Method, device and equipment for establishing dynamic permeability model and readable storage medium

Abstract

The invention discloses a method, a device and equipment for establishing a dynamic permeability model and a readable storage medium. The method comprises the following steps: selecting a target production well meeting a preset condition from each production well; calculating the dynamic permeability of each perforation section in the target production well; calculating a permeability dimensionless ratio based on the dynamic permeability of each perforation section; based on a preset logging curve and the permeability dimensionless ratio, obtaining a permeability ratio model through a Kriging method; and multiplying the static permeability model by the permeability ratio model to obtain a dynamic permeability model. According to the invention, the technical problem of low accuracy of the correction result of the permeability in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of carbonate reservoir development technology, and in particular to a method, apparatus, equipment, and readable storage medium for establishing a dynamic permeability model. Background Technology

[0002] Currently, the permeability model for bioclastic limestone is established based on rock classification and obtained through porosity-permeability transformation. Different reservoir rock types have similar geological origins, possess the same pore structure and physical properties. Under the control of rock type, a permeability model is obtained through porosity cloud transformation. The porosity transformation yields a static permeability model, which needs to be dynamically corrected to obtain a dynamic permeability model.

[0003] In related technologies, permeability correction typically employs a direct assignment method. Based on production dynamic data, multipliers are applied to the permeability of different rock types, causing the overall permeability model to increase or decrease exponentially. However, this method fails to consider the differences in the contribution of different rock types to production, or the overall effect of combinations of different rock types. Applying a general assignment method to a single rock type reduces the accuracy of the correction results. For oil wells in non-perforated sections or without well testing, using fixed correction values ​​to correct static permeability models results in low accuracy and high uncertainty in the corrected permeability. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and readable storage medium for establishing a dynamic permeability model, which can solve the technical problem of low accuracy of permeability correction results in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] In a first aspect, embodiments of the present invention provide a method for establishing a dynamic penetration rate model, the method comprising:

[0007] Select target production wells that meet the preset conditions from among the production wells;

[0008] Calculate the dynamic permeability of each perforated section in the target production well;

[0009] The dimensionless permeability ratio is calculated based on the dynamic permeability of each perforation section.

[0010] Based on the preset logging curves and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

[0011] Multiplying the static permeability model by the permeability ratio model yields the dynamic permeability model.

[0012] Secondly, embodiments of the present invention provide an apparatus for establishing a dynamic permeability model, the apparatus comprising:

[0013] The selection module is configured to select target production wells that meet preset conditions from among the various production wells;

[0014] The first calculation module is configured to calculate the dynamic permeability of each perforation section in the target production well;

[0015] The second calculation module is configured to calculate the dimensionless permeability ratio based on the dynamic permeability of each perforation section.

[0016] The model building module is configured to obtain a permeability ratio model based on a preset logging curve and the dimensionless permeability ratio using the Kriging method.

[0017] The third calculation module is configured to multiply the static permeability model by the permeability ratio model to obtain the dynamic permeability model.

[0018] Thirdly, embodiments of the present invention also provide an electronic device, including: a memory and a processor; the processor is configured to read and execute a computer program stored in the memory to implement the steps of the aforementioned method for establishing a dynamic penetration rate model.

[0019] Fourthly, embodiments of the present invention also provide a computer storage medium storing computer-executable instructions, which, when executed, implement the steps of the aforementioned method for establishing a dynamic penetration rate model.

[0020] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the aforementioned method for establishing a dynamic penetration rate model.

[0021] The beneficial effects of the technical solutions provided by the embodiments of the present invention include:

[0022] Select target production wells that meet the preset conditions from each production well; calculate the dynamic permeability of each perforation section in the target production well; calculate the dimensionless permeability ratio based on the dynamic permeability of each perforation section. Different rock types are given different influence weights in the process of calculating the dimensionless permeability ratio. It is not only based on the thickness of different rock types, but also takes into account the non-uniform contribution of different rock types to production. The splitting result is consistent with the actual situation in reservoir development.

[0023] Based on the preset logging curves and the dimensionless permeability ratio, a permeability ratio model is obtained through the Kriging method. The dimensionless permeability ratio is calibrated through the logging curves, and logging interpretation is performed on non-perforated sections and production wells without well test data. The permeability ratio model is generated through spatial interpolation, and the correction results are reasonably extended to the entire work area.

