Injection-production well group refracturing process strategy making method
By combining the analytic hierarchy process with numerical simulation, the influencing factors were quantified and weights were corrected, which solved the accuracy problem of the repeated fracturing process strategy and achieved the rational and rapid formulation of the injection and production well group.
Patent Information
- Application Number
- CN202510601891.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-12
- Publication Date
- 2025-09-16
AI Technical Summary
The formulation of existing refracturing process strategies mainly relies on experience and expert opinions, and lacks effective theoretical methods, resulting in insufficient accuracy and rationality of refracturing of injection-production well groups.
The analytic hierarchy process (AHP) is used in combination with reservoir dynamic parameters and formation dynamic stress field. A model is established through numerical simulation to quantify the influence of various factors. The weights are modified under special working conditions to formulate a reasonable repeated fracturing process strategy.
The accuracy and rationality of the repeated fracturing process strategy for the injection-production well group are achieved, the defects of experience reliance are overcome, and the rapidity and convenience of field application are ensured.
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Abstract
Description
Technical Field
[0001] The present invention relates to the field of oil and gas production, and in particular to a method for formulating a repeated fracturing process strategy for an injection-production well group. Background Art
[0002] As national energy strategic demands increase, my country must continue to explore for new reserves while also ensuring production capacity in existing development areas. Many mature oilfields are primarily developed using pre-fractured injection and production wells. However, over the years, the water content of crude oil produced by these fields has increased, leading to a rapid decline in production. Refracturing can unclog old fractures, improve conductivity, open new fractures, expand reservoir volume, and control oil-rich zones to stabilize oil production and control water content, thereby increasing oil recovery. Therefore, refracturing in many mature oil and gas fields that have already undergone initial fracturing is of great practical significance.
[0003] With the development of fracturing technology, the re-fracturing process strategy has also been expanded on the basis of the two traditional process modes of expanding old fractures and re-fracturing, and has added the following process modes: re-fracturing with volume (Zhang Gang. Research and application of re-fracturing technology for Niujuanhu sandstone reservoir. [J]. Chemical Engineering and Equipment. 2018; 9(31): 75-80), pre-fracturing energy replenishment + re-fracturing with volume (Pan Wenbo. Numerical simulation study on energy storage re-fracturing for water injection development reservoirs [M]. China University of Petroleum (Beijing). 2020), pre-fracturing energy replenishment + re-fracturing with volume (Li Lianqing et al. Research and application of energy storage fracturing technology in ultra-low permeability reservoirs in the B83 well area of a certain oil field. [J] China Petroleum and Chemical Standards and Quality, 2024, 44(11), 153-156). At present, the formulation of these process strategies is mainly based on experience and expert opinions, with a high influence of supervisory evaluation, and there is a lack of effective theoretical methods. Therefore, it is of great significance to explore the theoretical methods of re-fracturing process strategies.
[0004] In this context, the present invention is based on the actual geological characteristics of the reservoir and the development model, simulates the reservoir dynamic parameters (changes and distribution of reservoir pressure, dynamic distribution of oil and water) and the changing ground stress field (magnitude and direction of ground stress) of the reservoir development well group that change with production, and on this basis uses the APH hierarchical analysis method to formulate the repeated fracturing process strategy. Summary of the Invention
[0005] The purpose of the present invention is to provide a method for formulating a refracturing process strategy for an injection-production well group in order to solve the above problems.
[0006] The present invention achieves the above-mentioned purpose through the following technical solutions:
[0007] A method for formulating a refracturing process strategy for an injection-production well group comprises the following steps:
[0008] S1. Collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection-production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model;
[0009] S2. Establish a hierarchical model, construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and construct a solution layer based on the repeated fracturing process;
[0010] S3. Compare parameters that affect the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
[0011] In a preferred embodiment, step S1 further includes: obtaining initial fracture parameters and rock brittleness index.
[0012] In a preferred embodiment, the reservoir dynamic parameters in step S1 include reservoir pressure and reservoir oil-water distribution.
