A method for optimizing channel fracturing parameters

Abstract

The present application belongs to the technical field of oil and gas field development, and particularly relates to a channel fracturing parameter optimization method, comprising the following steps: obtaining fracturing parameters through a channel fracturing design method, and taking the obtained fracturing parameters as current optimal fracturing parameters; calculating a ratio of proppant mass concentration and fiber mass concentration in the fracturing parameters, under the ratio, using a mass of proppant and fiber mixed into a mass block with different diameters and different quantities to carry out a conductivity experiment, and obtaining an ideal channel rate; under the condition of the current optimal fracturing parameters, taking the ideal channel rate as an experimental target, constantly changing the fiber mass concentration to carry out a proppant migration experiment, and obtaining a current optimal fiber mass concentration; and determining an optimal proppant mass concentration according to the ratio and the current optimal fiber mass concentration. Through the above steps, the present application solves the problems of imperfect channel fracturing construction parameter design method, low fracturing parameter precision, and single experimental evaluation parameter and evaluation mode.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field development technology, and specifically relates to a method for optimizing channel fracturing parameters. Background Technology

[0002] Currently, my country's conventional oil and gas production is declining rapidly, necessitating hydraulic fracturing technology for production enhancement. Unconventional oil and gas development also requires hydraulic fracturing technology for commercial success, making it an essential tool in the current oil and gas field development field. Hydraulic fracturing involves injecting fracturing fluid into the formation to open it up, and then filling the fractures with proppant to maintain their conductivity. Therefore, the proppant filling situation is a crucial factor determining the fracturing effect. Currently, conventional hydraulic fracturing technology uses continuous proppant placement in the fractures, resulting in low flow efficiency of the produced fluid within the proppant layer. To improve fracture conductivity and achieve non-uniform proppant placement, researchers use pulsed pumping of fiber-containing fracturing fluid and proppant-carrying fluid to form proppant-fiber mixed clumps in the formation. These clumps form highly conductive channels, a process known as channel fracturing. However, research on channel fracturing is limited, and the design of channel fracturing construction parameters largely references conventional fracturing methods, lacking optimized methods suitable for channel fracturing construction parameter design. Current research indicates that the migration pattern of channel fracturing proppant in fractures is significantly different from that of conventional fracturing proppant due to the addition of fibers to the fracturing fluid. Therefore, optimizing specific construction parameters for channel fracturing is crucial to improving the effectiveness of channel fracturing operations.

[0003] Currently, the optimization of fracturing parameters for proppant transport is mainly based on visual experiments of proppant migration. During proppant migration experiments, "channel ratio" is an important quantitative evaluation parameter; however, the optimal channel ratio varies under different reservoir conditions. Proppant migration experiments can only determine the numerical value of the channel ratio under different construction conditions, lacking an optimization target for the "optimal channel ratio." Typically, the optimal channel ratio is taken as 50% of the channel ratio obtained through conventional hydraulic fracturing techniques or experience. This results in parameters that deviate significantly from actual conditions, leading to insufficient precision in the overall fracturing parameter optimization during proppant migration experiments. Summary of the Invention

[0004] The purpose of this invention is to provide a method for optimizing channel fracturing parameters, in order to solve the problem of low accuracy in optimizing channel fracturing parameters when using channel ratios designed based on conventional hydraulic fracturing techniques or experience.

[0005] To solve the above-mentioned technical problems, the technical solution provided by this invention and the corresponding beneficial effects of the technical solution are as follows:

[0006] The present invention provides a method for optimizing channel fracturing parameters, comprising the following steps:

[0007] S1. Fracturing parameters are obtained through the channel fracturing design method, and the obtained fracturing parameters are used as the current optimal fracturing parameters; the fracturing parameters include proppant particle size, fracturing fluid viscosity, fracturing fluid flow rate, proppant mass concentration, and fiber mass concentration;

[0008] S2. Calculate the ratio of proppant mass concentration to fiber mass concentration obtained in step S1. Under this ratio, conduct a flowability experiment using clumps of proppant and fiber with different diameters and quantities to test the flowability under different first channel ratios. The first channel ratio is the ratio of the cross-sectional area of ​​the flow chamber not occupied by the clumps to the area of ​​the flow chamber in the flowability experiment. The first channel ratio value used in the experiment when the flowability is highest is the ideal channel ratio.

