A method and system for optimizing design of compact gas fiber sand fracturing

Abstract

The application discloses a compact gas fiber sand fracturing optimization design method and system, and utilizes a numerical simulation technology to take a reservoir reconstruction volume and a fracture complexity degree as optimization targets, and optimizes to obtain fracturing construction parameters; and under the optimized fracturing construction parameters, indoor experiments are carried out to determine a fiber type, a dosage and a pumping mode and the like which have the minimum influence on a reverse flow capacity of a proppant filling layer and the optimal sand prevention effect, so that the optimization of the whole process of the compact gas fiber sand fracturing is realized, the sand production rate is effectively reduced, the fracture reverse flow capacity is ensured, the reservoir reconstruction effect is maximally improved, the yield is improved, and the cost is reduced.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas development technology, specifically relating to an optimized design method and system for tight gas fiber-assisted sand fracturing. Background Technology

[0002] Fracturing proppant consists of spherical particles used to support artificial fractures, thereby improving the permeability of oil and gas in the formation. It is one of the key materials in volumetric fracturing operations in tight sandstone. Proppant types can be classified according to the material, including quartz sand (mineral sand and natural river sand), ceramsite, and resin-coated proppant. Currently, the main proppants used in tight sandstone fracturing are 70 / 140 mesh quartz sand, 40 / 70 mesh quartz sand, 40 / 70 mesh coated quartz sand, and 30 / 50 mesh ceramsite. In a certain basin, as of July 2021, 27 horizontal wells in tight sandstone had been fracturing. During the drainage period, many wells experienced varying degrees of sand production, with the most severe sand production occurring in the horizontal wells of block XX-XX, reaching a maximum of 170 tons and a sand production rate of 6.93%. After applying coated quartz sand, the sand production improved somewhat, but the effect varied, and the sand production volume and rate remained high in some wells.

[0003] It can be seen that the existing sand fracturing technology has a high sand return rate after fracturing, which makes it impossible to stably control the backflow capacity of the fracture, thereby affecting the output and even damaging the ground pipelines, increasing the ground maintenance cost. Summary of the Invention

[0004] To address the problems of high sand return rates in existing proppant fracturing technologies, which affect fracture backflow capacity, resulting in poor production and even damage to surface pipelines, increasing surface maintenance costs, this invention provides an optimized design method and system for tight gas fiber proppant fracturing. This invention utilizes numerical simulation technology, using reservoir stimulation volume and fracture complexity as optimization targets to obtain optimized fracturing operation parameters. Under these optimized parameters, laboratory experiments are conducted to determine the fiber type, dosage, and pumping method that minimize the impact on the backflow capacity of the proppant-filled layer while achieving the best sand control effect. This optimizes the entire tight gas fiber proppant fracturing process, effectively reducing sand return rates, ensuring fracture backflow capacity, maximizing reservoir stimulation effect, increasing production, and reducing costs.

[0005] This invention is achieved through the following technical solution:

[0006] A method for optimizing the design of tight gas fiber reinforced sand fracturing, the method comprising:

[0007] Based on the logging curves, determine the reservoir section, identify the reservoir thickness, and divide the oil testing section;

[0008] Combined with the rock mechanics parameter curves of the reservoir section in the logging curve, stress and fracture pressure profiles are calculated, and the cluster perforation position is optimized according to the reservoir section physical property and the fracture pressure profile;

[0009] According to the geological basic parameters, the proppant type is selected, and the reservoir reconstruction volume and the fracture complexity are obtained by using the numerical simulation technology, so that the fracturing construction parameters are optimized.

[0010] Under the optimized fracturing construction parameters, indoor experiments are carried out, and the fiber type and the fiber amount are optimized to minimize the influence of the proppant packing layer on the flow conductivity and to optimize the sand prevention effect.

[0011] Under the optimized fiber type and fiber amount, the fiber pumping mode is optimized to maximize the gas production rate under the conditions of ensuring the minimum permeability sacrifice, the minimum fracture sand production and the optimal full fracture flow conductivity.

