in advance, and the constructed model does not need to calculate the perturbation variance between the saturated different fluid region poroelastic moduli, which has great practical application value.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of seismic rock physics, and particularly relates to a method and device for predicting seismic wave velocity dispersion and attenuation, equipment and medium. BACKGROUND

[0002] The phenomenon of non-uniform filling of pore fluid is common in the earth medium, and the propagation velocity of seismic waves in such medium has dispersion characteristics in actual oil and gas exploration. Accurate determination of seismic wave velocity and attenuation information in the medium is of great significance for high-precision seismic interpretation. According to the differences in macro, meso and micro scales, the frequency band range of seismic wave dispersion and attenuation also has corresponding differences. Research has shown that the dispersion and attenuation of rocks may be caused by the combined effects of fluid flow induced by multiple scale waves. The existing model attempts to couple models of different scales. In related technologies, the seismic wave velocity dispersion and attenuation prediction model cannot determine the micro crack structure of the pore type, such as pinch-off type and coin type structure, which leads to inaccurate prediction results. At the same time, the existing model usually contains parameters such as crack density and perturbation variance, which are difficult to accurately measure in practical applications.

[0003] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0004] The inventors have found that the existing seismic wave velocity dispersion and attenuation prediction model cannot determine the micro crack structure of the pore type, such as pinch-off type and coin type structure, which leads to inaccurate prediction results. At the same time, the existing model usually contains parameters such as crack density and perturbation variance, which are difficult to accurately measure in practical applications.

[0005] In view of the above problems, the present application discloses a multi-scale seismic wave velocity dispersion and attenuation prediction method, device, equipment and medium, which can reasonably and stably predict the seismic wave dispersion and attenuation in the seismic frequency band without determining the micro crack type in advance, while considering the micro jet flow mechanism and meso patch saturation mechanism. The constructed model does not need to calculate the perturbation variance between the pore elastic modulus of different fluid saturated regions, and the actual prediction effect is good, and the practical application value is great.

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

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

[0008] obtaining logging data and / or laboratory measurement data of seismic rocks;

[0009] determining the corrected wet-frame bulk modulus and shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data;

[0010] determining the equivalent plane wave modulus of the saturated rock based on the corrected wet-frame bulk modulus and shear modulus using the boundary-average dynamic effective medium model;

[0011] determining the seismic wave P-wave velocity and attenuation based on the equivalent plane wave modulus of the saturated rock.

[0012] In one embodiment of the present disclosure, the data obtained from the logging data and / or the laboratory measurement data of the seismic rock includes, but is not limited to, the following data:

[0013] the bulk modulus, the shear modulus and the density of the rock matrix; the bulk modulus, the density, the viscosity coefficient and the permeability of the contained fluid; the porosity.

[0014] In one embodiment of the present disclosure, the corrected wet-frame bulk modulus and shear modulus of the seismic rock are determined based on the logging data and / or the laboratory measurement data, including:

[0015] the corrected wet-frame bulk modulus and shear modulus of the seismic rock are determined based on the logging data and / or the laboratory measurement data using the Gurevich jet-flow model.

[0016] According to another aspect of the present disclosure, a multi-scale seismic wave velocity dispersion and attenuation prediction device is provided, including:

[0017] a data acquisition module configured to acquire logging data and / or laboratory measurement data of a seismic rock;

[0018] a first data processing module configured to determine the corrected wet-frame bulk modulus and shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data;

[0019] a second data processing module configured to determine the equivalent plane wave modulus of the saturated rock based on the corrected wet-frame bulk modulus and shear modulus using the boundary-average dynamic effective medium model;

[0020] a prediction module configured to determine the seismic wave P-wave velocity and attenuation based on the equivalent plane wave modulus of the saturated rock.

[0021] According to still another aspect of the present disclosure, an electronic device is provided, including: a memory configured to store instructions; and a processor configured to invoke the instructions stored in the memory to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described above.

[0022] According to still another aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described above.

[0023] According to still another aspect of the present disclosure, there is provided a computer program product having stored thereon instructions which, when executed by a computer, cause the computer to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described above.

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

[0025] the interface is configured to provide program instructions or data for the at least one processor;

[0026] the at least one processor is configured to execute the program instructions to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described above.

