Shale gas well fracturing parameter optimization method and system based on pump stop pressure drop

Abstract

The invention relates to the technical field of oil and gas field development, in particular to a shale gas well fracturing parameter optimization method and device based on pump stop pressure drop, and the method comprises the steps that fracturing construction parameters of a fracturing section are obtained; obtaining fracture network interpretation parameters and SRV parameters; obtaining production logging monitoring data of the fracturing section; according to the crack type of the fracturing section, the fracturing section is calibrated as a matrix section, a micro crack section and a bending section; the method comprises the following steps: respectively calling parameters for fracturing sections classified into a matrix section, a microfracture section and a bending section, forming an arrangement of two fracturing sections according to production logging monitoring data in the parameters and the numerical value of an SRV parameter, and screening out a plurality of fracturing sections located in a specified sorting interval in the two arrangements, and fracturing construction parameters are respectively used as preferable parameters of a matrix section, a microfracture section or a bending section. And subsequently, in a shale gas well fracturing section under the same geological background condition, fracturing parameter design can be carried out by referring to the optimal fracturing parameter range.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, specifically to a method and apparatus for optimizing fracturing parameters in shale gas wells based on pump shutdown pressure drop. Background Technology

[0002] Shale gas, an unconventional natural gas produced from shale reservoirs, has enormous development potential. However, the extremely low permeability and porosity of shale make shale gas extraction very difficult. To address this, fracturing technology is typically used, which involves injecting high-pressure fracturing fluid into the well to create and propagate fractures, thereby increasing the permeability of the shale reservoir and improving shale gas recovery. Shale gas well fracturing parameters are a series of technical indicators and parameters that need to be set and adjusted during the fracturing process. Optimizing these parameters not only maximizes the fracturing effect but also maximizes the economic benefits of shale gas development, makes the fracturing process more environmentally friendly and efficient, further reduces energy consumption and environmental pollution, and achieves low-carbon development. Therefore, optimizing shale gas well fracturing parameters is of great significance for achieving large-scale, efficient shale gas development.

[0003] Currently, optimizing fracturing parameters is primarily achieved through machine learning algorithms or numerical simulations. Machine learning algorithms can predict production yields for different combinations of fracturing parameters, ultimately assessing the impact of each parameter to derive the optimal combination. Numerical simulation methods utilize mature commercial software to build models and compare implementation effects with various combinations of fracturing parameters, ultimately generating targeted fracturing parameter optimization recommendations for shale gas wells. While these methods offer high testing accuracy, machine learning consumes significant computational resources, requiring a large number of sample points to build accurate algorithm models. Excessive training time can impact efficiency and carries the risk of overfitting. On the other hand, numerical simulation methods suffer from high computational complexity, with overly complex mathematical models resulting in excessive computational loads. Furthermore, these methods simulate simplified example wells, leading to deviations from actual conditions and affecting the optimization effectiveness of fracturing parameters.

[0004] Therefore, there is an urgent need to propose a convenient, fast, and reliable method for optimizing fracturing parameters. Summary of the Invention

[0005] To overcome at least one of the aforementioned shortcomings, this paper proposes a method and apparatus for optimizing fracturing parameters in shale gas wells based on pump shutdown pressure drop. By utilizing pressure data from the pump shutdown phase during fracturing operations for well test interpretation and analysis, the resulting single-stage fracturing network stimulation effect and the proportion of gas production contribution from single-stage production logging can be used to optimize fracturing parameters for fracturing stages of different natural fracture types. This provides optimal parameter recommendations for subsequent fracturing of similar gas wells. The method is simple to operate, the data is readily available and reliable, and it is precise down to the single fracturing stage, resulting in highly reliable analysis results. This method is of great significance for improving the development efficiency and economic benefits of shale gas wells.

[0006] To achieve the above objectives, the shale gas well fracturing parameter optimization method disclosed in this invention can adopt the following technical solution:

[0007] A method for optimizing fracturing parameters in shale gas wells based on pump shutdown pressure drop includes:

[0008] Obtain the fracturing operation parameters for each fracturing section of the target well during fracturing, and calibrate the fracturing operation flow rate, fracturing fluid strength, and fracturing proppant strength as fracturing parameter A, fracturing parameter B, and fracturing parameter C, respectively;

[0009] Based on the pressure second-point data of each fracturing section of the target well during the pump shutdown stage, pressure double logarithmic and derivative curves were plotted and interpreted to obtain the interpretation parameters of the fracturing network. The fracture half-length, fracture height, and fracture width were respectively labeled as interpretation parameters A, B, and C. The SRV parameters were obtained based on the interpretation parameters of the fracturing network.

