Method and system for evaluating pore connectivity of low-permeability compact sandstone reservoir and electronic equipment

Abstract

The invention relates to the technical field of pore connectivity evaluation methods, in particular to a low-permeability compact sandstone reservoir pore connectivity evaluation method and system and electronic equipment. The method comprises the following steps: based on reservoir parameters, obtaining a saturated rock longitudinal wave velocity in a pore non-communication state, a saturated rock transverse wave velocity in the pore non-communication state, a frequency-dependent saturated rock longitudinal wave velocity in a pore communication state and a frequency-dependent saturated rock transverse wave velocity in the pore communication state; and establishing an inversion pore connectivity prediction model. According to the method, the porosity of the connected pores and the porosity of the non-connected pores of the low-permeability tight sandstone reservoir are directly inverted by using the acoustic logging data on the basis of the rock physics theory and considering the frequency change information, so that factors are more comprehensively considered when the pore connectivity of the low-permeability tight sandstone reservoir is evaluated.

Description

Technical Field

[0001] This invention relates to the technical field of pore connectivity evaluation methods, and more specifically, to a method, system, and electronic equipment for evaluating pore connectivity in low-permeability tight sandstone reservoirs. Background Technology

[0002] Medium-deep tight sandstone natural gas reservoirs are generally characterized by low porosity and low permeability. Compared with conventional reservoirs, tight sandstone reservoirs, under intense diagenetic processes, typically have a porosity of less than 10%, resulting in low permeability and poor pore connectivity. Existing research indicates that some tight sandstone reservoirs contain 40%–75% non-connected porosity in their total porosity. Connected pores are those that are interconnected with other pores, serving as channels for pore fluid flow; fluid flow is generally considered to occur only in connected pores. Non-connected pores are isolated pores that do not connect with other pores and do not improve reservoir permeability. Therefore, accurately predicting the non-connected porosity of a reservoir is crucial for evaluating its permeability and productivity.

[0003] In existing technologies, Liu Qian et al. applied the velocity-porosity empirical formula to account for the influence of added non-connected pores in the matrix. They used the Raymer-Hunt-Gardner relation to estimate the matrix modulus containing non-connected pores under known matrix minerals and non-connected pore fluids, and used this to establish a rock physics model for P-wave and S-wave velocity prediction. Wang Pu et al. proposed a method for predicting pore connectivity in tight sandstone reservoirs based on the Mori-Tanaka model and the low-frequency Gassmann equation, and used a Markov Monte Carlo optimization algorithm to achieve the prediction of pore connectivity. Ba Jing et al. developed a method for predicting the elastic parameters of tight sandstone rocks considering pore connectivity. They optimized the percentage of connected pores using a simulated annealing algorithm, estimated the combined elastic properties of connected and non-connected pores on the reservoir rock, and finally calculated the P-wave and S-wave velocities. However, the above methods are mostly evaluated based on empirical formulas or equivalent medium theory, and the factors considered are not comprehensive enough. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies in evaluating the pore connectivity of low-permeability tight sandstone reservoirs by not comprehensively considering all factors, and to provide a method, system and electronic equipment for evaluating the pore connectivity of low-permeability tight sandstone reservoirs, which considers more comprehensive factors when evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs is provided, comprising the following steps: Obtain reservoir parameters and process the reservoir parameters; Based on the reservoir parameters, the longitudinal wave velocity and transverse wave velocity of saturated rock under the condition of pore non-interconnected state are obtained. Based on the reservoir parameters, the frequency-varying bulk modulus and the frequency-varying shear modulus of saturated rock under pore connectivity are obtained; based on the reservoir parameters, the frequency-varying bulk modulus of saturated rock under pore connectivity, and the frequency-varying shear modulus of saturated rock under pore connectivity, the frequency-varying P-wave velocity and the frequency-varying S-wave velocity of saturated rock under pore connectivity are obtained. Based on the longitudinal wave velocity of saturated rock under the condition of unconnected pores, the transverse wave velocity of saturated rock under the condition of unconnected pores, the frequency-varying longitudinal wave velocity of saturated rock under the condition of connected pores, and the frequency-varying transverse wave velocity of saturated rock under the condition of connected pores, an inversion pore connectivity prediction model is established. Based on the inverted pore connectivity prediction model, the pore connectivity is obtained by minimizing the sum of errors. Based on the pore connectivity and reservoir parameters, the porosity of connected pores and the porosity of non-connected pores are obtained.

