Shale rock physical modeling method, device, equipment, storage medium and product
By constructing a model of organic mineral mixtures including clay and kerogen, and combining it with boundary and DEM models, and taking into account fracture parameters, a more accurate shale petrophysical model was established. This solved the problem that existing models did not consider the orientation of clay minerals and the influence of pore fractures, and provided better support for seismic exploration and reservoir simulation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA NAT PETROLEUM CORP
- Filing Date
- 2024-12-30
- Publication Date
- 2026-06-30
AI Technical Summary
Existing shale petrophysical models fail to effectively account for the orientation of clay minerals and their impact on shale reservoirs, as well as the effects of porosity and fractures.
An anisotropic SCA model was used to establish an organic mineral mixture model containing clay and kerogen. By combining the boundary model, anisotropic DEM model and fracture model, a dry shale model with pores and fractures was constructed. The P-wave velocity was calculated by the fluid mixing model, and finally an anisotropic fluid substitution model was established.
A more accurate and realistic petrological model of shale reservoirs has been established, which can provide technical support for seismic forward/inverse modeling, seismically constrained reservoir numerical simulation, and time-shifted seismic analysis.
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Figure CN122307780A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of earthquake rock physical modeling technology, and in particular to a physical modeling method, apparatus, equipment, storage medium and product for shale rocks. Background Technology
[0002] Rock physics serves as a crucial link between seismic activity and reservoir engineering. Besides being influenced by excitation and reception conditions, seismic waves are also related to parameters such as rock velocity and density. These parameters are in turn closely related to rock composition, porosity, burial depth, pore fluid properties, pressure, strata heterogeneity, and other geological characteristics. Rock physics modeling attempts to establish a quantitative correspondence between physical quantities obtained from geophysical exploration and subsurface rock parameters using theoretical calculation methods.
[0003] Shale is characterized by low porosity and low permeability, and the content and directional arrangement of clay minerals are the main factors contributing to shale anisotropy. However, existing shale petrophysical models often fail to consider the orientation of clay minerals, treating them as isotropic media and neglecting the influence of porosity and fractures on shale reservoirs. Summary of the Invention
[0004] This invention provides a physical modeling method, apparatus, equipment, storage medium, and product for shale rocks, to address the problem that existing physical models of shale rocks do not consider the orientation of clay minerals and the influence of pores and fractures on shale reservoirs.
[0005] In a first aspect, embodiments of the present invention provide a physical modeling method for shale rocks, comprising:
[0006] An anisotropic SCA model was used to establish a model of an organic mineral mixture containing clay and kerogen.
[0007] A model of brittle mineral mixtures was established using the boundary model;
[0008] Using an anisotropic DEM model, a dry shale model containing pores is established based on the organic matter-mineral mixture model, the brittle mineral mixture model, and pore parameters.
[0009] Using the fracture model, a dry shale model containing pores and fractures is established based on the aforementioned dry shale model with pores and fracture parameters;
[0010] The longitudinal wave velocity of the mixed fluid is calculated based on the fluid characteristics using a fluid mixing model. An anisotropic fluid substitution model is then established based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity.
[0011] A physical model of shale rock is established based on the dry shale model containing pores and fractures using the anisotropic fluid replacement model.
[0012] Secondly, embodiments of the present invention provide a physical modeling apparatus for shale rocks, comprising:
[0013] The Organic Matter Mineral Mixture Model Building Module is used to build an organic matter mineral mixture model containing clay and kerogen using an anisotropic SCA model.
[0014] The brittle mineral mixture model building module is used to build brittle mineral mixture models using the boundary model;
[0015] A porous shale model building module is used to build a porous dry shale model based on the organic matter mineral mixture model, the brittle mineral mixture model, and pore parameters using an anisotropic DEM model.
[0016] A module for establishing a porous and fractured shale model is used to establish a porous and fractured dry shale model based on the porous dry shale model and fracture parameters using a fracture model.
[0017] The fluid replacement model establishment module is used to calculate the longitudinal wave velocity of the mixed fluid based on the fluid characteristics using the fluid mixing model, and to establish an anisotropic fluid replacement model based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity.
