Hydrate-containing formation velocity and attenuation characteristic analysis and model construction method, device and equipment and storage medium

Abstract

According to the hydrate-containing stratum velocity and attenuation characteristic analysis and model construction method, device and equipment and the storage medium provided by the embodiment of the invention, the influence of the hydrate on elastic parameters, permeability and fluid viscosity coefficients of a rock solid phase and a skeleton is particularly considered, and the depicting precision of the model on an actual hydrate reservoir is improved; according to the method, the relationship between hydrate mineral components, pore fluids and microstructures and the seismic macroscopic velocity and attenuation attributes is established, the seismic attributes of hydrate reservoirs such as different saturability, porosity and lithology can be analyzed, and the method has certain guiding significance for hydrate saturability estimation and occurrence type judgment by utilizing the velocity and attenuation attributes. And on the basis of the modeling method, diverse and practical hydrate models can be constructed, the method can be used for research such as seismic wave forward modeling and imaging of hydrate reservoirs, and a large amount of sample data can be provided for artificial intelligence seismic parameter inversion.

Description

Technical Field

[0001] This application relates to the fields of unconventional reservoir rock physics modeling and seismic exploration technology, and in particular to a method, apparatus, equipment and storage medium for analyzing and building models of hydrate-bearing formation velocity and attenuation characteristics. Background Technology

[0002] Natural gas hydrates are the most promising unconventional clean energy alternative to conventional fossil fuels. Most natural gas hydrates are distributed in marine sediments, characterized by high efficiency, cleanliness, and large reserves. Therefore, research on exploration and development technologies for natural gas hydrates is of significant strategic importance. With further research into hydrate resources, higher demands are placed on hydrate location and reservoir description. Target hydrate areas are often located in complex structures such as faults, bottom wefts, and mud volcanoes. Hydrate reservoirs are relatively thin, generally only tens to hundreds of meters thick, and exhibit strong lateral discontinuities. The main identification marker, seafloor reflection (BSR), does not have a completely one-to-one correspondence with hydrates. Rock physics and porous media modeling methods for hydrate reservoirs are fundamental for analyzing the seismic properties of hydrate-bearing strata, establishing effective hydrate identification markers, and constructing hydrate models. These methods can provide crucial data support for research on the seismic response characteristics of hydrate-bearing strata, seismic imaging, and seismic attribute parameter inversion.

[0003] Hydrate-bearing strata exhibit anomalous attenuation characteristics. Currently, rock attenuation theories based on porous media mainly include the Biot, BISQ, and White theories. Numerous scholars at home and abroad have studied the attenuation characteristics of hydrates based on these three theories, but there are still some controversies. There is a lack of unified and reasonable methods for the physical characterization of hydrate-attenuated rocks and the construction of viscoelastic-acoustic media models. Moreover, existing methods generally only consider the influence of hydrates on rock solids and frameworks. There is an urgent need to study a new method for analyzing the seismic properties of hydrates and for constructing viscoelastic-acoustic media models.

[0004] It should be noted that the information disclosed in the background section of this application is intended only to enhance the understanding of the general background of this application, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] In view of this, this application provides a method, apparatus, equipment, and storage medium for analyzing and constructing models of velocity and attenuation characteristics of hydrate-bearing strata. Specifically, it is a method for rock physical characterization and velocity and attenuation characteristic analysis of strata with various hydrate occurrence types in marine areas, as well as a method for automatically constructing batch models of viscous acoustic media, in order to solve the problem of the lack of a unified and reasonable analysis of seismic velocity and attenuation properties of hydrate-bearing strata and the automatic batch construction of model samples in the prior art.

[0006] For natural gas hydrate reservoirs, a complete and systematic method for seismic attribute analysis of multiple types of hydrates and a method for batch automatic construction of visco-acoustic media models are provided. The model is based on rock physics and porous media theory, and specifically considers the influence of different types of hydrates on rock solid phases, fluid bulk modulus, viscosity coefficient and permeability, which improves the accuracy of characterizing actual hydrate reservoirs. It establishes the relationship between the elastic parameters and contents of various rock components in hydrate strata and seismic wave velocity and attenuation characteristics, laying the foundation for hydrate reservoir identification, occurrence type determination, saturation estimation, wavefield characteristic analysis, and imaging and artificial intelligence seismic parameter inversion research.

[0007] In a first aspect, embodiments of this application provide a method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations, which includes the following steps:

[0008] S1: Obtain the elastic modulus of each mineral component of the rock;

[0009] S2: Calculate the shear modulus and bulk modulus of the solid phase and skeleton of rocks with different mineral compositions, different porosities, different hydrate saturation and occurrence types based on the results of step S1.

[0010] S3: Calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types based on the data obtained in step S2.

[0011] In some embodiments of the present invention, the hydrate occurrence types include: particle contact mode, suspension mode and cementation mode.

[0012] In some embodiments of the present invention, in step S2,

[0013] Under the particle contact mode, the elastic moduli K and G of the solid phase without hydrates are corrected to obtain the elastic moduli of the solid phase of the hydrate-bearing formation as follows:

[0014]

[0015] Among them G h f is the shear modulus of the pure hydrate. h The volume fraction of hydrate can be calculated using the following formula:

[0016]

[0017] The density of the solid phase also changes to ρ due to the filling of hydrates. s '=f h ρ h +(1-f h )ρ s .

[0018] Under cementation mode, the elastic modulus K of the dry rock skeleton dry and G dry Calculations were performed based on the cementation theory of Dvorkin and Nur (1993a):

[0019]

[0020] Where S n and S τ These are values ​​related to cementation pressure and hydrate content.

[0021] In some embodiments of the present invention, in step S3, by correcting the permeability in particle contact mode and cementation mode, and correcting the fluid bulk modulus and viscosity coefficient in suspension mode, the formation velocity and quality factors of different lithologies, different porosities, and different hydrate saturation and occurrence types are obtained.

[0022] According to another aspect of the present invention, a method for constructing a model of a multi-type hydrate-bearing strata viscosonic medium is provided, comprising the following steps:

[0023] Step 1: Randomly generate undulating strata;

[0024] Step 2: Calculate the formation velocity and quality factor of the undulating strata based on the above-mentioned analysis method for the velocity and attenuation characteristics of multi-type hydrate formations;

[0025] Step 3: Randomly generate the hydrate bottom interface, top interface, and free gas layer bottom interface;

[0026] Step 4: Calculate the formation velocity and quality factor of the hydrate layer and free gas layer based on the above-mentioned analysis methods for the velocity and attenuation characteristics of various types of hydrate-bearing formations;

[0027] Step 5: Randomly generate normal faults to obtain the viscous acoustic medium model.