[0012] The existing sand fracturing technology has high sand flowback rate after fracturing, and the fracture flowback capacity cannot be stably controlled, which finally leads to poor tight gas production, even damages the ground pipeline, increases the ground maintenance cost and other problems. The optimization design method provided by the present application optimizes the tight gas fiber sand fracturing construction parameters by using the numerical simulation technology, and carries out indoor experiments under the optimized fracturing construction parameters, optimizes the fiber type, fiber amount and fiber pumping process, realizes the whole process optimization of unconventional oil and gas sand control and sand prevention fracturing, effectively reduces the sand flowback rate, guarantees the fracture flowback capacity, improves the reservoir reconstruction effect, improves the oil and gas production, and reduces the cost.

[0013] As a preferred embodiment, the method of the present application selects a well section with a shale content of less than 20% and a porosity of more than 7% as the oil testing section.

[0014] As a preferred embodiment, the fracture pressure profile calculation method of the present application is specifically:

[0015] The rock mechanics parameters are calibrated by the data of the rock mechanics indoor experiment;

[0016] The fracture pressure curve of the reservoir section is calculated by the calibrated rock mechanics parameters.

[0017] As a preferred embodiment, the present application optimizes the perforation position based on the fracture pressure value of not more than 5MPa.

[0018] As a preferred embodiment, the fracturing construction parameter optimization process of the present application specifically includes:

[0019] The support agent type is selected according to the effective closure stress of logging, wherein the support agent type selection criteria are as follows: the effective closure stress below 42 MPa belongs to the quartz sand support range, the effective closure stress below 48 MPa belongs to the coated quartz sand support range, and the effective closure stress below 70 MPa belongs to the ceramic support range; if at least two support agent combinations are selected, the proportion is determined according to the reservoir geological characteristics and the Young's modulus size;

[0020] The reservoir reconstruction volume and the fracture complexity index under different fracturing construction parameters are calculated by using the numerical simulation technology;

[0021] The optimal fracturing construction parameter is determined according to the maximum weighted value of the reservoir reconstruction volume and the fracture complexity index.

[0022] As a preferred embodiment, the calculation method of the reservoir reconstruction volume of the present application is as follows:

[0023] V=L*H*W, wherein V represents the reservoir reconstruction volume, m 3 L represents the length of the fracture, m, H represents the height of the fracture, m, and W represents the width of the fracture, m;

[0024] The calculation method of the fracture complexity index is as follows:

[0025] As a preferred embodiment, the fiber type and fiber dosage optimization process of the present application specifically includes the following steps:

[0026] Under the optimized fracturing construction parameter, the indoor experiment of the flow conductivity is carried out, and the fiber type is optimized.

[0027] Under the optimized fracturing construction parameter, the indoor experiment of sand prevention and sand control is carried out, and the fiber dosage is optimized.

[0028] As a preferred embodiment, the fiber pumping mode optimization process of the present application specifically includes the following steps:

[0029] The fiber is injected in the form of trailing injection before and after the temporary plugging material is put, and the fiber type and fiber dosage are optimized.

[0030] On the other hand, the present application also provides a tight gas fiber sand fracturing optimization design system, which comprises:

[0031] A reservoir analysis unit, which determines the reservoir section according to the logging curve, identifies the reservoir thickness, and divides the oil test section;

[0032] A perforation position optimization unit, which combines the rock mechanics parameter curve of the reservoir section in the logging curve, calculates the stress and fracture pressure profile, and optimizes the cluster perforation position according to the reservoir section physical property and the fracture pressure profile.

[0033] a construction parameter optimization unit, which selects a proppant type according to geological base parameters, and obtains a reservoir reconstruction volume and a fracture complexity degree by using a numerical simulation technique, and optimizes fracturing construction parameters;

[0034] and a fiber process parameter optimization unit, which, under the optimized fracturing construction parameters, performs indoor experiments to optimize a fiber type and a fiber amount with the minimum influence on the flow conductivity of the proppant pack layer and the optimal sand prevention effect, and under the optimized fiber type and fiber amount, optimizes a fiber pumping mode with the maximum gas production rate under the conditions of the minimum sacrifice of permeability, the minimum sand production of the fracture and the optimal flow conductivity of the whole fracture.

[0035] As a preferred embodiment, the system of the present application further comprises:

[0036] an output unit for outputting the optimal scheme.

