Shale reservoir classification method and device based on bedding seams, electronic equipment and medium

Abstract

The embodiment of the invention relates to the technical field of reservoir geophysical logging, and provides a shale reservoir classification method and device based on bedding fractures, electronic equipment and a medium, and the method comprises the steps: obtaining first bedding fracture density data corresponding to different shale reservoirs of a target production well; for each shale reservoir, determining a first dessert reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; and classifying the shale reservoir based on the first dessert reservoir evaluation coefficient and a pre-established dessert reservoir division standard to obtain a classification result of the shale reservoir. Therefore, by counting the bedding fracture density of the shale reservoir, the contribution of the bedding fracture density to evaluation of the shale reservoir can be determined in combination with the formation testing result, and efficient and accurate evaluation of the shale reservoir and determination of the dessert reservoir are realized.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir geophysical logging, and in particular to a shale reservoir classification method, device, electronic equipment and medium based on bedding fractures. Background Art

[0002] Shale oil and gas are important unconventional oil and gas resources and play an important role in economic development. Compared with conventional reservoirs, shale reservoirs have worse physical properties and stronger heterogeneity. Natural fractures are the main seepage channels of shale reservoirs, and their development characteristics are of great significance to the development of shale oil and gas.

[0003] At present, conventional shale reservoir evaluation methods include: logging during drilling, electrical logging after drilling, and mechanical production logging. Logging during drilling is greatly affected by the wellbore interference, and the detection distance is limited to a few meters; electrical logging after drilling has many characteristic parameters and the multi-solution caused by nonlinearity leads to large deviations in the results; mechanical production logging can correct whether the interpretation results are accurate. On the one hand, the conditions for production logging are relatively harsh, and mechanical logging instruments need to be lowered. They are usually restricted by the completion method, wellbore integrity and other conditions. For example, casing deformation, throttling devices under the production string, or segmented ball-dropping sleeves are used. These wells cannot perform production logging; on the other hand, the test data obtained by production logging is only data at a time point, which is easily affected by the test environment. Therefore, production logging data does not have complete guiding significance; therefore, conventional shale reservoir evaluation methods may have identification biases. How to evaluate shale reservoirs efficiently and accurately to determine sweet spot reservoirs has become an urgent problem to be solved. Summary of the invention

[0004] The present invention provides a shale reservoir classification method, device, electronic equipment and medium based on bedding fractures, which are used to solve the defects of the shale reservoir evaluation method in the prior art that is complex and has inaccurate identification results, and to achieve efficient and accurate evaluation of shale reservoirs to determine sweet spot reservoirs.

[0005] The present invention provides a shale reservoir classification method based on bedding fractures, comprising: Obtain the first layer fracture density data corresponding to different shale reservoirs of the target production well; For each of the shale reservoirs, determining a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first layer fracture density data corresponding to the shale reservoir; The shale reservoir is classified based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

[0006] In a possible implementation, the method further includes: For each of the shale reservoirs, determining a target sweet spot reservoir based on the classification result of the shale reservoir; The shale reservoir is tested for oil, and the target sweet spot reservoir is verified based on the test results.

[0007] In a possible implementation, the method further includes: For each of the shale reservoirs, obtaining the number of core fractures and the core length of the shale reservoir; The first layer fracture density data corresponding to the shale reservoir is determined based on the ratio of the number of core fractures to the core length.

[0008] In a possible implementation, the method further includes: The first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir is determined by a first formula, wherein the first formula is: ; Among them, E is the first sweet spot reservoir evaluation coefficient; is the bedding density of the i-th shale reservoir, is the minimum bedding fracture density in the bedding fracture density range, is the maximum bedding fracture density in the bedding fracture density range.

[0009] In a possible implementation, the method further includes: Calculate the second sweet spot reservoir evaluation coefficient according to the second layer fracture density data corresponding to each shale reservoir of the produced wells; A sweet spot reservoir classification standard is established based on the second sweet spot reservoir evaluation coefficient and the oil test results of the produced well, wherein the sweet spot reservoir classification standard includes multiple classification categories, each classification category corresponds to a different sweet spot reservoir evaluation coefficient range and a minimum value of bedding fracture density.

[0010] In a possible implementation, the method further includes: According to the sweet spot reservoir classification standard, determine the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir and the classification category that the first layer fracture density data conforms to, and obtain the classification result of the shale reservoir; The shale reservoir classified as the first type is taken as the target sweet spot reservoir.

