A method, device, electronic equipment and medium for quantitative evaluation of pore flow capacity

Abstract

The present invention discloses a method, device, electronic device and medium for quantitatively evaluating pore flow capacity. The method includes: obtaining a rock sample of a target tight sandstone reservoir; determining a storage capacity index based on the porosity and permeability of the rock sample; determining the rock brittle boundary degree based on the mineral content test results and the number of mineral species of the rock sample; simulating the temperature and confining pressure of the underground environment, conducting an acoustic emission test on the rock sample, and obtaining the number of ringings corresponding to different times; determining the acoustic emission interference factor based on the number of ringings corresponding to different times; determining the rock sample communication coefficient based on the storage capacity index and the rock brittle boundary degree; determining the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluating the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient. This technical solution quantitatively characterizes the pore flow capacity through the reservoir flow coefficient, and can achieve the purpose of quantitatively evaluating the pore flow capacity of the tight oil reservoir.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum and natural gas engineering, and in particular to a method, device, electronic equipment and medium for quantitatively evaluating pore flow capacity. Background Art

[0002] Tight oil reservoirs are extremely rich in resources and have enormous development potential, holding important exploration and development prospects in the unconventional oil and gas sector. Finding favorable reservoir qualities is the primary goal of exploration and development and the key to achieving breakthroughs in single-well production. Pore flow capacity is a core factor directly impacting the potential of oil and gas exploration resources and the scale-effective development of these resources. However, with the shift toward unconventional resource exploration and development, tight oil reservoirs often feature thin interbedded sand and mud layers, along with well-developed natural fractures and strong heterogeneity. The question is how to further increase single-well production and fully release oil and gas reservoirs. Reservoir fluidity evaluation is fundamental to well and section selection for horizontal well volume fracturing.

[0003] Since the factors that affect the fluidity of tight oil reservoirs are numerous and their relationships are complex, domestic and foreign scholars have conducted extensive research on the evaluation of reservoir fluidity. Currently, there are mainly two methods: a method for characterizing the oil and gas phase equilibrium and flow capacity of porous rock media, and a method for calculating the apparent permeability of shale gas that considers the influence of multiple factors.

[0004] The above two methods calculate the permeability of reservoir rocks by establishing prediction models and experimental simulations, evaluate the pore flow capacity, and then evaluate the fluidity of the reservoir. However, the evaluation indicators are single, and there are significant differences between the models and experiments and the actual reservoir conditions. The evaluation accuracy needs to be further improved. Summary of the Invention

[0005] The present invention provides a method, device, electronic equipment and medium for quantitatively evaluating pore flow capacity, which simultaneously considers internal and external factors affecting pore flow capacity and quantitatively characterizes pore flow capacity through reservoir flow coefficient, thereby achieving the purpose of quantitatively evaluating the pore flow capacity of tight oil reservoirs with high evaluation accuracy.

[0006] According to one aspect of the present invention, a method for quantitatively evaluating pore flow capacity is provided, the method comprising:

[0007] Obtain rock samples from target tight sandstone reservoirs;

[0008] Determining a storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir;

[0009] Determine the rock brittleness boundary degree based on the mineral content test results and the number of mineral species of the rock sample; wherein the rock brittleness boundary degree is used to characterize the potential for microcrack development in energy storage after being stimulated by external factors;

[0010] Simulating the temperature and confining pressure of the underground environment, performing an acoustic emission test on the rock sample, and obtaining the number of ringing times corresponding to different times;

[0011] Determining an acoustic emission interference factor based on the number of ringings corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors that affect the flow capacity of rock pores;

[0012] Determining a rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock;

[0013] The reservoir flow coefficient is determined according to the rock sample communication coefficient and the acoustic emission interference factor, and the pore flow capacity of the tight oil reservoir is quantitatively evaluated according to the reservoir flow coefficient.