[0028] In some embodiments of the present invention, in the first step, the grid size and sampling interval for the vertical and horizontal directions of the model are set, and then sin(τ×π×x) is used. i / n x / d x The function randomly generates multiple stratigraphic interfaces, where τ is a random number controlling the undulation of the stratigraphic interfaces, and x... i n represents the horizontal coordinate position of the grid point. x d represents the number of horizontal grid points. x The horizontal grid spacing is defined, where the first layer represents the seabed interface, and the depths of the remaining layers are randomly generated below the seabed.

[0029] According to another aspect of the present invention, a multi-type hydrate-bearing formation velocity and attenuation characteristic analysis apparatus is also provided, comprising:

[0030] The acquisition module is used to obtain the elastic modulus of each mineral component of the rock;

[0031] The modulus calculation module is used to calculate the shear modulus and bulk modulus of rock solid phase and skeleton with different mineral components, different porosities and different hydrate occurrence types based on the result data obtained by the acquisition module.

[0032] The analysis module is used to calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types.

[0033] According to another aspect of the present invention, a device for constructing models of viscoacoustic media in multi-type hydrate-bearing strata is also provided, comprising:

[0034] The generation module is used to randomly generate undulating strata, as well as randomly generate the bottom interface, top interface, and bottom interface of the free gas layer.

[0035] The calculation module is used to calculate the formation velocity and quality factor of the undulating formation according to the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method; and to calculate the formation velocity and quality factor of the hydrate layer and the free gas layer according to the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method.

[0036] The model acquisition module is used to randomly generate normal faults to obtain a model of the viscous acoustic medium.

[0037] According to another aspect of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations as described above, and / or implements the method for constructing a model of a viscous acoustic medium of multiple types of hydrate-bearing formations as described above.

[0038] According to another aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations as described above, and / or implements the method for constructing a model of a viscous acoustic medium of multiple types of hydrate-bearing formations as described above.

[0039] According to another aspect of the present invention, a computer program product is also provided, characterized in that the computer program product includes a computer program that, when executed by a processor, implements the method described above.

[0040] The embodiments of this application have the following technical advantages and beneficial effects:

[0041] This invention specifically considers the influence of fluid viscosity coefficient, improving the accuracy of attenuation modeling for multiple types of hydrates. Furthermore, seismic forward modeling is fundamental for studying the seismic response characteristics of hydrate layers and identifying hydrate reservoirs. Current forward modeling studies for hydrate layers are mostly based on simple layered acoustic medium models. However, actual hydrate reservoirs exhibit anomalous attenuation and generally intersect with conventional strata. Using layered acoustic models to simulate seismic wave fields results in significant discrepancies with reality, reducing the understanding of hydrate reservoir propagation patterns and hindering reservoir identification. This invention proposes a velocity and attenuation modeling method for multiple types of hydrate-bearing strata based on an effective medium model and White's theory. It specifically considers the influence of different hydrate types on rock solid phases, fluid bulk modulus, viscosity coefficient, and permeability, improving modeling accuracy. Based on this method, the seismic properties of different hydrate strata can be analyzed, laying a theoretical foundation for estimating hydrate saturation and determining occurrence type using velocity and attenuation properties. It can also be used to construct different hydrate-bearing viscous-acoustic medium models in batches for seismic forward modeling, imaging, and artificial intelligence seismic parameter inversion studies related to hydrate reservoirs. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of "A Method for Analyzing the Velocity and Attenuation Characteristics of Multi-Type Hydrate Formations" provided in an embodiment of the present invention.

[0044] Figure 2 This is a flowchart of "A method for batch construction of velocity and attenuation models of multi-type hydrate formations" provided in an embodiment of the present invention.

[0045] Figure 3 The curves showing the variation of longitudinal wave velocity and inverse quality factor of various types of hydrate-bearing layers with hydrate saturation based on White theory (dominant frequency 35Hz) provided by this invention are shown.

[0046] Figure 4 This invention provides a viscous acoustic medium model containing a single hydrate under a randomly generated particle contact mode. The first row is the longitudinal wave velocity model, and the second row is the quality factor model.

[0047] Figure 5This invention provides a randomly generated adhesive acoustic medium model containing a single hydrate under a cementation mode, with the first row being the longitudinal wave velocity model and the second row being the quality factor model.

[0048] Figure 6 This invention provides a randomly generated viscous acoustic medium model containing a single hydrate in a suspension mode, with the first row being the longitudinal wave velocity model and the second row being the quality factor model.

[0049] Figure 7 This invention provides a more complex viscoacoustic medium model that is randomly generated and contains multiple hydrate reservoirs, different lithologies, and multiple faults. The first row is the P-wave velocity model, and the second row is the quality factor model.

[0050] Figure 8 This invention provides Figure 4 The forward modeling results for the viscous acoustic medium model are shown in the first row. The first row shows the forward modeling results of the attenuated wave field, and the second row shows the forward modeling results of the acoustic wave. The black arrows indicate the BSR positions.

[0051] Figure 9 This invention provides Figure 4 The imaging results of the viscous acoustic medium model are shown in the first row. The first row shows the attenuation-compensated imaging results, and the second row shows the uncompensated results. The black arrows indicate the BSR locations.

[0052] Figure 10 These are the velocity parameters of the neural network inversion obtained by training the hydrate model constructed using the present invention. The first row is the smooth initial model, the second row is the theoretical label, and the third row is the inversion result.

[0053] Figure 11 These are the quality factor parameters obtained by training a neural network using the hydrate model constructed in this invention. The first row represents the smooth initial model, the second row represents the theoretical label, and the third row represents the inversion result.

[0054] Figure 12 This is a schematic diagram of the structure of "a device for analyzing the velocity and attenuation characteristics of multi-type hydrate formations" provided by the present invention.

[0055] Figure 13 This is a schematic diagram of the structure of "a device for batch construction of velocity and attenuation models of multi-type hydrate formations" provided by the present invention.

[0056] Figure 14 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0057] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0058] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0059] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0060] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0061] Please see Figure 1 This invention provides a method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations, which includes the following steps:

[0062] S1: Obtain the elastic modulus of each mineral component of the rock;

[0063] S2: Calculate the shear modulus and bulk modulus of the solid phase and skeleton of rocks with different mineral compositions, different porosities, different hydrate saturation and occurrence types based on the results of step S1.