[0027] The multi-scale seismic wave velocity dispersion and attenuation prediction method provided by the embodiments of the present disclosure overcomes the deficiency of single-scale models that can only predict the velocity dispersion and attenuation of seismic waves in a specific frequency band, and can reasonably and stably predict the seismic wave dispersion and attenuation in a seismic frequency band without determining the micro-crack type in advance, and the constructed model does not need to calculate the standard deviation between the poro-elastic moduli of saturated different fluid regions.

[0028] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

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

[0030] Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor based on these drawings.

[0031] Figure 1 a flow chart of a multi-scale seismic wave velocity dispersion and attenuation prediction method in the embodiments of the present disclosure is shown;

[0032] Figure 2 a velocity dispersion curve determined using the seismic wave velocity dispersion and attenuation prediction method of the present disclosure is shown;

[0033] Figure 3 seismic wave attenuation determined using the seismic wave velocity dispersion and attenuation prediction method of the present disclosure is shown;

[0034] Figure 4 Fig. 1 shows a schematic diagram of a device for predicting multi-scale seismic wave velocity dispersion and attenuation according to an embodiment of the present disclosure;

[0035] Figure 5 Fig. 2 shows a structural block diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0036] Example implementations are described more fully below with reference to the accompanying drawings.

[0037] Note that example implementations can be implemented in a variety of forms, and should not be construed as being limited to the examples set forth herein.

[0038] Seismic rock physics modeling is an important method for studying the propagation of seismic waves in the earth medium. The actual earth medium is generally a two-phase medium composed of a solid matrix and a pore fluid, and the fluid is filled in the micro-pores, thereby causing considerable influence on the velocity dispersion and attenuation of seismic waves. With the increasing complexity of oil and gas resource exploration problems, higher accuracy is required for the interpretation of seismic data, and therefore, a corresponding rock physics forward modeling prediction method must be developed. At present, the fluid flow characteristics at different scales will affect the velocity dispersion and attenuation of seismic waves under certain conditions, but any model has its own limitations. According to the differences in macro, meso and micro scales, the frequency band range of seismic wave dispersion and attenuation also has corresponding differences. Research has shown that the dispersion and attenuation of rocks may be caused by the combined effects of fluid flow induced by multiple scale waves, and the development of multi-scale rock physics models that match the actual seismic exploration has practical engineering value.

[0039] When the rock develops random distribution of micro-fissures, wave-induced fluid flow may cause the existence of jet flow, and at this time, the dispersion and attenuation of seismic waves may occur in a higher frequency band range, but when the meso-scale fluid non-uniform distribution exists at the same time, the dispersion and attenuation of seismic waves may also be observed in a lower frequency band range. The inventors have found that for a specified type of pore and fissure structure, a wave-induced flow model containing a periodic layered patch saturation mechanism can be constructed to predict the velocity dispersion and attenuation of seismic waves.

[0040] The disadvantage of the prior art is that the seismic wave velocity dispersion and attenuation prediction model is not suitable for pore type uncertain micro-fissure structures such as pinch-off type and coin type structures, and the current method has the problem that the type of fissure cannot be known, resulting in inaccurate prediction results. At the same time, the existing model usually contains parameters such as crack density and perturbation variance, which are difficult to accurately measure in practical applications.

[0041] To solve the above problems, the present disclosure provides a multi-scale seismic wave velocity dispersion and attenuation prediction method, device, equipment and medium. Based on the Gurevich jet flow theory, the micro jet flow mechanism and the mesoscopic patch saturation mechanism are considered, and the seismic wave velocity dispersion and attenuation in the seismic frequency band can be reasonably and stably predicted without determining the micro crack type in advance. The constructed model does not need to calculate the perturbation variance between the pore elastic modulus of different fluid saturated regions, and has great practical application value.

[0042] The present example embodiment will be described in detail below with reference to the accompanying drawings and examples.

[0043] Figure 1 A flowchart of a multi-scale seismic wave velocity dispersion and attenuation prediction method in the embodiment of the present disclosure is shown as follows. Figure 1 As shown in the flowchart, the multi-scale seismic wave velocity dispersion and attenuation prediction method provided in the embodiment of the present disclosure includes steps S110-S140.

[0044] In S110, logging data and / or laboratory measurement data of the seismic rock are obtained.

[0045] In some embodiments, the data obtained in S110 includes but is not limited to the following data: rock matrix bulk modulus, shear modulus, density; volume modulus, density, viscosity coefficient, permeability of the contained fluid; porosity.

[0046] In S120, the corrected wet framework bulk modulus and shear modulus of the seismic rock are determined based on the logging data and / or laboratory measurement data.