[0014] According to another aspect of the present invention, there is provided a device for quantitatively evaluating pore flow capacity, the device comprising:

[0015] A rock sample acquisition module is used to obtain rock samples from target tight sandstone reservoirs;

[0016] A storage capacity index determination module is used to determine the storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir;

[0017] A rock brittle boundary determination module is used to determine the rock brittle boundary based on the mineral content test results and the number of mineral types of the rock sample; wherein the rock brittle boundary is used to characterize the potential for micro-crack development after energy storage is stimulated by external factors;

[0018] A ringing number obtaining module is used to simulate the temperature and confining pressure of the underground environment, perform an acoustic emission test on the rock sample, and obtain the ringing number corresponding to different times;

[0019] an acoustic emission interference factor determination module, configured to determine an acoustic emission interference factor according to the number of ringing times corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors affecting the flow capacity of rock pores;

[0020] a rock sample communication coefficient determination module, configured to determine the rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock;

[0021] The pore flow capacity quantitative evaluation module is used to determine the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and to quantitatively evaluate the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient.

[0022] According to another aspect of the present invention, an electronic device is provided, comprising:

[0023] at least one processor; and

[0024] a memory communicatively connected to the at least one processor; wherein,

[0025] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform a quantitative evaluation method for pore flow capacity according to any embodiment of the present invention.

[0026] According to another aspect of the present invention, a computer-readable medium is provided, wherein the computer-readable medium stores computer instructions, and the computer instructions are used to enable a processor to implement a quantitative evaluation method for pore flow capacity according to any embodiment of the present invention when executed.

[0027] The technical solution of the embodiment of the present invention obtains a rock sample of the target tight sandstone reservoir; determines the storage capacity index based on the porosity and permeability of the rock sample; determines the rock brittle boundary degree based on the mineral content test results and the number of mineral types in the rock sample; simulates the temperature and confining pressure of the underground environment, conducts an acoustic emission test on the rock sample, and obtains the number of ringing times corresponding to different times; determines the acoustic emission interference factor based on the number of ringing times corresponding to different times; determines the rock sample communication coefficient based on the storage capacity index and the rock brittle boundary degree; determines the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluates the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient. This technical solution simultaneously considers internal and external factors that affect the pore flow capacity, quantitatively characterizes the pore flow capacity through the reservoir flow coefficient, and can achieve the purpose of quantitatively evaluating the pore flow capacity of the tight oil reservoir with high evaluation accuracy.

[0028] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 This is a flow chart of a method for quantitatively evaluating pore flow capacity according to the first embodiment of the present invention;

[0031] Figure 2 A schematic structural diagram of a device for quantitatively evaluating pore flow capacity provided in a second embodiment of the present invention;

[0032] Figure 3 It is a schematic structural diagram of an electronic device for implementing a quantitative evaluation method of pore flow capacity according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "object" and "target" in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Example 1

[0036] Figure 1This is a flow chart of a method for quantitatively evaluating pore flow capacity according to the first embodiment of the present invention. This embodiment is applicable to the case of quantitatively analyzing the pore flow capacity of tight oil reservoirs. The method can be performed by a pore flow capacity quantitative evaluation device. The pore flow capacity quantitative evaluation device can be implemented in the form of hardware and / or software. The pore flow capacity quantitative evaluation device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0037] S110. Obtain rock samples from the target tight sandstone reservoir.

[0038] In this solution, the target tight sandstone reservoir can be cored, and the cored rock sample can be made into a standard rock sample, and then the moisture in the standard rock sample can be removed to obtain a dried rock sample. The cored rock sample can be made into a standard rock sample with a diameter of 2.5 cm and a length of 5 cm.

[0039] For example, actual downhole cores from tight oil reservoirs can be taken at a depth of 2000-2500 m, and the cored rock samples can be made into two standard rock samples with a diameter of 2.5 cm and a length of 5 cm. The rock samples are numbered X1 and X2, and X1 and X2 are placed in a 100°C oven and dried to constant weight, thereby obtaining two dried rock samples.

[0040] S120. Determine a storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir.

[0041] Among them, the larger the storage capacity index value, the better the rock sample physical properties and the stronger the pore flow capacity.