[0024] Multiplying the static permeability model with the permeability ratio model yields the dynamic permeability model. The permeability model is then corrected based on well test data and production test data. The static permeability model simulated by static data is corrected into a dynamic permeability model, making it more consistent with the actual underground conditions and development characteristics of the reservoir. This is beneficial for reservoir numerical simulation and historical fitting, and greatly improves the accuracy of the permeability correction results.

[0025] This invention solves the technical problem of low accuracy in permeability correction results in related technologies. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating an embodiment of the method for establishing a dynamic penetration rate model according to the present invention.

[0028] Figure 2 This is a schematic diagram of the oil and gas production composition in an oil well according to an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of permeability correction in an oil well according to an embodiment of the present invention;

[0030] Figure 4 for Figure 1 A detailed flowchart of step S20;

[0031] Figure 5 for Figure 1 A detailed flowchart of step S30;

[0032] Figure 6 for Figure 1 A detailed flowchart of step S40;

[0033] Figure 7 A schematic diagram of the functional modules of an embodiment of the apparatus for establishing a dynamic permeability model according to the present invention;

[0034] Figure 8This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] In a first aspect, embodiments of the present invention provide a method for establishing a dynamic penetration rate model.

[0038] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the method for establishing a dynamic penetration rate model according to the present invention. Figure 1 As shown, the methods for establishing a dynamic penetration rate model include:

[0039] Step S10: Select target production wells that meet preset conditions from among the various production wells;

[0040] In this embodiment, the preset conditions include: a first preset condition and a second preset condition; wherein, the first preset condition is that both well testing and production logging (PLT) are performed, and the second preset condition is that no production logging is performed, well testing is performed, and there is only one perforation section. The first preset condition has a higher priority than the second preset condition. That is, among all production wells, production wells that have both well testing and production logging (PLT) are selected as the target production wells, and production wells that have no PLT, well testing, and only one perforation section are selected as the next target production wells.

[0041] Step S20: Calculate the dynamic permeability of each perforated section in the target production well;

[0042] In some specific embodiments, reference is made to Figure 4 , Figure 4 for Figure 1 A detailed flowchart of step S20. (See attached diagram.) Figure 4 As shown, step S20 includes:

[0043] Step S201: Obtain the total oil and gas production, total formation coefficient, and thickness of each perforated section of the target production well;

[0044] Step S202: Obtain the oil and gas production of each perforated section in the target production well through production logging tests;

[0045] Step S203: Divide the oil and gas production of each perforation section by the total oil and gas production, and multiply the quotient by the total formation coefficient to obtain the formation coefficient of each perforation section.

[0046] Step S204: Divide the formation coefficient of each perforation section by the thickness of the corresponding perforation section to obtain the dynamic permeability of each perforation section in the target production well.

[0047] In this embodiment, after selecting the target production well, the total oil and gas production, total formation coefficient, and thickness of each perforated section of the target production well are obtained. Wherein, the total formation coefficient = total dynamic permeability K. 动 *Total thickness H of the perforation section.

[0048] Reference Figure 2 , Figure 2 This is a schematic diagram illustrating the composition of oil and gas production in an oil well according to an embodiment of the present invention. Figure 2 As shown, a well may contain multiple discontinuous oil-producing sections (also known as perforated sections). The total amount of oil and gas produced at the wellhead is the sum of the oil and gas produced from formations at different depths underground. Some wells may only have one producing section, but usually multiple sections produce oil simultaneously. To determine which underground layer the oil flowing out of the wellhead originates from, production logging testing (PLT) is required. Production logging testing can obtain the oil and gas production of each perforated section in the target production well. The sum of the oil and gas production of each perforated section equals the total oil and gas production of the target production well.

[0049] The formation coefficient for each perforated section is obtained by dividing the oil and gas production of each perforated section by the total oil and gas production, and then multiplying the quotient by the total formation coefficient. The sum of the formation coefficients for each perforated section equals the total formation coefficient of the target production well.

[0050] Specifically,

[0051] After obtaining the formation coefficient of each perforation section, the dynamic permeability of each perforation section in the target production well is obtained by dividing the formation coefficient of each perforation section by the thickness of the corresponding perforation section.