[0011] The present invention also provides a shale reservoir classification device based on bedding fractures, comprising the following modules: An acquisition module, used to acquire the first layer fracture density data corresponding to different shale reservoirs of the target production well; A determination module, for determining, for each of the shale reservoirs, a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first layer fracture density data corresponding to the shale reservoir; A classification module is used to classify the shale reservoir based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

[0012] The present invention also provides an electronic 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 computer program, a shale reservoir classification method based on bedding fractures as described above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the shale reservoir classification method based on bedding fractures as described in any one of the above is implemented.

[0014] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for classifying shale reservoirs based on bedding fractures as described above is implemented.

[0015] The shale reservoir classification method, device, electronic device and medium based on bedding fractures provided by the present invention obtain the first bedding fracture density data corresponding to different shale reservoirs of the target production well; for each shale reservoir, determine the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; classify the shale reservoir based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain the classification result of the shale reservoir. Compared with the defects of the shale reservoir evaluation method in the prior art that is complex and has inaccurate identification results, this solution can determine the contribution of bedding fracture density to shale reservoir evaluation by statistically analyzing the bedding fracture density of the shale reservoir and combining it with the oil test results, so as to achieve efficient and accurate evaluation of shale reservoirs and determine sweet spot reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is one of the flow diagrams of the shale reservoir classification method based on bedding fractures provided by the present invention.

[0018] Figure 2 This is the second flow chart of the shale reservoir classification method based on bedding fractures provided by the present invention.

[0019] Figure 3 This is a schematic diagram of the bedding fracture density and sweet spot reservoir distribution of Well A provided by the present invention.

[0020] Figure 4 It is a structural schematic diagram of a shale reservoir classification device based on bedding fractures provided by the present invention.

[0021] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below in conjunction with the accompanying drawings. The embodiments do not constitute a limitation on the embodiments of the present invention.

[0024] Figure 1 This is one of the flow diagrams of the shale reservoir classification method based on bedding fractures provided by the present invention, such as Figure 1 As shown, the method includes the following: S11, obtaining first layer fracture density data corresponding to different shale reservoirs of the target production well.

[0025] The embodiment of the present invention proposes a method for evaluating shale reservoirs by the degree of bedding fracture development. First, the first bedding fracture density data corresponding to different shale reservoirs of the target production well are obtained. The target production well is an oil and gas production well of the shale reservoir to be evaluated, and the first bedding fracture density data corresponding to different shale reservoirs can be obtained by core observation method or logging data interpretation method.

[0026] Specifically, the core observation method uses the core taken out from the well to directly observe the number of cracks and the length of the core, and takes the ratio of the number of cracks in the core to the length of the core as the density of the bedding fracture. Different shale reservoirs have corresponding first-layer fracture density data. The logging data interpretation method uses conventional logging data and imaging logging data to identify and study fractures.

[0027] S12. For each of the shale reservoirs, determine a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir.

[0028] The first sweet spot reservoir evaluation coefficient corresponding to each shale reservoir is calculated by the first formula, and the first formula is as follows:

[0029] Among them, E is the first sweet spot reservoir evaluation coefficient; is the bedding density of the i-th shale reservoir, in bars / m, is the minimum bedding fracture density in the bedding fracture density range, in units of bars / m, It is the maximum bedding fracture density in the bedding fracture density range, with the unit of bars / m.

[0030] S13. Classify the shale reservoir based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

[0031] In an embodiment of the present invention, a second sweet spot reservoir evaluation coefficient is calculated in advance based on the second bedding fracture density data corresponding to different shale reservoirs of the exploited production wells; and then a sweet spot reservoir classification standard is established based on the second sweet spot reservoir evaluation coefficient and the oil test results of the exploited production wells, wherein the sweet spot reservoir classification standard includes multiple classification categories, each classification category corresponding to a different sweet spot reservoir evaluation coefficient range and a minimum bedding fracture density value.

[0032] Furthermore, according to the pre-established sweet spot reservoir classification standard, the first sweet spot reservoir evaluation coefficient corresponding to different shale reservoirs of the target production well and the classification category that the first layer fracture density data conforms to are judged, and the classification results corresponding to different shale reservoirs are obtained, and the shale reservoir with the first classification result is taken as the target sweet spot reservoir.

[0033] Furthermore, oil tests can be conducted on different shale reservoirs of the target production wells, and the target sweet spot reservoir can be verified based on the oil test results. The verification results show that the oil test results of the target sweet spot reservoir determined by the above method are the best and have the most mining prospects.