[0010] Monitor the production logging of each fractured section of the target well and obtain production logging monitoring data;

[0011] Based on the fracture type of each fracturing section in the target well, the fracturing sections are respectively labeled as matrix section, microfracture section and flexural section;

[0012] Parameters were retrieved for each fracturing segment classified as matrix segment, microfracture segment, and flexure segment. Based on the production logging monitoring data and SRV parameter values ​​in the parameters, two fracturing segments were arranged. Several fracturing segments that were located in the specified sorting interval in both arrangements were selected, and their fracturing operation parameters were used as the preferred parameters for matrix segment, microfracture segment, or flexure segment, respectively.

[0013] The aforementioned method for optimizing fracturing parameters clarifies the optimal range of fracturing parameters under different natural fracture types. Therefore, subsequent fracturing sections in shale gas wells under the same geological conditions can be designed with reference to this optimal range of parameters for different natural fracture types. Adding more sample points for fracturing sections can further improve the accuracy of this optimal range of parameters.

[0014] The meanings of some concepts are explained here, as follows.

[0015] Fracturing fluid strength: The ratio of the total amount of fracturing fluid used in a certain section of a gas well to the length of that section.

[0016] Fracturing operation displacement: The amount of fracturing fluid injected into the formation per unit time in a certain section of a gas well.

[0017] Fracturing sand intensity: The ratio of the total amount of sand added during fracturing in a certain section of a gas well to the length of that section.

[0018] Matrix segment: This refers to the portion of a geological body that is unaffected or minimally affected by natural fissures. These areas typically lack well-developed fissures and are primarily composed of solid rock or soil matrix. Fissures in the matrix segment are usually relatively small.

[0019] Microfracture segments refer to geological sections with relatively small-scale, numerous, and widely distributed fractures. These fractures are typically narrow in width and relatively short in length, but their large number can form complex fracture networks. Although the scale of fractures in microfracture segments is small, their energy levels can be relatively high due to their large number and dense distribution.

[0020] Flexural sections refer to large-scale bending and deformation areas formed by geological processes such as crustal movement and plate tectonics. These areas are usually accompanied by significant stratigraphic folding and faulting, with large-scale and concentrated fractures. In flexural sections, the fractures are typically large in scale and have relatively high energy levels.

[0021] Furthermore, in this invention, the fracturing operation parameters are stored for subsequent analysis and processing. The specific storage method is not limited to one thing. Here, we optimize and propose the following feasible option: after obtaining the fracturing operation parameters, they are stored in the first storage unit; after obtaining the fracturing network interpretation parameters, they are stored in the second storage unit; and after obtaining the production logging monitoring data, they are stored in the third storage unit.

[0022] Furthermore, after processing the data, it can be reclassified and stored. Here, one feasible option is proposed: the parameters of the fracturing segment classified into the matrix segment are stored in the fourth storage unit, the parameters of the fracturing segment classified into the micro-fracture segment are stored in the fifth storage unit, and the parameters of the fracturing segment classified into the flexure segment are stored in the sixth storage unit.

[0023] Furthermore, in this invention, the SRV parameter is a user-defined parameter, and its specific determination method is: SRV parameter = Explanation parameter A × Explanation parameter B × Explanation parameter C × 0.01.

[0024] Furthermore, the production logging monitoring data includes the percentage of gas production contribution from a single fracturing stage.

[0025] Furthermore, production logging monitoring data can be obtained through tracer monitoring or fiber optic monitoring.

[0026] Tracer monitoring: Gas well tracer monitoring is a technique that uses tracers to understand the reservoir in a single well or between wells. Specifically, this technique mainly involves injecting tracers into a specific fractured section or completion section and monitoring the tracer production in that section to assess information such as fracturing effectiveness, reservoir connectivity, fracture morphology, and distribution. Therefore, the gas production capacity of the fractured section can be determined by the proportion of tracer flowback contribution in each section of the well.