[0006] In one alternative approach, the reservoir parameters include clay content, bulk modulus of clay components, bulk modulus of sand components, shear modulus of clay components, shear modulus of sand components, density of clay components, density of sand components, bulk modulus of formation water, bulk modulus of hydrocarbons, fluid saturation of formation water, total porosity, volume polarization factor, shear polarization factor, fluid density, matrix density, Poisson's ratio under dry rock pore and fracture conditions, fracture porosity, fracture density, rock matrix modulus, fracture aspect ratio, actual logging P-wave velocity, and actual logging S-wave velocity.

[0007] In one alternative approach, the reservoir parameters are processed to obtain the equivalent bulk modulus, equivalent shear modulus, equivalent density, pore fluid equivalent bulk modulus, and equivalent density of the saturated rock of the mineral-mixed matrix. The equivalent bulk modulus, equivalent shear modulus, and equivalent density of the mineral-mixed matrix are all obtained based on the reservoir parameters using the VRH averaging method. The equivalent bulk modulus of the pore fluid is obtained based on the reservoir parameters using a patch saturated fluid model.

[0008] In one alternative approach, obtaining the P-wave velocity and S-wave velocity of saturated rock under the unconnected pore state based on the reservoir parameters includes the following sub-steps: Based on the reservoir parameters, the bulk modulus of saturated rock under the condition of non-connected pores and the shear modulus of saturated rock under the condition of non-connected pores are obtained. The longitudinal wave velocity and transverse wave velocity of the saturated rock under the condition of non-connected pores are obtained based on the bulk modulus of the saturated rock under the condition of non-connected pores and the shear modulus of the saturated rock under the condition of non-connected pores.

[0009] In one alternative approach, obtaining the frequency-dependent bulk modulus of saturated rock and the frequency-dependent shear modulus of saturated rock under pore connectivity conditions based on the reservoir parameters includes the following sub-steps: Based on the reservoir parameters, the bulk modulus and shear modulus of the porous and fractured dry rock were obtained using Biot's coherent theory. The frequency-varying bulk modulus and shear modulus of the saturated rock in the pore-connected state are obtained based on the bulk modulus and shear modulus of the pore-connected dry rock.

[0010] In one alternative approach, establishing the inverted pore connectivity prediction model includes the following sub-steps: The calculated P-wave velocity is obtained based on the P-wave velocity of saturated rock in the state of non-connected pores and the P-wave velocity of frequency-varying saturated rock in the state of connected pores. The calculated shear wave velocity is obtained based on the shear wave velocity of saturated rock in the state of non-connected pores and the frequency-varying shear wave velocity of saturated rock in the state of connected pores. An inversion pore connectivity prediction model is established by summing the errors between the calculated P-wave velocity and the actual logging P-wave velocity with the errors between the calculated S-wave velocity and the actual logging S-wave velocity.

[0011] In one alternative approach, the inversion porosity connectivity prediction model specifically uses the following formula:

[0012] In the formula, Represent the inversion objective function; Indicates the first Calculated P-wave velocity at each sampling point; Indicates the first The actual logging P-wave velocity at each sampling point; Indicates the first Calculated transverse wave velocity at each sampling point; Indicates the first The actual logging shear wave velocity at each sampling point; The calculation of the longitudinal wave velocity specifically uses the following formula:

[0013] In the formula, This indicates the calculation of the longitudinal wave velocity; Indicates pore connectivity; This represents the frequency-varying longitudinal wave velocity of saturated rock under pore connectivity conditions. This represents the longitudinal wave velocity of saturated rock in a state where the pores are not interconnected. The calculation of the shear wave velocity specifically uses the following formula:

[0014] In the formula, This indicates the calculation of shear wave velocity; This represents the frequency-varying transverse wave velocity of saturated rock under pore connectivity conditions. This represents the transverse wave velocity of saturated rock in a state where the pores are not interconnected.

[0015] According to a second aspect of the present invention, a pore connectivity evaluation system for low-permeability tight sandstone reservoirs is provided, comprising: Parameter acquisition module: used to acquire reservoir parameters; Parameter processing module: used to obtain the P-wave velocity of saturated rock under the state of non-connected pores, the S-wave velocity of saturated rock under the state of non-connected pores, the frequency-varying P-wave velocity of saturated rock under the state of connected pores, and the frequency-varying S-wave velocity of saturated rock under the state of connected pores based on the reservoir parameters. The inversion pore connectivity prediction model establishment module is used to establish an inversion pore connectivity prediction model based on the saturated rock P-wave velocity under the pore non-connected state, the saturated rock S-wave velocity under the pore non-connected state, the frequency-varying saturated rock P-wave velocity under the pore connected state, and the frequency-varying saturated rock S-wave velocity under the pore connected state. Pore ​​connectivity evaluation module: used to obtain pore connectivity by minimizing the sum of errors based on the inverted pore connectivity prediction model; and to obtain the porosity of connected pores and non-connected pores based on the pore connectivity and reservoir parameters.