[0047] In some embodiments, S120 can be to determine the corrected wet framework bulk modulus and shear modulus of the seismic rock based on the logging data and / or laboratory measurement data using the Gurevich jet flow model.

[0048] In S130, the equivalent plane wave modulus of the saturated rock is determined based on the corrected wet framework bulk modulus and shear modulus using the boundary average dynamic effective medium model.

[0049] In S140, the seismic wave P-wave velocity and attenuation are determined based on the equivalent plane wave modulus of the saturated rock.

[0050] In some embodiments, the corrected wet framework bulk modulus and shear modulus of the seismic rock can be calculated by the following formula based on the logging data and / or laboratory measurement data using the Gurevich jet flow model:

[0051]

[0052]

[0053] where K mf (P, ω) is the bulk modulus of the wet skeleton, μ mf (P, ω) is the shear modulus of the wet skeleton. In some embodiments K mf (P, ω) and μ mf (P, ω) are the corrected "dry skeleton" moduli at different frequencies and pressures.

[0054] K s Ks is the bulk modulus of the rock matrix, which can be calculated by methods of the prior art.

[0055] K h Kdry is the bulk modulus of the dry rock skeleton with the soft pores completely closed, which can be replaced by the bulk modulus of the dry rock at sufficiently high pressure.

[0056] K dry Kdry(P) is the bulk modulus of the dry rock skeleton at different pressures, which can be measured in the laboratory or calculated by methods of the prior art.

[0057] μ dry μdry(P) is the shear modulus of the dry rock skeleton at different pressures, which can be measured in the laboratory or calculated by methods of the prior art.

[0058] ω is the angular frequency of the wave,

[0059] φ c φ(P) is the soft porosity at different pressures,

[0060] Kf is the characteristic fluid bulk modulus. The characteristic fluid bulk modulus Kf depends on the characteristic fracture aspect ratio a and the fluid viscosity η and can be solved by the following equation:

[0061]

[0062]

[0063] In some embodiments, the equivalent plane wave longitudinal wave modulus of the saturated rock is calculated by the following equation

[0064]

[0065] where, H GW is the upper limit of the saturated longitudinal wave modulus, H GH is the lower limit of the saturated longitudinal wave modulus, is a complex number that contains the frequency and the correlation function characteristics of the heterogeneity.

[0066] In some embodiments, the complex number containing the frequency and the heterogeneity correlation function features can be calculated by the following equation

[0067]

[0068] ( r The fluid non-uniform distribution upper and lower limits can be weighted between 0 and 1 as a function of frequency. s is the medium non-uniformity scale relative to the Biot slow wave wavelength, and is calculated as follows:

[0069]

[0070]

[0071] where f is the frequency, K d and μ d are the bulk and shear moduli of the dry rock; K s is the bulk modulus of the background mineral; φ is the total porosity; is the bulk modulus of water or gas.

[0072] In some embodiments, the seismic wave P-wave velocity V p and attenuation

[0073]

[0074]

[0075] where represents the saturated rock equivalent plane wave modulus, Re represents the real part of the complex number, Im represents the imaginary part of the complex number, ρ sat is the saturated rock density.

[0076] ρ sat can be calculated by the following equation:

[0077] ρ sat = ρ s [1-φ(P)]+φ(P)S Q ρ Q +φ(P)S N ρ N (11)

[0078] where S Q and S N are the gas and water saturations, respectively.

[0079] Figure 2The velocity dispersion curve determined using the seismic wave velocity dispersion and attenuation prediction method provided by the present disclosure is shown in the figure, in which the velocity varies with frequency (Frequency) and presents two dispersion peaks, the factors affecting the velocity dispersion are wave-induced fluid flow in the micro pore-fracture structure and mesoscopic fluid inhomogeneity, the influence of mesoscopic fluid inhomogeneity is significant in the low frequency band, while with the increase of frequency, the jet flow effect becomes significant, and the velocity stability is good in the high frequency stage.

[0080] Figure 3 The seismic wave attenuation determined using the seismic wave velocity dispersion and attenuation prediction method of the present disclosure is shown in the figure, the attenuation curve presents two peaks, the first one represents the influence of mesoscopic fluid inhomogeneity, and the second one represents the influence of micro jet flow effect, the scatter data is experimental data, which proves the rationality of the method.

[0081] In addition, although the various steps of the method in the present disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results.

[0082] In some embodiments, certain steps can be omitted, a plurality of steps can be combined into one step, and / or one step can be divided into a plurality of steps, etc.