[0064] S3: Calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types based on the data obtained in step S2.

[0065] As one specific implementation method, the following specific approach can be adopted:

[0066] Step 1: Calculate the rock elastic modulus using the effective medium model.

[0067] The effective medium model is mainly used to estimate the elastic modulus and velocity parameters of rocks. Here, this model is used to calculate the shear modulus and bulk modulus of hydrate-bearing strata and general sedimentary strata. This model utilizes both statistics and rock elasticity mechanics, and also considers the microstructure and macroscopic properties of the medium. The model first uses Hill's (1952) average formula (1) to calculate the bulk modulus K and shear modulus G of the solid phase of the rock:

[0068]

[0069] Where m is the number of mineral components that make up the solid phase of the rock, f i K represents the volume fraction of the i-th mineral component. i and G i Let K and G be the bulk modulus and shear modulus of the i-th mineral component, respectively. After obtaining the bulk modulus K and shear modulus G of the solid phase, the effective bulk modulus K of the dry rock skeleton at the critical porosity (typically 40%) can be calculated using Hertz-Mindlin (Mindlin, 1949) theory. HM and effective shear modulus G HM That is, as shown in equation (2):

[0070]

[0071] Where n is the average interparticle bonding coefficient (usually taken as 8 or 9), and P is the effective pressure. ρ s and ρ f Let be the density of the solid phase and the density of the fluid phase, respectively; g be the gravitational acceleration; h be the depth below the seabed; and υ be the Poisson's ratio of the solid phase, υ = (3K - 2G) / (6K + 2G).

[0072] When the porosity of the rock Not equal to critical porosity At that time, the bulk modulus K of the dry rock skeleton dry and shear modulus G dry The calculation can be performed in two cases based on the Hashin-Shtrikman upper and lower boundary conditions (Hashin and Shtrikman, 1963; Dvorkin et al., 1999). The first case is when the rock porosity... Less than critical porosity At that time, the elastic modulus K of the dry rock skeleton dry and G dry for:

[0073]

[0074] The second scenario is when the rock porosity... greater than critical porosity At that time, K dry and G dry for:

[0075]

[0076] in

[0077] The above is only a general method for calculating the elastic modulus of sedimentary strata. When hydrates are present, the above formula needs to be modified. Hydrates generally exist in rock pores in three modes: particle contact, suspension, and cementation. In the particle contact mode, hydrates can be regarded as part of the rock skeleton. The filling of hydrates will reduce the porosity. Where S h The saturation of hydrates will change the bulk modulus and shear modulus of the solid phase of the rock. According to formula (1), the elastic modulus K and G of the solid phase without hydrates can be corrected to obtain the elastic modulus of the solid phase of the hydrate-bearing strata as follows:

[0078]

[0079] Among them G h f is the shear modulus of the pure hydrate. h The volume fraction of hydrates can be calculated using the following formula:

[0080]

[0081] The density of the solid phase also changes to ρ due to the filling of hydrates. s '=f h ρ h +(1-f h )ρ s .

[0082] When hydrates are in suspension mode, they can be considered as pore fluids. In this case, hydrates do not change the elastic parameters of the rock solid phase and framework, only the fluid parameters. Finally, when hydrates are in cementation mode, the reduction in porosity is calculated in the same way as in the particle contact mode. Additionally, the elastic modulus K of the dry rock framework... dry and G dry Calculations need to be performed based on the cementation theory of Dvorkin and Nur (1993a):

[0083]

[0084] Where S n and S τ The values ​​related to cementation pressure and hydrate content are calculated as follows:

[0085] S n =A n (ω n )α 2 +B n (ω n )α+C n (ω n )

[0086]

[0087] S τ =A τ (ω τ ,υ)α 2 +B τ (ω τ ,υ)α+C τ (ω τ ,υ)

[0088]

[0089]

[0090] Where υ h Given the Poisson's ratio of pure hydrates, the shear modulus and bulk modulus of the solid phase and skeleton of rocks with different mineral components, different porosities, and different hydrate occurrence types can be calculated using the above formulas (1) to (7).

[0091] Step 2: Calculate formation velocity and quality factor using White's theory.

[0092] White's spherical theory uses a sphere containing two different pore fluids as the characteristic unit to study the propagation characteristics of longitudinal waves. The radius of the central spherical body is a1, and the radius of the outer water-containing shell is a2. The gas saturation S1 and water saturation S2 can be expressed as: S2 = 1 - S1. Using White's theory and the rock elastic modulus obtained in the previous step, the P-wave velocity and inverse quality factor of the formation can be calculated as follows:

[0093]

[0094] Where C is the longitudinal wave complex velocity, which can be expressed by the equivalent complex bulk modulus K of a partially saturated porous medium. * and dry rock skeleton shear modulus G dry The calculation yielded:

[0095]

[0096] Where ρ e The equivalent density of the feature unit is: ρ s The density of the solid phase of the medium. Equivalent density of the fluid in the pores of the medium: ρ g ,ρ f These represent the densities of the gas and fluid in the medium, respectively. The calculation methods for the remaining parameters are as follows:

[0097]

[0098]

[0099] Where κ is the rock permeability, η m Let m be the viscosity coefficient of the fluid (gas or water). Let be the bulk modulus of fluid m. The effects of hydrates on permeability, viscosity, and fluid bulk modulus are considered here. In the particle contact mode, hydrate presence only changes rock permeability, not fluid properties. Permeability is calculated using the following empirical formula:

[0100] κ'=κ(1-S h ) 7.9718 (10)

[0101] Where κ and κ' represent the permeability before and after hydrate filling, respectively. In the suspension mode, the hydrate can be considered as part of the fluid, altering the fluid's bulk modulus and viscosity coefficient. Changes in rock permeability are not considered. The formula for calculating the bulk modulus is:

[0102]

[0103] Where K h K w The bulk modulus of hydrates and seawater are given, respectively, and the viscosity coefficient is corrected for the viscosity of fluids containing particles.

[0104] η'=η(1-f h ) -2.5 (12)

[0105] Where η and η' are the viscosity coefficients before and after hydrate filling, respectively. In the cementation mode, the permeability is also corrected using formula (10) without changing the pore fluid properties.