[0016] According to a third aspect of the present invention, an electronic device is provided, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that enables the processor to implement the pore connectivity evaluation method for low-permeability tight sandstone reservoirs as described above.

[0017] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the above-described method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention discloses a method, system, and electronic equipment for evaluating the pore connectivity of low-permeability tight sandstone reservoirs. The method obtains the P-wave velocity, S-wave velocity, frequency-varying P-wave velocity, and frequency-varying S-wave velocity of saturated rock under non-connected pore conditions, based on reservoir parameters. Based on these velocities, an inversion pore connectivity prediction model is established. Using rock physics theory and considering frequency-varying information, the porosity of connected and non-connected pores in low-permeability tight sandstone reservoirs is directly inverted using sonic logging data. The physical meaning is clear, and the inversion reliability is high, making the evaluation of pore connectivity in low-permeability tight sandstone reservoirs more comprehensive. Attached Figure Description

[0019] Figure 1 A schematic flowchart of the first embodiment of the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs provided by the present invention is shown. Figure 2 The flowchart of a sub-step in step S2 of the first embodiment of the low-permeability tight sandstone reservoir pore connectivity evaluation method provided by the present invention is shown. Figure 3 The flowchart of a sub-step in step S3 of the first embodiment of the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs provided by the present invention is shown. Figure 4 The flowchart of a sub-step in step S4 of the first embodiment of the low-permeability tight sandstone reservoir pore connectivity evaluation method provided by the present invention is shown. Figure 5 The figure shows the evaluation results obtained using the low-permeability tight sandstone reservoir pore connectivity evaluation method provided by the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The present invention will be further described below with reference to specific embodiments.

[0021] Furthermore, if the embodiments of the present invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text is to include three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution that simultaneously satisfies A and B.

[0022] Example 1 Figure 1 A flowchart illustrating a first embodiment of the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to the present invention is shown. This method is executed by a system for evaluating the pore connectivity of low-permeability tight sandstone reservoirs. Figure 1 As shown, the method includes the following steps: Step S1: Obtain reservoir parameters and process them.

[0023] Specifically, reservoir parameters include clay content, bulk modulus of clay components, bulk modulus of sand components, shear modulus of clay components, shear modulus of sand components, density of clay components, density of sand components, bulk modulus of formation water, bulk modulus of hydrocarbons, fluid saturation of formation water, total porosity, volume polarization factor, shear polarization factor, fluid density, matrix density, Poisson's ratio under dry rock with coexisting pores and fractures, fracture porosity, fracture density, rock matrix modulus, fracture aspect ratio, actual logging P-wave velocity, and actual logging S-wave velocity. These reservoir parameters can be obtained through well logging.

[0024] Specifically, after processing the reservoir parameters, the equivalent bulk modulus, equivalent shear modulus, equivalent density, equivalent bulk modulus of pore fluid, and equivalent density of saturated rock are obtained. The equivalent bulk modulus, equivalent shear modulus, and equivalent density of the mineral mixed matrix are all obtained based on the reservoir parameters using the VRH averaging method. The equivalent bulk modulus of pore fluid is obtained based on the reservoir parameters using a patch saturated fluid model.

[0025] The equivalent bulk modulus of the mineral mixed matrix is ​​obtained through the following formula:

[0026] In the formula, Represents the equivalent bulk modulus of a mineral mixture matrix; Indicates the clay content; This represents the bulk modulus value of the clay component; This represents the bulk modulus value of the sandy component.

[0027] The equivalent shear modulus of the mineral mixed matrix is ​​obtained through the following formula:

[0028] In the formula, Represents the equivalent shear modulus of a mineral-mixed matrix; This represents the shear modulus value of the clay component; This represents the shear modulus value of the sandy component.

[0029] The equivalent density value of the mineral mixed matrix is ​​obtained through the following formula:

[0030] In the formula, This represents the equivalent density value of the mineral matrix mixture; This indicates the density value of the clay component; This indicates the density value of the sandy component.

[0031] The equivalent bulk modulus of the pore fluid is obtained through the following formula:

[0032] In the formula, Represents the equivalent bulk modulus of pore fluids; Indicates the bulk modulus of formation water; Indicates the bulk modulus of hydrocarbons (oil, gas); Indicates the saturation of hydrocarbon fluids. This indicates the fluid saturation of formation water; This represents the empirical constant term.