[0042] In this embodiment, the porosity and permeability of the rock sample can be tested respectively using a helium porosity automatic tester and an ultra-low permeability tester, and the porosity and permeability of the rock sample can be calculated to obtain the storage capacity index.

[0043] Optionally, determining a reservoir capacity index based on the porosity and permeability of the rock sample includes:

[0044] The porosity and permeability of the rock sample are multiplied to obtain the storage capacity index.

[0045] Specifically, the storage capacity index can be calculated using the following formula:

[0046]

[0047] in, is the storage capacity index, μm 2 ; k is the permeability of the rock sample, μm 2 ; is the porosity of the rock sample, %.

[0048] By determining the storage capacity index of rock samples, the storage capacity of fluids in porous media of reservoirs can be quantitatively evaluated.

[0049] For example, the porosity of the dried rock sample is tested using a helium porosity automatic tester and an ultra-low permeability tester. and permeability k, and using the formula Calculate the storage capacity index of rock samples The calculation results are shown in Table 1.

[0050] Table 1

[0051]

[0052] S130. Determine the rock brittleness boundary degree based on the mineral content test results and the number of mineral types of the rock sample; wherein the rock brittleness boundary degree is used to characterize the potential for microcrack development after energy storage is stimulated by external factors.

[0053] Among them, the larger the rock brittle boundary value, the more complex the mineral arrangement of the brittle boundary, the higher the degree of fragmentation of the rock sample caused by external force, the easier it is to connect the main hydraulic fractures, and the greater the potential to form a complex fracture network.

[0054] In this embodiment, an X-ray diffractometer can be used to test the mineral composition of the rock sample, and the mineral content test results of each mineral component can be obtained, and the number of mineral types can be obtained.

[0055] In this scheme, the mineral content test results and the number of mineral species can be combined and calculated to obtain the rock brittle boundary degree.

[0056] Optionally, determining the rock brittle boundary degree based on the mineral content test results and the number of mineral types of the rock sample includes steps A1-A4:

[0057] Step A1: determining the test results of the mineral content and the number of mineral types of the rock sample; wherein the test results of the mineral content include the test results of quartz content, dolomite content, calcite content, feldspar content, pyrite content, and clay content;

[0058] In this scheme, the X-ray diffractometer can be used to test the mineral content of the rock sample. i , specifically including quartz content test results, dolomite content test results, calcite content test results, feldspar content test results, pyrite content test results and clay content test results.

[0059] For example, the test results of each mineral content are shown in Table 2.

[0060] Table 2

[0061] Rock sample number dolomite(%) quartz(%) Calcite (%) Feldspar (%) Pyrite (%) clay(%) X1 22.22 22.56 4.76 26.87 5.31 18.28 X2 24.01 14.78 7.22 34.56 2.55 16.88

[0062] Step A2: determining the optimal brittle boundary coefficient based on the clay content test results and the number of mineral species;

[0063] In this embodiment, clay minerals are boundary-inhibiting minerals, while other minerals are boundary-promoting minerals, namely, quartz, dolomite, calcite, feldspar, and pyrite. The optimal brittle boundary coefficient can be determined based on the clay content test results and the number of mineral species using a predetermined formula for calculating the optimal brittle boundary coefficient.

[0064] Specifically, the following formula is used to calculate the optimal coefficient of the brittle junction:

[0065]

[0066] Among them, C n is the optimal coefficient of brittle junction, %; M 粘 is the clay content test result, %; n is the number of mineral types, pieces.

[0067] Step A3: determining the junction coefficient according to the optimal brittle junction coefficient and the test results of each mineral content;

[0068] In this embodiment, the actual deviation boundary coefficient can be determined according to the brittle boundary optimal coefficient and the test results of each mineral content, and all actual deviation boundary coefficients are summed to obtain the boundary coefficient.

[0069] Furthermore, the interface coefficient can be calculated using the following formula:

[0070]

[0071] Among them, C Z is the interface coefficient, %.

[0072] Step A4: Calculate the rock brittle boundary degree based on the boundary coefficient and the number of mineral species.

