Pore flow capacity quantitative evaluation method and device, electronic equipment and medium

Abstract

The invention discloses a quantitative evaluation method and device for pore flow capacity, electronic equipment and a medium. The method comprises the following steps: acquiring a rock sample of a target compact sandstone reservoir; determining a reservoir capacity index according to the porosity and permeability of the rock sample; determining the rock brittleness boundary degree according to the mineral content test result and the mineral type number of the rock sample; simulating the temperature and confining pressure of an underground environment, and carrying out an acoustic emission test on the rock sample to obtain ringing times corresponding to different times; determining an acoustic emission interference factor according to the ringing times corresponding to different times; determining a rock sample communication coefficient according to the reservoir capacity index and the rock brittleness boundary degree; and according to the rock sample communication coefficient and the acoustic emission interference factor, determining a reservoir flow coefficient, and according to the reservoir flow coefficient, carrying out quantitative evaluation on the compact oil reservoir pore flow capability. According to the technical scheme, the pore flow capacity is quantitatively characterized through the reservoir flow coefficient, and the purpose of quantitatively evaluating the pore flow capacity of the tight oil reservoir can be achieved.

Description

Technical Field

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

[0002] Tight oil reservoirs are extremely rich in resources and have great development potential. They have important exploration and development prospects in the field of unconventional oil and gas. Finding favorable reservoir quality is the primary goal of exploration and development, and is the key to achieving a breakthrough in single well production. Among them, pore flow capacity is a core factor that directly affects the potential of oil and gas exploration resources and scale-effective development. However, with the shift to unconventional resource exploration and development, tight oil reservoirs are usually thin interlayers of sand and mud, with natural fractures and strong heterogeneity. How to further increase single well production and fully release oil and gas reservoirs, reservoir fluidity evaluation is the basis for horizontal well volume fracturing well selection and section selection.

[0003] Since there are many factors affecting the fluidity of tight oil reservoirs and their relationships are complex, domestic and foreign scholars have done a lot of research on the evaluation of reservoir fluidity. Currently, there are mainly two methods: a method for characterizing the oil-gas phase equilibrium and flow capacity of rock porous 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 and evaluate the pore flow capacity and thus the fluidity of reservoirs by establishing prediction models and experimental simulations. However, the evaluation indicators are single and the models and experiments are quite different from 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 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] Determine a storage capacity index according to 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 brittle interface degree according to the mineral content test results and the number of mineral types of the rock sample; wherein the rock brittle interface degree is used to characterize the potential for microcrack development after energy storage is stimulated by external factors;

[0010] 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;

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

[0012] Determine the rock sample communication coefficient according to the reservoir capacity index and the rock brittleness interface; wherein the rock sample communication coefficient is used to characterize the external and internal factors that affect the rock pore flow capacity;

[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 of target tight sandstone reservoirs;

[0016] A storage capacity index determination module, used to determine the storage capacity index according to 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 according to 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 microcrack development of energy storage after being stimulated by external factors;

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

[0019] An acoustic emission interference factor determination module, used 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;

[0020] A rock sample communication coefficient determination module is used to determine the rock sample communication coefficient according to the reservoir capacity index and the rock brittleness boundary degree; wherein the rock sample communication coefficient is used to characterize the external factors and internal factors that affect the rock pore flow capacity;

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

[0022] According to another aspect of the present invention, an electronic device is provided, the electronic device 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 execute a method for quantitatively evaluating pore flow capacity described in 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 is to obtain a rock sample of the target tight sandstone reservoir; determine the storage capacity index according to the porosity and permeability of the rock sample; determine the rock brittle interface according to 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 ringings corresponding to different times; determine the acoustic emission interference factor according to the number of ringings corresponding to different times; determine the rock sample communication coefficient according to the storage capacity index and the rock brittle interface; determine the reservoir flow coefficient according to the rock sample communication coefficient and the acoustic emission interference factor, and quantitatively evaluate the pore flow capacity of the tight oil reservoir according to the reservoir flow coefficient. This technical solution simultaneously considers the 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, and the evaluation accuracy is high.