[0037] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0038] The present application optimizes the fiber sand fracturing construction parameters of the tight gas by using the numerical simulation technique, and performs indoor experiments under the optimized fracturing construction parameters to optimize the fiber type, the fiber amount and the fiber pumping process, realizes the optimization of the whole process of the unconventional oil and gas sand control and sand prevention fracturing, and overcomes the problems of the existing conventional sand fracturing technology, such as the high sand production rate after fracturing, the unstable control of the fracture flowback capacity, the poor production, the damage to the ground pipeline, the increase of the ground maintenance cost and the like.

[0039] The present application optimizes the sand prevention and sand control after fracturing of the tight sandstone reservoir, effectively reduces the sand production rate, guarantees the fracture flow conductivity, maximally improves the reconstruction effect of the reservoir, and reduces the maintenance cost, thereby providing technical support for the fiber sand optimization scheme of the tight gas horizontal well. DETAILED DESCRIPTION

[0040] The accompanying drawings, which are included to provide a further understanding of the embodiments of the present application and constitute a part of the application, illustrate embodiments of the present application and do not limit the present application. In the drawings:

[0041] Figure 1 is a method flowchart of the embodiments of the present application.

[0042] Figure 2 is a reservoir segmentation and clustering optimization design diagram of ZQ206-6-H2 well.

[0043] Figure 3 is a reservoir reconstruction volume under different cluster spacings.

[0044] Figure 4 Fracture complexity index for different cluster spacing.

[0045] Figure 5 Figure 6 is a graph showing the relationship between the amount of sand and the flow rate for different concentrations of 3mm fibers (30MPa closure pressure).

[0046] Figure 6 Figure 7 is a graph showing the relationship between the amount of sand and the flow rate for different concentrations of 9mm fibers (30MPa closure pressure).

[0047] Figure 7 Figure 8 is a graph showing the cumulative gas production for 5 years for three injection modes.

[0048] Figure 8 Figure 9 is a schematic block diagram of the system according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the objectives, technical solutions and advantages of the present application clearer and more comprehensible, the present application will be further described in detail below with reference to the embodiments and the accompanying drawings, the schematic embodiments of the present application and the description thereof are only used to explain the present application, and do not limit the present application.

[0050] Embodiment 1

[0051] The existing sand fracturing technology has a high sand flowback rate after fracturing, the fracture conductivity cannot be stably controlled, and finally leads to poor tight gas production, even damages the surface pipeline, increases the surface maintenance cost and a series of problems. Based on this, the present embodiment proposes a tight gas fiber sand fracturing optimization design method. The optimization design method proposed in the present embodiment uses the numerical simulation technology to take the reservoir reconstruction volume and the fracture complexity as the optimization target, and obtains the optimal fracturing construction parameter. Under the optimal fracturing construction parameter, the indoor experiment is carried out to study the influence of different fiber types, different concentrations of fibers and the fiber dosage on the conductivity of the proppant packing layer and the sand flow rate, so as to obtain the fiber sand fracturing parameter with the minimum influence on the conductivity of the proppant packing layer and the optimal sand prevention effect, realize the whole process optimization design of the fiber sand fracturing, effectively reduce the sand flowback rate, guarantee the fracture conductivity, maximize the reservoir reconstruction effect, improve the tight gas production and reduce the maintenance cost.

[0052] Specifically, as shown in the figure, the optimization design method proposed in the present embodiment includes the following steps: Figure 1

[0053] Step 1: Determine the reservoir section according to the logging curve, identify the reservoir thickness, and divide the oil test section.

[0054] ​Step 2: Combine the rock mechanics parameter curves of the reservoir section in the well logging curves to calculate the stress and fracture pressure profiles. Based on the reservoir section properties and fracture pressure profiles, select the optimal location for cluster perforations.

[0055] Step 3: Based on the basic geological parameters, select the proppant type and use numerical simulation technology to obtain the reservoir stimulation volume and fracture complexity, and optimize the fracturing construction parameters.

[0056] Step 4: Under optimized fracturing construction parameters, conduct indoor experiments to optimize fiber type and fiber dosage with the goal of minimizing the impact on the conductivity of the proppant filling layer and achieving the best sand control effect.

[0057] Step 5: With optimized fiber type and fiber dosage, and while ensuring minimal permeability sacrifice, minimal sand production from fractures, and optimal flow conductivity across all fractures, optimize the fiber pumping method with the goal of maximizing gas production.