[0106] The above method enables the modeling of velocities and quality factors in formations with different lithologies, porosities, hydrate saturations, and occurrence types. It specifically considers the influence of hydrates on the elastic parameters of the rock solid phase and framework, as well as permeability and fluid properties, achieving refined marine hydrate velocity and attenuation modeling. This model can be used to analyze the velocity and attenuation characteristics of different types of hydrate-bearing formations and lays a theoretical foundation for subsequent hydrate saturation estimation and occurrence type determination using velocity and attenuation-related attributes. Below is a method for randomly constructing multiple viscoacoustic media models of different types of hydrate-bearing formations based on steps one and two. This method can be used for research and applications related to seismic wavefield feature forward modeling, imaging, and artificial intelligence parameter inversion, such as... Figure 2 As shown.

[0107] Corresponding to the above embodiments, this application also provides a method for constructing a model of viscoacoustic media in multi-type hydrate-bearing formations, comprising the following steps:

[0108] Step 1: Randomly generate undulating strata;

[0109] Step 2: Calculate the formation velocity and quality factor of the undulating strata according to the multi-type hydrate formation velocity and attenuation characteristic analysis method described above;

[0110] Step 3: Randomly generate the hydrate bottom interface, top interface, and free gas layer bottom interface;

[0111] Step 4: Calculate the formation velocity and quality factor of the hydrate layer and free gas layer based on the multi-type hydrate-bearing formation velocity and attenuation characteristic analysis method described above;

[0112] Step 5: Randomly generate normal faults to obtain the viscous acoustic medium model.

[0113] As a specific implementation method, the following steps can be followed:

[0114] Step 1: Randomly generate undulating strata.

[0115] Set the grid size and sampling interval for the model's vertical and horizontal directions, and then use sin(τ×π×x) i / n x / d x The function randomly generates multiple stratigraphic interfaces, where τ is a random number controlling the undulation of the stratigraphic interfaces, and x... i n represents the horizontal coordinate position of the grid point. x d represents the number of horizontal grid points. x The horizontal grid spacing is defined, with the first layer being the seabed interface, generally controlled below a depth of 800m. The depths of the remaining layers are randomly generated below the seabed. In order to avoid the intersection of layer interfaces, the random depth range of each layer interface must be limited.

[0116] Step 2: Calculate the general formation velocity and Q value.

[0117] To calculate the velocity and quality factors of a typical undulating strata using the effective medium model and the White model, it is first necessary to determine the solid phase mineral composition, pore fluid composition, and rock porosity and permeability parameters of each layer. The porosity and permeability of each layer decrease with increasing layer depth, where the layer depth is taken as the depth of the stratum center. Then, the rock elastic parameters are calculated using the effective medium model, and the P-wave velocity and Q value of the strata are calculated using the White model. The velocity of the seawater layer is taken as 1500 m / s, and Q is taken as 150.

[0118] Step 3: Randomly generate the hydrate bottom interface, top interface, and free gas layer bottom interface.

[0119] After generating the general stratigraphic model, hydrate layers and free gas layers are randomly generated. Since the bottom interface of the hydrate layer undulates with the corresponding seafloor interface, a seafloor interface of arbitrary lateral length is randomly selected as the bottom interface of the hydrate layer. The depth of the bottom interface is randomly generated below the seafloor. The top interface of the hydrate layer is determined by the thickness of the hydrate reservoir. First, the maximum thickness of the hydrate layer is randomly generated. Then, several feature points are selected so that the thickness of the hydrate reservoir is maximum in the middle and gradually decreases to zero on both sides. The remaining values ​​are obtained by interpolation. Generally, there is a free gas layer below the hydrate layer. The generation method of the bottom interface of the gas layer is similar to that of the top interface of the hydrate layer. A maximum thickness is randomly generated in the center and then gradually decreases to zero on both sides.

[0120] Step 4: Calculate the velocity and Q value of the hydrate layer and the free gas layer.

[0121] After calculating the interface between the hydrate layer and the free gas layer, the P-wave velocity and Q-value were assigned to the hydrate layer and the gas layer using the effective medium model and the White model. First, the solid phase mineral composition, permeability, and porosity of the rock layer were determined. The porosity was randomly generated within a certain range. Then, the elastic parameters of the rock were calculated using the effective medium model. For the hydrate layer, the pore fluid includes water and hydrates. Since the reflection of the top interface of the hydrate-bearing layer is generally difficult to detect in actual seismic data, this indicates that the hydrate saturation reaches its maximum value near the BSR and then gradually decreases with decreasing depth (EcKer et al., 1998; Hyndman et al., 2001). At the same time, the high saturation and low permeability of the hydrate-bearing layer hinders the upward migration of the underlying free gas. Therefore, in this invention, the maximum hydrate saturation is randomly generated within a certain range. Then, several feature points are selected proportionally in the depth direction so that the hydrate saturation gradually decreases with decreasing depth. The velocity and Q-value of the feature points of the hydrate-bearing layer are calculated using the White model, and the rest are obtained by interpolation. For the gas-bearing layer, the pore fluid includes water and gas, the gas saturation is set to a fixed value, and finally the velocity and Q value of the gas-bearing layer are calculated by the White model.

[0122] Step 5: Randomly generate normal faults.

[0123] After determining the hydrate layer and general strata, normal faults are randomly generated with a certain probability. First, the coordinates of the two intersection points between the fault plane and the model boundary are randomly determined. Then, the hanging wall of the fault is randomly moved downwards to a certain depth to complete the fault generation. Finally, through the above steps, a large number of different types of natural gas hydrate viscosonic media models with rock physics basis can be quickly generated in batches.

[0124] This invention specifically considers the influence of fluid viscosity coefficient, improving the accuracy of attenuation modeling for multiple types of hydrates. Furthermore, seismic forward modeling is fundamental for studying the seismic response characteristics of hydrate layers and identifying hydrate reservoirs. Current forward modeling studies for hydrate layers are mostly based on simple layered acoustic medium models. However, actual hydrate reservoirs exhibit anomalous attenuation and generally intersect with conventional strata. Using layered acoustic models to simulate seismic wave fields results in significant discrepancies with reality, reducing the understanding of hydrate reservoir propagation patterns and hindering reservoir identification. This invention proposes a velocity and attenuation modeling method for multiple types of hydrate-bearing strata based on an effective medium model and White's theory. It specifically considers the influence of different hydrate types on rock solid phases, fluid bulk modulus, viscosity coefficient, and permeability, improving modeling accuracy. Based on this method, the seismic properties of different hydrate strata can be analyzed, laying a theoretical foundation for estimating hydrate saturation and determining occurrence type using velocity and attenuation properties. It can also be used to construct different hydrate-bearing viscous-acoustic medium models in batches for seismic forward modeling, imaging, and artificial intelligence seismic parameter inversion studies related to hydrate reservoirs.