[0013] In a preferred embodiment, step S2 also includes constructing a sub-criteria layer, wherein the parameters of the sub-criteria layer include the amount of fracturing fluid injected into the ground, the amount of proppant injected into the ground, the stable production period, the water content, the cumulative recovery degree, the phase permeability, the average oil saturation, the remaining oil saturation, the initial crack angle, the ground stress difference, the Young's modulus, the Poisson's ratio, the permeability, and the porosity.
[0014] In a preferred embodiment, the refracturing process in step S2 includes redirected refracturing, redirected volume refracturing, energy supplemented redirected refracturing, energy supplemented redirected volume refracturing, and refracturing along old fractures.
[0015] In a preferred embodiment, step S3 further includes, if there are special operating parameters, correcting the first weight value, obtaining a corrected second weight, and selecting a repeated fracturing process according to the second weight value.
[0016] In a preferred embodiment, step S3 further includes, if the reservoir pressure coefficient is less than 0.7, then modifying the weight of energy supplementation and switching to refracturing, and the modification formula is:
[0017]
[0018] If the brittle mineral content is greater than 50%, the proportion of the diverting area with a diverting angle greater than 45° is greater than 0.3, or the proportion of the area with oil saturation change is greater than 70%, the weight of the diverting volume for repeated fracturing is corrected. The correction formula is:
[0019] W′=W·(1+actual value-critical value)
[0020] If the ground stress difference is less than 5MPa or the stable production period is greater than 2 years, the weight of repeated fracturing along the old fractures is corrected. The correction formula is:
[0021]
[0022] Wherein, W is the first weight before correction, and W′ is the second weight after correction.
[0023] In order to solve the above technical problems, the present invention also provides a system for formulating a refracturing process strategy for an injection-production well group, comprising:
[0024] A parameter determination module is used to collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection and production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model;
[0025] A hierarchical model construction module is used to construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and to construct a solution layer based on the repeated fracturing process, and to build a hierarchical model;
[0026] The process determination module is used to compare parameters affecting the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
[0027] To solve the above technical problems, the present invention also provides a computer-readable storage medium comprising instructions, which, when executed on a computer, enable the computer to execute the method for formulating a repeated fracturing process strategy for an injection-production well group as provided in the above technical solution.
[0028] In order to solve the above technical problems, the present invention provides a computing device, including: a memory, a processor, and a computer program stored in the memory and run on the processor. When the processor executes the program, it implements the method for formulating a repeated fracturing process strategy for an injection and production well group as provided in the above technical solution.
[0029] The beneficial effects of the present invention are as follows: the present invention adopts the hierarchical analysis method to formulate the repeated fracturing process strategy of the injection and production well group, overcomes the defect of the experience and expert opinion method in the existing technology that the subjective influence is relatively large, quantifies the influence degree of the evaluation factors in each level, and further considers the threshold value of the evaluation factor for special working conditions to make weight corrections, realizes the reasonable supplement of the static model of the hierarchical analysis method, ensures the accuracy and rationality of the formulated strategy, and is conducive to the rapid and convenient application on site.
[0030] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 Schematic diagram of the method flow of the present invention;
[0032] Figure 2 A hierarchical structure diagram of a specific embodiment of the present invention;
[0033] Figure 3 This is a schematic diagram of an injection-production well group according to a specific embodiment of the present invention. DETAILED DESCRIPTION
[0034] The following describes the embodiments of the present disclosure through specific concrete examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.
[0035] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.
[0036] The embodiment of the present invention utilizes the AHP hierarchical analysis method to consider multiple levels of influencing factors to select the corresponding repeated fracturing process. In addition, corrections are made for special working conditions that affect the nonlinear changes of the fracturing process, thereby giving priority to key parameters under characteristic working conditions, making its application faster and more convenient.
[0037] Figure 1 The flow chart of the method for formulating a repeated fracturing process strategy for an injection-production well group provided by an embodiment of the present invention is as follows: Figure 1 As shown, the method includes:
[0038] S1. Collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection-production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model.