[0052] Specifically,

[0053] Step S30: Calculate the dimensionless permeability ratio based on the dynamic permeability of each perforation section;

[0054] In some specific embodiments, reference is made to Figure 5 , Figure 5 for Figure 1 A detailed flowchart of step S30. (See attached diagram.) Figure 5 As shown, step S30 includes:

[0055] Step S301: Based on the dynamic permeability of each perforation section, calculate the dynamic permeability of each rock type corresponding to each perforation section;

[0056] In some specific embodiments, step S301 includes:

[0057] For the i-th perforation segment, obtain the thickness and weight of each rock type corresponding to the i-th perforation segment;

[0058] Substitute the dynamic permeability of the i-th perforation section, the thickness and weight of each rock type corresponding to the i-th perforation section into the first preset formula to calculate the dynamic permeability of each rock type corresponding to the i-th perforation section.

[0059] The first preset formula is as follows:

[0060]

[0061] In the formula, k i Let n represent the dynamic permeability of the i-th perforation section, n represent the total number of each rock type, and k represent the total number of perforations. ij h represents the dynamic permeability of the j-th rock type corresponding to the i-th perforation segment, j∈[1,n] ij q represents the thickness of the j-th rock type corresponding to the i-th perforation segment. ij This represents the weight of the j-th rock type corresponding to the i-th perforation segment;

[0062] By analogy, the dynamic permeability of each rock type corresponding to each perforation section can be calculated.

[0063] In this embodiment, a thickness-weighted average method is proposed for the dynamic permeability of perforated sections divided into sections with different rock types. Weighting factors for different rock types are established. The strong heterogeneity of bioclastic limestone leads to significant differences in the contribution of different rock types to production. By assigning influence weights to different rock types, the dynamic permeability of the divided sections better reflects actual seepage characteristics. (Refer to...) Figure 3 , Figure 3 This is a schematic diagram illustrating permeability correction in an oil well according to an embodiment of the present invention. Figure 3 As shown, for the i-th perforation segment, taking rock type b and rock type a as examples, the thickness and weight of rock type b and rock type a are obtained.

[0064] The dynamic permeability of each perforation section is the thickness-weighted sum of the dynamic permeability of all rock types within the perforation section, i.e.

[0065] Based on the thickness-weighted average of different rock types, the dynamic permeability of the i-th perforation section is divided, i.e., each permeability value is multiplied by its corresponding thickness, summed, and then divided by the total thickness. In the perforation section, the optimal rock type has a weight of 0.6, the second-level rock type has a weight of 0.3, the third-level rock type has a weight of 0.1, and other rock types have a weight of 0. Where k i Let n represent the dynamic permeability of the i-th perforation section, n represent the total number of each rock type, and k represent the total number of perforations. ij h represents the dynamic permeability of the j-th rock type corresponding to the i-th perforation segment, j∈[1,n] ij q represents the thickness of the j-th rock type corresponding to the i-th perforation segment. ij This represents the weight of the j-th rock type corresponding to the i-th perforation segment.

[0066] Substitute the dynamic permeability of the i-th perforation segment, the thickness and weight of each rock type corresponding to the i-th perforation segment into the first preset formula. The dynamic permeability for each rock type corresponding to the i-th perforation section can then be calculated. This process can be repeated for each perforation section to calculate the dynamic permeability for each rock type; details will not be elaborated here.

[0067] In this embodiment, different rock types are assigned different influence weights, and the division is not based solely on the thickness of different rock types. It takes into account the non-uniform contribution of different rock types to production, and the division results are consistent with the actual situation in reservoir development.

[0068] Step S302: Calculate the average static permeability for each rock type;

[0069] In some specific embodiments, step S302 includes:

[0070] Obtain the static permeability corresponding to the i′th rock type and the corresponding static permeability model mesh thickness;

[0071] Substitute the static permeability corresponding to the i′ rock type and the static permeability model mesh thickness corresponding to the static permeability into the second preset formula to calculate the average static permeability of the i′ rock type.

[0072] The second preset formula is as follows:

[0073]

[0074] In the formula, k i′静 Let represent the average static permeability of the i′-th rock type, n′ represent the total number of static permeabilities, and k represent the average static permeability of the i′-th rock type. i′j′h represents the j′-th static permeability corresponding to the i′-th rock type, where j′∈[1, n′] i′j′ This represents the static permeability model mesh thickness corresponding to the j′ static permeability for the i′ rock type.