[0009] S3. Under the condition that all fracturing parameters except fiber mass concentration and proppant mass concentration are the current optimal fracturing parameters, with the ideal channel rate as the experimental target, and ensuring that the ratio remains unchanged, proppant transport experiments are conducted by continuously changing the fiber mass concentration and proppant mass concentration to obtain the second channel rate in the experiment. The second channel rate is the ratio of the area not occupied by proppant to the total fracture area. When the second channel rate in the experiment is closest to the ideal channel rate, the corresponding fiber mass concentration is the current optimal fiber mass concentration, and the corresponding proppant mass concentration is the current optimal proppant mass concentration; thus, the optimization of fiber mass concentration and proppant mass concentration is achieved.

[0010] The beneficial effects of the above technical solution are as follows:

[0011] This invention provides a method for optimizing channel fracturing parameters, which optimizes fiber and proppant mass concentrations. More importantly, this invention applies the ideal channel ratio obtained from fracturing conductivity experiments to proppant migration experiments. Specifically, it uses the ideal channel ratio optimized from conductivity experiments as the experimental target for proppant migration experiments, thereby optimizing fiber and proppant mass concentrations. The effective combination of channel fracturing conductivity experiments and proppant migration experiments for fracturing parameter optimization, taking conductivity factors into account, increases experimental reference data and yields more accurate fracturing parameters. Therefore, this invention provides a channel fracturing parameter optimization method capable of accurately optimizing fracturing parameters.

[0012] Furthermore, after step S3 or after step S2 and before step S3, a step of optimizing the fracturing fluid discharge rate is also included:

[0013] Under the condition that all fracturing parameters except for the fracturing fluid discharge rate are the current optimal fracturing parameters, proppant migration experiments are conducted by continuously changing the fracturing fluid discharge rate to obtain the channel connectivity in the experiment. The channel connectivity is the product of the number of clumps in the fracture range and the second channel rate in the fracture range. The fracturing fluid discharge rate corresponding to the optimal channel connectivity is selected as the current optimal fracturing fluid discharge rate to achieve optimization of the fracturing fluid discharge rate.

[0014] The beneficial effects of the above technical solution are as follows:

[0015] This invention provides a method for optimizing channel fracturing parameters. In the experiment, the optimal fracturing parameters are continuously adjusted according to the corresponding optimization parameter sequence. Under the condition that the remaining fracturing parameters are all the current optimal fracturing parameters, the fracturing fluid discharge is optimized. The experiment has more optimized parameters and more accurate data, thereby further improving the design method of channel fracturing construction parameters and further enriching the relevant experimental evaluation parameters.

[0016] Furthermore, after optimizing the fracturing fluid displacement, the process also includes optimizing the fracturing fluid viscosity.

[0017] Under the condition that all fracturing parameters except for fracturing fluid viscosity are the current optimal fracturing parameters, proppant transport experiments are carried out by continuously changing the fracturing fluid viscosity to obtain the channel connectivity in the experiment. The fracturing fluid viscosity corresponding to the optimal channel connectivity is selected as the current optimal fracturing fluid viscosity to achieve the optimization of fracturing fluid viscosity.

[0018] The beneficial effects of the above technical solution are as follows:

[0019] This invention provides a method for optimizing channel fracturing parameters. After optimizing the fracturing fluid displacement, if the channel connectivity is still insufficient, the fracturing fluid viscosity is further optimized to improve channel connectivity. This method considers multiple factors such as fracturing fluid displacement and viscosity, and improves channel connectivity through different methods, thereby making the optimized channel connectivity more accurate. This, in turn, ensures that other optimized fracturing parameters are more precise, further improving the design method for channel fracturing construction parameters and enriching the relevant experimental evaluation parameters.

[0020] Furthermore, after step S3, or after step S2 and before step S3, a step of optimizing the proppant particle size is also included:

[0021] Under the condition that all fracturing parameters except for the proppant particle size are the current optimal fracturing parameters, proppant migration experiments are conducted by continuously changing the proppant particle size. The volume of the sand embankment formed by the settlement of the lower part of the fracture is obtained in the experiment. The proppant particle size corresponding to the smallest sand embankment volume is selected as the current optimal proppant particle size to achieve the optimization of proppant particle size.