[0073] In this scheme, the rock brittle boundary degree can be calculated according to the predetermined rock brittle boundary degree calculation formula, the boundary coefficient and the number of mineral types.

[0074] Specifically, the rock brittle boundary degree can be calculated using the following formula:

[0075]

[0076] Among them, MC is the rock brittleness boundary degree.

[0077] For example, the rock brittle boundary degree calculated using the above formula is shown in Table 3.

[0078] Table 3

[0079]

[0080] By calculating the rock brittle boundary degree, the potential for microcrack development in the reservoir after external stimulation can be quantitatively evaluated based on the differences in rock mineral composition.

[0081] S140, simulating the temperature and confining pressure of an underground environment, performing an acoustic emission test on the rock sample, and obtaining the number of ringings corresponding to different times.

[0082] Among them, acoustic emission test refers to a detection test that evaluates the performance of rock samples by receiving and analyzing acoustic emission signals.

[0083] In this scheme, when the rock sample is in an environment with different temperatures and confining pressures, the trend, change amplitude and change speed of its acoustic emission curve will change significantly. The temperature and confining pressure of the underground environment can be simulated to conduct acoustic emission tests on the rock sample, and the number of ringing times corresponding to different times can be obtained. That is, the degree of interference of the changes of these two factors on the flow capacity of dense sandstone can be obtained through the number of ringing times.

[0084] S150. Determine an acoustic emission interference factor according to the number of ringing times corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors that affect the flow capacity of rock pores.

[0085] In this scheme, a larger acoustic emission interference factor indicates that the reservoir pressure and temperature have less inhibition on the rock flow capacity.

[0086] In this embodiment, the number of ringing times corresponding to the time period with the maximum acoustic emission change may be screened out, and the acoustic emission interference factor may be calculated based on the ringing coefficient.

[0087] Optionally, determining the acoustic emission interference factor according to the number of ringing times corresponding to the different times includes:

[0088] Determine the starting and ending points of the time period with the maximum acoustic emission change;

[0089] An acoustic emission interference factor is calculated based on the starting point, the number of ringings corresponding to the starting point, the ending point, and the number of ringings corresponding to the ending point.

[0090] In this solution, the acoustic emission test time can be pre-divided into multiple stages based on their duration. The stage with the greatest acoustic emission change can be determined from these stages, that is, the time period with the greatest acoustic emission change. For example, if each stage is 200 seconds and the acoustic emission time is 600 seconds, the time period with the greatest acoustic emission change can be found in each of the three stages.

[0091] Furthermore, after determining the time period with the maximum acoustic emission change, the starting point T of the time period with the maximum acoustic emission change can be determined. q and the end point T m .

[0092] Specifically, based on the starting point T q , starting point T q The corresponding ringing times Z q , end point T m , end point T m The corresponding ringing times Z m , the acoustic emission interference factor is calculated.

[0093] By calculating the acoustic emission interference factor, the flow capacity interference of tight sandstone can be quantitatively evaluated based on the acoustic emission interference factor.

[0094] Optionally, calculating the acoustic emission interference factor according to the starting point, the number of ringings corresponding to the starting point, the ending point, and the number of ringings corresponding to the ending point includes:

[0095] The acoustic emission interference factor is calculated using the following formula;

[0096]

[0097] Where SG represents the acoustic emission interference factor, s 3 / times, Z q Indicates the number of rings corresponding to the starting point, Z m Indicates the number of rings corresponding to the termination point, T q Indicates the starting point, T m Indicates the end point.

[0098] For example, assume that rock sample X1 is exposed to a confining pressure of 15 MPa and room temperature, while rock sample X2 is exposed to a confining pressure of 45 MPa and 60°C. An acoustic emission test was conducted to record the change in the number of ringings per second of rock samples X1 and X2 over time. The acoustic emission interference factor was calculated based on the ringing times for rock samples X1 and X2. The results are shown in Table 4.

[0099] Table 4

[0100]

[0101]

[0102] Furthermore, it can be seen from the trend change values ​​shown in Table 4 that the maximum 600s change of the X1 rock sample is between 3280s and 3880s, and the maximum 600s change of the X2 rock sample is between 2880s and 3480s. The corresponding acoustic emission interference factors can be calculated according to the time period with the maximum acoustic emission change.

