A carbonate interlayer isolation evaluation model establishing, evaluating method and device

Abstract

The application discloses a kind of carbonate rock interlayer sealing property evaluation model establishment, evaluation method and device.The carbonate rock interlayer sealing property evaluation model establishment method includes, by the method of numerical simulation, with the blocking time of carbonate rock interlayer as the basis, from the possible influence parameter set of carbonate rock interlayer sealing property, multiple sensitive parameters are screened;Determine multiple groups of examples, constitute example library, each group of examples includes the value of each sensitive parameter and corresponding interlayer blocking time;Selected machine learning model is trained using example library, and the evaluation model for evaluating the sealing property of carbonate rock interlayer is obtained.The blocking time is used as the characterization parameter of interlayer sealing property, and the sealing property of carbonate rock interlayer can be reasonably and quantitatively evaluated.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and apparatus for establishing and evaluating the sealing performance of carbonate rock interlayers. Background Technology

[0002] Interlayers within carbonate reservoirs differ from mudstone interlayers in clastic rocks. Interlayers in carbonate reservoirs are often permeable physical properties, which impede and delay fluid flow but cannot completely block its movement. During water injection development of carbonate reservoirs, the sealing performance of these physical interlayers is often a decisive factor in the water cone formation and water breakthrough time of production wells, thus affecting the formulation and optimization of carbonate reservoir development plans. Currently, there is no reasonable evaluation method for the sealing performance of carbonate interlayers, and evaluation methods for the sealing performance of interlayers in clastic rocks are not applicable to physical interlayers in carbonate rocks. Summary of the Invention

[0003] In view of the above problems, the present invention is proposed to provide a method and apparatus for establishing and evaluating the sealing properties of carbonate rock interlayers in order to overcome or at least partially solve the above problems, and to provide a reasonable quantitative evaluation of the sealing properties of carbonate rock interlayers.

[0004] In a first aspect, embodiments of the present invention provide a method for establishing a model for evaluating the sealing performance of carbonate rock interlayers, comprising:

[0005] Using numerical simulation, based on the isolation time of carbonate interlayers, several sensitive parameters were screened from the set of parameters that may affect the sealing performance of carbonate interlayers.

[0006] Multiple sets of calculation cases were identified to form a calculation case library. Each set of calculation cases included the values ​​of each sensitive parameter and the corresponding interlayer isolation time.

[0007] Using the aforementioned example library and a selected algorithm, a model is established to obtain an evaluation model for assessing the sealing properties of carbonate rock interlayers.

[0008] Secondly, embodiments of the present invention provide a method for evaluating the sealing performance of carbonate rock interlayers, including:

[0009] The values ​​of each sensitive parameter of the carbonate rock interlayer are input into the evaluation model to obtain the barrier time information of the carbonate rock interlayer. The sensitive parameters and the evaluation model are the sensitive parameters and the evaluation model obtained by the above method, respectively.

[0010] The sealing performance of the interlayer is evaluated based on the barrier time information.

[0011] Thirdly, embodiments of the present invention provide a device for establishing a model for evaluating the sealing performance of carbonate rock interlayers, comprising:

[0012] The sensitive parameter screening module is used to screen multiple sensitive parameters from a set of parameters that may affect the sealing performance of carbonate rock interlayers based on the isolation time of the interlayers using numerical simulation methods.

[0013] The calculation case library determination module is used to determine multiple sets of calculation cases to form a calculation case library. Each set of calculation cases includes the values ​​of each sensitive parameter and the corresponding interlayer isolation time.

[0014] The model building module is used to build a model using the selected algorithm from the example library to obtain an evaluation model for evaluating the sealing properties of carbonate rock interlayers.

[0015] Fourthly, embodiments of the present invention provide a computer program product with a function for evaluating the sealing properties of carbonate interlayers, including a computer program / instruction, wherein when the computer program / instruction is executed by a processor, it implements the above-mentioned method for establishing a carbonate interlayer sealing property evaluation model, or implements the above-mentioned method for evaluating the sealing properties of carbonate interlayers.