[0027] Fiber Optic Monitoring: Gas well fiber optic monitoring is a method for testing gas well production profiles using fiber optic sensing technology. This method primarily leverages the sensing characteristics of fiber optics, utilizing the high sensitivity and rapid response capabilities of fiber optic sensors to monitor downhole physical parameters such as temperature, pressure, and acoustic waves in real time, achieving high-precision testing of oil and gas well production profiles. By monitoring changes in downhole physical parameters in real time, the gas production status of different layers can be accurately identified, fracturing effectiveness can be evaluated, and important data can be provided for the optimized development and production adjustment of oil and gas wells.

[0028] Furthermore, the method for determining the preferred segment can be as follows: when screening fracturing segments in two arrangements, sort the production logging monitoring data and SRV parameter values ​​from largest to smallest, set the data volume in each arrangement to be the same, and select the top 30% of the fracturing segments. Then, retain the fracturing segments that rank in the top 30% in both arrangements as the preferred segments.

[0029] The above content describes the method for optimizing fracturing parameters. This invention also discloses the corresponding optimization system, which will be described below.

[0030] A shale gas well fracturing parameter optimization system based on pump shutdown pressure drop, used to implement the optimization method mentioned above: it includes a data acquisition module and several storage modules, as well as a data processing module and a main control module. The data acquisition module and storage module communicate with the data processing module, and the main control module communicates with the data acquisition module, storage module and data processing module.

[0031] Furthermore, the composition of the storage module can adopt various schemes and is not limited to one. Here, we optimize and propose one feasible option: the storage module includes a first to a sixth independent storage unit.

[0032] Compared with the prior art, some of the beneficial effects of the technical solution disclosed in this invention include:

[0033] 1. This invention utilizes pressure data from the pump shutdown phase during shale gas well fracturing to interpret and analyze well test data, thereby optimizing single-stage fracturing parameters. This process is simple to operate, and the pressure data from the pump shutdown phase during fracturing is readily available and reliable, resulting in highly credible analysis results. This is of great significance for improving the development efficiency and economic benefits of shale gas wells.

[0034] 2. Based on the analysis of pump shutdown pressure drop data in the fracturing section of a shale gas well, this invention can also be used to verify and analyze the production logging monitoring results of the same section of the well together. This improves and compensates for the shortcomings of single evaluation methods, such as large differences in adaptability and large deviations in analysis results. It greatly improves the accuracy of the evaluation results of the fracturing network effect in shale gas wells, and thus the accuracy of the optimal fracturing parameter range is also higher.

[0035] In summary, the method of this invention is simple, practical, economical, fast, and efficient, and has certain guiding significance for the optimization design of fracturing parameters in shale gas wells and the realization of large-scale and efficient development of shale gas. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a double logarithmic curve for fracturing section 1 in Case 1.

[0038] Figure 2 This is the double logarithmic curve of fracturing section 2 in Case 1.

[0039] Figure 3 This is the double logarithmic curve of fracturing section 3 in Case 1.

[0040] Figure 4 This is the double logarithmic curve of fracturing segment 4 in Case 1.

[0041] Figure 5 A bar chart was used to screen the percentage of gas production contribution in each gas-producing section.

[0042] Figure 6 This is a bar chart for screening SRVs in the matrix segment.

[0043] Figure 7 A bar chart showing the percentage contribution of gas production to micro-fracture segments.

[0044] Figure 8 A bar chart for screening SRVs in microcrack segments.

[0045] Figure 9A bar chart was used to screen the percentage of gas production contribution from the flexural section.

[0046] Figure 10 A bar chart for screening SRVs in the flexural segment. Detailed Implementation

[0047] The present invention will be further explained below with reference to the accompanying drawings and specific embodiments.

[0048] The existing methods for determining fracturing parameters in shale gas wells are relatively simple and do not consider all factors, resulting in insufficient quantification of the determined parameters. The following embodiments are optimized to overcome the defects of the existing technology.