[0033] The equivalent density of saturated rock is obtained using the following formula:

[0034] In the formula, Represents the equivalent density of saturated rock; Indicates total porosity; Indicates fluid density; This indicates the matrix density.

[0035] Step S2: Obtain the P-wave velocity and S-wave velocity of saturated rock under the state of pore disconnection based on reservoir parameters.

[0036] Step S3: Obtain the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity based on reservoir parameters; obtain the frequency-varying P-wave velocity and S-wave velocity of saturated rock under pore connectivity based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity.

[0037] Step S4: Based on the P-wave velocity of saturated rock under unconnected pore conditions, the S-wave velocity of saturated rock under unconnected pore conditions, the frequency-varying P-wave velocity of saturated rock under connected pore conditions, and the frequency-varying S-wave velocity of saturated rock under connected pore conditions, establish an inversion pore connectivity prediction model.

[0038] Step S5: Based on the inverted pore connectivity prediction model, minimize the sum of errors to obtain pore connectivity.

[0039] Step S6: Based on pore connectivity and reservoir parameters, obtain the porosity of connected pores and the porosity of non-connected pores.

[0040] The above method obtains the P-wave velocity, S-wave velocity, frequency-varying P-wave velocity, and frequency-varying S-wave velocity of saturated rock under unconnected pore conditions, and under connected pore conditions, based on reservoir parameters. Based on these velocities, an inversion model for predicting pore connectivity is established. Based on rock physics theory and considering frequency-varying information, the porosity of connected and unconnected pores in low-permeability tight sandstone reservoirs is directly inverted using sonic logging data. The physical meaning is clear, and the inversion reliability is high, allowing for a more comprehensive consideration of factors when evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0041] Figure 2 The flowchart of the sub-step in step S2 of the low-permeability tight sandstone reservoir pore connectivity evaluation method of the present invention is shown.

[0042] In step S2, the P-wave velocity and S-wave velocity of saturated rock under the state of pore disconnection are obtained based on reservoir parameters, including the following sub-steps: Step S21: Obtain the bulk modulus of saturated rock under the state of non-connected pores and the shear modulus of saturated rock under the state of non-connected pores based on reservoir parameters.

[0043] Specifically, the bulk modulus of saturated rock in a non-connected pore state is obtained using the following formula:

[0044] In the formula, This represents the bulk modulus of saturated rock in a state where the pores are not interconnected. Indicates total porosity; This represents the volume polarization factor, which is related to the aspect ratio of the pores.

[0045] Specifically, the shear modulus of saturated rock in a non-connected pore state is obtained by the following formula:

[0046] In the formula, This represents the shear modulus of saturated rock in a state where the pores are not interconnected. This represents a coefficient related to the matrix modulus. ; This represents the shear polarization factor, which is related to the pore aspect ratio.

[0047] Step S22: Obtain the longitudinal wave velocity and transverse wave velocity of saturated rock under the unconnected pore state based on the bulk modulus and shear modulus of saturated rock under the unconnected pore state.

[0048] Specifically, the P-wave velocity of saturated rock in a non-connected pore state is obtained by the following formula:

[0049] In the formula, This represents the longitudinal wave velocity of saturated rock in a state where the pores are not interconnected.

[0050] Specifically, the transverse wave velocity of saturated rock in a non-connected pore state is obtained by the following formula:

[0051] In the formula, This represents the transverse wave velocity of saturated rock in a state where the pores are not interconnected.

[0052] Figure 3 The flowchart of the sub-step in step S3 of the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs of the present invention is shown.

[0053] In step S3, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity are obtained based on reservoir parameters; based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity, the frequency-varying P-wave velocity and S-wave velocity of saturated rock under pore connectivity are obtained, including the following sub-steps: Step S31: Based on reservoir parameters, obtain the bulk modulus and shear modulus of dry rock containing pores and fractures using Biot's consistent theory.

[0054] Specifically, the bulk modulus of dry rock containing pores and fractures is obtained using the following formula:

[0055] In the formula, This indicates the bulk modulus of dry rock containing pores and fissures. Poisson's ratio represents the ratio of dry rock with both pores and fractures. This represents the shear modulus of dry rock containing pores and fissures.

[0056] Specifically, the shear modulus of dry rock containing pores and fractures is obtained using the following formula:

[0057] In the formula, This represents the total porosity after removing fracture porosity; This represents the coefficient related to Poisson's ratio. ; This represents the coefficient related to Poisson's ratio. ; This represents the fracture density.

[0058] Step S32: Based on the bulk modulus and shear modulus of dry rock with pores and fissures, obtain the frequency-varying bulk modulus of saturated rock under pore connectivity and the frequency-varying shear modulus of saturated rock under pore connectivity.