[0016] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0017] (1) The method for establishing a carbonate interlayer sealing performance evaluation model provided in this embodiment of the invention uses numerical simulation to select multiple sensitive parameters based on the isolation time of the carbonate interlayer, thereby obtaining a case study library; the case study library is used to establish a model to obtain an evaluation model for evaluating the sealing performance of carbonate interlayers. The sealing time is clearly defined as the characterization parameter of carbonate interlayer sealing performance. By using machine learning methods to perform data mining on the case study library, a carbonate interlayer sealing performance evaluation model is established, so that the acquisition of evaluation results no longer depends on time-consuming and laborious numerical simulation, which greatly improves the evaluation speed and efficiency; at the same time, it realizes a reasonable and quantitative evaluation of the sealing performance of carbonate interlayers; it can quickly predict the water / gas breakthrough time range of the water / gas injection scheme in the target carbonate reservoir, providing strong support for the optimization and adjustment of the development scheme.

[0018] (2) The method for establishing a carbonate rock interlayer sealing performance evaluation model provided in this embodiment of the invention solves the problem of selecting key parameters for carbonate rock interlayer sealing performance evaluation by performing sensitivity analysis on potentially sensitive parameters through numerical simulation, thereby reducing the difficulty and dimensionality of interlayer sealing performance evaluation.

[0019] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0020] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0021] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0022] Figure 1 This is a flowchart of the method for establishing a carbonate rock interlayer sealing performance evaluation model in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart illustrating the specific implementation of the carbonate rock interlayer sealing performance evaluation method in Embodiment 2 of the present invention.

[0024] Figure 3 This is a schematic diagram of the device for establishing a model for evaluating the sealing performance of carbonate rock interlayers in an embodiment of the present invention. Detailed Implementation

[0025] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0026] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0027] To address the problem of difficulty in reasonably evaluating the sealing properties of carbonate rock interlayers in existing technologies, embodiments of the present invention provide a model for establishing and evaluating the sealing properties of carbonate rock interlayers, as well as an evaluation method and apparatus, which can reasonably and quantitatively evaluate the sealing properties of carbonate rock interlayers.

[0028] Example 1

[0029] Embodiment 1 of the present invention provides a method for establishing an evaluation model for the sealing performance of carbonate rock interlayers, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0030] Step S11: Using numerical simulation, based on the isolation time of carbonate interlayers, several sensitive parameters are selected from the set of parameters that may affect the sealing properties of carbonate interlayers.

[0031] The aforementioned interlayers mainly refer to carbonate rock interlayers. These interlayers have a certain obstruction and delay effect on fluids, but they cannot completely block the movement of fluids. Therefore, the difference between the water flow time in the oil layer where the interlayer is located and the water flow time in the oil layer without the interlayer can be determined as the blocking time of the interlayer.

[0032] In some embodiments, numerical simulation can be used to obtain the change in interlayer sealing time caused by changes in sealing properties of the selected target area of ​​carbonate reservoir; based on the changes in sealing properties of the ...

[0033] Furthermore, the parameter set that may be affected includes at least one of the following parameters:

[0034] Static parameters: thickness of the oil layer containing the interlayer, oil layer porosity, oil layer permeability, interlayer thickness, interlayer porosity, interlayer permeability, distance of the interlayer from the top of the oil layer, interlayer wettability and quality index; oil layer permeability can be further subdivided into oil layer horizontal permeability, oil layer vertical permeability and oil layer total permeability; interlayer permeability can be further subdivided into interlayer horizontal permeability, interlayer vertical permeability and interlayer total permeability;

[0035] Dynamic parameters: average injection-production well spacing, fluid production rate, oil production rate (which can be the average annual oil production rate), water injection rate, and injection pressure of the well group containing the interlayer.

