Experimental device and experimental method for backflow of proppant in API (American Petroleum Institute) diversion chamber

Abstract

The invention discloses an API flow guide chamber proppant backflow experiment device and an experiment method, and relates to the technical field of fracturing. An upper piston and a lower piston are respectively arranged at the upper end and the lower end of the API diversion chamber, the hydraulic machine is respectively connected with the upper piston and the lower piston, and the hydraulic machine is used for applying closing pressure to the propping agent filling layer in the diversion chamber through the upper piston and the lower piston so as to simulate fracture closing pressure in a stratum; the plunger pump is connected with the inlet end of the API flow guide chamber; the intermediate container is arranged between the plunger pump and the API flow guide chamber and used for storing and adjusting the pressure and flow of the fluid; the preheater is arranged between the intermediate container and the API diversion chamber and is used for heating fluid; the sand collecting filter is connected with the outlet end of the API flow guide chamber; and the back-pressure valve is connected with the outlet end of the API flow guide chamber. The problem of how to simulate the fracture closing pressure in the stratum and the flowing condition of fluid in the fracture so as to more accurately evaluate and test the backflow condition of the proppant in the flow guide chamber is solved.

Description

Technical Field

[0001] This application relates to the field of fracturing technology, and in particular to an API flow chamber proppant reflux test apparatus and test method. Background Technology

[0002] Hydraulic fracturing technology creates fractures by injecting high-pressure fracturing fluid into the reservoir, aiming to increase oil and gas well production. Fracturing fluid flowback is a crucial step in hydraulic fracturing operations, involving the effective removal of fracturing fluid from the fractures to minimize reservoir damage. Depending on the flowback method, fracturing fluid flowback processes are mainly classified into several types, including low-volume flowback, forced closure flowback, and reverse sand removal. The core objectives of these processes are to optimize proppant distribution in the fractures, prevent proppant backflow, and minimize fracturing fluid damage to the reservoir.

[0003] Existing technologies have many shortcomings in simulating formation fracture conditions and evaluating proppant reflow performance, relying mainly on regional mine experience, which leads to significant arbitrariness and uncertainty in the on-site flowback process. Therefore, how to simulate fracture closure pressure and fluid flow within fractures while ensuring the stability and controllability of experimental conditions, in order to more accurately evaluate and test proppant reflow in the flow chamber, has become an urgent problem to be solved. Summary of the Invention

[0004] In this application embodiment, by providing an API flow chamber proppant backflow experimental device and method, the problem of how to simulate the fracture closure pressure in the formation and the flow of fluid in the fracture is solved, while ensuring the stability and controllability of the experimental conditions, so as to more accurately evaluate and test the backflow of proppant in the flow chamber.

[0005] In a first aspect, embodiments of this application provide an API proppant backflow experimental apparatus, including an API proppant chamber, a hydraulic plunger pump, an intermediate container, a preheater, a sand collection filter, a back pressure valve, a first pressure sensor, a second pressure sensor, and a vacuum pump. An upper piston and a lower piston are respectively installed at the upper and lower ends of the API proppant chamber. The hydraulic press is connected to the upper and lower pistons respectively, and the hydraulic press applies a closing pressure to the proppant filling layer in the proppant chamber through the upper and lower pistons to simulate the closure pressure of fractures in the formation. The plunger pump is connected to the inlet end of the API proppant chamber and is used to pump fluid into the API proppant chamber to simulate fluid flow within the fracture. An intermediate container is positioned between the plunger pump and the API flow chamber to store and regulate the pressure and flow rate of the fluid; a preheater is positioned between the intermediate container and the API flow chamber to heat the fluid; a sand filter is connected to the outlet of the API flow chamber to collect the proppant flowing back from the API flow chamber; a backpressure valve is connected to the outlet of the API flow chamber to regulate and control the pressure of the fluid flowing out of the API flow chamber; a first pressure sensor is positioned at the inlet of the API flow chamber, and a second pressure sensor is positioned at the outlet of the API flow chamber; a vacuum pump is connected to the outlet of the API flow chamber to evacuate the API flow chamber before the experiment.