[0058] In one optional implementation, this embodiment selects a tight sandstone reservoir in a specific block for exemplary analysis. The obtained logging curves include, but are not limited to: gamma curves, clay content, rock density, porosity, permeability, water saturation, triaxial stress, rock elastic modulus, and Poisson's ratio, etc. Figure 2 As shown. The reservoir sections are determined based on the signal characteristics of the logging curves. Further, based on the logging curves, sections with better physical properties (porosity, permeability), better gas content (high total hydrocarbon content, low resistivity), and lower clay content are identified as the testing sections, i.e., the fracturing operation sections. Specifically, in this embodiment, a section with low clay content (usually below 20%) and high porosity (above 7%) is selected as the testing section for this well.

[0059] In one optional implementation, the rock mechanics parameters in the logging curve, such as the reservoir rock elastic modulus, Poisson's ratio, and the magnitude and direction of triaxial stress (i.e., maximum horizontal principal stress, minimum horizontal principal stress, and vertical stress), are calculated from basic parameters, including but not limited to sonic transit time and P-wave / S-wave velocity ratio, and need to be calibrated using data from laboratory rock mechanics experiments. The fracture pressure curve of the reservoir section is calculated using the calibrated rock mechanics parameters, and the perforation location is selected based on the fracture pressure curve. Specifically, the optimal perforation location can be selected based on a fracture pressure value not exceeding 5 MPa.

[0060] In one optional implementation, the fracturing parameters include, but are not limited to, cluster spacing, sand dosage, fluid usage, and pump injection rate. Step 3 also includes the following sub-steps:

[0061] Step 31, selecting the proppant type. Specifically, the effective closure stress of 42 MPa or less belongs to the quartz sand propping range; the effective closure stress of 48 MPa or less belongs to the coated quartz sand propping range; the effective closure stress of 70 MPa or less belongs to the ceramic propping range; the ZQ206-6-H2 well in the embodiment is taken as an example for illustrative description, the effective closure stress of the ZQ206-6-H2 well is 40 MPa, which meets the propping requirements of quartz sand and coated quartz sand, and therefore the proppant type can be selected as the combined particle size of 70 / 140 mesh quartz sand + 40 / 70 mesh coated quartz sand, and the preferred ratio is 8:2. In another optional embodiment, the ratio can be determined according to the reservoir geological characteristics and Young's modulus, so as to facilitate smooth sanding construction.

[0062] Step 32, calculating the reservoir reconstruction volume and the fracture complexity degree. Specifically, the calculation method of the reservoir reconstruction volume is V=L*H*W, wherein V represents the reservoir reconstruction volume, m 3 , L represents the length of the fracture, m, H represents the height of the fracture, m, and W represents the width of the fracture, m; and the calculation method of the fracture complexity degree index is:

[0063] Step 33, using the petrel simulation technology to study the reservoir reconstruction volume and the fracture complexity degree index under different fracturing construction parameters, so as to determine the optimal fracturing construction parameter. The cluster spacing is taken as an example in the embodiment, the reservoir reconstruction volume and the fracture complexity degree index under different cluster spacings of the ZQ206-6-H2 well are studied, and the optimal cluster spacing is determined according to the maximum weighted value of the reservoir reconstruction volume and the fracture complexity degree index, as shown in FIG. 3. Figures 3-4

[0064] An optional embodiment, step 4 further includes the following sub-steps:

[0065] Step 41, under the optimized fracturing construction parameter, conducting the conductivity indoor experiment to optimize the fiber type. Specifically, based on the proppant type selected in the above step, the combined particle size of 70 / 140 mesh quartz sand + 40 / 70 mesh coated quartz sand is developed, the conductivity indoor experiment of 70 / 140 mesh quartz sand and 40 / 70 mesh coated quartz sand under different closure pressures, fiber lengths and fiber concentrations is carried out, and the conductivity of different types of proppants under different fiber lengths and fiber concentrations is obtained, as shown in Table 1. As shown in Table 1, the 9 mm fiber has the smallest conductivity damage for the 70 / 140 mesh quartz sand; the 3 mm fiber has the smallest conductivity damage for the 40 / 70 mesh coated quartz sand, and therefore 40 / 70+3 mm and 70 / 140+9 mm are preferred.