[0049] Example 1

[0050] This embodiment provides a method for optimizing fracturing parameters in shale gas wells based on pump shutdown pressure drop, including:

[0051] Obtain the fracturing operation parameters for each fracturing section of the target well during fracturing, and calibrate the fracturing operation flow rate, fracturing fluid strength, and fracturing proppant strength as fracturing parameter A, fracturing parameter B, and fracturing parameter C, respectively;

[0052] Based on the pressure second-point data of each fracturing section of the target well during the pump shutdown stage, pressure double logarithmic and derivative curves were plotted and interpreted to obtain the interpretation parameters of the fracturing network. The fracture half-length, fracture height, and fracture width were respectively labeled as interpretation parameters A, B, and C. The SRV parameters were obtained based on the interpretation parameters of the fracturing network.

[0053] Monitor the production logging of each fractured section of the target well and obtain production logging monitoring data;

[0054] Based on the fracture type of each fracturing section in the target well, the fracturing sections are respectively labeled as matrix section, microfracture section and flexural section;

[0055] Parameters were retrieved for each fracturing segment classified as matrix segment, microfracture segment, and flexure segment. Based on the production logging monitoring data and SRV parameter values ​​in the parameters, two fracturing segments were arranged. Several fracturing segments that were located in the specified sorting interval in both arrangements were selected, and their fracturing operation parameters were used as the preferred parameters for matrix segment, microfracture segment, or flexure segment, respectively.

[0056] The fracturing parameter optimization method disclosed in this embodiment clarifies the optimal fracturing parameter range under different natural fracture types. Therefore, subsequent fracturing sections of shale gas wells under the same geological background conditions can be designed with reference to this optimal fracturing parameter range for different natural fracture types. Adding more sample points for fracturing sections can further improve the accuracy of this optimal fracturing parameter range.

[0057] This embodiment explains the meaning of some concepts as follows.

[0058] Fracturing fluid strength: The ratio of the total amount of fracturing fluid used in a certain section of a gas well to the length of that section.

[0059] Fracturing operation displacement: The amount of fracturing fluid injected into the formation per unit time in a certain section of a gas well.

[0060] Fracturing sand intensity: The ratio of the total amount of sand added during fracturing in a certain section of a gas well to the length of that section.

[0061] Matrix segment: This refers to the portion of a geological body that is unaffected or minimally affected by natural fissures. These areas typically lack well-developed fissures and are primarily composed of solid rock or soil matrix. Fissures in the matrix segment are usually relatively small.

[0062] Microfracture segments refer to geological sections with relatively small-scale, numerous, and widely distributed fractures. These fractures are typically narrow in width and relatively short in length, but their large number can form complex fracture networks. Although the scale of fractures in microfracture segments is small, their energy levels can be relatively high due to their large number and dense distribution.

[0063] Flexural sections refer to large-scale bending and deformation areas formed by geological processes such as crustal movement and plate tectonics. These areas are usually accompanied by significant stratigraphic folding and faulting, with large-scale and concentrated fractures. In flexural sections, the fractures are typically large in scale and have relatively high energy levels.

[0064] In this embodiment, the fracturing operation parameters are stored for subsequent analysis and processing. The specific storage method is not limited to one. This embodiment optimizes and adopts the following feasible option: after obtaining the fracturing operation parameters, they are stored in the first storage unit; after obtaining the fracturing network interpretation parameters, they are stored in the second storage unit; and after obtaining the production logging monitoring data, they are stored in the third storage unit.

[0065] After processing the data, it can be reclassified and stored. In this embodiment, one feasible option is to store the parameters of the fracturing segment that belongs to the matrix segment in the fourth storage unit, store the parameters of the fracturing segment that belongs to the micro-fracture segment in the fifth storage unit, and store the parameters of the fracturing segment that belongs to the flexure segment in the sixth storage unit.

[0066] In this embodiment, the SRV parameter is a user-defined parameter, and its specific determination method is: SRV parameter = Explanation parameter A × Explanation parameter B × Explanation parameter C × 0.01.

[0067] In this embodiment, the production logging monitoring data includes the percentage of gas production contribution from a single fracturing stage.

[0068] In this embodiment, production logging monitoring data is obtained through tracer monitoring or fiber optic monitoring.