[0006] In one possible implementation, the plunger pump is connected to the intermediate vessel via a first pipeline; the intermediate vessel is connected to the preheater via a second pipeline; the preheater is connected to the inlet of the API flow chamber via a third pipeline; the outlet of the API flow chamber is connected to the vacuum pump via a fourth pipeline; the outlet of the API flow chamber is connected to the sand filter via a fifth pipeline; and the outlet of the API flow chamber is connected to the back pressure valve via a sixth pipeline.

[0007] In one possible implementation, valves are installed on the first, second, third, fourth, and fifth pipelines.

[0008] In one possible implementation, a differential pressure gauge is also included; the differential pressure gauge is connected to the inlet and outlet of the API diversion chamber via a seventh and an eighth pipeline.

[0009] Secondly, embodiments of this application provide a method for testing the backflow of proppant in an API flow chamber, comprising: installing the API flow chamber on an experimental platform, applying pressure simultaneously to the upper and lower pistons using a hydraulic press to simulate the closure pressure of fractures in the formation; closing the valves on the first, second, third, and fifth pipelines, opening the valve on the fourth pipeline, and using a vacuum pump to evacuate the API flow chamber to remove air and impurities inside; filling the API flow chamber with a layer of quartz sand having the same preset median particle size and proppant concentration as proppant, and calculating the required mass of proppant; preparing fracturing fluid as the fluid, placing it in an intermediate container, heating it to a preset temperature using a preheater and maintaining it at a constant temperature; closing the valve on the fourth pipeline, opening the valves on the first, second, third, and fifth pipelines, heating the API flow chamber to a preset experimental temperature using a flow chamber heating device, and injecting the fracturing fluid from the intermediate container into the API flow chamber at a preset initial flow rate using a plunger pump; and transmitting the first pressure... The flow rate is monitored by a first pressure sensor and a second pressure sensor. When the readings of the first and second pressure sensors remain stable, the flow rate is gradually increased by a preset gradient value based on a preset initial flow rate. At the same time, the back pressure valve is observed and adjusted to maintain the stability of the outflow fluid pressure. Each time the flow rate is increased, the flow is held for a first preset time. The data of the first and second pressure sensors are recorded every second preset time interval, and the changes in the proppant in the sand collection filter are observed. When the proppant begins to flow back from the outlet of the API flow rate chamber, the injection flow rate at the inlet of the API flow rate chamber is recorded. This injection flow rate is taken as the critical backflow flow rate of the proppant, and the critical backflow velocity of the proppant is determined based on the critical backflow flow rate of the proppant. The proppant flowing back from the sand collection filter is collected until the proppant no longer flows back from the outlet of the API flow rate chamber, and the backflow sand discharge rate of the proppant is calculated. After the collection of the proppant flowing back from the sand collection filter is completed, the flow rate is increased by a preset gradient value until the pressure in the API flow rate chamber changes abruptly, at which point the experiment is stopped.

[0010] In one possible implementation, the formula for calculating the required mass of proppant is: ;in, For the required quality of the proppant, The area of ​​the API diversion chamber. This refers to the sand concentration.

[0011] In one possible implementation, the formula for calculating the proppant return sand ratio is: ;in, The reflux sand discharge rate of the proppant, The quality of the proppant returning in the sand collection filter. The required quality of the proppant.

[0012] In one possible implementation, the method further includes: determining the critical backflow velocity of the proppant as a reference sequence; determining four factors—proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure—as a comparison sequence; and ranking the comparison sequences based on weighting coefficients to reflect the influence of each factor on the critical backflow velocity of the proppant. The calculation of the comprehensive evaluation value includes: calculating the correlation coefficient between the comparison sequences and the reference sequence; calculating the correlation degree of each comparison sequence based on the correlation coefficient; calculating the weighting coefficient of each comparison sequence based on the correlation degree; and calculating the comprehensive evaluation value based on the weighting coefficient of each comparison sequence. The calculation is based on the formula... Calculate the correlation coefficient between the comparison sequence and the reference sequence; where, To compare the correlation coefficient between the sequence and the reference sequence, For comparing sequences With reference sequence In the The absolute value of the difference at each data point. For all comparison sequences Compare sequences across all data points With reference sequence The minimum absolute value of the difference between them. For all comparison sequences Compare sequences across all data points With reference sequence The maximum absolute value of the difference between them. The correlation coefficient is used to distinguish the sequences. The correlation degree between each comparison sequence and the reference sequence is calculated using the following formula: ;in, The correlation between each comparison sequence, In the first For each data point, the correlation coefficient between the comparison sequence and the reference sequence is calculated, where n is the number of data points. This is the index variable, used to iterate through all data points in the dataset; the weight coefficient of each comparison sequence is calculated based on the correlation between the comparison sequences, using the following formula: ;in, Here are the weighting coefficients for each comparison sequence; the comprehensive evaluation value is calculated based on these weighting coefficients using the following formula: ;in, This is the comprehensive evaluation value.