[0103] S160. Determine a rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary degree; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock.

[0104] In this embodiment, the greater the value of the rock sample communication coefficient is, the greater the reservoir flow coefficient is when the rock sample itself is not disturbed by the external environment.

[0105] In this scheme, the storage capacity index and the rock brittleness interface have a positive correlation with each other. The storage capacity index and the rock brittleness interface can be combined to determine the rock sample communication coefficient.

[0106] Optionally, determining the rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary degree includes:

[0107] The following formula is used to determine the rock sample communication coefficient;

[0108]

[0109] Where NG represents the rock sample communication coefficient, μm 2 , MC represents the rock brittleness boundary degree, Represents the storage capacity index.

[0110] By combining the storage capacity index and the rock brittle boundary degree, the rock sample communication coefficient is calculated, which can be used to quantitatively evaluate the external and internal factors affecting the rock pore flow capacity.

[0111] S170. Determine a reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluate the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient.

[0112] In this scheme, the larger the reservoir flow coefficient value is, the stronger the pore flow capacity of the tight oil reservoir is.

[0113] In this embodiment, the rock sample communication coefficient and the acoustic emission interference factor can be combined to obtain the reservoir flow coefficient, so that the pore flow capacity of the tight oil reservoir can be quantitatively evaluated based on the reservoir flow coefficient.

[0114] Optionally, determining the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor includes:

[0115] The reservoir flow coefficient is determined using the following formula;

[0116]

[0117] Where CCG represents the reservoir flow coefficient, s 6 μm 2 / Second-rate 2 , SG represents the acoustic emission interference factor, and NG represents the rock sample communication coefficient.

[0118] In this scheme, the calculation results of the reservoir flow coefficient are shown in Table 5. The rock sample communication coefficient can be calculated based on the storage capacity index and the rock brittleness boundary using the above formula, and the reservoir flow coefficient can be calculated based on the rock sample communication coefficient and the acoustic emission interference factor.

[0119] Table 5

[0120]

[0121]

[0122] From Table 5, it can be concluded that the pore flow capacity of rock sample X1 is better than that of rock sample X2.

[0123] The technical solution of the embodiment of the present invention is to obtain a rock sample of the target tight sandstone reservoir; determine the storage capacity index based on the porosity and permeability of the rock sample; determine the rock brittle boundary degree based on the mineral content test results and the number of mineral types of the rock sample; simulate the temperature and confining pressure of the underground environment, conduct an acoustic emission test on the rock sample, and obtain the number of ringing times corresponding to different times; determine the acoustic emission interference factor based on the number of ringing times corresponding to different times; determine the rock sample communication coefficient based on the storage capacity index and the rock brittle boundary degree; determine the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluate the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient. By implementing this technical solution, while considering both internal and external factors that affect pore flow capacity, the pore flow capacity can be quantitatively characterized by the reservoir flow coefficient, thereby achieving the purpose of quantitatively evaluating the pore flow capacity of tight oil reservoirs. The evaluation is highly accurate, saving testing costs. The calculation method is simple and feasible, and is also applicable to the evaluation of the pore flow capacity of similar unconventional reservoirs. It has good application prospects and plays a good guiding role in the exploration and development of unconventional resources.

[0124] Example 2

[0125] Figure 2This is a schematic diagram of a device for quantitatively evaluating pore flow capacity provided by the second embodiment of the present invention. Figure 2 As shown, the device includes:

[0126] A rock sample acquisition module 210 is used to obtain rock samples of a target tight sandstone reservoir;

[0127] The storage capacity index determination module 220 is used to determine the storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir;

[0128] The rock brittle boundary determination module 230 is used to determine the rock brittle boundary based on the mineral content test results and the number of mineral species of the rock sample; wherein the rock brittle boundary is used to characterize the potential for micro-crack development in the energy storage after being stimulated by external factors;

[0129] The ringing number obtaining module 240 is used to simulate the temperature and confining pressure of the underground environment, perform an acoustic emission test on the rock sample, and obtain the ringing number corresponding to different time periods;

[0130] The acoustic emission interference factor determination module 250 is configured to determine the acoustic emission interference factor according to the number of ringing times corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors that affect the flow capacity of rock pores;

[0131] A rock sample communication coefficient determination module 260 is configured to determine a rock sample communication coefficient based on the reservoir capacity index and the rock brittleness boundary; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock;

[0132] The pore flow capacity quantitative evaluation module 270 is used to determine the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluate the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient.