[0075] In this embodiment, since the permeability of each rock type varies within a certain range, the average static permeability of each rock type is typically calculated using a thickness-weighted method. This involves obtaining the static permeability corresponding to the i′th rock type and the corresponding static permeability model mesh thickness, and then substituting these values ​​into the second preset formula. The average static permeability of the i′th rock type can then be calculated. Where k i′静 Let represent the average static permeability of the i′-th rock type, n′ represent the total number of static permeabilities, and k represent the average static permeability of the i′-th rock type. i′j′ h represents the j′-th static permeability corresponding to the i′-th rock type, where j′∈[1, n′] i′j′ This represents the static permeability model mesh thickness corresponding to the j′ static permeability for the i′ rock type.

[0076] Continue to refer to Figure 3 , Figure 3 The average static permeability of rock type a corresponding to the perforated section with oil and gas production of a is denoted as a. The calculation process for the average static permeability of other rock types is similar and will not be repeated here.

[0077] Step S303: Divide the dynamic permeability of each rock type by the average static permeability of that rock type, and use the quotient as the dimensionless permeability ratio.

[0078] In this embodiment, we continue to refer to... Figure 3 , k a1 k represents the dynamic permeability of rock type a corresponding to the perforated section with oil and gas production of a. 静1 R represents the average static permeability of rock type a corresponding to the perforated section with oil and gas production of a. k1 This represents the dimensionless permeability ratio of rock type a corresponding to the perforated section with oil and gas production of 'a'. The calculation process for the dimensionless permeability ratio of other rock types is similar and will not be repeated here. For rock types with an influence weight of 0, the dimensionless permeability ratio is set to 1.

[0079] Step S40: Based on the preset logging curve and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

[0080] In some specific embodiments, reference is made to Figure 6 , Figure 6 for Figure 1 A detailed flowchart of step S40. (See attached diagram.) Figure 6 As shown, step S40 includes:

[0081] Step S401: Based on the preset logging curve and the dimensionless permeability ratio, establish a regression equation;

[0082] In some specific embodiments, step S401 includes:

[0083] Calculate the arithmetic mean of each preset logging curve, wherein the preset logging curves include: natural gamma curve, resistivity curve and density curve;

[0084] The arithmetic mean and the dimensionless ratio of permeability are calibrated and fitted to establish a regression equation R. k =2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 ;

[0085] In the formula, R k GR represents the dimensionless ratio of permeability, RT represents the arithmetic mean of the natural gamma curve, and DEN represents the arithmetic mean of the resistivity curve.

[0086] In this embodiment, it is proposed to use logging curves to calibrate the dimensionless permeability ratio. By optimizing logging curves based on lithology, physical properties, and oil-bearing properties, the logging curve value of the perforated section is determined and fitted with the dimensionless permeability ratio of the perforated section to establish a regression equation. Based on this equation, logging interpretation is performed on all wells to obtain the permeability ratio factor of all wells, thus extending the research results of the perforated section to the entire work area.

[0087] Continue to refer to Figure 3 The preset logging curves include natural gamma curve (GR), resistivity curve (RT), and density curve (DEN). The logging curves are continuous data. The GR, RT, and DEN values ​​corresponding to each rock type are not constants. Within the depth range corresponding to the same rock type, the arithmetic mean of each preset logging curve is calculated. That is, the arithmetic mean of the GR, RT, and DEN values ​​is used as the GR, RT, and DEN values ​​for that rock type.

[0088] The arithmetic mean was calibrated and fitted to the dimensionless ratio of permeability for different rock types to obtain the regression equation R. k =F(GR, RT, DEN) = 2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 .

[0089] Step S402: Based on the regression equation, calculate the permeability ratio of the non-perforated section and all untested wells;

[0090] In some specific embodiments, step S402 includes:

[0091] Substituting GR, RT, and DEN of the non-perforated section into the regression equation, the permeability ratio of the non-perforated section is calculated.

[0092] Substitute the GR, RT, and DEN values ​​for each untested well into the regression equation to calculate the permeability ratios for all untested wells.