[0018] The shale physical model building module is used to build a physical model of shale rock based on the dry shale model containing pores and fractures using the anisotropic fluid replacement model.
[0019] Thirdly, embodiments of the present invention provide an electronic device, the electronic device comprising:
[0020] At least one processor; and
[0021] A memory communicatively connected to the at least one processor; wherein,
[0022] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the physical modeling method for shale rocks according to any embodiment of the present invention.
[0023] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the physical modeling method for shale rocks according to any embodiment of the present invention.
[0024] Fifthly, embodiments of the present invention provide a computer program product including a computer program that, when executed by a processor, implements the physical modeling method for shale rocks as described in any embodiment of the present invention.
[0025] The technical solution of this invention involves: establishing an organic matter-mineral mixture model including clay and kerogen using an anisotropic SCA model; establishing a brittle mineral mixture model using a boundary model; establishing a porous dry shale model using an anisotropic DEM model based on the organic matter-mineral mixture model, the brittle mineral mixture model, and pore parameters; establishing a porous and fractured dry shale model using a fracture model based on the porous dry shale model and fracture parameters; calculating the P-wave velocity of the mixed fluid using a fluid mixing model based on fluid characteristics, and establishing an anisotropic fluid substitution model based on the compliance matrix and P-wave velocity of the porous and fractured dry shale model; and establishing a physical model of the shale rock using the anisotropic fluid substitution model based on the porous and fractured dry shale model. Taking into account the directional arrangement of clay and kerogen and the anisotropy caused by fractures, a more realistic and accurate rock physics model for shale reservoirs is established. This solves the problem that existing shale rock physics models do not consider the orientation of clay minerals and the influence of pores and fractures on shale reservoirs. It can provide technical support for seismic forward / inverse modeling, seismically constrained reservoir numerical simulation, and time-lapse seismic analysis.
[0026] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description
[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0028] Figure 1 A flowchart illustrating a physical modeling method for shale rock according to Embodiment 1 of the present invention;
[0029] Figure 2 A flowchart illustrating another physical modeling method for shale rocks provided in an embodiment of the present invention;
[0030] Figure 3 This is a measured logging curve of a certain well;
[0031] Figure 4A comparison chart of measured well logging curves and calculation results from rock physics models;
[0032] Figure 5 This is a schematic diagram of the structure of a physical modeling device for shale rock provided in Embodiment 3 of the present invention;
[0033] Figure 6 A schematic diagram of the structure of an electronic device for implementing the physical modeling method for shale rocks according to embodiments of the present invention. Detailed Implementation
[0034] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0035] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0036] Example 1
[0037] Figure 1 This is a flowchart of a physical modeling method for shale rock according to Embodiment 1 of the present invention. This embodiment is applicable to the construction of physical models of shale rock. The method can be executed by a physical modeling device for shale rock, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:
[0038] S110. Use the anisotropic SCA model to establish a model of an organic mineral mixture containing clay and kerogen.
[0039] Organic matter-mineral mixtures refer to complexes formed by the interaction of organic matter and mineral particles in rocks. Service Component Architecture (SCA) is a simplified service-oriented architecture (SOA) programming / deployment model. Although the SCA model is primarily used in the field of software architecture, this invention borrows core concepts from the SCA model to construct an organic matter-mineral mixture model. In soil science, organic matter-mineral mixture models need to consider the interactions and assembly between organic matter and minerals. The assembly concept of the SCA model can be used to simulate the interactions between organic matter and minerals, where service components can represent organic matter or mineral components in rocks, and service assemblies can represent the combination and interactions of these components in rocks.
[0040] Specifically, clay and kerogen are interwoven within shale minerals. Kerogen exhibits significant differences in elastic parameters compared to other minerals; the elastic moduli of other minerals are relatively large, while kerogen's elastic modulus is small, very close to that of fluids. Furthermore, kerogen is embedded within clay minerals, and both clay and kerogen typically exhibit directional arrangement and distribution characteristics. Therefore, considering clay and kerogen separately, an anisotropic SCA model is used to simulate the interaction between organic matter and minerals, establishing a model of an organic matter-mineral mixture including clay and kerogen.
