CN112379416A - Method and device for predicting transverse wave through coal rock physical modeling and electronic equipment - Google Patents
Method and device for predicting transverse wave through coal rock physical modeling and electronic equipment Download PDFInfo
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Abstract
The embodiment of the invention discloses a method, a device and electronic equipment for predicting transverse waves by physical modeling of coal rocks, wherein the method comprises the following steps: determining the content of inorganic components and the content of solid phases in organic components according to the coring analysis test result data of target coal, establishing an inorganic component framework model according to the content of the inorganic components, and obtaining an elastic model of a coal-rock framework mixture according to the inorganic component framework model and the content of the solid phases; determining the pore diameters of pores and fractures of the target coal; adding the void and the crack into the elastic model of the coal-rock skeleton mixture to obtain a dry coal-rock physical model; establishing a fluid rock physical model according to the mass ratio of mobile phase low-molecular organic matters, water and free gas in target coal; and obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and further predicting the transverse wave velocity of the target coal. The mineral framework of the invention accords with the actual situation of the coal bed, and the accuracy of the transverse wave prediction result is superior to that of other models.
Description
Technical Field
The embodiment of the invention relates to the field of seismic exploration, in particular to a method and a device for predicting transverse waves through coal rock physical modeling and electronic equipment.
Background
With the development of seismic exploration and the advancement of hydraulic fracturing technology, coal bed gas has entered a large-scale commercial exploitation stage as one of the most prominent unconventional energy sources. China has rich coal bed gas resources, and the total amount of the resources is about 32 x 1012Cubic meter. The resource amount is equivalent to that of the conventional natural gas. Along with the exploration and development of the coal bed gas; the method has the advantages that pre-stack seismic data are utilized to predict coal rock elastic mechanical parameters and identify a coal bed gas dessert area, and guidance suggestions and the like are provided for ensuring the stability of a well wall and a hydraulic fracturing scheme for coal bed gas drilling in the later period more and more common. A bridge for evaluating seismic data and coal-rock comprehensive geology-oil deposit is built by utilizing a rock physical modeling technology, and plays an increasingly important role.
The rock physical modeling mainly comprises two modes, the first mode is empirical formula modeling, the modeling mode is simple, statistical analysis is mainly carried out on regional measured data, a regression equation is adopted to obtain a regional empirical index, and a functional relation among longitudinal wave velocity, transverse wave velocity and density is further built. The Castagna formula, the Han formula, the ganli lamp formula and the like are well known at home and abroad. This modeling method, while simple and useful, does not reveal the relationship between the elastic parameters and the diagenetic minerals, pore structure, fluid properties. The second rock modeling method is theoretical modeling, and the method mainly obtains a rock physical model with universality by constructing corresponding equations through different elastic parameters of diagenetic minerals, pore structures and fluid properties; further, the built-in relation between the longitudinal wave velocity, the transverse wave velocity and the density is cleared, and the famous theoretical models at home and abroad include a Voigt-reus-Hill model, a Hashin-Shtrikman model, a Wood model, a Wyllie model, a Gassmann model, a Biot model, a Bisq model, a Korrinaga model, a Kuster-Toksoz model, a Berryman model, an Xu-White model, an Xu-Payne model, a Hertz model and the like, and the models are mainly used for conventional oil and gas reservoirs; the primary suitable formations are also conventional clastic and carbonate rock. Not applicable to coal rock reservoirs.
Disclosure of Invention
The embodiment of the invention aims to provide a method, a device and electronic equipment for predicting transverse waves in coal rock physical modeling, which are used for solving the problem that the existing rock physical modeling cannot accurately reflect coal rock characteristics.