[0093] In this embodiment, an oilfield may contain hundreds or even thousands of wells, but the proportion of wells with available well test data is typically small. A single well can reach depths of several thousand meters, and the reservoir thickness can reach hundreds of meters. The cumulative thickness of the perforated section is only tens, hundreds, or a few meters. Therefore, the amount of data calculated within the perforated section is very limited. Spatial interpolation based on such limited data results in highly uncertain data volumes. However, every well has logging curves, from shallow to deep, and the permeability ratio Rk of the non-perforated section can be calculated from these curves. This ensures that all wells within the reservoir have data, and well logging interpretation can be performed even in wells without well test data, significantly increasing the number of permeability ratios Rk and greatly reducing uncertainty during spatial interpolation. Therefore, substituting GR, RT, and DEN of the non-perforated section into the regression equation R... k =2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 The permeability ratio of the non-perforated section can then be calculated. Substituting the GR, RT, and DEN values ​​for each untested well into the regression equation R... k =2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 This allows us to calculate the permeability ratios of all untested wells.

[0094] Step S403: Based on the permeability ratio and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

[0095] In this embodiment, the dimensionless permeability ratios of the perforated sections, the permeability ratios of the non-perforated sections, and the permeability ratios of all untested wells are sampled into the geological model grid. A permeability ratio model is then obtained through Kriging interpolation. Kriging is a regression algorithm that uses covariance functions to spatially model and predict (interpolate) stochastic processes / random fields.

[0096] Step S50: Multiply the static permeability model by the permeability ratio model to obtain the dynamic permeability model.

[0097] In this embodiment, after obtaining the permeability ratio model, each grid in the model corresponds to a specific value. The static permeability model is multiplied by the three-dimensional permeability ratio model to achieve dynamic correction of the static permeability model, resulting in a dynamic permeability model. This ensures that the data of each grid in the work area model is correctable. Moreover, correcting the static permeability model simulated by static data into a dynamic permeability model makes it more consistent with the actual underground conditions and development characteristics of the reservoir. This is beneficial for reservoir numerical simulation and historical fitting, and greatly improves the accuracy of the permeability correction results.

[0098] In this embodiment, target production wells that meet preset conditions are selected from various production wells; the dynamic permeability of each perforation section in the target production well is calculated; a dimensionless permeability ratio is calculated based on the dynamic permeability of each perforation section; a permeability ratio model is obtained by using the Kriging method based on preset logging curves and the dimensionless permeability ratio; and a dynamic permeability model is obtained by multiplying the static permeability model with the permeability ratio model.

[0099] The permeability field is constructed based on static data. However, the actual underground conditions of an oil reservoir are influenced by multiple factors such as pressure, fluid, wellbore, and development methods, leading to a mismatch between the static permeability field and the actual development situation. Therefore, the static permeability field needs to be corrected. Well testing yields the product of the production, overall permeability, and cumulative thickness for each well. Production testing data provides the production for each perforated section. By dividing the production data, the permeability and thickness product for each perforated section can be determined. Perforated sections typically contain multiple rock types. Different rock types in bioclastic limestone exhibit significant differences in permeability and pore structure, contributing differently to production during development. Therefore, different rock types are assigned different weights, and the permeability is divided based on the weighted thickness to obtain the dynamic permeability for each rock type within the perforated section. Since the data obtained within the perforated section is limited, the research results are extended to all wells based on logging calibration and interpretation to establish a permeability ratio factor data body, thereby achieving permeability correction for the entire working area. This greatly improves the accuracy of the permeability correction results. Through this embodiment, the technical problem of low accuracy of permeability correction results in related technologies is solved.

[0100] Secondly, embodiments of the present invention also provide an apparatus for establishing a dynamic permeability model.

[0101] In one embodiment, reference is made to Figure 7 , Figure 7 This is a functional module diagram of an embodiment of the apparatus for establishing a dynamic permeability model according to the present invention. Figure 7 As shown, the apparatus for establishing a dynamic permeability model includes:

[0102] The selection module 10 is configured to select target production wells that meet preset conditions from among the production wells;

[0103] The first calculation module 20 is configured to calculate the dynamic permeability of each perforation section in the target production well;

[0104] The second calculation module 30 is configured to calculate the dimensionless permeability ratio based on the dynamic permeability of each perforation section.