[0059] Specifically, the frequency-varying bulk modulus of saturated rock in a pore-connected state is obtained using the following formula:

[0060] In the formula, This represents the frequency-varying bulk modulus of saturated rock in a state of pore connectivity. Represents the Biot coefficient. ; Indicates the modulus of the rock matrix; Indicates the contribution of the jet stream. ; Represents pi; The Poisson's ratio represents the dry medium. =(3 -2 ) / (6 +2 ); express The saturated rock shear modulus at that time is numerically equal to the dry rock shear modulus. ; Represents quantities related to fluids; This represents the bulk modulus of saturated rock at the high-frequency limit, numerically equal to... ; This indicates the aspect ratio of the fracture.

[0061] Specifically, the frequency-varying shear modulus of saturated rock in a pore-connected state is obtained through the following formula:

[0062] In the formula, This represents the frequency-varying shear modulus of saturated rock in a state of pore connectivity. This represents the drying shear modulus, which is numerically equal to... ; The bulk modulus represents the mass modulus when the fractured fluid is fully relaxed. This is part of the formula for the frequency-dependent bulk modulus of saturated rock in a pore-connected state. time Find the answer.

[0063] Step S33: Based on reservoir parameters, the frequency-varying bulk modulus of saturated rock under pore connectivity, and the frequency-varying shear modulus of saturated rock under pore connectivity, obtain the frequency-varying P-wave velocity and the frequency-varying S-wave velocity of saturated rock under pore connectivity.

[0064] Specifically, the frequency-varying P-wave velocity of saturated rock in a pore-connected state is obtained through the following formula:

[0065] In the formula, This represents the frequency-varying longitudinal wave velocity of saturated rock under interconnected pore conditions.

[0066] Specifically, the frequency-varying shear wave velocity of saturated rock in a pore-connected state is obtained by the following formula:

[0067] In the formula, This represents the frequency-varying longitudinal wave velocity of saturated rock under interconnected pore conditions.

[0068] Figure 4 The flowchart of the sub-step in step S4 of the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs of the present invention is shown.

[0069] In step S4, an inversion porosity connectivity prediction model is established, including the following sub-steps: Step S41: Calculate the P-wave velocity based on the P-wave velocity of saturated rock under unconnected pore conditions and the frequency-varying P-wave velocity of saturated rock under connected pore conditions. Specifically, obtain the velocity using the following formula:

[0070] In the formula, This indicates the calculation of the longitudinal wave velocity; Indicates pore connectivity; This represents the frequency-varying longitudinal wave velocity of saturated rock under pore connectivity conditions. This represents the longitudinal wave velocity of saturated rock in a state where the pores are not interconnected.

[0071] Step S42: Calculate the shear wave velocity based on the shear wave velocity of saturated rock under unconnected pore conditions and the frequency-varying shear wave velocity of saturated rock under connected pore conditions. Specifically, obtain the velocity using the following formula:

[0072] In the formula, This indicates the calculation of shear wave velocity; This represents the frequency-varying transverse wave velocity of saturated rock under pore connectivity conditions. This represents the transverse wave velocity of saturated rock in a state where the pores are not interconnected.

[0073] Step S43: Based on the sum of the errors in calculating the P-wave velocity and the actual logging P-wave velocity and the errors in calculating the S-wave velocity and the actual logging S-wave velocity, establish an inversion porosity connectivity prediction model. Specifically, use the following formula:

[0074] In the formula, Represent the inversion objective function; Indicates the first Calculation of P-wave velocity at each sampling point This indicates the dominant frequencies of the P-waves and S-waves in acoustic logging. Indicates the first Pore ​​connectivity at each sampling point express, Indicates the first The aspect ratio of the cracks at each sampling point; Indicates the first The actual logging P-wave velocity at each sampling point; Indicates the first Calculated transverse wave velocity at each sampling point; Indicates the first The actual logging shear wave velocity at each sampling point.

[0075] In step S5, based on the inverted pore connectivity prediction model, the sum of errors is minimized to obtain the pore connectivity.

[0076] Specifically, reservoir parameters are collected at multiple sampling points, and the formula in step S41 is used to calculate the first... The calculated P-wave velocity at the sampling point is then used to calculate the velocity of the first sampling point using the formula in step S42. The calculated transverse wave velocity at each sampling point is fed into the inversion pore connectivity prediction model in step S43. The model is then iteratively trained using the particle swarm optimization algorithm to obtain the pore connectivity that minimizes the sum of errors.