[0083] Based on the same inventive concept, the present disclosure also provides a multi-scale seismic wave velocity dispersion and attenuation prediction device, as described in the following embodiments. Since the principle of solving problems of the device embodiment is similar to the above-mentioned method embodiment, the implementation of the device embodiment can be referred to the implementation of the above-mentioned method embodiment, and the repeated parts will not be described here.

[0084] Figure 4 A schematic diagram of a multi-scale seismic wave velocity dispersion and attenuation prediction device in an embodiment of the present disclosure is shown, as shown in the figure, the multi-scale seismic wave velocity dispersion and attenuation prediction device 400 comprises: Figure 4 a data acquisition module 402, configured to acquire logging data and / or laboratory measurement data of a seismic rock;

[0085] the data acquisition module 402, configured to acquire logging data and / or laboratory measurement data of a seismic rock;

[0086] a first data processing module 404, configured to determine a corrected wet framework bulk modulus and a shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data;

[0087] a second data processing module 406, configured to determine an equivalent plane wave modulus of a saturated rock using a boundary average dynamic effective medium model based on the corrected wet framework bulk modulus and the shear modulus;

[0088] The prediction module 408 is configured to determine the seismic wave P-wave velocity and attenuation based on the saturated rock equivalent plane wave modulus.

[0089] In some embodiments, the data acquired in the data acquisition module 402 includes, but is not limited to, the following data: rock matrix bulk modulus, shear modulus, density; the bulk modulus, density, viscosity coefficient, permeability of the contained fluid; porosity.

[0090] In some embodiments, the first data processing module 404 is specifically configured to determine the corrected wet frame bulk modulus and shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data using the Gurevich jet flow model.

[0091] The terms "first", "second", and the like in the present disclosure are merely used to distinguish different devices, modules or units, and do not imply the sequence or interdependence of the functions performed by these devices, modules or units.

[0092] As to the multi-scale seismic wave velocity dispersion and attenuation prediction device in the above-described embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the multi-scale seismic wave velocity dispersion and attenuation prediction method, and will not be described in detail here.

[0093] 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.

[0094] In fact, according to the embodiments 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 several modules or units.

[0095] Some of the block diagrams shown in the drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0096] The electronic device provided by the embodiments of the present disclosure will be described below with reference to Figure 5 The electronic device provided by the embodiments of the present disclosure will be described below with reference to Figure 5 The electronic device 500 shown is merely an example, and should not impose any limitation on the functions and use range of the embodiments of the present disclosure.

[0097] Figure 5 An architectural schematic diagram of an electronic device 500 provided by the embodiments of the present disclosure is shown. As Figure 5As shown, the electronic device 500 includes, but is not limited to, at least one processor 510, at least one memory 520.

[0098] The memory 520 is configured to store instructions.

[0099] In some embodiments, the memory 520 can include a readable medium in the form of volatile storage such as random access memory (RAM) 5201 and / or cache memory 5202, and can further include a non-volatile storage such as read-only memory (ROM) 5203.

[0100] In some embodiments, the memory 520 can further include a program / utility 5204 having a set (at least one) of program modules 5205, including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or a combination can include implementation of a network environment.

[0101] In some embodiments, the memory 520 can store an operating system. The operating system can be a real-time operating system (RTX), LINUX, UNIX, WINDOWS, or OS X.

[0102] In some embodiments, the memory 520 can also store data.

[0103] As an example, the processor 510 can read data stored in the memory 520, which can be stored in the same storage address as the instructions, or which can be stored in a different storage address from the instructions.

[0104] The processor 510 is configured to invoke the instructions stored in the memory 520 to implement the steps of various exemplary embodiments according to the present disclosure described in the above "Exemplary Methods" section of the present specification. For example, the processor 510 can perform the following steps of the above method embodiments:

[0105] Obtaining logging data and / or laboratory measurement data of the seismic rock;

[0106] Determining a corrected wet bulk modulus and a shear modulus of the seismic rock based on the logging data and / or the laboratory measurement data;

[0107] Determining an equivalent plane wave modulus of the saturated rock using a boundary averaged dynamic effective medium model based on the corrected wet bulk modulus and the shear modulus;

[0108] Determining a seismic wave P-wave velocity and attenuation based on the equivalent plane wave modulus of the saturated rock.

[0109] It should be noted that the processor 510 can be a general processor or a special-purpose processor. The processor 510 can include one or more processing cores, and the processor 510 performs various functional applications and data processing by running instructions.