In order to achieve the above object, the embodiments of the present invention mainly provide the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for predicting transverse waves through coal rock physical modeling, including: determining the content of inorganic components and the content of solid phases in organic components according to the coring analysis test result data of target coal, establishing an inorganic component framework model according to the content of the inorganic components, and obtaining an elastic model of a coal-rock framework mixture according to the inorganic component framework model and the content of the solid phases; determining the porosity of the target coal by a method combining a mercury intrusion method and well logging interpretation, carrying out quantitative analysis on the geometric shape of coal rock pores by an electron microscope scanning method, and obtaining the pore diameters of pores and fractures of the target coal according to an equivalent principle; adding empty pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters and the fractures of the target coal, and obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model; establishing a fluid rock physical model according to the mass ratio of the mobile phase low-molecular organic matter, water and free gas in the target coal; and obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predicting the transverse wave velocity of the target coal according to the coal rock physical model.
According to an embodiment of the present invention, obtaining an elastic model of a coal-rock skeleton mixture based on the inorganic component skeleton model and the solid phase content includes: calculating the elastic modulus of the solid phase content by using an empirical formula, wherein the empirical formula is as follows:
Eog＝aVmic+bImic+cV+dI+eAad+f
wherein E isogIs the modulus of elasticity, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadThe content of organic ash is shown, and a, b, c, d, e and f are fitting coefficients;
and obtaining an elastic model of the coal-rock skeleton mixture according to the elastic modulus and the inorganic component skeleton model.
According to one embodiment of the invention, the equivalent principle comprises: defining the aperture aspect ratio within the range of 0.8-0.2 as an ellipsoid hole, defining the aperture aspect ratio within the range of 0.2-0.01 as a coin-shaped crack hole, defining the aperture aspect ratio within the range of 0.01-0.001 as a micro-crack hole, and carrying out distribution calculation on the pores beyond the aperture aspect ratio according to the principle of near.
According to one embodiment of the invention, the establishment of the fluid petrophysical model according to the mass ratio of the mobile phase low molecular organic matter, water and free gas in the target coal comprises:
and obtaining a fluid rock physical model by adopting a Brie fluid empirical model according to the mass ratio of mobile phase low-molecular-weight organic matters, water and free gas in the target coal, wherein the Brie fluid empirical model is used for calculating the following:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
According to one embodiment of the invention, obtaining a coal petrophysical model from the dry coal petrophysical model and the fluid petrophysical model comprises: and fusing the dry coal rock physical model and the fluid rock physical model by adopting a Brown-Korrina fluid replacement model to obtain the coal rock physical model.
In a second aspect, an embodiment of the present invention further provides a coal petrophysical modeling transverse wave prediction apparatus, including: the acquisition module is used for acquiring coring analysis and test result data of target coal; the control processing module is used for determining the content of inorganic components and the content of solid phases in organic components according to the coring analysis and assay result data of the target coal, establishing an inorganic component framework model according to the content of the inorganic components, and obtaining an elastic model of a coal-rock framework mixture according to the inorganic component framework model and the content of the solid phases; the control processing module is also used for determining the porosity of the target coal by adopting a method of combining a mercury intrusion method and well logging interpretation, carrying out quantitative analysis on the geometric shape of coal rock pores by adopting an electron microscope scanning method, and obtaining the pore diameters of pores and fractures of the target coal according to an equivalent principle; the control processing module is also used for adding hollow pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters of the pores and the fractures of the target coal, obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model, and establishing a fluid rock physical model according to the mass ratio of mobile phase low-molecular organic matters, water and free gas in the target coal; the control processing module is further used for obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predicting the transverse wave velocity of the target coal according to the coal rock physical model; and the output module is used for outputting the transverse wave velocity of the target coal.
According to one embodiment of the invention, the control processing module is configured to calculate the modulus of elasticity of the solid phase content using an empirical formula:
Eog＝aVmic+bImic+cV+dI+eAad+f
wherein E isogIs the modulus of elasticity, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadThe content of organic ash is shown, and a, b, c, d, e and f are fitting coefficients;
the control processing module is further used for obtaining an elastic model of the coal-rock skeleton mixture according to the elastic modulus and the inorganic component skeleton model.