[0066] Table 1. The conductivity of different types of proppants under different fiber lengths and fiber concentrations

[0067] ​

[0068] Step 42, under the optimized fracturing operation parameters, carry out sand control indoor experiment, optimize the amount of fiber. Specifically, using conventional flow channel, carry out indoor experiment of sand control hole under different fiber concentration, the results show that 40 / 70+3mm uses 0.6% fiber concentration, the sand production is low, the sand control effect is good, 70 / 140+9mm uses 0.4% fiber concentration, the sand production is low, the sand control effect is good, therefore, 40 / 70+3mm(0.6%), 70 / 140+9mm(0.4%) can be selected, as shown in Figures 5-6 .

[0069] An alternative embodiment, step 5 further comprises:

[0070] Respectively, using tail injection mode (mode one), slug injection mode (mode two), full range with injection mode (mode three), in each stage before and after the temporary plugging material is put into the fiber (and proppant together into the wellbore) according to the mode of 40 / 70+3mm(0.6%), 70 / 140+9mm(0.4%), in the case of ensuring the permeability of the minimum sacrifice, the least sand production of the fracture, the optimal full fracture conductivity, improve the gas production. Get the second stage pump injection program table of ZQ206-6-H2 well as shown in table 2.

[0071] Table 2 ZQ206-6-H2 well second stage pump injection program table

[0072]

[0073]

[0074] Using numerical simulation technology can get the cumulative gas production of 5 years of three kinds of injection mode, as shown in Figure 7 , from the figure, the cumulative gas production of mode two is the highest in the three modes, therefore, mode two is preferred, that is, slug type as the optimal fiber pump injection mode.

[0075] The embodiment is aimed at the characteristics of a certain dense gas sandstone reservoir, studies the influence of different cluster spacings, sanding intensities, fluid scales, and discharge capacities of sandstone strata on fracture extension, deepens the influence law of construction parameters on reservoir reconstruction volume and fracture complexity, determines optimal construction parameters with reservoir reconstruction volume and fracture complexity as targets, studies the influence of different fiber types, dosages, and pumping modes on fracture conductivity and oil and gas production through indoor experiments, obtains optimal fiber types, dosages, and pumping modes with minimum damage to conductivity and optimal sand prevention effect, so as to realize optimization of the whole process of unconventional oil and gas sand control and sand prevention fracturing, effectively reduce the sand production rate, guarantee fracture flowback capacity, improve the reconstruction effect of the reservoir, increase oil and gas production, and reduce costs, and provide technical support for the formulation of a fiber sanding optimization scheme for dense gas horizontal wells.

[0076] Based on the same technical concept, the embodiment further provides a dense gas fiber sanding fracturing optimization design system, as shown in Figure 8 The fracturing optimization design system of the embodiment comprises:

[0077] a reservoir analysis unit, which judges a reservoir section, identifies reservoir thickness, and divides a test oil section according to a well logging curve.

[0078] a perforation position optimization unit, which calculates stress and fracture pressure profiles in combination with a rock mechanics parameter curve of the reservoir section in the well logging curve, and optimizes cluster perforation positions according to reservoir section properties and the fracture pressure profiles.

[0079] a construction parameter optimization unit, which selects a proppant type according to geological basic parameters, and obtains reservoir reconstruction volume and fracture complexity by using a numerical simulation technology, and optimizes fracturing construction parameters.

[0080] a fiber process parameter optimization unit, which, under the optimized fracturing construction parameters, performs indoor experiments to optimize fiber types and dosages with minimum influence on the conductivity of the proppant pack and optimal sand prevention effect as a target; and under the optimized fiber types and dosages, optimizes a fiber pumping mode with minimum sand production and optimal full-fracture conductivity as a target while guaranteeing minimum permeability sacrifice.

[0081] an output unit, which is configured to output an optimal scheme, including optimal fracturing construction parameters and fiber process parameters.