[0110] In some embodiments, the processor 510 can include a central processing unit (CPU) and / or a baseband processor.

[0111] In some embodiments, the processor 510 can determine an instruction according to a priority identifier and / or a function category information carried in each control instruction.

[0112] In the present disclosure, the processor 510 and the memory 520 can be separately provided or integrated together.

[0113] As an example, the processor 510 and the memory 520 can be integrated on a single board or a system on chip (SOC).

[0114] As shown in FIG. 5, the electronic device 500 is in the form of a general computing device. The electronic device 500 can also include a bus 530. Figure 5

[0115] The bus 530 can be one or more of various types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration bus, a processor or local bus using any of a variety of bus architectures.

[0116] The electronic device 500 can also communicate with one or more external devices 540, such as a keyboard or pointing device, a Bluetooth device, etc.; other devices that enable a user to interact with the electronic device 500; and / or any devices (e.g., a router, a modem, etc.) that enable the electronic device 500 to communicate with one or more other computing devices. Such communication can occur via an input / output (I / O) interface 550.

[0117] Also, the electronic device 500 can communicate with one or more networks, such as a local area network (LAN), a wide area network (WAN), and / or the public networks, such as the Internet, via a network adapter 560.

[0118] As shown in FIG. 5, the network adapter 560 communicates with other modules of the electronic device 500 via the bus 530. Figure 5

[0119] ​​It should be appreciated that, although not shown, the electronic device 500 can employ other hardware and / or software modules that can be used in connection with the electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0120] It can be understood that the structures shown in the embodiments of the present disclosure do not constitute a specific limitation on the electronic device 500. In other embodiments of the present disclosure, the electronic device 500 can include more or fewer components than those shown, or combine certain components, or split certain components, or different arrangement of components. Figure 5 ​ The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0121] The present disclosure also provides a computer readable storage medium having stored thereon computer instructions, which when executed by a processor implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described in the above method embodiments.

[0122] In the embodiments of the present disclosure, the computer readable storage medium is a computer readable medium that can send, propagate or transfer a computer program for use by or in connection with an instruction execution system, apparatus or device.

[0123] As an example, the computer readable storage medium is a non-transitory storage medium.

[0124] In some embodiments, more specific examples of the computer readable storage medium in the present disclosure can include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, a U disk, a mobile hard disk, or any appropriate combination of the above.

[0125] In the embodiments of the present disclosure, the computer readable storage medium can include a data signal propagating in a baseband or as a carrier wave in a propagated data signal, in which computer instructions (readable program code) are carried.

[0126] Such a propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any appropriate combination of the above.

[0127] In some examples, the computer instructions contained on the computer readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any appropriate combination of the above.

[0128] ​The embodiment of the present disclosure further provides a computer program product, which stores instructions, and the instructions, when executed by a computer, cause the computer to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described in the above method embodiment.

[0129] The above instructions can be program codes. In a specific implementation, the program codes can be written in any combination of one or more programming languages.

[0130] The programming languages include object-oriented programming languages such as Java, C++, and the like, and conventional procedural programming languages such as the “C” language or similar programming languages.

[0131] The program codes can be executed completely on a user computing device, partially on a user device, as an independent software package, partially on a user computing device and partially on a remote computing device, or completely on a remote computing device or server.

[0132] In a case involving a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, through the Internet by using an Internet service provider).

[0133] The embodiment of the present disclosure further provides a chip, which comprises at least one processor and an interface;

[0134] The interface is configured to provide program instructions or data for the at least one processor;

[0135] The at least one processor is configured to execute the program instructions to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method described in the above method embodiment.

[0136] In some embodiments, the chip can further comprise a memory configured to store the program instructions and the data, and the memory is located in or outside the processor.

[0137] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiments can be implemented in the form of completely hardware, completely software (including firmware, microcode, etc.), or a combination of hardware and software, which can be collectively referred to as “circuitry”, “module” or “system” here.

[0138] Other embodiments of the present disclosure will be apparent to those skilled in the art with the consideration of the specification and practice of the invention disclosed herein.

[0139] The present disclosure is intended to embrace any and all variations, uses, or adaptations of the disclosure that follow, in general, the principles of the disclosure and include variations and / or modifications that are within the skill and purview of those in the art, and which fall within the scope of the disclosure. The above description is meant to be illustrative only and not limiting as to the scope of the disclosure. The true scope and spirit of the disclosure are indicated by the appended claims.