[0041] Optionally, the expression for utilizing the anisotropic SCA model is:
[0042]
[0043] Among them, G n Let I be the shape tensor of the nth phase, and C be the unit stiffness tensor. * Let C be the stiffness tensor of the background medium. n Let V be the stiffness tensor of the nth phase material. n G represents the volume fraction of the nth phase. P Let V be the shape tensor of the P-th phase material. P C is the volume fraction of the P-th phase material. P Let be the stiffness tensor of the P-th phase material.
[0044] S120. Establish a model of brittle mineral mixtures using the boundary model.
[0045] Brittle minerals refer to mixtures of minerals other than clay and kerogen, and may include quartz, pyrite, calcite, dolomite, and illite. The boundary model is a theoretical model used to predict the effective properties of composite materials. Based on variational principles, it provides boundaries for the effective bulk modulus and shear modulus of multiphase (macroscopically isotropic) composite materials.
[0046] Specifically, brittle minerals have a larger elastic modulus and are more brittle than clay and kerogen, and their elastic modulus is relatively similar. Therefore, brittle minerals are classified into a single class of minerals, and a boundary model is used to establish a separate brittle mineral mixture model for brittle minerals.
[0047] Optionally, the boundary boundary model is:
[0048]
[0049] Where: K + It is the upper limit of the equivalent bulk modulus of brittle mineral mixtures; μ + K1 is the upper limit of the equivalent shear modulus of the brittle mineral mixture, K2 is the bulk modulus of the first component, μ1 is the shear modulus of the first component, μ2 is the shear modulus of the second component, f1 is the volume fraction of the first component, and f2 is the volume fraction of the second component; K - It is the lower limit of the equivalent bulk modulus of brittle mineral mixtures, μ - K is the lower limit of the equivalent shear modulus of brittle mineral mixtures. HM Assuming the effective bulk modulus is an arrangement of identical spheres, μ HM Let φ be the shear modulus assuming an identical arrangement of spheres, and φ be the porosity. c Critical porosity.
[0050] For example, the physical elastic parameters of brittle minerals are shown in Table 1.
[0051] Table 1
[0052]
[0053] S130. Using an anisotropic DEM model, a porous dry shale model is established based on all organic-mineral mixture models, brittle mineral mixture models, and pore parameters.
[0054] Pore parameters can be understood as parameters used to represent the pores in rocks, such as porosity and pore aspect ratio, used to describe the spatial distribution and morphology of pores. Porosity can be understood as the proportion of the volume of rock not occupied by solid phase, and is usually used to describe the spatial distribution of pores. Pore aspect ratio can be understood as the ratio of the minor axis to the major axis of the pore, and is usually used to characterize the shape of the pore.
[0055] Anisotropic differential effective medium (DEM) models are physical models used to simulate the interactions between phases in multiphase media. In particular, in the field of rock physics, they are used to predict the elastic properties of rocks.
[0056] Specifically, using an anisotropic DEM model, a shale model is constructed based on an organic matter mineral mixture model and a brittle mineral mixture model. Porosity is then added to the shale model based on pore parameters to obtain a dry shale model containing pores.
[0057] S140. Using the fracture model, establish a dry shale model containing pores and fractures based on the dry shale model containing pores and fracture parameters.
[0058] Crack parameters can be understood as a series of physical quantities describing crack characteristics. Crack parameters may include crack aperture, size, orientation, spacing, density, crack aspect ratio, and crack elastic parameters. The crack model describes the macroscopic properties of the medium, considers the interactions between cracks, and is applicable to cracked media with arbitrary aspect ratios.
[0059] Specifically, using a fracture model, fractures are added to a porous dry shale model based on fracture parameters to obtain a dry shale model containing both porosity and fractures. The fracture model is used to construct an equivalent elastic modulus model of a transversely isotropic rock with a horizontal axis of symmetry within a fractured rock medium. The assumptions are: a transversely isotropic background medium; sparsely distributed ellipsoidal fractures; vertically oriented fractures; low fracture content; and arbitrary aspect ratios.