[0022] The beneficial effects of the above technical solution are as follows:

[0023] This invention provides a method for optimizing channel fracturing parameters. In experiments, the optimal fracturing parameters are continuously adjusted according to the corresponding optimization parameter sequence. The optimized parameters are comprehensive, the data is more accurate, the design method for channel fracturing construction parameters is improved, and the relevant experimental evaluation parameters and evaluation methods are richer. Moreover, when optimizing the proppant particle size after step S2 and before step S3, it is not necessary to repeatedly optimize the fiber mass concentration and proppant mass concentration in step S3, which simplifies the optimization procedure and improves the optimization efficiency.

[0024] Furthermore, if the minimum sandbank volume is greater than a set volume threshold, the fiber length is increased;

[0025] If the step of optimizing the proppant particle size is after step S3, then after increasing the fiber length, step S3 needs to be repeated using the increased fiber length to optimize the fiber mass concentration and proppant mass concentration, and the proppant particle size needs to be optimized again.

[0026] If the step of optimizing the proppant particle size occurs before step S3, then after increasing the fiber length, the proppant particle size is re-optimized, and step S3 is directly executed using the fiber with increased length to achieve optimization of fiber mass concentration and proppant mass concentration.

[0027] The beneficial effects of the above technical solution are as follows:

[0028] This invention provides a method for optimizing channel fracturing parameters. In experiments, the optimal fracturing parameters are continuously adjusted according to the corresponding optimization parameter sequence. Furthermore, iterative optimization is performed by considering the correlation between the mutual influences of the fracturing parameters, ensuring more accurate fracturing parameter data in the experiments. Therefore, this invention provides a channel fracturing parameter optimization method with a complete design method for channel fracturing construction parameters, accurate fracturing parameter data, and richer related experimental evaluation parameters and methods.

[0029] Furthermore, in order to obtain the second channel rate more accurately, a light source was set on one side of the crack during the proppant transport experiment.

[0030] Furthermore, the fracturing parameters obtained in step S1 also include the fracture width, the formation filtration coefficient, the rock fracture surface morphology, and the rock fracture surface roughness parameters. The proppant migration experimental device used in the proppant migration experiment includes two parallel plates, and a transparent resin fracture surface is provided on one side of each of the two parallel plates. The transparent resin fracture surface is made according to the rock fracture surface morphology and rock fracture surface roughness parameters. The proppant migration experimental device also includes a sealing strip disposed between the transparent resin fracture surfaces. The width of the sealing strip is the fracture width, and the filtration coefficient simulated by the proppant migration experimental device is the filtration coefficient of the formation.

[0031] Furthermore, in step S2, when conducting the flowability experiment using clumps made of different diameters and different amounts of proppant mixed with fibers, different clump spacings were also set.

[0032] Furthermore, the fracturing parameters obtained in step S1 also include the closure pressure of the fracture; in step S2, the closure pressure of the fracture is applied to the flow chamber during the flow capacity experiment. Attached Figure Description

[0033] Figure 1-1 This is a schematic diagram of the distribution of a proppant and fiber clumps within the channel connectivity sampling area in an embodiment of the present invention;

[0034] Figure 1-2 This is a schematic diagram of the distribution of another type of proppant and fiber clumps within the channel connectivity sampling area in an embodiment of the present invention;

[0035] Figure 1-3 This is a schematic diagram of the distribution of another type of proppant and fiber clumps within the channel connectivity sampling area in an embodiment of the present invention;

[0036] Figure 1-4 This is a schematic diagram of the distribution of another type of proppant and fiber clumps within the channel connectivity sampling area in an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of the sand embankment formed at the bottom of the crack due to excessively large proppant particle size in the present invention;

[0038] Figure 3 This is a flowchart of a channel fracturing parameter optimization method according to the present invention;

[0039] Figure 4 This is a schematic diagram of experimental crack assembly in an embodiment of the present invention.