[0077] In step S6, based on pore connectivity and reservoir parameters, the porosity of connected pores and the porosity of non-connected pores are obtained.

[0078] Specifically, the porosity of the interconnected pores is obtained using the following formula:

[0079] In the formula, This indicates the porosity of the connected holes.

[0080] Specifically, the porosity of non-connected pores is obtained using the following formula:

[0081] In the formula, This indicates the porosity of non-connected pores.

[0082] Specifically, Figure 5 A visualization is shown using the low-permeability tight sandstone reservoir pore connectivity evaluation method provided by this invention.

[0083] This invention considers the pore connectivity of mid-deep, low-permeability tight sandstone reservoirs, establishes a petrophysical model suitable for these reservoirs, and achieves direct quantitative inversion prediction of porosity in both connected and disconnected pores. For disconnected pores, the velocity of the saturated fluid rock medium is calculated using KT high-frequency theory; for connected pores, the velocity of the saturated fluid rock medium is calculated using frequency-varying squirting flow theory in the logging band. The P-wave and S-wave velocities for disconnected and connected pores are allocated using pore connectivity parameters. This method has a reasonable and clear physical meaning, overcoming the shortcomings of conventional methods that rely on empirical relationships and insufficient consideration of dispersion factors. This invention realizes acoustic logging evaluation of pore connectivity in low-permeability tight sandstone reservoirs.

[0084] Example 2 This embodiment, based on Embodiment 1, provides a pore connectivity evaluation system for low-permeability tight sandstone reservoirs, which can execute the pore connectivity evaluation method for low-permeability tight sandstone reservoirs as described in Embodiment 1. Specifically, it includes: a data acquisition module, a parameter processing module, an inversion pore connectivity prediction model establishment module, and a pore connectivity evaluation module.

[0085] The parameter acquisition module is used to acquire reservoir parameters. The parameter processing module is used to obtain the P-wave velocity of saturated rock under non-connected pore conditions, the S-wave velocity of saturated rock under non-connected pore conditions, the frequency-varying P-wave velocity of saturated rock under connected pore conditions, and the frequency-varying S-wave velocity of saturated rock under connected pore conditions based on reservoir parameters. The inversion pore connectivity prediction model building module is used to build an inversion pore connectivity prediction model based on the P-wave velocity of saturated rock under non-pore connectivity, the S-wave velocity of saturated rock under non-pore connectivity, the frequency-varying P-wave velocity of saturated rock under connectivity, and the frequency-varying S-wave velocity of saturated rock under connectivity. The pore connectivity evaluation module is used to obtain pore connectivity by minimizing the sum of errors based on the inverted pore connectivity prediction model; and to obtain the porosity of connected pores and non-connected pores based on pore connectivity and reservoir parameters.

[0086] The above system obtains the P-wave velocity, S-wave velocity, and frequency-varying P-wave velocity of saturated rock under unconnected pore conditions, as well as the frequency-varying S-wave velocity under connected pore conditions, based on reservoir parameters. Based on these velocities, an inversion model for predicting pore connectivity is established. Using rock physics theory and considering frequency-varying information, the system directly inverts the porosity of connected and unconnected pores in low-permeability tight sandstone reservoirs using sonic logging data. This method has clear physical meaning, high reliability, and allows for a more comprehensive consideration of factors when evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0087] Example 3 The specific embodiments of the present invention do not limit the specific implementation of the electronic device.

[0088] An electronic device may include: a processor, a communications interface, memory, and a communications bus.

[0089] The processor, communication interface, and memory communicate with each other via a communication bus. The communication interface is used to communicate with other devices, such as electronic devices or other server network elements. The processor executes the program, which, during execution, implements the steps described above in the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs to evaluate the pore connectivity of the low-permeability tight sandstone reservoirs.

[0090] Specifically, a program may include program code, which includes computer-executable instructions.

[0091] Specifically, the processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The electronic device may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0092] Memory is used to store programs. Memory may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive.

[0093] The program can be called by the processor to cause the electronic device to perform the following operations: Obtain reservoir parameters and process them; Based on reservoir parameters, the P-wave velocity and S-wave velocity of saturated rock under unconnected pore conditions were obtained. Based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity are obtained; based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity are obtained, and the frequency-varying P-wave velocity and S-wave velocity of saturated rock under pore connectivity are obtained. Based on the P-wave velocity of saturated rock under unconnected pore conditions, the S-wave velocity of saturated rock under unconnected pore conditions, the frequency-varying P-wave velocity of saturated rock under connected pore conditions, and the frequency-varying S-wave velocity of saturated rock under connected pore conditions, an inversion pore connectivity prediction model is established. Based on the inverted pore connectivity prediction model, the pore connectivity is obtained by minimizing the sum of errors. Based on pore connectivity and reservoir parameters, the porosity of connected pores and the porosity of non-connected pores are obtained.