[0060] S140. Calculate the longitudinal wave velocity of the mixed fluid based on the fluid characteristics using a fluid mixing model, and establish an anisotropic fluid replacement model based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity.
[0061] The fluid mixing model is a mathematical model used to simulate multiphase flow, assuming that the phases reach equilibrium in a local region, and is applicable to various flow conditions. Fluid properties can include the fluid's pressure, temperature, and composition (such as gas, oil, and water). The anisotropic fluid replacement model is a mathematical model used to describe the fluid replacement process in anisotropic media.
[0062] Specifically, the P-wave velocity of the mixed fluid is calculated using a fluid mixing model based on the fluid's pressure and temperature characteristics. An anisotropic fluid substitution model is then established based on the compliance matrix of the aforementioned dry shale model containing pores and fractures and the calculated P-wave velocity.
[0063] Optionally, the expression for the fluid mixing model is:
[0064]
[0065] Where ρ is density, T is pressure, P is temperature, and V is the longitudinal wave velocity of the mixed fluid.
[0066] Optionally, the compliance matrix of the dry shale model containing pores and fractures is:
[0067]
[0068] Where, matrix C -1 Let C be the compliance matrix of the dry shale model. -1 Let C be the inverse of matrix C, where C is the stiffness matrix of the dry shale model containing pores and fractures. 11 C 13 C 33 C 44 and C 66 All of these are stiffness coefficients of the porous dry shale model.
[0069] S150. Using an anisotropic fluid substitution model, a physical model of shale rock is established based on a dry shale model containing pores and fractures.
[0070] Specifically, using an anisotropic fluid replacement model, the pores and fractures in the dry shale model containing pores and fractures are filled with mixed fluid to obtain a physical model of saturated fluid shale rock.
[0071] The technical solution of this invention establishes a model of an organic matter-mineral mixture including clay and kerogen using an anisotropic SCA model; establishes a brittle mineral mixture model using a boundary model; establishes a porous dry shale model using an anisotropic DEM model based on the organic matter-mineral mixture model, the brittle mineral mixture model, and pore parameters; establishes a porous and fractured dry shale model using a fracture model based on the porous dry shale model and fracture parameters; calculates the P-wave velocity of the mixed fluid using a fluid mixing model based on fluid characteristics, and establishes an anisotropic fluid substitution model based on the compliance matrix and P-wave velocity of the porous and fractured dry shale model; and establishes a physical model of shale rock using the anisotropic fluid substitution model based on the porous and fractured dry shale model. By comprehensively considering the directional arrangement of clay and kerogen and the anisotropy caused by fractures, a more realistic and accurate rock physics model for shale reservoirs is established, providing technical support for seismic forward / inverse modeling, seismically constrained reservoir numerical simulation, and time-lapse seismic analysis. As an optional embodiment of this application, S130, the step of establishing a porous dry shale model based on the organic matter mineral mixture model, the brittle mineral mixture model, and pore parameters using an anisotropic DEM model includes:
[0072] S131. Using the organic mineral mixture model as the background medium model, the brittle mineral mixture model is added to the background medium model using an anisotropic DEM model to obtain a shale background medium model without pores.
[0073] Among them, the background medium model refers to the model constructed in rock physics modeling that treats rocks as a homogenized medium composed of different minerals.
[0074] Specifically, an organic mineral mixture model containing clay and kerogen is used as the background medium model. The dispersion state of brittle minerals is simulated using a DEM model. The brittle mineral mixture model is used as an inclusion and added to the background medium using an anisotropic DEM model to obtain a shale background medium model without pores.
[0075] S132. Using an anisotropic DEM model, empty pores are added to the pore-free shale background medium model according to the pore parameters to obtain a dry shale model with pores; the pore parameters include: pore aspect ratio.