[0039] Since the development of injection and production well groups after fracturing is a dynamic process, it is necessary to simulate the reservoir dynamic parameters and stress field parameters of the development well group that change with production based on the actual geological characteristics of the reservoir and development simulation. The reservoir dynamic parameters can be used to obtain the changes and distribution of reservoir pressure, the dynamic distribution of oil and water, etc. The dynamic stress field of the formation can be used to obtain the size and direction of the ground stress.
[0040] Specifically, technicians can use CMG, Petrel, Eclipse, Abques and other numerical simulation methods to obtain a numerical simulation model for repeated fracturing of the injection and production well group based on the collected basic parameters such as reservoir porosity, permeability, original oil saturation, original reservoir pressure, reservoir temperature, phase permeability curve, well pattern, well spacing, rock mechanics parameters, original geostress field, initial fracturing crack length, and conductivity.
[0041] Furthermore, to determine the impact of the initial fracturing on refracturing, the initial fracturing parameters can be inverted based on the initial fracturing parameters. A corresponding hydraulic fracturing model can then be constructed based on the initial fracturing parameters and embedded into the numerical simulation model. Specifically, existing commercial software such as FracPro, GOHFER, Stimplan, and Mayer can be used to perform net pressure fitting using the initial fracturing curve to determine parameters such as the length, width, height, and conductivity of the initial fracturing.
[0042] Furthermore, to determine the impact of formation lithology on refracturing, rock mechanical parameters can be derived through experimental testing, P- and S-wave testing, and other methods. The reservoir rock brittleness index can then be calculated to assess the impact of the formation brittleness index on refracturing. Specifically, methods such as the brittleness index of mineral composition, the Rickman brittleness index, a brittleness index based on strength parameters, and brittleness evaluation using the body wave / shear wave velocity ratio can be used to obtain the rock brittleness index.
[0043] S2. Establish a hierarchical model, construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and construct a solution layer based on the repeated fracturing process;
[0044] like Figure 2As shown, step S2 also includes constructing a sub-criteria layer, and the sub-criteria layer parameters include the amount of fracturing fluid injected into the ground, the amount of proppant injected into the ground, the stable production period, the water content, the cumulative recovery degree, the phase permeability, the average oil saturation, the remaining oil saturation, the initial fracture angle, the ground stress difference, the Young's modulus, the Poisson's ratio, the permeability, and the porosity.
[0045] The refracturing process in step S2 includes steering refracturing, steering volume refracturing, energy supplement steering refracturing, energy supplement steering volume refracturing, and refracturing along old fractures.
[0046] S3. Compare parameters that affect the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
[0047] Specifically, in step S3, it is necessary to establish a judgment matrix, which is an m*n order matrix for pairwise comparison between factors.
[0048] The specific expression is:
[0049]
[0050] The elements of A satisfy: 1) a ij >0;2) 3)a ii =1
[0051] By comparing the importance of each pair of factors affecting the refracturing process strategy, the scale size is determined according to the following Table 1:
[0052] Table 1 Determination of scale size
[0053]
[0054]
[0055] In order to calculate the specific weights between different elements, after establishing the judgment matrix, it is necessary to normalize each column vector in the m*n matrix to form a new m*n order matrix K, where the element calculation formula of K is:
[0056]
[0057] Then, the weight value of each factor can be obtained by summing each row of the elements of the normalized matrix B and normalizing it. The specific calculation expression is:
[0058]
[0059] Furthermore, step S3 also includes checking the weight value, and the steps are mainly as follows:
[0060] (a) First, calculate the maximum eigenvalue based on the weight matrix. The formula is:
[0061]
[0062] Among them, AW is the product of the judgment matrix and the standardized weight.