[0036] Numerical simulations determined that the following parameters in the parameter set that may affect the sealing performance of carbonate rock interlayers meet the set sensitivity conditions, and are listed in descending order of sensitivity:

[0037] Intercalation permeability, average injection-production well spacing of the well group containing the intercalation, intercalation thickness, average water injection rate of the well group containing the intercalation, permeability of the oil layer containing the intercalation, and average annual oil production rate of the well group containing the intercalation;

[0038] Select at least one of the above parameters as a sensitive parameter in the order listed above.

[0039] You can designate all six parameters as sensitive parameters; or you can select the first few parameters as sensitive parameters, for example, select the top five sensitive parameters.

[0040] The sealing properties of interlayers in carbonate rocks are no longer a simple static problem. Depending on the development method and dynamic parameters, the same interlayer can exhibit different sealing states. By introducing a combination of dynamic and static parameters, the dynamic characterization of the sealing properties of interlayers in carbonate rocks has been solved.

[0041] Step S12: Determine multiple sets of calculation examples to form a calculation example library.

[0042] Each set of calculations includes the values ​​of each sensitive parameter and the corresponding interlayer isolation time.

[0043] In some embodiments, the method may include: determining the set number of values ​​for each sensitive parameter based on the value range of each sensitive parameter of the target carbonate reservoir; using a combination method to obtain multiple sets of sensitive parameter values ​​based on the set number of values ​​for each sensitive parameter; and using numerical simulation to determine the corresponding interlayer isolation time for each set of sensitive parameter values ​​to obtain a set of calculation examples.

[0044] Furthermore, if the sensitive parameter is a continuously distributed parameter, the sampling interval of the parameter is determined by setting a number, and the value of the set number of parameters is obtained according to the sampling interval; if the sensitive parameter is not a continuously distributed parameter, the value of the set number of parameters is obtained by enumeration.

[0045] The number of values ​​that can be set for each sensitive parameter can be the same or different.

[0046] Step S13: Use the selected algorithm from the example library to build a model and obtain an evaluation model for evaluating the sealing properties of carbonate rock interlayers.

[0047] Based on the example library, K-nearest neighbor regression, decision tree, random four-year forest, support vector machine and neural network algorithms were used for modeling. The optimal model was selected from the obtained models as the evaluation model for evaluating the sealing performance of carbonate rock interlayers.

[0048] The method for establishing a carbonate interlayer sealing performance evaluation model provided in Embodiment 1 of this invention uses numerical simulation to select multiple sensitive parameters based on the isolation time of the carbonate interlayer, thereby obtaining a sample library. A machine learning model is then trained using this sample library to obtain an evaluation model for assessing the sealing performance of carbonate interlayers. The sealing time is clearly defined as the characterizing parameter of carbonate interlayer sealing performance. By using machine learning to mine data from the sample library, an evaluation model for carbonate interlayer sealing performance is established. This eliminates the reliance on time-consuming and laborious numerical simulations in obtaining evaluation results, greatly improving the speed and efficiency of evaluation. Simultaneously, it achieves a reasonable and quantitative evaluation of the sealing performance of carbonate interlayers. It can quickly predict the water / gas breakthrough time range of water / gas injection schemes in target carbonate reservoirs, providing strong support for the optimization and adjustment of development plans.

[0049] By conducting sensitivity analysis on potentially sensitive parameters through numerical simulation, the problem of selecting key parameters for evaluating the sealing performance of carbonate rock interlayers was solved, reducing the difficulty and complexity of the interlayer sealing performance evaluation.

[0050] Example 2

[0051] Embodiment 2 of the present invention provides a method for evaluating the sealing performance of carbonate rock interlayers, comprising:

[0052] The values ​​of various sensitive parameters of the carbonate rock interlayer are input into the evaluation model to obtain the barrier time information of the carbonate rock interlayer. The sensitive parameters and the evaluation model are the sensitive parameters and the evaluation model obtained by the above method, respectively. The sealing performance of the interlayer is evaluated based on the barrier time information.