[0105] The model building module 40 is configured to obtain a permeability ratio model based on a preset logging curve and the dimensionless permeability ratio using the Kriging method.

[0106] The third calculation module 50 is configured to multiply the static permeability model with the permeability ratio model to obtain the dynamic permeability model.

[0107] Optionally, in one embodiment, the preset conditions include: a first preset condition and a second preset condition;

[0108] The first preset condition is that both well testing and production logging tests are performed, while the second preset condition is that there is no production logging test, well testing is performed, and there is only one perforation section. The first preset condition has a higher priority than the second preset condition.

[0109] Optionally, in one embodiment, the first computing module 20 is configured to:

[0110] Obtain the total oil and gas production, total formation coefficient, and thickness of each perforated section of the target production well;

[0111] The oil and gas production of each perforated section in the target production well was obtained through production logging tests.

[0112] The formation coefficient for each perforation section is obtained by dividing the oil and gas production of each perforation section by the total oil and gas production, and then multiplying the quotient by the total formation coefficient.

[0113] The dynamic permeability of each perforated section in the target production well is obtained by dividing the formation coefficient of each perforated section by the thickness of the corresponding perforated section.

[0114] Optionally, in one embodiment, the second computing module 30 is configured to:

[0115] Based on the dynamic permeability of each perforation section, the dynamic permeability of each rock type corresponding to each perforation section is calculated;

[0116] Calculate the average static permeability for each rock type;

[0117] The dynamic permeability of each rock type is divided by the average static permeability of that rock type, and the quotient is used as the dimensionless permeability ratio.

[0118] Optionally, in one embodiment, the second computing module 30 is configured to:

[0119] For the i-th perforation segment, obtain the thickness and weight of each rock type corresponding to the i-th perforation segment;

[0120] Substitute the dynamic permeability of the i-th perforation section, the thickness and weight of each rock type corresponding to the i-th perforation section into the first preset formula to calculate the dynamic permeability of each rock type corresponding to the i-th perforation section.

[0121] The first preset formula is as follows:

[0122]

[0123] In the formula, k i Let n represent the dynamic permeability of the i-th perforation section, n represent the total number of each rock type, and k represent the total number of perforations. ij h represents the dynamic permeability of the j-th rock type corresponding to the i-th perforation segment, j∈[1,n] ij q represents the thickness of the j-th rock type corresponding to the i-th perforation segment. ij This represents the weight of the j-th rock type corresponding to the i-th perforation segment;

[0124] By analogy, the dynamic permeability of each rock type corresponding to each perforation section can be calculated.

[0125] Optionally, in one embodiment, the second computing module 30 is configured to:

[0126] Obtain the static permeability corresponding to the i′th rock type and the corresponding static permeability model mesh thickness;

[0127] Substitute the static permeability corresponding to the i′ rock type and the static permeability model mesh thickness corresponding to the static permeability into the second preset formula to calculate the average static permeability of the i′ rock type.

[0128] The second preset formula is as follows:

[0129]

[0130] In the formula, k i′静 Let represent the average static permeability of the i′-th rock type, n′ represent the total number of static permeabilities, and k represent the average static permeability of the i′-th rock type. i′j′ h represents the j′-th static permeability corresponding to the i′-th rock type, where j′∈[1, n′] i′j′This represents the static permeability model mesh thickness corresponding to the j′ static permeability for the i′ rock type.

[0131] Optionally, in one embodiment, the model building module 40 is configured to:

[0132] A regression equation is established based on the preset well logging curve and the dimensionless permeability ratio.

[0133] Based on the regression equation, the permeability ratio of the non-perforated section and all untested wells was calculated.

[0134] Based on the permeability ratio and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

[0135] Optionally, in one embodiment, the model building module 40 is configured to:

[0136] Calculate the arithmetic mean of each preset logging curve, wherein the preset logging curves include: natural gamma curve, resistivity curve and density curve;

[0137] The arithmetic mean and the dimensionless ratio of permeability are calibrated and fitted to establish a regression equation R. k =2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 ;

[0138] In the formula, R k GR represents the dimensionless ratio of permeability, RT represents the arithmetic mean of the natural gamma curve, and DEN represents the arithmetic mean of the resistivity curve.

[0139] Optionally, in one embodiment, the model building module 40 is configured to:

[0140] Substituting GR, RT, and DEN of the non-perforated section into the regression equation, the permeability ratio of the non-perforated section is calculated.