[0013] One possible implementation also includes: establishing a critical backflow velocity prediction model to predict the critical backflow velocity of the proppant under different conditions, and obtaining a formula for calculating the critical backflow rate at the wellhead under field formation fracture conditions based on the critical backflow velocity prediction model; the expression of the critical backflow velocity prediction model is: ;in, The critical reflux velocity of the proppant. For the particle size of the proppant, To determine the sand concentration, For backflow viscosity, The closing pressure; the formula for calculating the critical wellhead backflow rate under field formation fracture conditions is: ;in, The critical wellhead backflow rate under field formation fracture conditions. The critical reflux velocity of the proppant. The width of the crack. The diameter of the wellbore. For the number of segments, This represents the number of clusters.

[0014] One or more technical solutions provided in this application embodiment have at least the following technical effects: This application embodiment provides an API flow chamber proppant backflow experimental device. A hydraulic press applies closing pressure to the proppant filling layer in the API flow chamber via an upper and lower piston, which can highly simulate the actual closure state of fractures in the formation, thereby ensuring the accuracy and reliability of the experimental results. The cooperation between the plunger pump and the intermediate container can stably pump fluid into the API flow chamber and heat the fluid through a preheater to simulate the flow of fluid in formation fractures under different temperature and pressure conditions. The sand collection filter and back pressure valve can not only effectively collect the proppant backflowing from the API flow chamber but also regulate and control the pressure of the outflowing fluid, thereby realizing real-time monitoring and analysis of the proppant backflow phenomenon and providing important data for evaluating proppant performance. A first pressure sensor and a second pressure sensor are respectively installed at the inlet and outlet of the API flow chamber, which can measure the pressure change of the fluid during the flow process in the flow chamber in real time and accurately, providing strong support for analyzing the influence of fluid flow characteristics and fracture closure pressure on proppant performance. A vacuum pump is used to evacuate the API flow chamber before the experiment, effectively removing air and other impurities to ensure a pure and stable experimental environment, thereby improving the accuracy and repeatability of the experiment. This solves the problem of simulating fracture closure pressure and fluid flow within fractures while ensuring the stability and controllability of experimental conditions, enabling more accurate evaluation and testing of proppant backflow within the flow chamber. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments of this application or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic diagram of the API flow chamber support reflux experimental apparatus provided in the embodiments of this application; Figure 2 A flowchart of the API flow chamber proppant reflux test method provided in the embodiments of this application; Figure 3 Photographs of quartz sand samples provided in the embodiments of this application; Figure 4 A diagram showing the particle size distribution of the proppant provided in the embodiments of this application; Figure 5 A schematic diagram showing the viscosity test results of fracturing fluids with different crosslinking ratios at 25°C and 60°C, provided in the embodiments of this application; Figure 6 A schematic diagram of the critical backflow rate of the proppant when the closing pressure is 0 MPa, as provided in the embodiments of this application; Figure 7 A schematic diagram showing the backflow sand discharge rate of the proppant when the closing pressure is 0 MPa, as provided in the embodiments of this application; Figure 8 A schematic diagram illustrating the critical reflux flow rate of 20 / 40 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 9 This is a schematic diagram showing the reflux sand discharge rate of 20 / 40 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 10 A schematic diagram illustrating the critical reflux flow rate of 40 / 70 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 11 This is a schematic diagram showing the reflux sand discharge rate of 40 / 70 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 12 A schematic diagram illustrating the influence of proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure on the critical backflow velocity, provided in the embodiments of this application. Figure 13 A schematic diagram illustrating the effect of proppant backflow on closure pressure provided in an embodiment of this application; Figure 14 A schematic diagram illustrating the effect of proppant refluxing on conductivity in an embodiment of this application; Figure 15 A schematic diagram of the linear regression results of the critical backflow velocity of the crack support provided in the embodiments of this application; Figure 16 A comparison chart showing the prediction results of the critical backflow velocity prediction model provided in the embodiments of this application.