[0133] Optionally, the storage capacity index determination module 220 is specifically configured to:

[0134] The porosity and permeability of the rock sample are multiplied to obtain the storage capacity index.

[0135] Optionally, the rock brittle boundary determination module 230 is specifically configured to:

[0136] Determining the test results of each mineral content and the number of mineral types of the rock sample; wherein the test results of each mineral content include the test results of quartz content, dolomite content, calcite content, feldspar content, pyrite content and clay content;

[0137] Determine the optimal coefficient of brittle junction based on the clay content test results and the number of mineral species;

[0138] Determining the junction coefficient according to the optimal coefficient of the brittle junction and the test results of each mineral content;

[0139] The rock brittle boundary degree is calculated based on the boundary coefficient and the number of mineral species.

[0140] Optionally, the acoustic emission interference factor determination module 250 includes:

[0141] A starting point and end point determination submodule is used to determine the starting point and end point of the time period with the maximum acoustic emission change;

[0142] The acoustic emission interference factor calculation submodule is used to calculate the acoustic emission interference factor according to the starting point, the number of ringing times corresponding to the starting point, the ending point, and the number of ringing times corresponding to the ending point.

[0143] Optional, acoustic emission interference factor calculation submodule, specifically used for:

[0144] The acoustic emission interference factor is calculated using the following formula;

[0145]

[0146] Among them, SG represents the acoustic emission interference factor, Z q Indicates the number of rings corresponding to the starting point, Z m Indicates the number of rings corresponding to the termination point, T q Indicates the starting point, T m Indicates the end point.

[0147] Optionally, the rock sample communication coefficient determination module 260 is specifically used to

[0148] The following formula is used to determine the rock sample communication coefficient;

[0149]

[0150] Among them, NG represents the rock sample communication coefficient, MC represents the rock brittle boundary degree, Represents the storage capacity index.

[0151] Optionally, the pore flow capacity quantitative evaluation module 270 is specifically used to:

[0152] The reservoir flow coefficient is determined using the following formula;

[0153]

[0154] Among them, CCG represents the reservoir flow coefficient, SG represents the acoustic emission interference factor, and NG represents the rock sample communication coefficient.

[0155] The pore flow capacity quantitative evaluation device provided by an embodiment of the present invention can execute a pore flow capacity quantitative evaluation method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method.

[0156] Example 3

[0157] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0158] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0159] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0160] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as a method for quantitatively evaluating pore flow capacity.

[0161] In some embodiments, a method for quantitatively evaluating pore flow capacity can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for quantitatively evaluating pore flow capacity described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform a method for quantitatively evaluating pore flow capacity by any other appropriate means (e.g., via firmware).

[0162] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0163] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0164] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0165] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0166] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0167] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0168] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0169] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for quantitatively evaluating pore flow capacity, characterized in that: include: Obtain rock samples from target tight sandstone reservoirs; Determining a storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir; Determine the rock brittleness boundary degree based on the mineral content test results and the number of mineral species of the rock sample; wherein the rock brittleness boundary degree is used to characterize the potential for microcrack development in energy storage after being stimulated by external factors; Simulating the temperature and confining pressure of the underground environment, performing an acoustic emission test on the rock sample, and obtaining the number of ringing times corresponding to different times; Determining an acoustic emission interference factor based on the number of ringings corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors that affect the flow capacity of rock pores; Determining a rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock; The reservoir flow coefficient is determined according to the rock sample communication coefficient and the acoustic emission interference factor, and the pore flow capacity of the tight oil reservoir is quantitatively evaluated according to the reservoir flow coefficient.