[0040] In the figure: 1. Channel connectivity sampling area; 2. Clump; 3. Sand embankment; 4. Sealing strip; 5. Transparent parallel plate; 6. Transparent resin crack surface; 7. Imaging device; 8. Light source. Detailed Implementation

[0041] Method Implementation Examples:

[0042] This invention provides a method for optimizing channel fracturing parameters. Based on a large-scale visualized proppant migration simulation device that considers the rough fracture wall and filtration loss, the method conducts comparative experiments on different fracturing parameters (construction parameters) by carrying out proppant migration experiments and flow conductivity experiments in channel fracturing. The experimental results are then analyzed and evaluated to optimize the fracturing parameters and provide a reference for channel fracturing construction design.

[0043] The following is combined with Figure 3 The detailed steps of the method of the present invention are as follows:

[0044] Step 1: Design fracturing parameters based on current channel fracturing design methods, obtaining parameters such as design fracture length, fracture width w, fracture closure pressure, and formation filtration coefficient. Select proppant particle size, fracturing fluid viscosity, fracturing fluid flow rate, proppant mass concentration P, and fiber mass concentration F as the objects of fracturing parameter optimization, and take the selected fracturing parameters as the current optimal fracturing parameters. Perform three-dimensional scanning on the fracture surface of reservoir cores or outcrops of the same stratum to obtain the rock fracture surface morphology and roughness parameters.

[0045] Step 2: Flow-carrying capacity test; based on the proppant mass concentration P = 15% (unit: kg / m³) in the construction design. 3 ) and fiber mass concentration F = 5% (unit: kg / m 3 The proppant particle size was 20 / 40 mesh. The proppant and fiber were mixed into clumps with diameters of 3 cm, 3.2 cm and 3.5 cm and a height equal to the designed crack width w, according to the proppant to fiber mass ratio of 3. The guar gum liquid was used as the adhesive. The clumps were used for the flow conductivity experiment.

[0046] Place the agglomerate into the flow chamber, and use agglomerates of different diameters and different intervals to simulate different flow rates. The flow rate is the ratio of the cross-sectional area of ​​the flow chamber not occupied by the agglomerate to the area of ​​the flow chamber, and this flow rate is recorded as the first flow rate.

[0047] The area of ​​the diversion chamber is 64.52 cm². 2 The cross-sectional areas of the three different diameter clumps were 7.07 cm³. 2 8.04cm 2 and 9.62cm 2 The experiment can be conducted by adjusting the diameter and number of clumps placed in the flow guide chamber, as shown in Table 1:

[0048] Table 1. Number of clusters of different diameters and channel efficiency

[0049] Number of clumps of different diameters Channel ratio / % 3.5cm x 5 25.45 3.2cm x 5 37.70 3.0cm×5 45.22 3.5cm x 4 40.36 3.2cm×4 37.70 3.0cm×4 56.19 3.5cm×3 + 3.0cm×2 57.00 3.5cm×2 + 3.0cm×3 59.00 3.2cm×3 + 3.0cm×2 61.74 3.5cm x 3 71.14

[0050] Following the above scheme, fracturing conductivity experiments were conducted on the channel. Formation closure pressure was applied to the flow chamber, and the conductivity of the fracture was measured. By changing the diameter and spacing of the aggregates, the conductivity under different first channel ratios was obtained. The first channel ratio value used in the experiment with the highest conductivity was taken as the ideal channel ratio T.

[0051] Step 3: Preparation for proppant transport experiments; such as Figure 4 As shown, based on the three-dimensional scanning results of reservoir cores or outcrops, transparent resin fracture surfaces 6 with the same roughness are printed using 3D printing technology. The rough surface of the printed transparent resin fracture surface 6 is then pasted onto the transparent parallel plates 5 on both sides of the fracture of the device, with the rough surface facing inward. The transparent parallel plates 5 are made of plexiglass. The width of the sealing strip 4 between the two transparent parallel plates is adjusted to reach the designed fracture width. The filter pore switch of the device is adjusted so that the filter loss coefficient of the experimental device is the same as the filter loss coefficient of the actual formation.