[0069] Tracer monitoring: Gas well tracer monitoring is a technique that uses tracers to understand the reservoir in a single well or between wells. Specifically, this technique mainly involves injecting tracers into a specific fractured section or completion section and monitoring the tracer production in that section to assess information such as fracturing effectiveness, reservoir connectivity, fracture morphology, and distribution. Therefore, the gas production capacity of the fractured section can be determined by the proportion of tracer flowback contribution in each section of the well.

[0070] Fiber Optic Monitoring: Gas well fiber optic monitoring is a method for testing gas well production profiles using fiber optic sensing technology. This method primarily leverages the sensing characteristics of fiber optics, utilizing the high sensitivity and rapid response capabilities of fiber optic sensors to monitor downhole physical parameters such as temperature, pressure, and acoustic waves in real time, achieving high-precision testing of oil and gas well production profiles. By monitoring changes in downhole physical parameters in real time, the gas production status of different layers can be accurately identified, fracturing effectiveness can be evaluated, and important data can be provided for the optimized development and production adjustment of oil and gas wells.

[0071] The method for determining the preferred segment can be as follows: When screening fracturing segments in two arrangements, sort the production logging monitoring data and SRV parameter values ​​from largest to smallest, set the data volume in each arrangement to be the same, and select the top 30% of the fracturing segments. Then, retain the fracturing segments that rank in the top 30% in both arrangements as the preferred segments.

[0072] Example 2

[0073] The above-described embodiment 1 illustrates the method for optimizing fracturing parameters. This embodiment discloses the corresponding optimization system, which will be described below.

[0074] A shale gas well fracturing parameter optimization system based on pump shutdown pressure drop, used to implement the optimization method mentioned above: it includes a data acquisition module and several storage modules, as well as a data processing module and a main control module. The data acquisition module and storage module communicate with the data processing module, and the main control module communicates with the data acquisition module, storage module and data processing module.

[0075] The composition of the storage module can adopt various schemes and is not limited to one. Here, we optimize and propose one feasible option: the storage module includes a first to a sixth independent storage unit.

[0076] Preferably, the first to sixth storage units are all memory devices.

[0077] Based on the methods and systems disclosed in the above embodiments, a practical example is provided here for illustration.

[0078] Case 1

[0079] The shale gas horizontal well in this case is located in the Puluchang Syncline of the Xishan Structure in the Yuxi Block, with a depth of 6425m and a vertical depth of 3567m. The well is located in the Longmaxi Formation and has 32 fractured sections.

[0080] The following are the steps for storing gas well data for this well:

[0081] (1) Record the single-stage fracturing operation displacement of the gas well, denoted as "fracturing parameter A":

[0082] Table 1 Summary of Fracturing Parameters A (Partial Section)

[0083] Fracturing section 1 2 3 … … … 30 31 32 Fracturing operation displacement (cubic meters / minute) 17.6 19.8 17.8 … … … 20.0 17.7 18.8

[0084] (2) Record the strength of the single-stage fracturing fluid for this gas well, denoted as "fracturing parameter B":

[0085] Table 2 Summary of Fracturing Parameters B (Partial Section)

[0086] Fracturing section 1 2 3 … … … 30 31 32 Fracturing fluid strength (cubic meters) 37.91 44.01 51.93 … … … 39.72 35.86 44.18

[0087] (3) Record the single-stage fracturing sand addition intensity of the gas well, denoted as "fracturing parameter C":

[0088] Table 3 Summary of Fracturing Parameters C (Partial Section)

[0089] Fracturing section 1 2 3 … … … 30 31 32 Fracture sand-addition intensity (tons / meter) 2.70 4.33 4.30 … … … 4.03 3.72 4.64

[0090] (4) Obtain the pressure data per second during the pump shutdown phase of a single section of the well during fracturing. Further, after converting the data to the bottom of the well, plot the double logarithmic and derivative curves of the pressure based on this data, as shown below:

[0091] Table 4 Summary Table of Double Logarithmic Pressure Drop Curves During Pump Shutdown (Partial Section)

[0092] Fracturing section 1 2 … 31 32 Double logarithmic curve like Figure 1 As shown like Figure 2 As shown … like Figure 3 As shown like Figure 4 As shown

[0093] (5) The double logarithmic and derivative curves of the pump stop pressure drop of each segment of the gas well were interpreted and analyzed using the "Shale Gas Volumetric Fracturing Pump Stop Pressure Drop Analysis Software" of China University of Petroleum (Beijing).