[0125] Corresponding to the above embodiments, this application also provides a device for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations, such as... Figure 12 As shown, it includes:

[0126] The acquisition module is used to obtain the elastic modulus of each mineral component of the rock;

[0127] The modulus calculation module is used to calculate the shear modulus and bulk modulus of rock solid phase and skeleton with different mineral components, different porosities and different hydrate occurrence types based on the result data obtained by the acquisition module.

[0128] The analysis module is used to calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types.

[0129] The embodiment of the multi-type hydrate formation velocity and attenuation characteristic analysis device provided by the present invention can be used to execute the processing flow of the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method. Its function will not be repeated here, but can be referred to the detailed description of the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method.

[0130] Based on the above-mentioned method for constructing models of viscoacoustic media in various types of hydrate-bearing formations, this application also provides a device for analyzing the velocity and attenuation characteristics of various types of hydrate-bearing formations, such as... Figure 13 As shown, it includes:

[0131] The generation module is used to randomly generate undulating strata, as well as randomly generate the bottom interface, top interface, and bottom interface of the free gas layer.

[0132] The calculation module is used to calculate the formation velocity and quality factor of the undulating formation according to the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method; and to calculate the formation velocity and quality factor of the hydrate layer and the free gas layer according to the above-mentioned multi-type hydrate formation velocity and attenuation characteristic analysis method.

[0133] The model acquisition module is used to randomly generate normal faults to obtain a model of the viscous acoustic medium.

[0134] The embodiments of the multi-type hydrate-bearing strata viscoacoustic medium model construction device provided by the present invention can be used to execute the processing flow of the above-mentioned multi-type hydrate-bearing strata viscoacoustic medium model construction method. Its functions will not be repeated here, but can be referred to the detailed description of the above-mentioned multi-type hydrate-bearing strata viscoacoustic medium model construction method.

[0135] Corresponding to the above embodiments, this application also provides an electronic device.

[0136] This application also provides a schematic diagram of the structure of an electronic device. For example... Figure 14 As shown, the electronic device 1000 may include a processor 1001, a memory 1002, and a communication unit 1003. These components communicate via one or more buses. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the embodiments of this application. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0137] The communication unit 1003 is used to establish a communication channel, thereby enabling the electronic device to communicate with other devices.

[0138] The processor 1001 serves as the control center of the electronic device, connecting various parts of the device via various interfaces and lines. It executes software programs and / or modules stored in the memory 1002, and calls data stored in the memory to perform various functions and / or process data. The processor may be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 1001 may consist only of a central processing unit (CPU). In this embodiment, the CPU may have a single processing core or include multiple processing cores.

[0139] Memory 1002 is used to store the execution instructions of processor 1001. Memory 1002 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0140] When the execution instructions in memory 1002 are executed by processor 1001, the electronic device 1000 is able to perform some or all of the steps in the above method embodiments.

[0141] Corresponding to the above embodiments, this application also provides a computer-readable storage medium, wherein the computer-readable storage medium may store a computer program, and when the computer program is executed by a processor, it may implement some or all of the steps in the above method embodiments.

[0142] In specific implementations, the computer-readable storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0143] Corresponding to the above embodiments, this application also provides a computer program product, which includes a computer program that, when executed by a processor, can implement some or all of the steps in the above method embodiments.

[0144] The following is a further explanation with reference to specific embodiments.

[0145] See Figure 1 This paper demonstrates the method and process for analyzing the velocity and attenuation characteristics of various types of hydrate-bearing formations in this invention. A detailed description is provided below with reference to Example 1:

[0146] Example 1: Analysis of hydrate formation velocity and attenuation characteristics based on effective medium model and White theory.

[0147] Step 1: First, set the mineral composition of the rock solid phase. Here, it is given as 22% clay, 30% quartz, 20% muscovite, 20% calcite, and 8% plagioclase. The elastic parameters of each component are shown in Table 1. The porosity is set to 0.3. The bulk modulus K and shear modulus G of the rock solid phase are calculated by formula (1). If it is a particle contact mode, the elastic parameters and porosity of the solid phase need to be corrected according to the hydrate saturation using formulas (5) and (6). Then, the effective elastic modulus of the rock skeleton is calculated using formula (2), and the bulk modulus K of the dry rock skeleton is calculated using formulas (3) and (4). dry and shear modulus G dry When the hydrate is in a cemented mode, the reduction in porosity is calculated in the same way as in the particle contact mode (6). In addition, the elastic modulus K of the dry rock skeleton dry and G dry The calculations need to be performed using formula (7) based on the cementation theory of Dvorkin and Nur (1993a). No corrections are required for the suspension mode and the particle contact mode.

[0148] Step 2: Calculate the formation velocity and inverse quality factor parameters using formulas (8) and (9) from White's theory. The permeability before hydrate infill is set to 1 Darcy. Considering the influence of hydrate on permeability, viscosity coefficient, and fluid bulk modulus, in the particle contact mode, hydrate presence only changes rock permeability without altering fluid properties. Permeability is calculated using empirical formula (10). In the suspension mode, hydrate can be considered as part of the fluid, changing the fluid's bulk modulus and viscosity coefficient. Changes in rock permeability are not considered, and bulk modulus and viscosity coefficient are calculated using formulas (11) and (12). In the cementation mode, formula (10) is also used to correct permeability without changing pore fluid properties.

[0149] Step 3: Gradually increase the hydrate saturation from 0 to 0.8, without changing other parameters, and calculate the curves of the rate and adverse quality factor as a function of hydrate saturation under different hydrate occurrence modes, as shown below. Figure 3 As shown, formation velocities increase continuously with increasing hydrate saturation, regardless of the occurrence mode. The cemented mode shows the largest increase in velocity, while the suspended mode shows the smallest increase, with the grain contact mode falling in between. Regarding attenuation characteristics, in the cemented mode, the cementation between hydrate and rock particles weakens overall with increasing hydrate saturation. In the suspended mode, attenuation initially increases with increasing hydrate saturation and then gradually decreases. The attenuation characteristics in the grain contact mode are similar to those in the suspended mode, but the maximum attenuation value is smaller and reaches its maximum at lower hydrate saturation levels.