According to one embodiment of the invention, the control processing module is used for obtaining a fluid petrophysical model by using a Brie fluid empirical model according to the mass ratio of mobile phase low molecular organic matters, water and free gas in the target coal, wherein the Brie fluid empirical model performs the following calculation:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: at least one processor and at least one memory; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method for predicting shear waves in coal petrophysical modeling according to the first aspect.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium containing one or more program instructions for being executed with the method for predicting shear waves by coal petrophysical modeling according to the first aspect.
The technical scheme provided by the embodiment of the invention at least has the following advantages:
according to the method, the device and the electronic equipment for predicting the transverse wave of the coal rock physical modeling, the elastic parameters of the coal rock physical modeling are fused into the crystal mineral framework by adopting the coal bed two-phase model and the empirical formula, the method is more consistent with the actual situation of the coal bed, the anisotropic fluid replacement method adopted in fluid replacement is better than the Gassmann fluid replacement method, and the precision of the transverse wave prediction result is better than that of other models.
Drawings
FIG. 1 is a flowchart of a method for predicting transverse waves through coal rock physical modeling according to an embodiment of the invention.
FIG. 2 is a cross-sectional diagram of the measured results and the predicted results of the longitudinal and transverse wave velocities of the coal seam.
Fig. 3 is a structural block diagram of a coal rock physical modeling shear wave prediction device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure.
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
FIG. 1 is a flowchart of a method for predicting transverse waves through coal rock physical modeling according to an embodiment of the invention. As shown in fig. 1, a method for predicting transverse waves through coal rock physical modeling according to an embodiment of the present invention includes:
s1: and determining the content of the inorganic component and the content of the solid phase in the organic component according to the coring analysis test result data of the target coal. And establishing an inorganic component framework model according to the content of the inorganic component, and obtaining an elastic model of the coal-rock framework mixture according to the inorganic component framework model and the content of the solid phase.
Specifically, coring analysis and assay are carried out on target coal, inorganic components and organic components of coal rock are separated according to coring analysis and assay result data of the target coal, the content of the inorganic components is determined by combining an electrical measurement interpretation curve, and a Reuss-Voigt-Hill model formula (1) is adopted to establish an inorganic component skeleton model:
wherein, KReussElastic modulus, K, representing the Reuss modelVoigtExpressing the elastic modulus of the Voigt model, Fi expressing the percentage of the ith mineral in the total mineral, Ki expressing the elastic modulus of the ith mineral, Ks expressing the elastic modulus of the mineral model with an inorganic framework, and KVRHRepresents the arithmetic mean of the Reuss model and the Voigt model.
The elastic modulus of the organic components in the target coal is calculated by adopting an empirical formula (2):
Eog＝aVmic+bImic+cV+dI+eAad+ f formula (2)
Wherein, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadAnd a, b, c, d, e and f are fitting coefficients.
And obtaining the elastic model of the coal-rock skeleton mixture by adopting an anisotropic DEM integration method according to the elastic modulus and the inorganic component skeleton model.
S2: the porosity of the target coal is determined by a method combining a mercury intrusion method and well logging interpretation, the geometric shape of the pores of the coal rock is quantitatively analyzed by an electron microscope scanning method, and the pore diameters of the pores and fractures of the target coal are obtained according to an equivalent principle.
Specifically, Mercury Intrusion Porosimetry (MIP), also known as Mercury porosimetry. Is a method for determining the pore size distribution of partially mesoporous and macroporous pores.
The core of the well logging interpretation is to determine the applied relation between the well logging information and the geological information and to process the well logging information into the geological information by adopting a correct method.
The method of mercury intrusion method and well logging interpretation are combined to determine the porosity of the target coal, and are methods well-known to those skilled in the art.
The scanning method of the electron microscope is a method for analyzing the structure and the performance of a sample by using the scanning electron microscope. The geometrical shape of the coal rock pore can be quantitatively analyzed by an electron microscope scanning method, and the pore diameters of the pore and the fracture of the target coal are obtained according to an equivalent principle.
In one embodiment of the invention, the equivalence principle comprises: defining the aperture aspect ratio within the range of 0.8-0.2 as an ellipsoid hole, defining the aperture aspect ratio within the range of 0.2-0.01 as a coin-shaped crack hole, defining the aperture aspect ratio within the range of 0.01-0.001 as a micro-crack hole, and carrying out distribution calculation on the pores beyond the aperture aspect ratio according to the principle of near.