[0141] Substitute the GR, RT, and DEN values ​​for each untested well into the regression equation to calculate the permeability ratios for all untested wells.

[0142] The functions of each module in the above-mentioned device for establishing a dynamic penetration rate model correspond to the steps in the above-mentioned method embodiment for establishing a dynamic penetration rate model, and their functions and implementation processes will not be described in detail here.

[0143] Thirdly, embodiments of the present invention also provide an electronic device, the structure of which is as follows: Figure 8As shown, it includes: a memory and a processor, wherein the processor is used to read and execute the computer program stored in the memory to implement the aforementioned method for establishing a dynamic penetration rate model.

[0144] Fourthly, embodiments of the present invention also provide a computer storage medium storing computer-executable instructions, which, when executed, implement the aforementioned method for establishing a dynamic penetration rate model.

[0145] Fifthly, embodiments of the present invention provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the method embodiment for establishing a dynamic penetration rate model as described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0146] Finally, it should be noted that while some processes described in the embodiments of the present invention include multiple operations or steps that appear in a specific order, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of the present invention, or may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0147] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for establishing a dynamic penetration rate model, characterized in that, The method includes: Select target production wells that meet the preset conditions from among the production wells; Calculate the dynamic permeability of each perforated section in the target production well; The dimensionless permeability ratio is calculated based on the dynamic permeability of each perforation section. Based on the preset logging curves and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method. Multiplying the static permeability model by the permeability ratio model yields the dynamic permeability model.

2. The method for establishing a dynamic penetration rate model according to claim 1, characterized in that, The preset conditions include: a first preset condition and a second preset condition; The first preset condition is that both well testing and production logging tests are performed, while the second preset condition is that there is no production logging test, well testing is performed, and there is only one perforation section. The first preset condition has a higher priority than the second preset condition.

3. The method for establishing a dynamic penetration rate model according to claim 1, characterized in that, The step of calculating the dynamic permeability of each perforated section in the target production well includes: Obtain the total oil and gas production, total formation coefficient, and thickness of each perforated section of the target production well; The oil and gas production of each perforated section in the target production well was obtained through production logging tests. The formation coefficient for each perforation section is obtained by dividing the oil and gas production of each perforation section by the total oil and gas production, and then multiplying the quotient by the total formation coefficient. The dynamic permeability of each perforated section in the target production well is obtained by dividing the formation coefficient of each perforated section by the thickness of the corresponding perforated section.

4. The method for establishing a dynamic penetration rate model according to claim 1, characterized in that, The step of calculating the dimensionless permeability ratio based on the dynamic permeability of each perforation section includes: Based on the dynamic permeability of each perforation section, the dynamic permeability of each rock type corresponding to each perforation section is calculated; Calculate the average static permeability for each rock type; The dynamic permeability of each rock type is divided by the average static permeability of that rock type, and the quotient is used as the dimensionless permeability ratio.

5. The method for establishing a dynamic permeability model according to claim 4, characterized in that, The step of calculating the dynamic permeability of each perforation section for each rock type based on the dynamic permeability of each perforation section includes: For the i-th perforation segment, obtain the thickness and weight of each rock type corresponding to the i-th perforation segment; Substitute the dynamic permeability of the i-th perforation section, the thickness and weight of each rock type corresponding to the i-th perforation section into the first preset formula to calculate the dynamic permeability of each rock type corresponding to the i-th perforation section. The first preset formula is as follows: In the formula, k i Let n represent the dynamic permeability of the i-th perforation section, n represent the total number of each rock type, and k represent the total number of perforations. ij h represents the dynamic permeability of the j-th rock type corresponding to the i-th perforation segment, j∈[1,n] ij q represents the thickness of the j-th rock type corresponding to the i-th perforation segment. ij This represents the weight of the j-th rock type corresponding to the i-th perforation segment; By analogy, the dynamic permeability of each rock type corresponding to each perforation section can be calculated.