[0063] (b) After solving the maximum eigenvalue, the consistency index CI is calculated, and the formula is:
[0064]
[0065] (c) The consistency ratio CR can be calculated using the consistency index CI and the random consistency index RI. The formula is:
[0066]
[0067] The RI value can be found by looking up the table. This is the random consistency index RI value provided by Franek and Kresta as shown in Table 2:
[0068] Table 1 RI values corresponding to matrix orders
[0069]
[0070]
[0071] Substitute the RI value corresponding to the order for calculation to obtain CR. When CR < 0.1, it indicates that the consistency of the judgment matrix A is considered to be within the allowable range. At this time, the eigenvector of A can be used to perform weight vector calculation. If CR ≥ 0.1, it indicates that a logical error occurred when constructing the judgment matrix, and the judgment matrix A needs to be corrected.
[0072] Based on the above method, the weights Wb1, Wb2, Wb3, Wb4, and Wb5 of the criterion layer (initial fracturing fracture parameters, reservoir pressure distribution under production dynamics, reservoir oil-water distribution, ground stress field, and rock brittleness index) for the repeated fracturing strategy are calculated. The total hierarchical weight ranking of the plan layer C to the decision layer B is further calculated. The calculation formula is:
[0073]
[0074] At the same time, further consistency test is carried out. Assume that the C-layer strategies 1, 2, 3, 4, and 5 have no effect on the factors (b i ) is the hierarchical order consistency index CI i (i=1···5), random consistency index is RI i (i=1···5), the consistency ratio of the total hierarchical order is:
[0075]
[0076] Similarly, when CR<0.1, the hierarchical total ranking passes the consistency test, otherwise it is necessary to readjust the element values of the judgment matrix.
[0077] In step S3, if there are special operating parameters, the first weight value is corrected to obtain the corrected second weight, and the repeated fracturing process is selected according to the second weight value.
[0078] While the weights of various factors in the AHP are static, in practice, the weights of certain factors may change dynamically based on changes in specific engineering data. Therefore, when the weight of a factor reaches a certain threshold, the impact of that factor on the refracturing process exhibits nonlinear changes, necessitating corrections to the specific operating conditions corresponding to that factor. This correction also enables local sensitivity analysis of key factors. When these key factors fall within a specific range, the weight corrections achieve a shift in priority in decision-making.
[0079] Specifically, the correction strategy for special working conditions is shown in Table 3.
[0080] Table 3 Characteristic working condition parameter correction table
[0081]
[0082] In addition, based on the same inventive concept of the method provided by the present invention, an embodiment of the present invention further provides a system for formulating a refracturing process strategy for an injection-production well group, comprising:
[0083] A parameter determination module is used to collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection and production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model;
[0084] A hierarchical model construction module is used to construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and to construct a solution layer based on the repeated fracturing process, and to build a hierarchical model;
[0085] The process determination module is used to compare parameters affecting the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
[0086] An embodiment of the present invention further provides a computer-readable storage medium comprising instructions, which, when executed on a computer, enable the computer to execute the method for formulating a repeated fracturing process strategy for an injection-production well group as provided in the above embodiment.
[0087] An embodiment of the present invention also provides a computing device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for formulating a repeated fracturing process strategy for an injection-production well group as provided in the above embodiment is implemented.
[0088] Practical application cases
[0089] The data used in a practical application case of the present invention comes from an injection-production well group in the M oil field. This well group is an inverted nine-point injection-production well pattern, with a water injection well in the middle and the remaining eight horizontal wells. Figure 3 The fracture information of each fractured well in the well group was obtained by inverting the actual fracturing construction data in the injection and production well network, and the results are shown in Table 4.
[0090] Table 4 Basic parameters of well group inversion
[0091]
[0092] A reservoir flow-stress simulation model was constructed by combining the region's reservoir parameters, well pattern spacing, rock mechanics and geostress parameters, and fracture simulation results. The simulation results were used to calculate the diversion angle of each well and the percentage of area within each well's control range with a diversion angle greater than 45°.
[0093] Among them, the calculation expression of the maximum principal stress turning angle is:
[0094]
[0095] Further calculate the steering area when the steering angle is greater than 45°:
[0096] The stress diversion situation of the well group can be obtained as shown in Table 5.