[0076] Specifically, considering that the pores in shale are mainly unconnected pores, an anisotropic DEM model is used to add empty pores without any fluid to the pore-free shale background medium model according to the pore aspect ratio. In this process, the elastic modulus of the empty pores is set to 0, thereby obtaining a dry shale model with pores.
[0077] Optionally, the expression for the anisotropic DEM model is:
[0078]
[0079] Among them, C * Let C be the stiffness tensor of the background medium. i Let C be the stiffness tensor of the i-th phase material, C′ be the Kelvin parameter matrix, and v i Let G be the volume fraction of the i-th phase, and G be the shape tensor of the inclusions.
[0080] In an optional embodiment, the porosity is obtained by inverting the logging data using a traversal search method with logging speed as a constraint.
[0081] Specifically, since the porosity of different formations is usually different, it is not advisable to set the porosity as a constant value in the rock physics modeling process. Therefore, the porosity is obtained by inverting the logging data using a traversal search method with logging speed as a constraint.
[0082] For example, an initial value for the pore aspect ratio is set, which can be determined within a reasonable search range based on the pore structure analysis of the core sample. The P-wave and S-wave velocities and elastic stiffness coefficients are calculated using the basic physical property parameters obtained from well logging interpretation and the rock physics model. The sum of the squares of the differences between the well-logged P-wave and S-wave velocities and the predicted P-wave and S-wave velocities is determined as the objective function, for example:
[0083]
[0084] Among them, V P V represents the longitudinal wave velocity in well logging. S V represents the shear wave velocity in well logging. PP V represents the predicted P-wave velocity. PS This indicates the predicted transverse wave velocity.
[0085] If the objective function does not meet the accuracy requirements, the loop returns to reassign the porosity until the objective function meets the accuracy requirements, at which point the loop exits and the calculation results are output. Alternatively, an improved simulated annealing method can be used to update the inversion parameters. This involves sequentially changing the model parameters using a hot bath algorithm and combining this with the Metropolis criterion to determine whether to accept the new parameters.
[0086] This embodiment effectively extracts the porosity aspect ratio from actual well logging data, providing important parameters for rock physics modeling and reservoir evaluation.
[0087] As an optional embodiment of this application, S140, the step of establishing a dry shale model containing pores and fractures based on the porous dry shale model and fracture parameters using a fracture model includes: using the fracture model, adding fractures to the porous dry shale model according to the fracture parameters to obtain a dry shale model containing pores and fractures; the fracture parameters include the fracture elastic modulus, and the fracture elastic modulus is set to 0.
[0088] Specifically, fractures are added to a porous dry shale model using a fracture model. During the fracture addition process, the elastic modulus of the fractures can be set to 0, thus obtaining a dry shale model containing both porosity and fractures. Pores and microfractures are the main reservoir spaces for shale oil.
[0089] In a specific example Figure 2 A flowchart of another physical modeling method for shale rocks provided in an embodiment of the present invention is shown below. Figure 2As shown, an anisotropic SCA model is used to establish an organic mineral mixture model containing clay and kerogen. A boundary model is used to establish a brittle mineral mixture model containing quartz, pyrite, calcite, dolomite, and illite. An anisotropic DEM model is used to establish a background medium model based on the organic mineral mixture model and the brittle mineral mixture model. Porosity is added to the background medium model to obtain a porous dry shale model. A fracture model is used to add fractures to the porous dry shale model to obtain a dry shale model containing both porosity and fractures. A fluid mixing model is used based on fluid characteristics. The P-wave velocity of the mixed fluid is calculated, and an anisotropic fluid substitution model is established based on the compliance matrix of the dry shale model containing pores and fractures and the P-wave velocity. The pores and fractures of the dry shale model containing pores and fractures are filled with mixed fluid using the fluid mixing model to obtain a physical model of saturated fluid shale rock. Taking into account the directional arrangement of clay and kerogen and the anisotropy caused by fractures, a more realistic and accurate rock physics model for shale reservoirs is established, which can provide technical support for seismic forward / inverse modeling, seismically constrained reservoir numerical simulation, and time-lapse seismic analysis.