[0034] The shale reservoir classification method based on bedding fractures provided by the present invention obtains the first bedding fracture density data corresponding to different shale reservoirs of the target production well; for each shale reservoir, the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir is determined based on the first bedding fracture density data corresponding to the shale reservoir; the shale reservoir is classified based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain the classification result of the shale reservoir. Compared with the defects of the shale reservoir evaluation method in the prior art that is complex and has inaccurate identification results, this method can determine the contribution of bedding fracture density to shale reservoir evaluation by statistically analyzing the bedding fracture density of the shale reservoir and combining it with the oil test results, so as to achieve efficient and accurate evaluation of shale reservoirs and determine the sweet spot reservoirs.

[0035] Figure 2 This is the second flow chart of the shale reservoir classification method based on bedding fractures provided by the present invention, such as Figure 2 As shown, the method includes the following: S21. For each of the shale reservoirs, obtain the number of core fractures and the core length of the shale reservoir.

[0036] S22. Determine the first layer fracture density data corresponding to the shale reservoir based on the ratio of the number of core fractures to the core length.

[0037] The embodiment of the present invention proposes a method for evaluating shale reservoirs by the degree of bedding fracture development. First, the first bedding fracture density data corresponding to different shale reservoirs of the target production well are obtained. The target production well is an oil and gas production well of the shale reservoir to be evaluated, and the first bedding fracture density data corresponding to different shale reservoirs can be obtained by core observation method or logging data interpretation method.

[0038] Specifically, the core observation method uses the core taken out from the well to directly observe the number of cracks and the length of the core; the logging data interpretation method uses conventional logging data and imaging logging data to identify and study cracks, and also obtains the number of cracks and core lengths corresponding to different shale reservoirs. Further, the ratio of the number of core cracks and the core length is used as the bedding fracture density, and different shale reservoirs have corresponding first bedding fracture density data. For example, the number of cracks can be counted in detail by microscopes, scanning electron microscopes and other equipment. The core length can be obtained by actual measurement. This step is the basic data collection link, which provides a basis for subsequent calculations and evaluations. The bedding fracture density of high-density lamellar shale reservoirs can reach hundreds or even thousands per meter. The higher the bedding fracture density, the more developed the reservoir fractures are, and the more favorable it is for the storage and seepage capacity of oil and gas.

[0039] S23. Determine a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir by using a first formula.

[0040] The first sweet spot reservoir evaluation coefficient corresponding to each shale reservoir is calculated by the first formula, and the first formula is as follows:

[0041] Among them, E is the first sweet spot reservoir evaluation coefficient; is the bedding density of the i-th shale reservoir, in bars / m, is the minimum bedding fracture density in the bedding fracture density range, in units of bars / m, It is the maximum bedding fracture density in the bedding fracture density range, with the unit of bars / m.

[0042] Taking the data in Table 1 below as an example, after obtaining the bedding fracture density of 5 layers, the maximum fracture density of 58.77 and the minimum fracture density of 35.45 can be selected from the 5 bedding fracture densities, and then according to the target bedding fracture density range of 58.77 and the minimum fracture density of 35.45, it is assumed to be 35~60, and then the bedding fracture density of each layer can be normalized according to the above formula to obtain the reservoir evaluation coefficient of each layer. Taking the bedding fracture density of 58.39 of the first layer as an example, the reservoir evaluation coefficient of the first layer can be calculated as E1=(58.39-35) / (60-35)≈0.94. The reservoir evaluation coefficient of each layer can be calculated by this method.

[0043] Exploration and development practices show that the more developed the natural fractures in the shale reservoir, the better the physical properties of the shale reservoir, and the easier it is to extract oil and gas. The embodiment of the present invention evaluates the shale reservoir from the perspective of bedding fractures, and can clarify the impact of bedding fractures on the shale reservoir.

[0044] In an embodiment of the present invention, a second sweet spot reservoir evaluation coefficient is calculated in advance based on the second bedding fracture density data corresponding to different shale reservoirs of the exploited production wells, and then a sweet spot reservoir classification standard is established based on the second sweet spot reservoir evaluation coefficient and the oil test results of the exploited production wells, wherein the sweet spot reservoir classification standard includes multiple classification categories, each classification category corresponding to a different sweet spot reservoir evaluation coefficient range and a minimum bedding fracture density value.

[0045] For example, a part of the well section of Well A with well-developed bedding fractures in a certain block was selected to statistically analyze the density of bedding fractures in a single well through core and logging data, and the sweet spot reservoir evaluation coefficient E (Table 1) was calculated, and the sweet spot reservoir division standard was established.