[0052] Step 4: Optimization of fiber and proppant mass concentrations; Since the channel ratio of channel fracturing is mainly affected by the fiber mass concentration, experiments were conducted first under the conditions of optimal proppant particle size, optimal fracturing fluid viscosity, and optimal fracturing fluid flow rate, with the ideal channel ratio T optimized by the conductivity experiment as the experimental target. The fiber and proppant mass concentrations were varied. During the experiment, the placement of clumps in the fracture was photographed using imaging device 7. Because a rough, transparent resin fracture surface was adhered inside the fracture, a strong light source 8 was placed on the other side of the fracture to increase the clarity of the photographic acquisition by utilizing the light-blocking properties of the proppant. The second channel ratio is the ratio of the area not occupied by clumps in the acquired photographs to the entire fracture area. Experiments were conducted by varying the fiber mass concentration to obtain the fiber mass concentration corresponding to the second channel ratio closest to the ideal channel ratio T, and this fiber mass concentration was taken as the current optimal fiber mass concentration. To ensure that the proppant-to-fiber ratio in the aggregates formed during the proppant transport experiment is consistent with that used in the proppant-fiber column in the flow conductivity experiment, the sand ratio P (proppant mass concentration) needs to be adjusted accordingly while changing the fiber mass concentration F, so that the proppant-to-fiber mass ratio P / F remains consistent. Based on this ratio and the current optimal fiber mass concentration, the current optimal proppant mass concentration is determined; thus, the optimization of both fiber and proppant mass concentrations is achieved.

[0053] Step 5: Optimize channel connectivity; the main factor affecting channel connectivity is the fracturing fluid discharge rate. To achieve optimal channel connectivity, the fracturing fluid discharge rate parameters for channel fracturing are optimized. Channels are actually formed by discontinuous proppant placement, so the number and connectivity of channels are related to the number, distribution, and connectivity of clumps. To evaluate the connectivity of clumps in the fracture, it is proposed to use the product of the number of independent clumps X within a specified fracture range and the second channel rate R within that range as the evaluation index for channel connectivity. The sampling fracture range is selected based on the height of the parallel plate used in the experiment. If the height of the experimental setup is 0.6m, a fracture range of 0.6m × 0.6m is selected for clump connectivity evaluation. Figure 1-1 As shown, the number of clumps 2 (X) and the second channel rate (R) within the sampling area 1 of the channel connectivity are represented, where channel connectivity = X * R. Under the condition that all fracturing parameters except for the fracturing fluid displacement are the current optimal fracturing parameters, experiments were conducted with different fracturing fluid displacements. The optimal fracturing fluid displacement was selected based on the fracturing fluid displacement corresponding to the maximum channel connectivity. Different fracturing fluid displacements yielded different results. The following section compares and illustrates the results using four different experimental result graphs, such as... Figure 1-1 , Figure 1-2 , Figure 1-3 and Figure 1-4 As shown, when there are many clusters 2 and the area of ​​a single cluster 2 is relatively large, the number of clusters 2 X is larger, the second channel rate R is larger, the channel connectivity value is larger, and a wide channel will not appear in the crack. Moreover, when the number of clusters 2 is larger, the connectivity between channels is guaranteed.

[0054] Step 6: Optimize fracturing fluid viscosity; fracturing fluid viscosity mainly affects the size of the fracturing fluid. If adjusting the flow rate cannot achieve good channel connectivity and the area of ​​a single fracturing fluid in the fracture is still large, then under the condition that all fracturing parameters except for the fracturing fluid viscosity are the current optimal fracturing parameters, the channel connectivity can be improved by increasing the fracturing fluid viscosity. The fracturing fluid viscosity corresponding to the optimal channel connectivity is selected as the current optimal fracturing fluid viscosity.

[0055] Step 7: Optimize the proppant particle size; the proppant particle size affects the ability of the proppant to bind with the fiber, and determines the proppant content in the aggregate 2 formed by the proppant and fiber mixture, such as... Figure 2 As shown, if the proppant cannot bond uniformly with the fibers, it will settle at the bottom of the fracture to form a continuously laid sand embankment 3. Under the condition that all fracturing parameters except for the proppant particle size are the current optimal fracturing parameters, with the optimization objective of minimizing the volume of the sand embankment 2 at the bottom of the fracture, proppant migration experiments were conducted by changing the proppant particle size to select the proppant particle size corresponding to the smallest sand embankment volume as the current optimal proppant particle size.