[0150] This embodiment only changes the hydrate saturation while keeping other parameters fixed. It can be used to analyze the influence of hydrate saturation on formation velocity and decay characteristics under different occurrence types. It can also be used to analyze the velocity and decay characteristics of multiple types of hydrates under different lithologies and porosities. Furthermore, it can lay a theoretical foundation for modeling the velocity and decay of hydrate-bearing formations and using velocity and decay attributes to estimate hydrate saturation and determine occurrence types.

[0151] Table 1. Rock components and elastic parameters

[0152]

[0153] See Figure 2 This paper demonstrates the method and process for batch construction of velocity and attenuation models of multiple types of hydrate-bearing formations in this invention. Steps one through seven are used. For the sake of brevity and clarity, steps one and two will not be described in detail here. The following is a detailed description in conjunction with Examples 2 and 3:

[0154] Example 2: Randomly batch-constructing multiple hydrate-containing viscous acoustic medium models with different storage types

[0155] Step 1: Randomly generate general stratigraphic interfaces. The model size is 411×411, and the spatial sampling interval in the x and z directions is 5m. The first step in model generation is to randomly generate four stratigraphic interfaces using the sin(τ×π×xi / nx / dx) function. The first interface is the seafloor interface, where τ∈[1,3] is a random number that controls the undulation of the stratigraphic interface, xi∈[5,2055] is the horizontal coordinate position, nx=411 is the number of horizontal grid points, and dx=5 is the horizontal grid spacing. To avoid the intersection of the layers, the seafloor interface is controlled within the depth range of 860 m to 1140 m, and the depths of the remaining layers are randomly generated within the ranges of [1160m,1440m], [1460m,1740m], and [1760m,2040m], respectively.

[0156] Step 2: The velocity and quality factor of a general undulating stratum are calculated using the effective medium model and White theory. First, the solid phase mineral composition of each layer needs to be determined. The solid phase composition consists of 22% clay, 30% quartz, 20% muscovite, 20% calcite, and 8% plagioclase. The elastic parameters of each component are shown in Table 1. The porosity and permeability of each layer decrease with increasing layer depth. The porosity gradually decreases from 0.5 to 0.3 from the seabed to the maximum depth of the model, and the permeability gradually decreases from 1 Darcy to 0.5 Darcy. The layer depth is taken as the depth of the layer center. After determining the above basic rock parameters, the elastic parameters of the rock can be calculated using the effective medium model formulas (1) to (7), the solid phase mineral composition and the elastic parameters of each component, and the porosity parameter. Then, the P-wave velocity and Q value of the general undulating stratum are calculated using the White model formulas (8) to (12) combined with the elastic parameters of the rock, permeability, pore fluid, and the elastic parameters of each fluid component.

[0157] Step 3: Then, the hydrate layer and free gas layer are randomly generated. Since the bottom interface of the hydrate layer is consistent with the undulation of the corresponding seabed interface, a seabed interface of arbitrary horizontal length is randomly selected as the bottom interface of the hydrate. In this embodiment, the horizontal extension range of the hydrate layer is randomly generated from 250 m to 1000 m, and the depth of the bottom interface is randomly generated from 150 m to 400 m. The top interface of the hydrate is determined by the thickness of the hydrate reservoir. First, the maximum thickness of the hydrate layer is randomly generated. Then, several feature points are selected so that the thickness of the hydrate reservoir is the largest in the middle and gradually decreases to zero on both sides. The remaining values ​​are obtained by interpolation. In this embodiment, the maximum hydrate thickness hmax is randomly generated between 100 m and 250 m. The horizontal extension range of the hydrate reservoir is taken as [xmin, xmax]. The feature point selected in this embodiment is [xmin, 0.15*(xmax-xmin)+xmin, (xmin+xmax) / 2, 0.85*(xmax-xmin)+xmin, xmax], and the corresponding hydrate layer thickness is [0, 0.85*hmax, hmax, 0.85*hmax, 0]. Other values ​​are obtained through interpolation. Generally, a free gas layer exists below the hydrate layer. The generation method of the gas layer bottom interface is similar to that of the hydrate top interface, randomly generating a maximum thickness at the center and then gradually decreasing to zero towards both sides. In this embodiment, the maximum gas layer thickness is randomly generated between 100 m and 280 m, and the feature point selection method is consistent with that of the hydrate layer. Through this step, the bottom interface, top interface, and bottom interface of the free gas layer are determined.

[0158] Step 4: After calculating the interface between the hydrate layer and the free gas layer, the longitudinal wave velocity and Q value of the hydrate layer and gas layer with different occurrence types are calculated using formulas (1) to (12). First, the solid phase composition is still composed of 22% clay, 30% quartz, 20% muscovite, 20% calcite and 8% plagioclase. The porosity is randomly generated in the range of [0.3, 0.5], and the permeability is taken as 1 Darcy. The rock elastic parameters are calculated through the effective medium model. Then, for the hydrate layer, the pore fluid includes water and hydrate. The maximum hydrate saturation Shmax is randomly generated in the range of [0.3, 0.5]. Then, several feature points are selected proportionally in the depth direction. To ensure that the hydrate saturation gradually decreases with decreasing depth, let ymax be the ordinate of the bottom of the hydrate layer at any horizontal position, and h be the thickness. In this embodiment, the selected feature point is [ymax-h, ymax-0.8*h, ymax], and its corresponding hydrate saturation is [0.2*Shmax, 0.85*Shmax, Shmax]. Then, the velocity and Q value of the feature point of the hydrate layer are calculated using the White model, and the rest are obtained by interpolation. For the gas-bearing layer, the pore fluid includes water and gas. In this embodiment, the gas saturation is set to a fixed value of 0.05. Finally, the velocity and Q value of the gas-bearing layer are calculated using the White model.

[0159] Step 5: After determining the hydrate layer and general strata, normal faults are randomly generated with a certain probability. In this embodiment, the fault generation probability is 50%. First, the coordinates of the two intersection points between the fault plane and the model boundary are randomly determined. Then, the hanging wall of the fault is randomly moved downwards to a certain depth to complete the fault generation. Finally, through the above steps, a large number of hydrate-bearing viscosonic media models with different occurrence types and rock physics basis can be quickly generated in batches. Some of the generated models are shown below. Figure 4 , Figure 5 and Figure 6 As shown, the occurrence modes are particle contact, cementation, and suspension modes. It can be seen that the cementation mode has the highest hydrate layer velocity and Q value, while the suspension mode has the lowest. The generated viscoacoustic medium model can be used to study the seismic wave propagation characteristics, imaging, and seismic parameter inversion of various types of hydrate reservoirs.