[0053] This study employs reservoir numerical simulation to characterize the sealing performance of interlayers by their fluid isolation time, and based on this, identifies key static and dynamic parameters affecting the sealing performance of interlayers. Then, through sampling / enumeration and combination of these key static and dynamic parameters within the reservoir, a reservoir numerical simulation example library is formed. The calculation results of these examples reflect the different fluid isolation effects of interlayers under different parameter combinations. Using these key dynamic parameters and their calculation results as a database, appropriate machine learning algorithms (such as decision trees and random forests) are selected for data mining. The algorithm with the best fitting effect is selected to establish an evaluation model that directly obtains the sealing performance of interlayers from key reservoir static and dynamic parameters, thereby achieving rapid evaluation of the sealing performance of carbonate rock interlayers.

[0054] The following section uses a carbonate reservoir as an example to provide a detailed explanation of the method for evaluating the sealing performance of carbonate rock interlayers. (See also...) Figure 2 As shown, it includes the following steps:

[0055] Step S21: Determine the location of interlayers in the selected carbonate reservoir.

[0056] Collect or build dynamic and static models of selected carbonate reservoirs, and determine the location of potential interlayers by comparing physical properties (e.g., permeability comparison).

[0057] In a geological model of a carbonate reservoir, a set of strata with significantly lower permeability than the strata above and below it was found in the vertical direction, and it was stably distributed throughout the area. This was identified as a potential physical property interlayer.

[0058] Step S22: Select typical regions representing different dynamic and static characteristics to perform block numerical simulation, evaluate the sensitivity of the physical property interlayer to fluid barrier time under different dynamic and static parameters, and screen out the sensitive parameters that affect the sealing performance of the physical property interlayer.

[0059] A region whose physical properties and dynamic development parameters are at the reservoir average was selected as a typical region. The static and dynamic parameters related to the interlayers in this typical region are shown in Tables 1 and 2 below:

[0060] Table 1. Statistical table of static parameters related to physical properties and interlayers in typical regions.

[0061]

[0062] Table 2. Statistical table of dynamic parameters related to physical property interlayers in typical regions.

[0063] Dynamic parameters Injection-production well spacing Liquid collection rate Annual oil production rate Water injection speed Injection pressure unit m STB / d ％ STB / d psi value 1000 2200 0.95 2900 5030

[0064] Using the difference between the water breakthrough time of model wells in this typical region and the water breakthrough time of model wells under conditions where interlayers are removed (i.e., the time taken for fluid to pass through the interlayer, the isolation time) as the objective function, numerical simulations were performed on this typical region to determine the sensitivity of various dynamic and static parameters within the reservoir range. Taking interlayer thickness as an example, the results of the time taken for injected water to pass through the interlayer, i.e., the isolation time, under different interlayer thicknesses are as follows:

[0065] Table 3. Statistics on interlayer thickness and its barrier time in typical areas.

[0066]

[0067] Based on the sensitivity analysis results, the six parameters that are most sensitive to the objective function and their sensitivity ranking are as follows: interlayer permeability > injection-production well spacing > interlayer thickness > injection rate > reservoir permeability > annual oil production rate.

[0068] The above six parameters can be used as sensitive parameters.

[0069] Step S23: Determine the value range of each sensitive parameter based on the actual situation of the reservoir. For continuously distributed sensitive parameters, sample values ​​at fixed intervals. For discontinuous sensitive parameters, use an enumeration method to obtain values. Determine the set of sensitive parameter values ​​and combine them to form a reservoir numerical simulation example library.

[0070] The above six sensitive parameters were sampled and enumerated based on the actual parameter range of the reservoir. Six interlayer permeability samples were collected, nine injection-production well spacing samples were enumerated, six interlayer thickness samples were collected, six water injection rates were collected, five oil layer permeability samples were collected, and five annual oil production rates were collected. The above parameters were combined to obtain a numerical simulation case library containing 48,600 cases.