[0056] Reducing the particle size of proppant can decrease proppant settling at the fracture bottom, but smaller particle size proppant will weaken the supporting effect on the fracture, significantly reducing the fracturing effect. Therefore, it is necessary to test the commonly used proppant particle size. The largest particle size proppant commonly used in oilfields, 20 / 40 mesh proppant, was selected for the experiment. If a sand dam with a height greater than 3 cm appeared at the fracture bottom during proppant migration experiments, a smaller particle size proppant, 30 / 50 mesh proppant, was selected for the experiment.

[0057] If a large amount of proppant still settles after reducing the proppant particle size to the smallest particle size for fracturing, 70 / 140 mesh, then the fiber length should be increased. After repeating step 4 to optimize the fiber mass concentration, the proppant particle size should be optimized again starting from 20 / 40 mesh proppant.

[0058] If the proppant particle size and fiber length change, the fiber and proppant agglomerates need to be remade, and the conductivity test should be repeated according to the optimal channel ratio. If the conductivity value differs from the previously optimized optimal channel ratio by less than 5%, re-optimization is not necessary. If the difference is greater than 5%, steps 2-7 should be repeated.

[0059] In this embodiment, the optimization order of the five fracturing parameters is "fiber mass concentration → proppant mass concentration → fracturing fluid flow rate → fracturing fluid viscosity → proppant particle size". However, this optimization order can be adjusted. "Fracturing fluid flow rate" must precede "fracturing fluid viscosity", while the optimization order of the other parameters is flexible. For example, optimization can be performed in the order of "fracturing fluid flow rate → fracturing fluid viscosity → fiber mass concentration → proppant mass concentration → proppant particle size". Details are as follows:

[0060] After preparing for the proppant migration experiment, the connectivity of the channels was first optimized to optimize the fracturing fluid discharge rate, obtaining the optimal fracturing fluid discharge rate, which was then used as the current optimal fracturing fluid discharge rate. Next, assuming all fracturing parameters except for the fracturing fluid viscosity were at their current optimal levels, the fracturing fluid viscosity was optimized to obtain the optimal fracturing fluid viscosity, which was then used as the current optimal fracturing fluid viscosity. Finally, assuming all fracturing parameters except for the fiber mass concentration were at their current optimal levels, the fiber mass concentration was further optimized to obtain the optimal fiber mass concentration and the optimal proppant mass concentration, which were then used as the current optimal fiber mass concentration and the optimal proppant mass concentration.

[0061] For example, optimization can be performed in the following order: "proppant particle size → fiber mass concentration → proppant mass concentration → fracturing fluid flow rate → fracturing fluid viscosity". The details are as follows:

[0062] After preparing for the proppant migration experiment, the proppant particle size was first optimized to obtain the optimal particle size, which was then used as the current optimal proppant particle size. Next, under the condition that all fracturing parameters except for fiber mass concentration were at their current optimal levels, the fiber mass concentration was optimized to obtain the optimal fiber mass concentration and the optimal proppant mass concentration, which were then used as the current optimal fiber mass concentration and the current optimal proppant mass concentration. Finally, under the current optimal fracturing parameters, the connectivity of the channels was optimized to optimize the fracturing fluid discharge and the fracturing fluid viscosity.

[0063] Of course, these changes in the optimization order will lead to different final optimized parameter values. Several schemes can achieve the optimization goal and the optimal channel ratio. The choice should be made based on the actual equipment conditions and construction capabilities during on-site construction.

[0064] Through the above steps, it can be seen that this invention combines flow capacity experiments with proppant migration visualization experiments. In the experiments, the optimal fracturing parameters are continuously adjusted according to the corresponding optimized parameter sequence. Furthermore, by iteratively optimizing the interrelationships between fracturing parameters, the accuracy of the optimized fracturing parameter data is ensured. The experiments optimize different construction parameters such as fiber mass concentration, proppant mass concentration, fracturing fluid flow rate, fracturing fluid viscosity, and proppant particle size. This provides diverse evaluation parameters and richer evaluation methods, forming a complete and highly accurate method for designing fracturing construction parameters that guide the process.