2. The method according to claim 1, characterized in that Determine the reservoir capacity index based on the porosity and permeability of the rock sample, including: The porosity and permeability of the rock sample are multiplied to obtain the storage capacity index.

3. The method according to claim 1, characterized in that Based on the mineral content test results and the number of mineral species of the rock sample, the rock brittleness boundary is determined, including: Determining the test results of each mineral content and the number of mineral types of the rock sample; wherein the test results of each mineral content include the test results of quartz content, dolomite content, calcite content, feldspar content, pyrite content and clay content; Determining the optimal coefficient of brittle junction based on the clay content test results and the number of mineral species; Determining the junction coefficient according to the optimal coefficient of the brittle junction and the test results of each mineral content; The rock brittle boundary degree is calculated based on the boundary coefficient and the number of mineral species.

4. The method according to claim 1, wherein Determining an acoustic emission interference factor according to the number of ringing times corresponding to the different times includes: Determine the starting and ending points of the time period with the maximum acoustic emission change; An acoustic emission interference factor is calculated based on the starting point, the number of ringings corresponding to the starting point, the ending point, and the number of ringings corresponding to the ending point.

5. The method according to claim 4, characterized in that The acoustic emission interference factor is calculated based on the starting point, the number of ringings corresponding to the starting point, the ending point, and the number of ringings corresponding to the ending point, including: The acoustic emission interference factor is calculated using the following formula; Among them, SG represents the acoustic emission interference factor, Z q Indicates the number of rings corresponding to the starting point, Z m Indicates the number of rings corresponding to the termination point, T q Indicates the starting point, T m Indicates the end point.

6. The method according to claim 1, characterized in that According to the storage capacity index and rock brittleness boundary degree, the rock sample communication coefficient is determined, including: The following formula is used to determine the rock sample communication coefficient; Among them, NG represents the rock sample communication coefficient, MC represents the rock brittle boundary degree, Represents the storage capacity index.

7. The method according to claim 1, characterized in that Determine the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, including: The reservoir flow coefficient is determined using the following formula; Among them, CCG represents the reservoir flow coefficient, SG represents the acoustic emission interference factor, and NG represents the rock sample communication coefficient.

8. A device for quantitatively evaluating pore flow capacity, characterized in that: include: A rock sample acquisition module is used to obtain rock samples from target tight sandstone reservoirs; A storage capacity index determination module is used to determine the storage capacity index based on the porosity and permeability of the rock sample; wherein the storage capacity index is used to characterize the storage capacity of the fluid in the porous medium of the reservoir; A rock brittle boundary determination module is used to determine the rock brittle boundary based on the mineral content test results and the number of mineral types of the rock sample; wherein the rock brittle boundary is used to characterize the potential for micro-crack development after energy storage is stimulated by external factors; A ringing number obtaining module is used to simulate the temperature and confining pressure of the underground environment, perform an acoustic emission test on the rock sample, and obtain the ringing number corresponding to different times; an acoustic emission interference factor determination module, configured to determine an acoustic emission interference factor according to the number of ringing times corresponding to the different times; wherein the acoustic emission interference factor is used to characterize external factors affecting the flow capacity of rock pores; a rock sample communication coefficient determination module, configured to determine the rock sample communication coefficient based on the storage capacity index and the rock brittleness boundary; wherein the rock sample communication coefficient is used to characterize external and internal factors that affect the pore flow capacity of the rock; The pore flow capacity quantitative evaluation module is used to determine the reservoir flow coefficient based on the rock sample communication coefficient and the acoustic emission interference factor, and to quantitatively evaluate the pore flow capacity of the tight oil reservoir based on the reservoir flow coefficient.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform a method for quantitatively evaluating pore flow capacity according to any one of claims 1 to 7.

10. A computer-readable medium, characterized in that The computer-readable medium stores computer instructions, and the computer instructions are used to enable a processor to implement a quantitative evaluation method for pore flow capacity according to any one of claims 1 to 7 when executed.

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