[0046] Table 1 Data table of sweet spot reservoir evaluation coefficients in different well sections of Well A

[0047] Through the analysis of the sweet spot reservoir evaluation coefficient, the larger the coefficient, the better the sweet spot reservoir type, and the easier it is to exploit the reservoir oil and gas. According to the sweet spot reservoir evaluation coefficient, shale reservoirs can be divided into the following three categories: The sweet spot evaluation coefficient of Class I reservoirs is greater than 0.7, and the density of bedding fractures in this type of reservoir is greater than 52 lines / m.

[0048] The sweet spot evaluation coefficient of Class II reservoirs is 0.3~0.7, and the density of bedding fractures in this type of reservoir is greater than 43 / m.

[0049] The sweet spot evaluation coefficient of Class III reservoirs is less than 0.3, and the density of bedding fractures of this type is greater than 30 / m.

[0050] This method was used to evaluate the sweet spot reservoir types in different sections of Well A, and the following results were obtained: Figure 3 The classification results are shown.

[0051] S24. Determine the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir and the classification category that the first layer fracture density data conforms to according to the sweet spot reservoir classification standard, and obtain the classification result of the shale reservoir.

[0052] S25. The shale reservoir classified as the first type is taken as a target sweet spot reservoir.

[0053] After establishing the sweet spot reservoir classification standard, the classification results corresponding to different shale reservoirs of the target production wells can be determined based on the first sweet spot reservoir evaluation coefficient and the first layer fracture density data corresponding to different shale reservoirs of the target production wells.

[0054] The shale reservoirs that meet the first category in the classification results are taken as target sweet spot reservoirs. Sweet spot reservoirs refer to areas with high oil and gas enrichment, good reservoir performance and high development potential. These areas usually have high bedding fracture density and good permeability, and are the key targets of shale oil and gas development.

[0055] S26. Conduct oil testing on the shale reservoir, and verify the target sweet spot reservoir based on the oil testing results.

[0056] Furthermore, oil tests can be conducted on each shale reservoir of the target production well, and the target sweet spot reservoir can be verified based on the oil test results. The verification results show that the oil test results of the target sweet spot reservoir determined by the above method are the best and have the most potential for exploitation. Oil testing is to obtain actual oil and gas production, pressure and other data by conducting small-scale oil and gas production tests in the reservoir. The oil test results can verify the accuracy of the previous evaluation and further confirm the development potential and economic value of the target sweet spot reservoir.

[0057] The above method can quantitatively evaluate shale reservoirs from the perspective of bedding fractures. Compared with traditional shale reservoir evaluation methods, it can clarify the impact of the development of bedding fractures on the distribution of sweet spots in shale reservoirs.

[0058] The shale reservoir classification method based on bedding fractures provided by the present invention obtains the first bedding fracture density data corresponding to different shale reservoirs of the target production well; for each shale reservoir, the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir is determined based on the first bedding fracture density data corresponding to the shale reservoir; the shale reservoir is classified based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain the classification result of the shale reservoir. According to this method, by statistically analyzing the bedding fracture density of the shale reservoir and combining it with the oil test results, the contribution of the bedding fracture density to the shale reservoir evaluation can be determined, so as to achieve efficient and accurate evaluation of the shale reservoir and determine the sweet spot reservoir.

[0059] The shale reservoir classification device based on bedding fractures provided by the present invention is described below. The shale reservoir classification device based on bedding fractures described below and the shale reservoir classification method based on bedding fractures described above can be referred to each other.

[0060] Figure 4 The structure diagram of the shale reservoir classification device based on bedding fractures provided by the present invention specifically includes: An acquisition module 401 is used to acquire first layer fracture density data corresponding to different shale reservoirs of a target production well; A determination module 402 is used to determine, for each of the shale reservoirs, a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; The classification module 403 is used to classify the shale reservoir based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain the classification result of the shale reservoir.

[0061] In a possible implementation, the acquisition module 401 is specifically used to acquire the number of core fractures and the core length of each shale reservoir; and determine the first layer fracture density data corresponding to the shale reservoir based on the ratio of the number of core fractures to the core length.

[0062] In a possible implementation, the determination module 402 is specifically configured to determine a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir by using a first formula, wherein the first formula is: ; Wherein, E is the first sweet spot reservoir evaluation coefficient; is the bedding density of the i-th shale reservoir, is the minimum bedding fracture density in the bedding fracture density range, is the maximum bedding fracture density in the bedding fracture density range.

[0063] In a possible implementation, the classification module 403 is specifically used to determine the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir and the classification category that the first layer fracture density data conforms to according to the sweet spot reservoir classification standard, and obtain the classification result of the shale reservoir; and take the shale reservoir with the first category as the classification result as the target sweet spot reservoir.