S3: and adding empty pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters and the fractures of the target coal, and obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model.
Specifically, the pore diameter ratio in step S3 is subjected to monto-carlo random simulation, and the pore diameter ratios of different types in step S2 are determined with the maximum a posteriori probability, which is the ratio used in the final calculation. And then adding the void pores and the fractures into the elastic model of the coal-rock skeleton mixture, and obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model.
S4: and establishing a fluid rock physical model according to the mass ratio of the mobile phase low-molecular organic matter, water and free gas in the target coal.
Specifically, because the coal seam has high porosity-low permeability characteristics and poor connectivity, a fluid petrophysical model is obtained by adopting a Brie fluid empirical model according to the mass ratio of mobile phase low molecular organic matters, water and free gas in target coal, wherein the Brie fluid empirical model performs the following calculation:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
S5: and obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predicting the transverse wave velocity of the target coal according to the coal rock physical model.
Specifically, the fluid modulus obtained in the step S4 is added into the dry coal rock physical model by adopting a Brown-Korrina equation to obtain a coal rock elastic parameter model of the saturated fluid, and the model is obtained according to the longitudinal wave velocity VpTransverse wave velocity VsThe relation with the elastic modulus can be calculated by the formulas (4) and (5) to obtain the longitudinal and transverse directions of the coal rockWave velocity:
where K is the bulk modulus, μ is the shear modulus, and ρ is the density.
FIG. 2 is a cross-sectional diagram of the measured results and the predicted results of the longitudinal and transverse wave velocities of the coal seam. In fig. 2, the left first measured compressional wave is intersected with the prediction result of the Xu-White model, the left second measured compressional wave is intersected with the prediction result of the Xu-Payne model, the left three measured compressional waves are intersected with the prediction result of the model, the right first measured shear wave is intersected with the prediction result of the Xu-White model, the right second measured shear wave is intersected with the prediction result of the Xu-Payne model, and the right three measured shear waves are intersected with the prediction result of the model. As can be seen from FIG. 2, the transverse wave prediction result of the invention is superior to other model prediction results.
According to the method for predicting transverse waves through coal rock physical modeling, which is provided by the embodiment of the invention, the elastic parameters of the coal rock physical modeling are fused into the crystal mineral framework by adopting a coal bed two-phase model and an empirical formula, so that the method is more consistent with the actual situation of a coal bed, the method for replacing the fluid by adopting the anisotropic fluid is also superior to the Gassmann fluid replacement method, and the precision of the transverse wave prediction result is superior to that of other models.
Fig. 3 is a structural block diagram of a coal rock physical modeling shear wave prediction device according to an embodiment of the present invention. As shown in fig. 3, the coal rock physical modeling transverse wave prediction device according to the embodiment of the present invention includes: an acquisition module 100, a control processing module 200 and an output module 300.
The obtaining module 100 is configured to obtain coring analysis test result data of target coal. The control processing module 200 is used for determining the inorganic component content and the solid phase content in the organic component according to the coring analysis and assay result data of the target coal, establishing an inorganic component framework model according to the inorganic component content, and obtaining an elastic model of the coal-rock framework mixture according to the inorganic component framework model and the solid phase content. The control processing module 200 is further configured to determine the porosity of the target coal by a method combining a mercury intrusion method and well logging interpretation, quantitatively analyze the geometric shape of the pores of the coal rock by an electron microscope scanning method, and obtain the pore diameters of the pores and fractures of the target coal according to an equivalent principle. The control processing module 200 is further configured to add empty pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters of the pores and fractures of the target coal, obtain a dry coal-rock physical model by using an anisotropic DEM integral model, and establish a fluid rock physical model according to the mass ratio of mobile phase low-molecular organic matter, water and free gas in the target coal. The control processing module 200 is further configured to obtain a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predict the transverse wave velocity of the target coal according to the coal rock physical model. The output module 300 is used for outputting the target coal shear wave velocity.