6. The method for establishing a dynamic penetration rate model according to claim 4, characterized in that, The steps for calculating the average static permeability for each rock type include: Obtain the static permeability corresponding to the i′th rock type and the corresponding static permeability model mesh thickness; Substitute the static permeability corresponding to the i′ rock type and the static permeability model mesh thickness corresponding to the static permeability into the second preset formula to calculate the average static permeability of the i′ rock type. The second preset formula is as follows: In the formula, k i′静 Let represent the average static permeability of the i′-th rock type, n′ represent the total number of static permeabilities, and k represent the average static permeability of the i′-th rock type. i′j′ h represents the j′-th static permeability corresponding to the i′-th rock type, where j′∈[1, n′] i′j′ This represents the static permeability model mesh thickness corresponding to the j′ static permeability for the i′ rock type.

7. The method for establishing a dynamic permeability model according to claim 1, characterized in that, The step of obtaining the permeability ratio model using the Kriging method based on the preset well logging curve and the dimensionless permeability ratio includes: A regression equation is established based on the preset well logging curve and the dimensionless permeability ratio. Based on the regression equation, the permeability ratio of the non-perforated section and all untested wells was calculated. Based on the permeability ratio and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

8. The method for establishing a dynamic permeability model according to claim 7, characterized in that, The step of establishing a regression equation based on the preset well logging curve and the dimensionless permeability ratio includes: Calculate the arithmetic mean of each preset logging curve, wherein the preset logging curves include: natural gamma curve, resistivity curve and density curve; The arithmetic mean and the dimensionless ratio of permeability are calibrated and fitted to establish a regression equation R. k =2.3GR -2.005 ×1.6RT 1.743 ×3.1DEN -3.459 ; In the formula, R k GR represents the dimensionless ratio of permeability, RT represents the arithmetic mean of the natural gamma curve, and DEN represents the arithmetic mean of the resistivity curve.

9. The method for establishing a dynamic penetration rate model according to claim 8, characterized in that, The step of calculating the permeability ratio of the non-perforated section and all untested wells based on the regression equation includes: Substituting GR, RT, and DEN of the non-perforated section into the regression equation, the permeability ratio of the non-perforated section is calculated. Substitute the GR, RT, and DEN values ​​for each untested well into the regression equation to calculate the permeability ratios for all untested wells.

10. An apparatus for establishing a dynamic permeability model, characterized in that, The device includes: The selection module is configured to select target production wells that meet preset conditions from among the various production wells; The first calculation module is configured to calculate the dynamic permeability of each perforation section in the target production well; The second calculation module is configured to calculate the dimensionless permeability ratio based on the dynamic permeability of each perforation section. The model building module is configured to obtain a permeability ratio model based on a preset logging curve and the dimensionless permeability ratio using the Kriging method. The third calculation module is configured to multiply the static permeability model by the permeability ratio model to obtain the dynamic permeability model.

11. The apparatus for establishing a dynamic permeability model according to claim 10, characterized in that, The first computing module is specifically configured to: Obtain the total oil and gas production, total formation coefficient, and thickness of each perforated section of the target production well; The oil and gas production of each perforated section in the target production well was obtained through production logging tests. The formation coefficient for each perforation section is obtained by dividing the oil and gas production of each perforation section by the total oil and gas production, and then multiplying the quotient by the total formation coefficient. The dynamic permeability of each perforated section in the target production well is obtained by dividing the formation coefficient of each perforated section by the thickness of the corresponding perforated section.

12. The apparatus for establishing a dynamic permeability model according to claim 10, characterized in that, The second computing module is specifically configured to: Based on the dynamic permeability of each perforation section, the dynamic permeability of each rock type corresponding to each perforation section is calculated; Calculate the average static permeability for each rock type; The dynamic permeability of each rock type is divided by the average static permeability of that rock type, and the quotient is used as the dimensionless permeability ratio.

13. The apparatus for establishing a dynamic permeability model according to claim 10, characterized in that, The model building module is specifically configured to: A regression equation is established based on the preset well logging curve and the dimensionless permeability ratio. Based on the regression equation, the permeability ratio of the non-perforated section and all untested wells was calculated; Based on the permeability ratio and the dimensionless permeability ratio, a permeability ratio model is obtained using the Kriging method.

14. An electronic device, characterized in that, include: Memory and processor; The processor is configured to read and execute the computer program stored in the memory to implement the steps of the method for establishing a dynamic penetration rate model as described in any one of claims 1-9.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, implement the steps of the method for establishing a dynamic penetration rate model as described in any one of claims 1-9.

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