[0071] Step S24: Perform simulation calculations on the reservoir numerical simulation case library, obtain the isolation time of each case as a quantitative evaluation result of the sealing performance of the interlayer, and obtain the sample dataset.

[0072] Numerical simulations were performed on the examples in the example library to calculate the time it took for injected water to pass through the interlayer in each example, i.e. the interlayer blocking time, resulting in 48,600 sets of training sample data for machine learning.

[0073] Optionally, cluster analysis algorithms can be used to classify the blocking time, which can serve as a qualitative evaluation result of the sealing performance of the interlayer. That is, each training sample contains not specific blocking times, but blocking classifications, such as different blocking levels.

[0074] Step S25: Using the sample dataset as training data, select a machine learning algorithm for data mining to establish the optimal physical property interlayer sealing performance evaluation model.

[0075] Based on the above training sample data, K-nearest neighbor regression, decision tree, random four-year forest, support vector machine and neural network algorithms were used for modeling, the algorithm performance of the models was evaluated, and the best result was selected as the random forest algorithm. The model based on random forest was selected as the evaluation model of the interlayer sealing properties of the reservoir.

[0076] The model fit based on the random forest algorithm was verified to be 93.3%.

[0077] Step S26: Input the sensitive parameters of the block to be evaluated, and use the established physical property interlayer sealing performance evaluation model to obtain the physical property interlayer sealing performance evaluation results of the block.

[0078] Based on the inventive concept of this invention, embodiments of this invention also provide a device for establishing an evaluation model for the sealing performance of carbonate rock interlayers, the structure of which is as follows: Figure 3 As shown, it includes:

[0079] Sensitive parameter screening module 31 is used to screen multiple sensitive parameters from the set of parameters that may affect the sealing performance of carbonate rock interlayers based on the isolation time of carbonate rock interlayers through numerical simulation.

[0080] The calculation case library determination module 32 is used to determine multiple sets of calculation cases to form a calculation case library. Each set of calculation cases includes the values ​​of each sensitive parameter and the corresponding interlayer isolation time.

[0081] The model building module 33 is used to build a model using the selected algorithm from the example library to obtain an evaluation model for evaluating the sealing properties of carbonate rock interlayers.

[0082] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0083] Based on the inventive concept of this invention, embodiments of this invention also provide a computer program product with a function for evaluating the sealing properties of carbonate rock interlayers, including a computer program / instruction, wherein when the computer program / instruction is executed by a processor, it implements the above-mentioned method for establishing a carbonate rock interlayer sealing property evaluation model, or implements the above-mentioned method for evaluating the sealing properties of carbonate rock interlayers.

[0084] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0085] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0086] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0087] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0088] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0089] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0090] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A method for establishing an evaluation model for the sealing performance of carbonate rock interlayers, characterized in that, include: To obtain the changes in interlayer sealing time caused by variations in parameters that may affect the sealing performance of the target area in the selected carbonate reservoir. Based on the changes in the parameters that may be affected by the sealing properties and the resulting changes in sealing time, determine the sensitivity coefficient of the parameters that may be affected by the sealing properties; determine the parameters that may be affected by the sealing properties with sensitivity coefficients greater than the sensitivity coefficient threshold as sensitive parameters, or determine a set number of parameters that may be affected by the sealing properties as sensitive parameters according to the size of the sensitivity coefficient. Based on the value range of each sensitive parameter of the target carbonate reservoir, the set number of each sensitive parameter is determined. If the sensitive parameter is continuously distributed, the sampling interval of the parameter is determined using the set number, and the set number of the parameter is obtained based on the sampling interval. If the sensitive parameter is not continuously distributed, the set number of the parameter is obtained by enumeration. Multiple sets of sensitive parameter values ​​are obtained. For each set of sensitive parameter values, the corresponding interlayer isolation time is determined using numerical simulation, resulting in a set of calculation examples. Multiple sets of calculation cases were identified to form a calculation case library. Each set of calculation cases included the values ​​of each sensitive parameter and the corresponding interlayer isolation time. Using the aforementioned example library, K-nearest neighbor regression, decision tree, random forest, support vector machine, and neural network algorithms were employed for modeling. The optimal model was selected from the obtained models to be used as the evaluation model for assessing the sealing properties of carbonate rock interlayers.