In one embodiment of the present invention, the control processing module 200 is configured to calculate the modulus of elasticity for the solid phase content using the empirical formula:
Eog＝aVmic+bImic+cV+dI+eAad+f
wherein E isogIs modulus of elasticity, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadAnd a, b, c, d, e and f are fitting coefficients.
The control processing module 200 is further configured to obtain an elastic model of the coal-rock skeleton mixture according to the elastic modulus and the inorganic component skeleton model.
In one embodiment of the present invention, the control processing module 200 is configured to obtain a fluid petrophysical model by using a Brie fluid empirical model according to the mass ratio of mobile phase low molecular organics, water and free gas in target coal, wherein the Brie fluid empirical model performs the following calculation:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
It should be noted that a specific implementation manner of the device for predicting transverse waves through coal-rock physical modeling in the embodiment of the present invention is similar to a specific implementation manner of the method for predicting transverse waves through coal-rock physical modeling in the embodiment of the present invention, and specific reference is specifically made to the description of the method for predicting transverse waves through coal-rock physical modeling, and details are not repeated for reducing redundancy.
In addition, other structures and functions of the coal rock physical modeling transverse wave prediction device in the embodiment of the invention are known to those skilled in the art, and are not described in detail in order to reduce redundancy.
An embodiment of the present invention further provides an electronic device, including: at least one processor and at least one memory; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method for predicting shear waves in coal petrophysical modeling according to the first aspect.
The disclosed embodiments of the present invention provide a computer-readable storage medium having stored therein computer program instructions, which, when run on a computer, cause the computer to execute the above-mentioned coal rock physical modeling shear wave prediction method.
In an embodiment of the invention, the processor may be an integrated circuit chip having signal processing capability. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The processor reads the information in the storage medium and completes the steps of the method in combination with the hardware.
The storage medium may be a memory, for example, which may be volatile memory or nonvolatile memory, or which may include both volatile and nonvolatile memory.
The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory.
The volatile Memory may be a Random Access Memory (RAM) which serves as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (ddr Data Rate SDRAM), Enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).
The storage media described in connection with the embodiments of the invention are intended to comprise, without being limited to, these and any other suitable types of memory.
Those skilled in the art will appreciate that the functionality described in the present invention may be implemented in a combination of hardware and software in one or more of the examples described above. When software is applied, the corresponding functionality may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for predicting transverse waves through coal rock physical modeling is characterized by comprising the following steps:
determining the content of inorganic components and the content of solid phases in organic components according to the coring analysis test result data of target coal, establishing an inorganic component framework model according to the content of the inorganic components, and obtaining an elastic model of a coal-rock framework mixture according to the inorganic component framework model and the content of the solid phases;
determining the porosity of the target coal by a method combining a mercury intrusion method and well logging interpretation, carrying out quantitative analysis on the geometric shape of coal rock pores by an electron microscope scanning method, and obtaining the pore diameters of pores and fractures of the target coal according to an equivalent principle;
adding empty pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters and the fractures of the target coal, and obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model;
establishing a fluid rock physical model according to the mass ratio of the mobile phase low-molecular organic matter, water and free gas in the target coal;
and obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predicting the transverse wave velocity of the target coal according to the coal rock physical model.
2. The method for predicting transverse waves through coal rock physical modeling according to claim 1, wherein obtaining an elastic model of a coal rock skeleton mixture according to the inorganic component skeleton model and the solid phase content comprises:
calculating the elastic modulus of the solid phase content by using an empirical formula, wherein the empirical formula is as follows:
Eog＝aVmic+bImic+cV+dI+eAad+f
wherein E isogIs the modulus of elasticity, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadThe content of organic ash is shown, and a, b, c, d, e and f are fitting coefficients;
and obtaining an elastic model of the coal-rock skeleton mixture according to the elastic modulus and the inorganic component skeleton model.