Claims

1. A method for predicting the velocity dispersion and attenuation of multi-scale seismic waves, characterized in that, include: Acquire well logging data and / or laboratory measurement data of seismic rocks; Based on the well logging data and / or the laboratory measurement data, determine the corrected wet skeleton bulk modulus and shear modulus of the seismic rock; Based on the modified wet skeleton bulk modulus and the shear modulus, the equivalent plane wave modulus of saturated rock is determined using the boundary-averaged dynamic equivalent medium model. Based on the equivalent plane wave modulus of the saturated rock, the P-wave velocity and attenuation of the seismic wave are determined; The equivalent plane wave P-wave modulus of saturated rock is calculated using the following formula. : ； in, This is the lower limit of the saturated longitudinal wave modulus. This represents the upper limit of the saturated longitudinal wave modulus. It is a complex number that includes the characteristics of frequency and heterogeneous correlation functions; The complex number containing the characteristics of frequency and heterogeneous correlation functions is calculated using the following formula. : ； Where s is the medium inhomogeneity scale relative to the Biot slow wave wavelength.

2. The method according to claim 1, characterized in that, The data obtained from the well logging data and / or laboratory measurement data of the seismic rocks includes, but is not limited to, the following data: The bulk modulus, shear modulus, and density of the rock matrix; the bulk modulus, density, viscosity coefficient, and permeability of the fluids contained therein; and porosity.

3. The method according to claim 1, characterized in that, Based on the well logging data and / or the laboratory measurement data, determine the corrected wet skeleton bulk modulus and shear modulus of the seismic rock, including: Based on the well logging data and / or the laboratory measurement data, the corrected wet skeleton bulk modulus and shear modulus of the seismic rocks are determined using the Gurevich jet flow model.

4. The method according to claim 3, characterized in that, The determination of the corrected wet skeleton bulk modulus and shear modulus of seismic rocks using the Gurevich jet flow model, based on the well logging data and / or the laboratory measurement data, includes: The corrected wet skeleton bulk modulus and shear modulus of earthquake rocks are calculated using the following formulas: ； ； in, The bulk modulus of the wet skeleton is given. This represents the shear modulus of the wet skeleton. The bulk modulus of the rock matrix. This represents the bulk modulus of the dry rock skeleton after the soft pores in the rock have completely closed. The bulk modulus of the dry rock skeleton under different pressures. Shear modulus of dry rock skeleton under different pressures The angular frequency of the wave. For soft porosity under different pressures, The characteristic fluid bulk modulus.

5. The method according to claim 1, characterized in that, The determination of the P-wave velocity and attenuation of seismic waves based on the equivalent plane wave modulus of the saturated rock includes: The P-wave velocity of a seismic wave is determined by the following formula. and attenuation : ； ； in, Let represent the equivalent plane wave modulus of saturated rock, Re denotes the real part of the complex number, and Im denote the imaginary part of the complex number. This represents the density of saturated rock.

6. A multi-scale seismic wave velocity dispersion and attenuation prediction device, characterized in that, include: The data acquisition module is used to acquire well logging data and / or laboratory measurement data of seismic rocks; The first data processing module is used to determine the corrected wet skeleton bulk modulus and shear modulus of the seismic rock based on the well logging data and / or the laboratory measurement data. The second data processing module is used to determine the equivalent plane wave modulus of saturated rock based on the corrected wet skeleton bulk modulus and the shear modulus, using a boundary-averaged dynamic equivalent medium model. The prediction module is used to determine the P-wave velocity and attenuation of seismic waves based on the equivalent plane wave modulus of the saturated rock. The second data processing module calculates the equivalent plane wave longitudinal modulus of saturated rock using the following formula. : ； in, This is the lower limit of the saturated longitudinal wave modulus. This represents the upper limit of the saturated longitudinal wave modulus. It is a complex number that includes the characteristics of frequency and heterogeneous correlation functions; The complex number containing the characteristics of frequency and heterogeneous correlation functions is calculated using the following formula. : ； Where s is the medium inhomogeneity scale relative to the Biot slow wave wavelength.

7. An electronic device, characterized in that, include: Memory, used to store instructions; The processor is used to call the instructions stored in the memory to implement the multi-scale seismic wave velocity dispersion and attenuation prediction method as described in any one of claims 1-5.

8. A computer-readable storage medium storing computer instructions thereon, characterized in that, When the computer instructions are executed by the processor, they implement the multi-scale seismic wave velocity dispersion and attenuation prediction method according to any one of claims 1-5.

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