[0094] (6) The crack half-length in the interpretation results is denoted as "interpretation parameter A":

[0095] Table 5 Summary Table of Explanation of Parameter A (Partial Section)

[0096] Fracturing section 1 2 3 … … … 30 31 32 Half the length of the crack (meters) 135.8 276.7 135.4 … … … 142.3 128.9 239.1

[0097] (7) The crack height in the interpretation results is denoted as "Interpretation Parameter B":

[0098] Table 6 Summary Table of Explanation of Parameter B (Partial Section)

[0099] Fracturing section 1 2 3 … … … 30 31 32 Crack height (meters) 34.9 34.1 32.3 … … … 16.6 29.6 30.1

[0100] (8) The crack width in the interpretation results is denoted as "interpretation parameter C":

[0101] Table 7 Summary Table of Explanation of Parameter C (Partial Section)

[0102]

[0103]

[0104] (9) Calculate the SRV of this gas well section as follows:

[0105] Table 8 SRV Summary Table (Partial Section)

[0106] Fracturing section 1 2 3 … … … 30 31 32 SRV (Wanfang) 121.4 239.7 102.6 … … … 78.7 128.1 214.9

[0107] 10) Obtain and record the percentage of gas production contribution from a single stage of production logging monitoring for this gas well, as shown below:

[0108] Table 9 Summary of Gas Production Contribution from Production Logging (Partial Section)

[0109] Fracturing section 1 2 3 … … … 30 31 32 Gas production contribution percentage 6.31 6.01 5.59 … … … 6.33 5.70 6.02

[0110] (11) Obtain the natural fracture types of all fractured sections of the gas well, and classify all fractured sections of the gas well as follows:

[0111] Table 10 Summary of Natural Crack Types (Partial Section)

[0112] Fracturing section 1 2 … 31 32 Natural crack types Matrix segment Microcrack segment … Flexural segment Matrix segment

[0113] The following are the steps for optimizing gas well fracturing parameters for this well:

[0114] (1) For the "matrix section", sort the "gas production contribution ratio" of each section in ascending order, such as Figure 5 As shown; sort the "SRV parameters" of each segment in ascending order, such as... Figure 6 As shown. Based on the "top 30%" principle, the overlapping sections of "segments with a large gas production contribution" and "segments with high SRV" were selected. Figure 5 and Figure 6 Darker colors are used to indicate this.

[0115] (2) For the "micro-fracture segment", the "gas production contribution ratio" of each segment is sorted in ascending order, such as... Figure 7As shown; sort the "SRV parameters" of each segment in ascending order, such as... Figure 8 As shown. Based on the "top 30%" principle, the overlapping sections of "segments with a large gas production contribution" and "segments with high SRV" were selected. Figure 7 and Figure 8 Darker colors indicate:

[0116] (3) For the "flexural segment", sort the "gas production contribution ratio" of each segment in ascending order, such as Figure 9 As shown; sort the "SRV parameters" of each segment in ascending order, such as... Figure 10 As shown. Based on the "top 30%" principle, the overlapping sections of "segments with a large gas production contribution" and "segments with high SRV" were selected. Figure 9 and Figure 10 Darker colors indicate:

[0117] (4) Extract the "fracture parameters" of the overlapping dark segments, a total of 3, namely "fracture parameter A", "fracture parameter B" and "fracture parameter C". The optimal values ​​of the parameters for each natural fracture type are summarized as follows:

[0118] Table 11 Optimal values ​​of fracturing parameters for the matrix section

[0119]

[0120] Optimal values ​​of fracturing parameters for 12 micro-fracture segments

[0121]

[0122] Table 13 Optimal values ​​of fracturing parameters for the matrix section

[0123]

[0124] Therefore, based on Tables 11-13, the optimal fracturing parameter range for the matrix section of this gas well can be determined as follows: fracturing operation flow rate between 19.5 and 20.0 cubic meters per minute; fracturing fluid strength between 43.5 and 44.0 cubic meters per meter; and fracturing sand strength between 4.30 and 4.35 tons per meter.