[0028] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily 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 is a flow chart of a method for quantitatively evaluating pore flow capacity provided according to Embodiment 1 of the present invention;

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

[0032] Figure 3 It is a structural schematic 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 scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the term "target" and the like in the specification 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 data 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 of their variations 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 that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Embodiment 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 a tight oil reservoir. 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 of the target tight sandstone reservoir.

[0038] In this scheme, the target tight sandstone reservoir can be cored, and the cored rock sample can be made into a standard rock sample, and then the water 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 coring depth of 2000-2500m, and the cored rock samples can be made into two standard rock samples with a diameter of 2.5cm and a length of 5cm. 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 according to 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 properties and the stronger the pore flow capacity.

[0042] In this embodiment, the porosity and permeability of the rock sample can be tested respectively by 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 the rock sample, the storage capacity of the fluid in the porous medium of the reservoir can be quantitatively evaluated.

[0049] For example, the porosity of the dried rock samples 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 brittle boundary degree according to the test results of the mineral content of the rock sample and the number of mineral types; wherein the rock brittle 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 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 types can be combined and calculated to obtain the rock brittle boundary degree.

[0056] Optionally, the rock brittle boundary degree is determined according to the test results of the mineral content of the rock sample and the number of mineral types, including 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] Exemplarily, 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 coefficient of brittle interface according to the clay content test results and the number of mineral species;

[0063] In this embodiment, clay minerals are boundary inhibition minerals, and other minerals are boundary promotion minerals, that is, quartz, dolomite, calcite, feldspar, and pyrite are boundary promotion minerals. The optimal brittle boundary coefficient can be determined based on the clay content test results and the number of mineral types according to a predetermined brittle boundary optimal coefficient calculation formula.

[0064] Specifically, the optimal coefficient of the brittle junction is calculated using the following formula;

[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 interface coefficient according to the optimal coefficient of the brittle interface 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 interface degree according to the interface coefficient and the number of mineral species.

[0073] In this scheme, the rock brittle interface degree can be calculated according to the predetermined rock brittle interface degree calculation formula, based on the interface 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 being stimulated by external factors can be quantitatively evaluated based on the differences in rock mineral composition.

[0081] S140, simulating the temperature and confining pressure of the 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 of different temperature and confining pressure, 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, and the acoustic emission test can be carried out on the rock sample to obtain the number of ringing times corresponding to different times. That is, the interference degree of the changes of these two 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, the larger the acoustic emission interference factor is, the less the reservoir pressure and temperature inhibit the rock flow capacity.

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

[0090] In this scheme, the acoustic emission test time can be divided into multiple stages according to the length of time in advance, and the stage with the largest acoustic emission change can be determined from the multiple stages, that is, the time period with the largest acoustic emission change can be determined. For example, taking 200 seconds as one stage and assuming that the acoustic emission time is 600 seconds, the time period with the largest acoustic emission change can be found from the three stages respectively.

[0091] Further, 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, the acoustic emission interference factor is calculated 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, including:

[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 the environment of rock sample X1 is a confining pressure of 15 MPa and a temperature of room temperature; the environment of rock sample X2 is a confining pressure of 45 MPa and a temperature of 60°C. The acoustic emission test records the change of the number of ringings per second of rock samples X1 and X2 over time. The acoustic emission interference factor is calculated based on the number of ringings of rock samples X1 and X2, and 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, and the corresponding acoustic emission interference factors can be calculated according to the maximum time period of acoustic emission change.

[0103] S160. Determine a rock sample communication coefficient based on the reservoir 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 reservoir capacity index and the rock brittle interface degree have a positive correlation with each other. The reservoir capacity index and the rock brittle interface degree can be combined to determine the rock sample communication coefficient.

[0106] Optionally, the rock sample communication coefficient is determined according to the reservoir capacity index and the rock brittleness interface, including:

[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 reservoir capacity index and the rock brittle interface, the rock sample communication coefficient is calculated, and the external and internal factors affecting the pore flow capacity of the rock can be quantitatively evaluated based on the rock sample communication coefficient.

[0111] S170, determining a 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.