[0094] The data stream described above is consistent with the data stream in Embodiment 1. For details, please refer to the description in Embodiment 1. This embodiment will not repeat the description.

[0095] The above electronic equipment obtains the P-wave velocity, S-wave velocity, frequency-varying P-wave velocity, and frequency-varying S-wave velocity of saturated rock under unconnected pore conditions, as well as under connected pore conditions, based on reservoir parameters. Based on these velocities, an inversion model for predicting pore connectivity is established. Using rock physics theory and considering frequency-varying information, the porosity of connected and unconnected pores in low-permeability tight sandstone reservoirs is directly inverted using sonic logging data. The physical meaning is clear, and the inversion reliability is high, allowing for a more comprehensive consideration of factors when evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0096] Example 4 This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on an electronic device, causes the electronic device to perform the low-permeability tight sandstone reservoir pore connectivity evaluation method described in Embodiment 1 above.

[0097] Executable instructions can be used to cause an electronic device to perform the following operations: Obtain reservoir parameters and process them; Based on reservoir parameters, the P-wave velocity and S-wave velocity of saturated rock under unconnected pore conditions were obtained. Based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity are obtained; based on reservoir parameters, the frequency-varying bulk modulus and shear modulus of saturated rock under pore connectivity are obtained, and the frequency-varying P-wave velocity and S-wave velocity of saturated rock under pore connectivity are obtained. Based on the P-wave velocity of saturated rock under unconnected pore conditions, the S-wave velocity of saturated rock under unconnected pore conditions, the frequency-varying P-wave velocity of saturated rock under connected pore conditions, and the frequency-varying S-wave velocity of saturated rock under connected pore conditions, an inversion pore connectivity prediction model is established. Based on the inverted pore connectivity prediction model, the pore connectivity is obtained by minimizing the sum of errors. Based on pore connectivity and reservoir parameters, the porosity of connected pores and the porosity of non-connected pores are obtained.

[0098] By obtaining the P-wave velocity, S-wave velocity, and frequency-varying P-wave velocity of saturated rock under unconnected pore conditions, and under connected pore conditions, based on reservoir parameters, and then establishing an inversion model for predicting pore connectivity, this model is used to directly invert the porosity of connected and unconnected pores in low-permeability tight sandstone reservoirs using sonic logging data. The model has clear physical meaning and high reliability, allowing for a more comprehensive consideration of factors when evaluating the pore connectivity of low-permeability tight sandstone reservoirs.

[0099] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0100] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. Similarly, for the sake of brevity and to aid in understanding one or more aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0101] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

[0102] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs, characterized in that, Includes the following steps: Obtain reservoir parameters and process the reservoir parameters; Based on the reservoir parameters, the longitudinal wave velocity and transverse wave velocity of saturated rock under the condition of pore non-interconnected state are obtained. Based on the reservoir parameters, the frequency-varying bulk modulus and the frequency-varying shear modulus of saturated rock under pore connectivity are obtained; based on the reservoir parameters, the frequency-varying bulk modulus of saturated rock under pore connectivity, and the frequency-varying shear modulus of saturated rock under pore connectivity, the frequency-varying P-wave velocity and the frequency-varying S-wave velocity of saturated rock under pore connectivity are obtained. Based on the longitudinal wave velocity of saturated rock under the condition of unconnected pores, the transverse wave velocity of saturated rock under the condition of unconnected pores, the frequency-varying longitudinal wave velocity of saturated rock under the condition of connected pores, and the frequency-varying transverse wave velocity of saturated rock under the condition of connected pores, an inversion pore connectivity prediction model is established. Based on the inverted pore connectivity prediction model, the pore connectivity is obtained by minimizing the sum of errors. Based on the pore connectivity and reservoir parameters, the porosity of connected pores and the porosity of non-connected pores are obtained.

2. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to claim 1, characterized in that, The reservoir parameters include clay content, bulk modulus of clay components, bulk modulus of sand components, shear modulus of clay components, shear modulus of sand components, density of clay components, density of sand components, bulk modulus of formation water, bulk modulus of hydrocarbons, fluid saturation of formation water, total porosity, volume polarization factor, shear polarization factor, fluid density, matrix density, Poisson's ratio under dry rock with coexisting pores and fractures, fracture porosity, fracture density, rock matrix modulus, fracture aspect ratio, actual logging P-wave velocity, and actual logging S-wave velocity.

3. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to claim 2, characterized in that, After processing the reservoir parameters, the equivalent bulk modulus, equivalent shear modulus, equivalent density, pore fluid equivalent bulk modulus, and saturated rock equivalent density of the mineral mixed matrix are obtained. The equivalent bulk modulus, equivalent shear modulus, and equivalent density of the mineral mixed matrix are all obtained based on the reservoir parameters using the VRH averaging method. The equivalent bulk modulus of the pore fluid is obtained based on the reservoir parameters using a patch saturated fluid model.

4. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to claim 2, characterized in that, The process of obtaining the P-wave velocity and S-wave velocity of saturated rock under unconnected pore conditions based on the reservoir parameters includes the following sub-steps: Based on the reservoir parameters, the bulk modulus of saturated rock under the condition of non-connected pores and the shear modulus of saturated rock under the condition of non-connected pores are obtained. The longitudinal wave velocity and transverse wave velocity of the saturated rock under the condition of non-connected pores are obtained based on the bulk modulus of the saturated rock under the condition of non-connected pores and the shear modulus of the saturated rock under the condition of non-connected pores.

5. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to claim 2, characterized in that, The process of obtaining the frequency-varying bulk modulus of saturated rock and the frequency-varying shear modulus of saturated rock under pore connectivity based on the reservoir parameters includes the following sub-steps: Based on the reservoir parameters, the bulk modulus and shear modulus of the porous and fractured dry rock were obtained using Biot's coherent theory. The frequency-varying bulk modulus and shear modulus of the saturated rock in the pore-connected state are obtained based on the bulk modulus and shear modulus of the pore-connected dry rock.

6. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to any one of claims 1 to 5, characterized in that, The establishment of the inversion porosity connectivity prediction model includes the following sub-steps: The calculated P-wave velocity is obtained based on the P-wave velocity of saturated rock in the state of non-connected pores and the P-wave velocity of frequency-varying saturated rock in the state of connected pores. The calculated shear wave velocity is obtained based on the shear wave velocity of saturated rock in the state of non-connected pores and the frequency-varying shear wave velocity of saturated rock in the state of connected pores. An inversion pore connectivity prediction model is established by summing the errors between the calculated P-wave velocity and the actual logging P-wave velocity with the errors between the calculated S-wave velocity and the actual logging S-wave velocity.

7. The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to claim 6, characterized in that, The inverted porosity connectivity prediction model specifically uses the following formula: In the formula, Represents the inversion objective function; Indicates the first Calculated P-wave velocity at each sampling point; Indicates the first The actual logging P-wave velocity at each sampling point; Indicates the first Calculated transverse wave velocity at each sampling point; Indicates the first The actual logging shear wave velocity at each sampling point; The calculation of the longitudinal wave velocity specifically uses the following formula: In the formula, This indicates the calculation of the longitudinal wave velocity; Indicates pore connectivity; This represents the frequency-varying longitudinal wave velocity of saturated rock under pore connectivity conditions. This represents the longitudinal wave velocity of saturated rock in a state where the pores are not interconnected. The calculation of the shear wave velocity specifically uses the following formula: In the formula, This indicates the calculation of shear wave velocity; This represents the frequency-varying transverse wave velocity of saturated rock under pore connectivity conditions. This represents the transverse wave velocity of saturated rock in a state where the pores are not interconnected.

8. A system for evaluating the pore connectivity of low-permeability tight sandstone reservoirs, characterized in that, The method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs according to any one of claims 1 to 7 includes: Parameter acquisition module: used to acquire reservoir parameters; Parameter processing module: used to obtain the P-wave velocity of saturated rock under the state of non-connected pores, the S-wave velocity of saturated rock under the state of non-connected pores, the frequency-varying P-wave velocity of saturated rock under the state of connected pores, and the frequency-varying S-wave velocity of saturated rock under the state of connected pores based on the reservoir parameters. The inversion pore connectivity prediction model establishment module is used to establish an inversion pore connectivity prediction model based on the saturated rock P-wave velocity under the pore non-connected state, the saturated rock S-wave velocity under the pore non-connected state, the frequency-varying saturated rock P-wave velocity under the pore connected state, and the frequency-varying saturated rock S-wave velocity under the pore connected state. Pore ​​connectivity evaluation module: used to obtain pore connectivity by minimizing the sum of errors based on the inverted pore connectivity prediction model; and to obtain the porosity of connected pores and non-connected pores based on the pore connectivity and reservoir parameters.

9. An electronic device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to implement the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the method for evaluating the pore connectivity of low-permeability tight sandstone reservoirs as described in any one of claims 1 to 7.

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