[0090] Taking the shear wave prediction of a shale reservoir section in a certain well in a certain region as an example, Figure 3 This is a measured well logging curve for a certain well. For example... Figure 3 As shown, from left to right, the first channel is the depth channel; the second is the density channel; the third is the P-wave transit time; the fourth is the S-wave transit time; the fifth is the porosity; the sixth is the water saturation; and the seventh is the mineral content, including quartz, pyrite, calcite, dolomite, illite, and kerogen. The shale section of this well is 4096-4153 meters deep, and it generally exhibits logging response characteristics of high sonic transit time, high porosity, and low density. The minerals in the shale are mainly quartz and illite, with relatively less calcite and dolomite, and a small amount of pyrite intercalated.
[0091] Figure 4 This is a comparison between measured well logging curves and calculation results from rock physics models. For example... Figure 4 As shown in the figure, the black lines represent the P-wave and S-wave velocities measured by well logging, while the red curves represent the P-wave and S-wave velocities obtained from rock physics modeling. Since the inversion of the porosity aspect ratio during modeling uses the P-wave measured by well logging as a constraint, the P-wave velocities obtained from measurement and modeling are very close, almost identical. The error between the S-wave velocities obtained from well logging and modeling is small. The modeling results for both P-wave and S-wave are in good agreement with the well logging results, further demonstrating the applicability and rationality of the model presented in this paper.
[0092] Example 2
[0093] Figure 5This is a schematic diagram of a physical modeling device for shale rock provided in Embodiment 2 of the present invention. Figure 5 As shown, the device includes: an organic mineral mixture model building module 510, a brittle mineral mixture model building module 520, a porous shale model building module 530, a fractured shale model building module 540, a fluid replacement model building module 550, and a shale physical model building module 560; wherein,
[0094] Organic matter and mineral mixture model building module 510 is used to build an organic matter and mineral mixture model containing clay and kerogen using an anisotropic SCA model;
[0095] The brittle mineral mixture model building module 520 is used to build brittle mineral mixture models using the boundary model;
[0096] The porous shale model establishment module 530 is used to establish a porous dry shale model based on the organic matter mineral mixture model, the brittle mineral mixture model and pore parameters using an anisotropic DEM model.
[0097] The porous and fractured shale model establishment module 540 is used to establish a porous and fractured dry shale model based on the porous dry shale model and fracture parameters using the fracture model.
[0098] The fluid replacement model establishment module 550 is used to calculate the longitudinal wave velocity of the mixed fluid based on the fluid characteristics using the fluid mixing model, and to establish an anisotropic fluid replacement model based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity.
[0099] Shale physical model building module 560 is used to build a physical model of shale rock based on the dry shale model containing pores and fractures using the anisotropic fluid replacement model.
[0100] The technical solution of this invention involves: establishing an organic-mineral mixture model including clay and kerogen using an anisotropic SCA model; establishing a brittle mineral mixture model using a boundary model; establishing a porous dry shale model using an anisotropic DEM model based on the organic-mineral mixture model, the brittle mineral mixture model, and pore parameters; establishing a porous and fractured dry shale model using a fracture model based on the porous dry shale model and fracture parameters; calculating the P-wave velocity of the mixed fluid using a fluid mixing model based on fluid characteristics, and establishing an anisotropic fluid substitution model based on the compliance matrix and P-wave velocity of the porous and fractured dry shale model; and establishing a physical model of the shale rock using the anisotropic fluid substitution model based on the porous and fractured dry shale model. The boundary model comprehensively considers the directional arrangement of clay and kerogen and the anisotropy caused by fractures, establishing a more realistic and accurate rock physics model for shale reservoirs, which can provide technical support for seismic forward / inverse modeling, seismically constrained reservoir numerical simulation, and time-lapse seismic analysis.