[0097] Table 5 Stress steering situation
[0098]
[0099] The corresponding elastic modulus and Poisson's ratio are calculated using the logging curves of each well, and the brittleness index of the rock is further calculated using the Rickman method. The calculation formula of the brittleness index is:
[0100]
[0101] Where E represents Young's modulus, 104 MPa; μ represents Poisson's ratio.
[0102] Table 6 shows the calculated brittleness index corresponding to each well.
[0103] Table 6 Calculation results of brittleness index
[0104] hashtag Well Type Brittleness Index M1 production wells 0.43 M2 production wells 0.32 M3 production wells 0.56 M4 production wells 0.41
[0105] By comparing the importance of each pair of factors affecting the refracturing process strategy, the scale size is determined and a judgment matrix is constructed as shown in Table 7.
[0106] Table 7 Judgment Matrix
[0107] Initial fracturing crack Reservoir pressure Residual oil distribution Ground stress diversion Rock brittleness index Initial fracturing crack 1 2 1 0.5 4 Reservoir pressure 0.5 1 0.5 0.25 3 Residual oil distribution 1 2 1 0.5 4 Ground stress diversion 2 4 2 1 5 Rock brittleness index 0.25 1 / 3 0.25 0.2 1
[0108] The first weight values obtained through normalized calculation are 0.22 for primary fracturing cracks, 0.12 for reservoir pressure, 0.22 for remaining oil distribution, 0.39 for ground stress turning, and 0.05 for rock brittleness index.
[0109] In addition, the test of weight value includes the following steps:
[0110] First, calculate the maximum eigenvalue according to the weight matrix. The calculation method is:
[0111]
[0112] Where AW is the product of the judgment matrix and the normalized weights. The maximum eigenvalue is 5.062.
[0113] According to the maximum eigenvalue, the consistency index CI is calculated as follows:
[0114]
[0115] The consistency index CI was calculated to be 0.016.
[0116] By dividing the consistency index CI by the random consistency index RI, the consistency ratio CR can be calculated. The formula is:
[0117]
[0118] The RI value can be found by looking up the table. This is the random consistency index (RI) value obtained from 1000 Satty simulations. Refer to Table 2. From Table 2, the RI value corresponding to the 5th order is 1.12. Substituting this into the calculation, the CR is 0.014. When CR < 0.1, the consistency of judgment matrix A is considered to be within the acceptable range. If CR ≥ 0.1, a logical error occurred in the construction of the judgment matrix and the judgment matrix needs to be corrected. Since 0.014 < 0.1, the verification passes.
[0119] Calculations for each criterion layer yielded scores of 0.211 for the "Volume Refracturing" strategy, 0.152 for the "Energy Replenishment" strategy, 0.213 for the "Volume Refracturing" strategy, 0.197 for the "Replenishment" strategy, and 0.167 for the "Replenishment Along Existing Fractures" strategy. The most heavily weighted strategy, "Energy Replenishment" for the "Volume Refracturing" strategy, received a quantitative score of 0.213.
[0120] The weights of each refracturing process in the scenario layer were calculated using the formula described in S7. CR was verified by combining RI. According to the RI table, the corresponding RI value was 1.11. Therefore, CR = CI / RI = 0.014 (0.044) < 0.1. Ultimately, both layers B and C passed the consistency test and met the normative requirements of the AHP methodology.
[0121] Taking Well M3 in the M well group as an example, the refracturing process was selected. Because the well's brittleness index was 56% (>50%), a correction was made to the diverted volume refracturing factor, resulting in a value of 0.224. Other parameters were within the specified range and did not require correction. The corrected diverted volume refracturing factor had the highest weight, so this process was selected. The corrections in this case are shown in Table 8. The corrected second weight coefficient was then used to determine the final refracturing process.
[0122] Table 8 Re-fracturing process correction
[0123]
[0124]
[0125] As can be seen, the present invention, based on the Analytic Hierarchy Process (AHP), provides a method, apparatus, and readable storage medium for formulating a refracturing strategy for an injection-production well group. This overcomes the significant subjective influence of prior art methods based on experience and expert opinion. The present method quantifies the impact of evaluation factors at each level and, considering the thresholds of these factors, weights them appropriately for specific operating conditions. This rationally complements the static model of the AHP, ensures the accuracy and rationality of strategy formulation, and facilitates rapid and convenient on-site application.