[0160] Example 2 is only a method for constructing a viscoacoustic medium model containing a single hydrate reservoir. This invention can also conveniently generate more complex and diverse viscoacoustic medium models containing multiple hydrate reservoirs, different lithologies, and different numbers of faults, which are closer to reality. This will be specifically described in Example 3:

[0161] Example 3: Change the mineral composition of the formation, the thickness and saturation of hydrates, the number of hydrate layers and faults, the number of layers, etc.

[0162] Step 1: Randomly generate general stratigraphic interfaces. The model size is set to 1211×2011, and the spatial sampling interval in the x and z directions is 3 m. Eight stratigraphic interfaces are randomly generated using the sin(τ×π×xi / nx / dx+rand(1)*20)*9+0.02*xi function. The first interface is the seafloor interface, where τ∈[3,6] is a random number that controls the undulation of the stratigraphic interface, xi∈[3,6033] is the horizontal coordinate position, nx=2011 is the number of horizontal grid points, and dx=3 is the horizontal grid spacing. At the same time, to avoid the intersection of stratigraphic interfaces, the seafloor interface is controlled between 860 m and 1186 m. Within a depth range of m, the depths of the remaining layers are randomly generated within the ranges of [1206m, 1533m], [1553m, 1879m], [1899m, 2226m], [2246m, 2573m], [2593m, 2919m], [2939m, 3266m], and [3286m, 3613m].

[0163] Step 2: The velocity and quality factor of a general undulating stratum are calculated using the effective medium model and White theory. First, the solid phase mineral composition of each layer needs to be determined. The solid phase composition consists of 22% clay, 30% quartz, 20% muscovite, 20% calcite, and 8% plagioclase. The elastic parameters of each component are shown in Table 1. The porosity and permeability of each layer decrease with increasing layer depth. The porosity gradually decreases from 0.4 to 0.2 from the seabed to the maximum depth of the model, and the permeability gradually decreases from 1 Darcy to 0.5 Darcy. The layer depth is taken as the depth of the layer center. After determining the above basic rock parameters, the elastic parameters of the rock can be calculated using the effective medium model formulas (1) to (7), the solid phase mineral composition and the elastic parameters of each component, and the porosity parameter. Then, the P-wave velocity and Q value of the general undulating stratum are calculated using the White model formulas (8) to (12) combined with the elastic parameters of the rock, permeability, pore fluid, and the elastic parameters of each fluid component.

[0164] Step 3: Then, the hydrate layer and free gas layer are randomly generated. Since the bottom interface of the hydrate layer is consistent with the undulation of the corresponding seabed interface, a seabed interface of arbitrary horizontal length is randomly selected as the bottom interface of the hydrate. In this embodiment, the horizontal extension range of the hydrate layer is randomly generated from 195 m to 1900 m, and the depth of the bottom interface is randomly generated from 150 m to 600 m. The top interface of the hydrate is determined by the thickness of the hydrate reservoir. First, the maximum thickness of the hydrate layer is randomly generated. Then, several feature points are selected so that the thickness of the hydrate reservoir is the largest in the middle and gradually decreases to zero on both sides. The remaining values ​​are obtained by interpolation. In this embodiment, the maximum hydrate thickness hmax is randomly generated between 50 m and 150 m. The horizontal extension range of the hydrate reservoir is taken as [xmin, xmax]. The feature point selected in this embodiment is [xmin, 0.15*(xmax-xmin)+xmin, (xmin+xmax) / 2, 0.85*(xmax-xmin)+xmin, xmax], and the corresponding hydrate layer thickness is [0, 0.85*hmax, hmax, 0.85*hmax, 0]. Other values ​​are obtained through interpolation. Generally, a free gas layer exists below the hydrate layer. The generation method of the bottom interface of the gas layer is similar to that of the top interface of the hydrate layer, randomly generating a maximum thickness at the center, and then gradually decreasing to zero towards both sides. In this embodiment, the maximum thickness of the gas layer is randomly generated between 50 m and 150 m, and the feature point selection method is consistent with that of the hydrate layer. Through this step, the bottom interface, top interface of the hydrate-containing layer, and bottom interface of the free gas-containing layer are determined.

[0165] Step 4: After calculating the interface between the hydrate layer and the free gas layer, the longitudinal wave velocity and Q value of the hydrate layer and the gas layer are calculated using formulas (1) to (12). In this embodiment, it is assumed that the hydrate is in particle contact mode, and the solid phase composition is different from that of general sedimentary strata, consisting of 32% clay, 20% quartz, 20% muscovite, 20% calcite and 8% plagioclase. The porosity is randomly generated in the range of [0.2, 0.4], and the permeability is taken as 1 Darcy. The rock elastic parameters are calculated using the effective medium model. Then, for the hydrate layer, the pore fluid includes water and hydrate, and the maximum hydrate saturation Shmax is randomly generated in the range of [0.15, 0.35]. Then, in the depth direction, according to Several feature points are selected proportionally so that the hydrate saturation gradually decreases with decreasing depth. Let ymax be the ordinate of the bottom layer at any horizontal position in the hydrate layer, and h be the thickness. In this embodiment, the selected feature points are [ymax-h, ymax-0.8*h, ymax], and their corresponding hydrate saturation is [0.3*Shmax, 0.85*Shmax, Shmax]. Then, the velocity and Q-value of the feature points in the hydrate-bearing layer are calculated using the White model. The remaining values ​​are obtained through interpolation. For gas-bearing layers, the pore fluid includes water and gas. In this embodiment, the gas saturation is set to a fixed value of 0.05. Finally, the velocity and Q-value of the gas-bearing layer are calculated using the White model. Repeating steps three and four can generate a model containing multiple hydrate reservoirs simultaneously.

[0166] Step 5: After determining the hydrate layer and general strata, normal faults are randomly generated with a certain probability. In this embodiment, the fault generation probability is 80%. First, the coordinates of the two intersection points between the fault plane and the model boundary are randomly determined. Then, the hanging wall of the fault is randomly moved downwards to a certain depth to complete the fault generation. Repeating step 5 can generate multiple faults. Example 3 can quickly generate a large number of complex and diverse hydrate-bearing viscoacoustic media models with different lithologies, different numbers of faults, and multiple hydrate layers, which are closer to reality. Some of the generated models are shown below. Figure 7 As shown.