[0101] Optionally, the expression for utilizing the anisotropic SCA model is:
[0102]
[0103] Among them, G n Let I be the shape tensor of the nth phase, and C be the unit stiffness tensor. * Let C be the stiffness tensor of the background medium. n Let V be the stiffness tensor of the nth phase material. n G represents the volume fraction of the nth phase. P V is the shape tensor of the P-th phase material. P C is the volume fraction of the P-th phase material. P Let be the stiffness tensor of the P-th phase material.
[0104] Optionally, the boundary model is:
[0105]
[0106] Where: K + It is the upper limit of the equivalent bulk modulus of brittle mineral mixtures; μ + K1 is the upper limit of the equivalent shear modulus of the brittle mineral mixture, K2 is the bulk modulus of the first component, μ1 is the shear modulus of the first component, μ2 is the shear modulus of the second component, f1 is the volume fraction of the first component, and f2 is the volume fraction of the second component; K - It is the lower limit of the equivalent bulk modulus of brittle mineral mixtures, μ - K is the lower limit of the equivalent shear modulus of brittle mineral mixtures.HM Assuming the effective bulk modulus is an arrangement of identical spheres, μ HM Let φ be the shear modulus assuming an identical arrangement of spheres, and φ be the porosity. c Critical porosity.
[0107] Optionally, the porous shale model building module 530 is specifically used for:
[0108] The organic matter mineral mixture model is used as the background medium model. The brittle mineral mixture model is added to the background medium model using an anisotropic DEM model to obtain a shale background medium model without pores.
[0109] Using an anisotropic DEM model, empty pores are added to the pore-free shale background medium model according to the pore parameters to obtain a dry shale model with pores; the pore parameters include: pore aspect ratio;
[0110] The expression for the anisotropic DEM model is:
[0111]
[0112] Among them, C * It is the stiffness tensor of the background medium, C i Let C be the stiffness tensor of the i-th phase material, C′ be the Kelvin parameter matrix, and v i Let G be the volume fraction of the i-th phase, and G be the tensor of the inclusions.
[0113] Optionally, the expression for the fluid mixing model is:
[0114]
[0115] Where ρ is density, T is pressure, P is temperature, and V is the longitudinal wave velocity of the mixed fluid.
[0116] Optionally, the compliance matrix of the dry shale model containing pores and fractures is:
[0117]
[0118] Where, matrix C -1 Let C be the compliance matrix of the dry shale model. -1 Let C be the inverse of matrix C, where C is the stiffness matrix of the dry shale model containing pores and fractures. 11 C 13 C 33 C 44 and C 66 All of these are stiffness coefficients of the porous dry shale model.
[0119] The physical modeling device for shale rocks provided in this embodiment of the invention can execute the physical modeling method for shale rocks provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.
[0120] Example 3
[0121] Figure 6 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.
[0122] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0123] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0124] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as physical modeling methods for shale rocks.
[0125] In some embodiments, the physical modeling method for shale rocks may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the physical modeling method for shale rocks described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the physical modeling method for shale rocks by any other suitable means (e.g., by means of firmware).
[0126] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0127] In some embodiments, the physical modeling method for shale rock can be implemented as a computer program, which is implicitly included in a computer program product. When executed by a processor, the computer program implements the physical modeling method for shale rock of the present invention. The computer program product can be understood as a software product that primarily implements its solution through a computer program. The computer program used to implement the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0128] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0129] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0130] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.
[0131] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.
[0132] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.
[0133] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.
Claims
1. A method of physical modeling of a shale rock, characterized in that, include: An anisotropic SCA model was used to establish a model of an organic mineral mixture containing clay and kerogen; A model of brittle mineral mixtures was established using the boundary model; Using an anisotropic DEM model, a dry shale model containing pores is established based on the organic matter-mineral mixture model, the brittle mineral mixture model, and pore parameters. Using the fracture model, a dry shale model containing pores and fractures is established based on the aforementioned dry shale model containing pores and fracture parameters; The longitudinal wave velocity of the mixed fluid is calculated based on the fluid characteristics using a fluid mixing model. An anisotropic fluid substitution model is then established based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity. A physical model of shale rock is established based on the dry shale model containing pores and fractures using the anisotropic fluid replacement model.