2. The method as described in claim 1, characterized in that, The set of parameters that may be affected includes at least one of the following parameters: The thickness of the oil layer containing the interlayer, the porosity of the oil layer, the permeability of the oil layer, the thickness of the interlayer, the porosity of the interlayer, the permeability of the interlayer, the distance of the interlayer from the top of the oil layer, the wettability and quality index of the interlayer; The average injection-production well spacing, fluid production rate, oil production rate, water injection rate, and injection pressure of the well group containing the interlayer.

3. The method as described in claim 2, characterized in that, Select multiple sensitive parameters from the set of parameters that may have an impact, specifically including: The following parameters in the parameter set that may affect the sealing properties of carbonate rock interlayers meet the set sensitivity conditions, and are listed in descending order of sensitivity: Intercalation permeability, average injection-production well spacing of the well group containing the intercalation, intercalation thickness, average water injection rate of the well group containing the intercalation, permeability of the oil layer containing the intercalation, and average oil production rate of the well group containing the intercalation; Select at least one of the above parameters as a sensitive parameter in the order listed above.

4. A method for evaluating the sealing performance of carbonate rock interlayers, characterized in that, include: The values ​​of each sensitive parameter of the carbonate rock interlayer are input into the evaluation model to obtain the barrier time information of the carbonate rock interlayer. The sensitive parameters and the evaluation model are obtained by the method according to any one of claims 1 to 3. The sealing performance of the interlayer is evaluated based on the barrier time information.

5. A device for establishing a model for evaluating the sealing performance of carbonate rock interlayers, characterized in that, include: The sensitive parameter filtering module is used to obtain the changes in interlayer sealing time caused by changes in parameters that may affect the sealing performance of the selected target area of ​​carbonate reservoir. Based on the changes in the parameters that may be affected by the sealing properties and the resulting changes in sealing time, determine the sensitivity coefficient of the parameters that may be affected by the sealing properties; determine the parameters that may be affected by the sealing properties with sensitivity coefficients greater than the sensitivity coefficient threshold as sensitive parameters, or determine a set number of parameters that may be affected by the sealing properties as sensitive parameters according to the size of the sensitivity coefficient. The case study library determination module is used to determine the set number of each sensitive parameter based on the value range of each sensitive parameter of the target carbonate reservoir; if the sensitive parameter is a continuously distributed parameter, the sampling interval of the parameter is determined by the set number, and the set number of the parameter is obtained according to the sampling interval; if the sensitive parameter is not a continuously distributed parameter, the set number of the parameter is obtained by enumeration; multiple sets of sensitive parameter values ​​are obtained; for each set of sensitive parameter values, the corresponding interlayer isolation time is determined by numerical simulation, resulting in a set of case studies; Multiple sets of calculation cases were identified to form a calculation case library. Each set of calculation cases included the values ​​of each sensitive parameter and the corresponding interlayer isolation time. The model building module is used to build models using the example library, employing K-nearest neighbor regression, decision tree, random forest, support vector machine, and neural network algorithms respectively. The optimal model was selected from the obtained models to be used as the evaluation model for assessing the sealing properties of carbonate rock interlayers.

6. A computer program product with the function of evaluating the sealing performance of carbonate rock interlayers, comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the method for establishing a carbonate rock interlayer sealing performance evaluation model as described in any one of claims 1 to 3, or the method for evaluating carbonate rock interlayer sealing performance as described in claim 4.

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