[0064] In a possible implementation, the classification module 403 is further used to determine a target sweet spot reservoir for each of the shale reservoirs based on the classification results of the shale reservoirs; conduct oil testing on the shale reservoirs, and verify the target sweet spot reservoirs based on the oil testing results.

[0065] In a possible embodiment, the classification module 403 is also used to calculate a second sweet spot reservoir evaluation coefficient based on the second bedding fracture density data corresponding to each shale reservoir of the exploited production wells; and to establish a sweet spot reservoir classification standard based on the second sweet spot reservoir evaluation coefficient and the oil test results of the exploited production wells, wherein the sweet spot reservoir classification standard includes multiple classification categories, each classification category corresponding to a different sweet spot reservoir evaluation coefficient range and a minimum bedding fracture density value.

[0066] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute a shale reservoir classification method based on bedding fractures, the method comprising: obtaining first bedding fracture density data corresponding to different shale reservoirs of the target production well; for each of the shale reservoirs, determining a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; classifying the shale reservoir based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

[0067] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment 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 codes.

[0068] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the shale reservoir classification method based on bedding fractures provided by the above-mentioned methods, and the method includes: obtaining first bedding fracture density data corresponding to different shale reservoirs of the target production well; for each of the shale reservoirs, determining a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; classifying the shale reservoir based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir division standard to obtain a classification result of the shale reservoir.

[0069] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the shale reservoir classification method based on bedding fractures provided by the above-mentioned methods, the method comprising: obtaining first bedding fracture density data corresponding to different shale reservoirs of a target production well; for each of the shale reservoirs, determining a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir; classifying the shale reservoir based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir division standard to obtain a classification result of the shale reservoir.

[0070] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0071] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A shale reservoir classification method based on bedding fractures, characterized in that: include: Obtain the first layer fracture density data corresponding to different shale reservoirs of the target production well; For each of the shale reservoirs, determining a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first layer fracture density data corresponding to the shale reservoir; The shale reservoir is classified based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

2. The method according to claim 1, characterized in that: The method further comprises: For each of the shale reservoirs, determining a target sweet spot reservoir based on the classification result of the shale reservoir; The shale reservoir is tested for oil, and the target sweet spot reservoir is verified based on the test results.

3. The method according to claim 1, characterized in that The step of obtaining the first layer fracture density data corresponding to different shale reservoirs of the target production well includes: For each of the shale reservoirs, obtaining the number of core fractures and the core length of the shale reservoir; The first layer fracture density data corresponding to the shale reservoir is determined based on the ratio of the number of core fractures to the core length.

4. The method according to claim 3, characterized in that The determining of a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first bedding fracture density data corresponding to the shale reservoir includes: The first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir is determined by a first formula, wherein the first formula is: ; Among them, E is the first sweet spot reservoir evaluation coefficient; is the bedding density of the i-th shale reservoir, is the minimum bedding fracture density in the bedding fracture density range, is the maximum bedding fracture density in the bedding fracture density range.

5. The method according to claim 1, characterized in that The method further comprises: Calculate the second sweet spot reservoir evaluation coefficient according to the second layer fracture density data corresponding to each shale reservoir of the produced wells; A sweet spot reservoir classification standard is established based on the second sweet spot reservoir evaluation coefficient and the oil test results of the produced well, wherein the sweet spot reservoir classification standard includes multiple classification categories, each classification category corresponds to a different sweet spot reservoir evaluation coefficient range and a minimum value of bedding fracture density.

6. The method according to any one of claims 1 to 5, characterized in that: The classifying the shale reservoir based on the first sweet spot reservoir evaluation coefficient and the pre-established sweet spot reservoir classification standard to obtain the classification result of the shale reservoir includes: According to the sweet spot reservoir classification standard, determine the first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir and the classification category that the first layer fracture density data conforms to, and obtain the classification result of the shale reservoir; The shale reservoir classified as the first type is taken as the target sweet spot reservoir.

7. A shale reservoir classification device based on bedding fractures, characterized in that: include: An acquisition module, used to acquire the first layer fracture density data corresponding to different shale reservoirs of the target production well; A determination module, for determining, for each of the shale reservoirs, a first sweet spot reservoir evaluation coefficient corresponding to the shale reservoir based on the first layer fracture density data corresponding to the shale reservoir; A classification module is used to classify the shale reservoir based on the first sweet spot reservoir evaluation coefficient and a pre-established sweet spot reservoir classification standard to obtain a classification result of the shale reservoir.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the shale reservoir classification method based on bedding fractures as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the shale reservoir classification method based on bedding fractures as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the shale reservoir classification method based on bedding fractures as described in any one of claims 1 to 6 is implemented.

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