2. The method of physical modeling of shale rock according to claim 1, characterized in that, The expression for the anisotropic SCA model is as follows: where G n is the shape tensor of the nth phase material, G P is the shape tensor of the Pth phase material, I is the identity tensor, C * is the stiffness tensor of the background medium, C n is the stiffness tensor of the nth phase material, V n is the volume fraction of the nth phase material, V P is the volume fraction of the Pth phase material, C P is the stiffness tensor of the Pth phase material.
3. The method of physical modeling of shale rock according to claim 1, characterized in that, The boundary model is as follows: In the formula: K + It is the upper limit of the equivalent bulk modulus of brittle mineral mixtures; μ + K1 is the upper limit of the equivalent shear modulus of the brittle mineral mixture, K2 is the bulk modulus of the first component, μ1 is the shear modulus of the first component, μ2 is the shear modulus of the second component, f1 is the volume fraction of the first component, and f2 is the volume fraction of the second component; K - It is the lower limit of the equivalent bulk modulus of brittle mineral mixtures, μ - K is the lower limit of the equivalent shear modulus of brittle mineral mixtures. HM Assuming the effective bulk modulus is an arrangement of identical spheres, μ HM Let φ be the shear modulus assuming an identical arrangement of spheres, and φ be the porosity. c Critical porosity.
4. The method of physical modeling of shale rocks according to claim 1, characterized in that, The step of establishing a porous dry shale model using an anisotropic DEM model based on the organic matter-mineral mixture model, the brittle mineral mixture model, and pore parameters includes: The organic matter mineral mixture model is used as the background medium model. The brittle mineral mixture model is added to the background medium model using an anisotropic DEM model to obtain a shale background medium model without pores. Using an anisotropic DEM model, empty pores are added to the pore-free shale background medium model according to the pore parameters to obtain a dry shale model with pores; the pore parameters include: pore aspect ratio; The expression for the anisotropic DEM model is: where C * is the stiffness tensor of the background medium, C i is the stiffness tensor of the i-th phase material, C' is the Kelvin parameter matrix, v i is the volume fraction of the i-th phase material, and G is the shape tensor of the inclusion.
5. The method of physical modeling of shale rocks according to claim 1, characterized in that, The expression for the fluid mixing model is: Where ρ is density, T is pressure, P is temperature, and V is the longitudinal wave velocity of the mixed fluid.
6. The method of physical modeling of shale rocks according to claim 1, characterized in that, The compliance matrix of the dry shale model containing pores and fractures is: wherein matrix C -1 is the compliance matrix of the dry shale model, matrix C -1 is the inverse matrix of matrix C, matrix C is the stiffness matrix of the dry shale model with pores and fractures, C 11 , C 13 , C 33 , C 44 and C 66 are the stiffness coefficients of the dry shale model with pores.
7. A device for physical modeling of shale rock, characterized by include: The Organic Matter Mineral Mixture Model Building Module is used to build an organic matter mineral mixture model containing clay and kerogen using an anisotropic SCA model. The brittle mineral mixture model building module is used to build brittle mineral mixture models using the boundary model; A porous shale model building module is used to build a porous dry shale model based on the organic matter mineral mixture model, the brittle mineral mixture model, and pore parameters using an anisotropic DEM model. A module for establishing a porous and fractured shale model is used to establish a porous and fractured dry shale model based on the porous dry shale model and fracture parameters using a fracture model. The fluid replacement model establishment module is used to calculate the longitudinal wave velocity of the mixed fluid based on the fluid characteristics using the fluid mixing model, and to establish an anisotropic fluid replacement model based on the compliance matrix of the dry shale model containing pores and fractures and the longitudinal wave velocity. The shale physical model building module is used to build a physical model of shale rock based on the dry shale model containing pores and fractures using the anisotropic fluid replacement model.
8. An electronic device, comprising: The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the physical modeling method for shale rock according to any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the physical modeling method for shale rock as described in any one of claims 1-6.
10. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by a processor, implements the physical modeling method for shale rock according to any one of claims 1-6.