[0125] Furthermore, the optimal fracturing parameters for the micro-fractured section of the gas well can be determined as follows: fracturing flow rate between 18.0 and 19.0 cubic meters per minute; fracturing fluid strength between 43.5 and 45.0 cubic meters per meter; and fracturing proppant strength between 3.90 and 4.00 tons per meter.

[0126] Furthermore, the optimal fracturing parameters for the flexural section of the gas well can be determined as follows: fracturing flow rate between 17.5 and 18.5 cubic meters per minute; fracturing fluid strength between 35.5 and 40.0 cubic meters per meter; and fracturing proppant strength between 3.7 and 4.30 tons per meter.

[0127] The above are the embodiments listed in this example. However, this example is not limited to the optional embodiments described above. Those skilled in the art can arbitrarily combine the above methods to obtain other various embodiments. Anyone can derive other various forms of embodiments under the guidance of this example. The above specific embodiments should not be construed as limiting the scope of protection of this example. The scope of protection of this example should be defined in the claims.

Claims

1. A method for optimizing fracturing parameters in shale gas wells based on pump shutdown pressure drop, characterized in that, include: Obtain the fracturing operation parameters for each fracturing section of the target well during fracturing, and calibrate the fracturing operation flow rate, fracturing fluid strength, and fracturing proppant strength as fracturing parameter A, fracturing parameter B, and fracturing parameter C, respectively; Based on the pressure second-point data of each fracturing section of the target well during the pump shutdown stage, pressure double logarithmic and derivative curves were plotted and interpreted to obtain the interpretation parameters of the fracturing network. The fracture half-length, fracture height, and fracture width were respectively labeled as interpretation parameters A, B, and C. The SRV parameters were obtained based on the interpretation parameters of the fracturing network. Monitor the production logging of each fractured section of the target well and obtain production logging monitoring data; Based on the fracture type of each fracturing section in the target well, the fracturing sections are respectively labeled as matrix section, microfracture section and flexural section; Parameters were retrieved for each fracturing segment classified as matrix segment, microfracture segment, and flexure segment. Based on the production logging monitoring data and SRV parameter values ​​in the parameters, two fracturing segments were arranged. Several fracturing segments that were located in the specified sorting interval in both arrangements were selected, and their fracturing operation parameters were used as the preferred parameters for matrix segment, microfracture segment, or flexure segment, respectively.

2. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1, characterized in that: After obtaining the fracturing construction parameters, they are stored in the first storage unit; after obtaining the fracturing network interpretation parameters, they are stored in the second storage unit; and after obtaining the production logging monitoring data, they are stored in the third storage unit.

3. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1 or 2, characterized in that: The parameters of the fracturing segments classified as matrix segments are additionally stored in the fourth storage unit, the parameters of the fracturing segments classified as micro-fracture segments are additionally stored in the fifth storage unit, and the parameters of the fracturing segments classified as flexural segments are additionally stored in the sixth storage unit.

4. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1, characterized in that: The SRV parameter is defined as: Explanation parameter A × Explanation parameter B × Explanation parameter C × 0.

01.

5. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1, characterized in that: The production logging monitoring data includes the percentage of gas production contribution from a single fracturing stage.

6. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1 or 5, characterized in that: Production logging data is obtained through tracer monitoring or fiber optic monitoring.

7. The method for optimizing fracturing parameters of shale gas wells based on pump shutdown pressure drop according to claim 1, characterized in that: When screening fracturing segments in two arrangements, the values ​​of production logging monitoring data and SRV parameters are sorted from largest to smallest. The data volume in each arrangement is set to be the same, and the top 30% of the fracturing segments are selected. Fracturing segments that rank in the top 30% in both arrangements are retained as preferred segments.

8. A shale gas well fracturing parameter optimization system based on pump shutdown pressure drop, used to implement the optimization method according to any one of claims 1 to 7, characterized in that: It includes a data acquisition module and several storage modules, as well as a data processing module and a main control module. The data acquisition module and the storage module communicate with the data processing module, and the main control module communicates with the data acquisition module, the storage module and the data processing module.

9. The shale gas well fracturing parameter optimization system based on pump shutdown pressure drop according to claim 8, characterized in that: The storage module includes six independent storage units.

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