[0167] To make the scope of application of this invention clearer and more explicit, the following will be used as an example. Figure 4 Taking the model as an example, forward modeling can be performed on different generated hydrate models to analyze the seismic wavefield characteristics of hydrate layers with different saturation levels, lithologies, and occurrence types, especially the characteristics of the identification marker BSR. This analysis can guide the identification and characterization of hydrate-bearing reservoirs. Furthermore, this model can be used to study the influence of medium viscosity on the seismic wavefield characteristics and imaging quality of hydrate layers, such as... Figure 8 and Figure 9 They are respectively Figure 4The forward modeling and imaging results show that viscosity leads to a significant attenuation of seismic wave amplitude and a change in phase. This is reflected in the imaging results, where the BSR reflection amplitude and antipolarity characteristics at the hydrate bottom interface are not obvious. The attenuation compensation imaging results can significantly enhance the BSR amplitude and correct the phase.

[0168] Similarly, the large number of hydrate-bearing models generated in batches can serve as sample data for AI-based seismic parameter inversion. Since AI methods heavily rely on training samples, and obtaining high-precision parameter models based on actual seismic data is extremely difficult and expensive, network training typically involves pre-training the neural network using a theoretical model that closely approximates reality. The trained neural network can then be used for seismic parameter inversion. Subsequently, a small amount of actual seismic data can be used for transfer learning optimization of the network model, increasing its applicability to real-world data. Therefore, sample generation is a crucial step in neural network parameter inversion. This invention can conveniently provide a large number of training samples for hydrate reservoirs to the neural network. Using the 195 models generated by this invention as samples to train the neural network, and then using this network model to perform seismic parameter inversion on other hydrate models, the results are as follows: Figure 10 and Figure 11 As shown, the inversion results are basically consistent with the theoretical model, which demonstrates the richness and rationality of the constructed viscous acoustic medium model.

[0169] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0170] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0171] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0172] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0173] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for analyzing the velocity and attenuation characteristics of multi-type hydrate formations, characterized in that, include: S1: Obtain the elastic modulus of each mineral component of the rock; S2: Calculate the shear modulus and bulk modulus of the solid phase and skeleton of rocks with different mineral components, different porosities, different hydrate saturation and occurrence types based on the results of step S1. S3: Calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types based on the data obtained in step S2.

2. The method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations according to claim 1, characterized in that, The hydrate occurrence types include: particle contact mode, suspension mode, and cementation mode.

3. The method for analyzing the velocity and attenuation characteristics of multi-type hydrate-bearing formations according to claim 2, characterized in that, In step S2, Under the particle contact mode, the elastic moduli K and G of the solid phase without hydrates are corrected to obtain the elastic moduli of the solid phase of the hydrate-bearing formation as follows: Among them G h f is the shear modulus of the pure hydrate. h The volume fraction of hydrate can be calculated using the following formula: The density of the solid phase also changes to ρ due to the filling of hydrates. s '=f h ρ h +(1-f h )ρ s ; Under cementation mode, the elastic modulus K of the dry rock skeleton dry and G dry Calculations were performed based on the cementation theory of Dvorkin and Nur (1993a): Where S n and S τ These are values ​​related to cementation pressure and hydrate content.

4. The method for analyzing the velocity and attenuation characteristics of multiple types of hydrate-bearing formations according to claim 3, characterized in that, In step S3, by correcting the permeability in particle contact mode and cementation mode, and the fluid bulk modulus and viscosity coefficient in suspension mode, the formation velocity and quality factors for different lithologies, different porosities, different hydrate saturation and occurrence types are obtained.

5. A method for constructing a model of viscoacoustic media in multi-type hydrate-bearing formations, characterized in that, Includes the following steps: Step 1: Randomly generate undulating strata; Step 2: Calculate the formation velocity and quality factor of the undulating strata according to the multi-type hydrate formation velocity and attenuation characteristic analysis method according to any one of claims 1-4; Step 3: Randomly generate the hydrate bottom interface, top interface, and free gas layer bottom interface; Step 4: Calculate the formation velocity and quality factor of the hydrate layer and the free gas layer according to the multi-type hydrate-bearing formation velocity and attenuation characteristic analysis method according to any one of claims 1-4; Step 5: Randomly generate normal faults to obtain the viscous acoustic medium model.

6. The method for constructing a multi-type hydrate-bearing strata viscoacoustic medium model according to claim 5, characterized in that, In the first step, the grid size and sampling interval for the vertical and horizontal directions of the model are set, and then sin(τ×π×x) is used. i / n x / d x The function randomly generates multiple stratigraphic interfaces, where τ is a random number controlling the undulation of the stratigraphic interfaces, and x... i n represents the horizontal coordinate position of the grid point. x d represents the number of horizontal grid points. x The horizontal grid spacing is defined, where the first layer represents the seabed interface, and the depths of the remaining layers are randomly generated below the seabed.

7. A device for analyzing the velocity and attenuation characteristics of multi-type hydrate-bearing formations, characterized in that, include: The acquisition module is used to obtain the elastic modulus of each mineral component of the rock; The modulus calculation module is used to calculate the shear modulus and bulk modulus of rock solid phase and skeleton with different mineral components, different porosities, and different hydrate saturation and occurrence types based on the results data obtained by the acquisition module. The analysis module is used to calculate the formation velocity and quality factors for different lithologies, porosities, hydrate saturation, and occurrence types.

8. A device for constructing a model of viscoacoustic media in multi-type hydrate-bearing strata, characterized in that, include: The generation module is used to randomly generate undulating strata, as well as randomly generate the bottom interface, top interface, and bottom interface of the free gas layer. The calculation module is used to calculate the formation velocity and quality factor of the undulating formation according to the multi-type hydrate formation velocity and attenuation characteristic analysis method according to any one of claims 1-4; and to calculate the formation velocity and quality factor of the hydrate layer and the free gas layer according to the multi-type hydrate formation velocity and attenuation characteristic analysis method according to any one of claims 1-4. The model acquisition module is used to randomly generate normal faults to obtain a model of the viscous acoustic medium.

9. An electronic device, characterized in that, include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and when executed by the processor, the computer program implements the method of any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-4.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-4.

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