Claims

1. A method for optimizing channel fracturing parameters, characterized in that, include: S1. Fracturing parameters are obtained through the channel fracturing design method, and the obtained fracturing parameters are used as the current optimal fracturing parameters; the fracturing parameters include proppant particle size, fracturing fluid viscosity, fracturing fluid flow rate, proppant mass concentration P, and fiber mass concentration F; S2. Using the ratio of P to F obtained in S1, conduct flowability experiments with clumps of different diameters and quantities of proppant mixed with fibers to test the flowability under different first channel ratios. The first channel ratio is the ratio of the cross-sectional area of ​​the flow chamber not occupied by the clumps to the area of ​​the flow chamber in the flowability experiment. The first channel rate value used in the experiment to obtain the highest flow rate was the ideal channel rate T. S3. Under the condition that all fracturing parameters except F and P are currently optimal, with T as the experimental target and the ratio kept constant, F and P are continuously changed to carry out proppant migration experiments to obtain the second channel ratio R in the experiment. R is the ratio of the area not occupied by proppant to the total fracture area. When R is closest to T in the experiment, the corresponding F and P are the current optimal; thus, the optimization of F and P is achieved. After S3, or after S2 and before S3, optimize the fracturing fluid flow rate and then optimize the fracturing fluid viscosity, and optimize the proppant particle size. If a large amount of proppant still settles after the proppant particle size is reduced to the minimum particle size, increase the fiber length. When the proppant particle size and fiber length change, re-make the agglomerate composed of proppant and fiber, and conduct a conductivity test. If the difference between the re-measured conductivity value and the conductivity value corresponding to T is greater than the threshold, then repeat S2 to determine a new T.

2. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, Steps to optimize fracturing fluid displacement: Under the condition that all fracturing parameters except for the fracturing fluid discharge rate are the current optimal fracturing parameters, proppant migration experiments are conducted by continuously changing the fracturing fluid discharge rate to obtain the channel connectivity in the experiment. The channel connectivity is the product of the number of clumps in the fracture range and the second channel rate in the fracture range. The fracturing fluid discharge rate corresponding to the optimal channel connectivity is selected as the current optimal fracturing fluid discharge rate to achieve optimization of the fracturing fluid discharge rate.

3. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, Steps for optimizing fracturing fluid viscosity: Under the condition that all fracturing parameters except for fracturing fluid viscosity are the current optimal fracturing parameters, proppant transport experiments are carried out by continuously changing the fracturing fluid viscosity to obtain the channel connectivity in the experiment. The fracturing fluid viscosity corresponding to the optimal channel connectivity is selected as the current optimal fracturing fluid viscosity to achieve the optimization of fracturing fluid viscosity.

4. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, Steps for optimizing proppant particle size: Under the condition that all fracturing parameters except for the proppant particle size are the current optimal fracturing parameters, proppant migration experiments are conducted by continuously changing the proppant particle size. The volume of the sand embankment formed by the settlement of the lower part of the fracture is obtained in the experiment. The proppant particle size corresponding to the smallest sand embankment volume is selected as the current optimal proppant particle size to achieve the optimization of proppant particle size.

5. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, If the step of optimizing the proppant particle size is after S3, then after increasing the fiber length, it is necessary to re-execute S3 using the increased fiber length to optimize F and P, and then re-optimize the proppant particle size. If the step of optimizing the proppant particle size is performed before S3, then after increasing the fiber length, the proppant particle size is re-optimized, and S3 is directly performed using the fiber with increased length to achieve optimization of F and P.

6. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, In the proppant transport experiment, a light source was placed on one side of the crack.

7. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, The fracturing parameters obtained in S1 also include fracture width, formation filtration coefficient, rock fracture surface morphology, and rock fracture surface roughness parameters. The proppant migration experimental device used in the proppant migration experiment includes two parallel plates, and transparent resin fracture surfaces are provided on opposite sides of the two parallel plates. The transparent resin fracture surfaces are made according to the rock fracture surface morphology and rock fracture surface roughness parameters. The proppant migration experimental device also includes a sealing strip set between the transparent resin fracture surfaces. The width of the sealing strip is the fracture width. The filtration coefficient simulated by the proppant migration experimental device is the filtration coefficient of the formation.

8. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, In S2, when conducting flowability experiments using clumps of proppant with different diameters and quantities mixed with fibers, different clump spacings were also set.

9. The method for optimizing channel fracturing parameters according to claim 1, characterized in that, The fracturing parameters obtained in S1 also include the closure pressure of the fracture; in S2, the closure pressure of the fracture is applied to the flow chamber during the flow capacity experiment.

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