[0126] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.
[0127] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical functional division. In actual implementation, other division methods may be used, such as combining or integrating multiple units or components into another system, or ignoring or not implementing certain features.
[0128] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of the embodiments of the present invention.
[0129] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.
[0130] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.
[0131] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
Claims
1. A method for formulating a repeated fracturing process strategy for an injection-production well group, characterized in that: The following steps are involved: S1. Collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection-production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model; S2. Establish a hierarchical model, construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and construct a solution layer based on the repeated fracturing process; S3. Compare parameters that affect the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
2. The method for formulating a repeated fracturing process strategy for an injection-production well group according to claim 1, wherein: Step S1 also includes: obtaining initial crack parameters and rock brittleness index.
3. The method for formulating a repeated fracturing process strategy for an injection-production well group according to claim 1, wherein: The reservoir dynamic parameters in step S1 include reservoir pressure and reservoir oil-water distribution.
4. The method for formulating a repeated fracturing process strategy for an injection-production well group according to claim 1, wherein: Step S2 also includes constructing a sub-criteria layer, wherein the sub-criteria layer parameters include the amount of fracturing fluid injected into the ground, the amount of proppant injected into the ground, the stable production period, the water content, the cumulative recovery degree, the phase permeability, the average oil saturation, the remaining oil saturation, the initial fracture angle, the ground stress difference, the Young's modulus, the Poisson's ratio, the permeability, and the porosity.
5. The method for formulating a refracturing process strategy for an injection-production well group according to claim 1, wherein: The refracturing process in step S2 includes redirected refracturing, redirected volume refracturing, energy supplemented redirected refracturing, energy supplemented redirected volume refracturing, and refracturing along old fractures.
6. The method for formulating a refracturing process strategy for an injection-production well group according to claim 1, wherein: Step S3 also includes, if there are special operating parameters, correcting the first weight value, obtaining the corrected second weight, and selecting the repeated fracturing process according to the second weight value.
7. The method for formulating a refracturing process strategy for an injection-production well group according to claim 6, wherein: Step S3 also includes, if the reservoir pressure coefficient is less than 0.7, then the weight of energy supplementation and re-fracturing is corrected, and the correction formula is: If the brittle mineral content is greater than 50%, the proportion of the diverting area with a diverting angle greater than 45° is greater than 0.3, or the proportion of the area with oil saturation change is greater than 70%, the weight of the diverting volume for repeated fracturing is corrected. The correction formula is: W′=W·(1+actual value-critical value) If the ground stress difference is less than 5MPa or the stable production period is greater than 2 years, the weight of repeated fracturing along the old fractures is corrected. The correction formula is: Wherein, W is the first weight before correction, and W′ is the second weight after correction.
8. A system for formulating a repeated fracturing process strategy for an injection-production well group, characterized in that: include: A parameter determination module is used to collect basic parameters, establish a numerical simulation model for repeated fracturing of the injection and production well group, and obtain reservoir dynamic parameters and formation dynamic stress field parameters based on the numerical simulation model; A hierarchical model construction module is used to construct a criterion layer based on the initial fracture parameters, reservoir pressure, reservoir oil-water distribution, formation stress field, and rock brittleness index, and to construct a solution layer based on the repeated fracturing process, and to build a hierarchical model; The process determination module is used to compare parameters affecting the refracturing process strategy, scale the parameters, calculate a first weight value, and select a refracturing process according to the first weight value.
9. A computer-readable storage medium comprising instructions, which, when executed on a computer, enable the computer to execute the method for formulating a refracturing process strategy for an injection-production well group according to any one of claims 1 to 7.
10. A computing device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for formulating a repeated fracturing process strategy for an injection-production well group is implemented as described in any one of claims 1-7.