3. The method for predicting transverse waves through coal petrophysical modeling according to claim 1, wherein the equivalence principle comprises: defining the aperture aspect ratio within the range of 0.8-0.2 as an ellipsoid hole, defining the aperture aspect ratio within the range of 0.2-0.01 as a coin-shaped crack hole, defining the aperture aspect ratio within the range of 0.01-0.001 as a micro-crack hole, and carrying out distribution calculation on the pores beyond the aperture aspect ratio according to the principle of near.
4. The method for predicting transverse waves through coal rock petrophysical modeling according to claim 1, wherein the establishing of the fluid petrophysical model according to the mass ratio of mobile phase low molecular organic matter, water and free gas in the target coal comprises the following steps:
and obtaining a fluid rock physical model by adopting a Brie fluid empirical model according to the mass ratio of mobile phase low-molecular-weight organic matters, water and free gas in the target coal, wherein the Brie fluid empirical model is used for calculating the following:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
5. The method for predicting transverse waves through coal petrophysical modeling according to claim 1, wherein obtaining a coal petrophysical model from the dry coal petrophysical model and the fluid petrophysical model comprises:
and fusing the dry coal rock physical model and the fluid rock physical model by adopting a Brown-Korrina fluid replacement model to obtain the coal rock physical model.
6. The utility model provides a coal petrography physical modeling prediction shear wave device which characterized in that includes:
the acquisition module is used for acquiring coring analysis and test result data of target coal;
the control processing module is used for determining the content of inorganic components and the content of solid phases in organic components according to the coring analysis and assay result data of the target coal, establishing an inorganic component framework model according to the content of the inorganic components, and obtaining an elastic model of a coal-rock framework mixture according to the inorganic component framework model and the content of the solid phases; the control processing module is also used for determining the porosity of the target coal by adopting a method of combining a mercury intrusion method and well logging interpretation, carrying out quantitative analysis on the geometric shape of coal rock pores by adopting an electron microscope scanning method, and obtaining the pore diameters of pores and fractures of the target coal according to an equivalent principle; the control processing module is also used for adding hollow pores and fractures into the elastic model of the coal-rock skeleton mixture according to the pore diameters of the pores and the fractures of the target coal, obtaining a dry coal-rock physical model by adopting an anisotropic DEM integral model, and establishing a fluid rock physical model according to the mass ratio of mobile phase low-molecular organic matters, water and free gas in the target coal; the control processing module is further used for obtaining a coal rock physical model according to the dry coal rock physical model and the fluid rock physical model, and predicting the transverse wave velocity of the target coal according to the coal rock physical model;
and the output module is used for outputting the transverse wave velocity of the target coal.
7. The coal rock petrophysical modeling prediction shear wave device of claim 6, wherein the control processing module is configured to calculate the elastic modulus of the solid phase content using an empirical formula, the empirical formula being:
Eog＝aVmic+bImic+cV+dI+eAad+f
wherein E isogIs the modulus of elasticity, VmicContent% of Microspecular coal, ImicIs the content of inert coal, V is the content of vitrinite, I is the content of inert aggregate, AadThe content of organic ash is shown, and a, b, c, d, e and f are fitting coefficients;
the control processing module is further used for obtaining an elastic model of the coal-rock skeleton mixture according to the elastic modulus and the inorganic component skeleton model.
8. The coal petrophysical modeling shear wave prediction device of claim 6, wherein the control processing module is configured to obtain a fluid petrophysical model by using a Brie fluid empirical model according to the mass ratio of mobile phase low molecular organic matter, water and free gas in the target coal, wherein the Brie fluid empirical model performs the following calculation:
wherein, KlIs liquid phase bulk modulus, KgIn order to be the gas bulk modulus,
e is an empirical index factor.
9. An electronic device, characterized in that the electronic device comprises: at least one processor and at least one memory;
the memory is to store one or more program instructions;
the processor configured to execute one or more program instructions to perform the method of predicting shear waves for coal petrophysical modeling according to any of claims 1 to 5.
10. A computer readable storage medium having one or more program instructions embodied therein for performing the coal petrophysical modeling prediction shear wave method of any of claims 1-5.
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