[0082] The above detailed description of the specific embodiments of the present application has been given to understand the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for designing a compact gas fiber sand fracturing optimization, characterized in that, The method comprises: judging a reservoir section according to a well logging curve, identifying a reservoir thickness, and dividing a test oil section; in combination with a rock mechanics parameter curve of the reservoir section in the well logging curve, calculating a stress and a fracture pressure profile, and according to a reservoir section physical property and the fracture pressure profile, optimizing a cluster perforation position; according to a geological basic parameter, selecting a proppant type, and using a numerical simulation technology to obtain a reservoir reconstruction volume and a fracture complexity, and optimizing a fracturing construction parameter; under the optimized fracturing construction parameter, performing an indoor experiment, and optimizing a fiber type and a fiber amount with a minimum impact on a proppant packing layer flow conductivity and an optimal sand control effect as a target; under the optimized fiber type and fiber amount, in a case of guaranteeing a minimum permeability sacrifice, a minimum fracture sanding, and an optimal full fracture flow conductivity, optimizing a fiber pumping mode with a maximum gas production as a target; the numerical simulation technology comprises: using the numerical simulation technology to calculate a reservoir reconstruction volume and a fracture complexity index under different fracturing construction parameters; determining an optimal fracturing construction parameter according to a maximum weighted value of the reservoir reconstruction volume and the fracture complexity index.

2. The method according to claim 1, wherein, The method selects a well section with a shale content lower than 20% and a porosity of more than 7% as the test oil section.

3. The method according to claim 1, wherein, The fracture pressure profile calculation method specifically comprises: calibrating a rock mechanics parameter through data of a rock mechanics indoor experiment; calculating a fracture pressure curve of the reservoir section through the calibrated rock mechanics parameter.

4. The method according to claim 3, wherein, The fracture pressure value is not more than 5 MPa as a basis for optimizing the perforation position.

5. The method according to claim 1, wherein, The proppant type selection comprises: selecting a proppant type according to an effective closure stress of the well logging, wherein the proppant type selection standard is that an effective closure stress of 42 MPa or below belongs to a quartz sand propping range, an effective closure stress of 48 MPa or below belongs to a coated quartz sand propping range, and an effective closure stress of 70 MPa or below belongs to a ceramic propping range; if at least two kinds of proppants are selected in combination, the proportion is determined according to reservoir geological characteristics and a Young's modulus.

6. The method according to claim 1, wherein, The reservoir reconstruction volume calculation method comprises: wherein V represents the reservoir stimulation volume, L represents the length of the fracture, H represents the height of the fracture, and W represents the width of the fracture; The calculation method of the crack complexity index is: .

7. The method according to claim 1, wherein, The fiber type and fiber amount optimization process specifically comprises: under the optimized fracturing construction parameter, performing a flow conductivity indoor experiment, and optimizing a fiber type; under the optimized fracturing construction parameter, performing a sand control indoor experiment, and optimizing a fiber amount.

8. The method according to claim 1, wherein, The fiber pumping mode optimization process specifically comprises: using a tail-chasing injection fiber mode, and injecting the fiber in an optimized fiber type and fiber amount mode at each stage before and after the temporary plugging material is put in.

9. A system for designing a compact gas fiber sand fracturing optimization, characterized in that, The system comprises: a reservoir analysis unit that judges a reservoir section according to a well logging curve, identifies a reservoir thickness, and divides a test oil section; a perforation position optimization unit that, in combination with a rock mechanics parameter curve of the reservoir section in the well logging curve, calculates a stress and a fracture pressure profile, and according to a reservoir section physical property and the fracture pressure profile, optimizes a cluster perforation position; a construction parameter optimization unit that, according to a geological basic parameter, selects a proppant type, and using a numerical simulation technology to obtain a reservoir reconstruction volume and a fracture complexity, and optimizes a fracturing construction parameter. And a fiber process parameter optimization unit, which carries out indoor experiments under optimized fracturing operation parameters to optimize fiber types and fiber dosages with the objectives of minimum influence on the flow conductivity of the proppant pack and optimal sand prevention effect; and under optimized fiber types and fiber dosages, optimizes fiber pumping modes with the objective of maximum gas production rate under the conditions of minimum sacrifice of permeability, minimum sand production from fractures and optimal flow conductivity of the whole fracture. The reservoir reconstruction volume and the fracture complexity degree are obtained by using the numerical simulation technology, and the fracturing operation parameters are optimized, including: The reservoir reconstruction volume and the fracture complexity degree index under different fracturing operation parameters are calculated by using the numerical simulation technology; The optimal fracturing operation parameters are determined according to the maximum weighted value of the reservoir reconstruction volume and the fracture complexity degree index.

10. The system for designing a compact gas fiber sand fracturing optimization of claim 9, wherein, The system further comprises: An output unit for outputting the optimal scheme.

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