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

[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 according to 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 according to the reservoir capacity index and the rock brittle interface by the above formula, and the reservoir flow coefficient can be calculated according to 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 a target tight sandstone reservoir; determine a storage capacity index based on the porosity and permeability of the rock sample; determine the rock brittle interface 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 interface; 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 the internal and external factors that affect the pore flow capacity, the pore flow capacity is quantitatively characterized by the reservoir flow coefficient, so as to achieve the purpose of quantitative evaluation of the pore flow capacity of tight oil reservoirs, and the evaluation accuracy is high, saving the test cost, and the calculation method is simple and feasible, which 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] Embodiment 2

[0125] Figure 2This is a schematic diagram of the structure of a quantitative evaluation device for pore flow capacity provided in Example 2 of the present invention. Figure 2 As shown, the device comprises:

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

[0127] A reservoir capacity index determination module 220 is used to determine a reservoir capacity index according to the porosity and permeability of the rock sample; wherein the reservoir capacity index is used to characterize the reservoir 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 according to 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 microcrack development of 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 times;

[0130] The acoustic emission interference factor determination module 250 is used 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 the external factors that affect the flow capacity of rock pores;

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

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

[0136] Determine the test results of the mineral content of the rock sample and the number of mineral types; 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;

[0137] Determine the optimal coefficient of brittle interface according to the clay content test results and the number of mineral species;

[0138] Determine the interface coefficient according to the optimal coefficient of the brittle interface 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 an ending point determination submodule is used to determine the starting point and the ending 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 ringings corresponding to the starting point, the ending point, and the number of ringings corresponding to the ending point.

[0143] Optionally, the acoustic emission interference factor calculation submodule is 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 for:

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

[0156] Embodiment 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 required herein.

[0158] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and 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 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0159] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.

[0160] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The 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 may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for quantitatively evaluating pore flow capacity described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a method for quantitatively evaluating pore flow capacity by any other appropriate means (e.g., by means of firmware).

[0162] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

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

[0165] To provide interaction with a user, the systems and techniques described herein may 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0166] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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 a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0168] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0169] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope 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; Determine a storage capacity index according to 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 brittle interface degree according to the mineral content test results and the number of mineral types of the rock sample; wherein the rock brittle interface degree is used to characterize the potential for microcrack development after energy storage is stimulated by external factors; 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; Determine the acoustic emission interference factor according to the number of ringings corresponding to the different times; wherein the acoustic emission interference factor is used to characterize the external factors that affect the flow capacity of rock pores; Determine the rock sample communication coefficient according to the reservoir capacity index and the rock brittleness interface; wherein the rock sample communication coefficient is used to characterize the external and internal factors that affect the rock pore flow capacity; 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 According to the porosity and permeability of the rock sample, the reservoir capacity index is determined, 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 According to the test results of the mineral content and the number of mineral species of the rock sample, the rock brittleness boundary is determined, including: Determine the test results of the mineral content of the rock sample and the number of mineral types; 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; Determine the optimal coefficient of brittle interface according to the clay content test results and the number of mineral species; Determine the interface coefficient according to the optimal coefficient of the brittle interface 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, characterized in that: Determining the 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; The acoustic emission interference factor is calculated 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.

5. The method according to claim 4, characterized in that The acoustic emission interference factor is calculated 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, 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 reservoir capacity index and rock brittleness boundary, 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 According to the rock sample communication coefficient and the acoustic emission interference factor, the reservoir flow coefficient is determined, 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 of target tight sandstone reservoirs; A storage capacity index determination module, used to determine the storage capacity index according to 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 according to 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 microcrack development of energy storage after being stimulated by external factors; A ringing frequency obtaining module is used to simulate the temperature and confining pressure of the underground environment, conduct an acoustic emission test on the rock sample, and obtain the ringing frequency corresponding to different times; An acoustic emission interference factor determination module, used 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; A rock sample communication coefficient determination module is used to determine the rock sample communication coefficient according to the reservoir capacity index and the rock brittleness boundary degree; wherein the rock sample communication coefficient is used to characterize the external factors and internal factors that affect the rock pore flow capacity; The pore flow capacity quantitative evaluation module is used to determine the reservoir flow coefficient according to the rock sample communication coefficient and the acoustic emission interference factor, and to quantitatively evaluate the pore flow capacity of the tight oil reservoir according to 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, and the computer program is executed by the at least one processor so that the at least one processor can 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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