[0017] Reference numerals: 1-API flow chamber; 2-Hydraulic press; 3-Plunger pump; 4-Intermediate container; 5-Preheater; 6-Sand filter; 7-Back pressure valve; 8-First pressure sensor; 9-Second pressure sensor; 10-Vacuum pump; 11-First pipeline; 12-Second pipeline; 13-Third pipeline; 14-Fourth pipeline; 15-Fifth pipeline; 16-Sixth pipeline; 17-Differential pressure gauge; 18-Seventh pipeline; 19-Eighth pipeline. Detailed Implementation

[0018] In the description of the embodiments of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the embodiments of this application and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. The terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] Figure 1 A schematic diagram of the API flow chamber support reflux experimental apparatus provided in the embodiments of this application is shown below. Figure 1 As shown, it includes an API flow chamber 1, a hydraulic press 2, a plunger pump 3, an intermediate container 4, a preheater 5, a sand filter 6, a back pressure valve 7, a first pressure sensor 8, a second pressure sensor 9, and a vacuum pump 10.

[0021] An upper piston and a lower piston are respectively installed at the upper and lower ends of the API flow chamber 1. A hydraulic press 2 is connected to the upper and lower pistons respectively. The hydraulic press 2 applies closing pressure to the proppant filling layer in the flow chamber through the upper and lower pistons to simulate the closure pressure of fractures in the formation. A plunger pump 3 is connected to the inlet end of the API flow chamber 1 to pump fluid into the API flow chamber 1 to simulate fluid flow in fractures. An intermediate container 4 is located between the plunger pump 3 and the API flow chamber 1 to store and regulate the pressure and flow rate of the fluid. A preheater 5 is located between the intermediate container 4 and the API flow chamber 1 to heat the fluid. A sand filter 6 is connected to the outlet end of the API flow chamber 1 to collect the proppant returning from the API flow chamber 1. A back pressure valve 7 is connected to the outlet end of the API flow chamber 1 to regulate and control the pressure of the fluid flowing out of the API flow chamber 1. A first pressure sensor 8 is located at the inlet end of the API flow chamber 1, and a second pressure sensor 9 is located at the outlet end of the API flow chamber 1. Vacuum pump 10 is connected to the outlet of API flow chamber 1 and is used to evacuate API flow chamber 1 before the experiment. Plunger pump 3 is connected to intermediate container 4 via first line 11. Intermediate container 4 is connected to preheater 5 via second line 12. Preheater 5 is connected to the inlet of API flow chamber 1 via third line 13. The outlet of API flow chamber 1 is connected to vacuum pump 10 via fourth line 14. The outlet of API flow chamber 1 is connected to sand filter 6 via fifth line 15. The outlet of API flow chamber 1 is connected to back pressure valve 7 via sixth line 16.

[0022] This application also includes a differential pressure gauge 17. The differential pressure gauge 17 is connected to the inlet and outlet ends of the API flow chamber 1 via a seventh line 18 and an eighth line 19. Specifically, by measuring the pressure difference between the inlet and outlet ends of the API flow chamber 1 under different proppant conditions, the flow carrying capacity and resistance characteristics of the proppant can be evaluated.

[0023] This application provides a method for testing the reflux of proppant in an API flow chamber, such as... Figure 2 As shown, the method includes steps S101 to S111. Wherein, Figure 2 This is merely one execution order shown in the embodiments of this application and does not represent the only execution order for an API flow chamber proppant reflux test method. Where the final result can be achieved, Figure 2 The steps shown can be performed in parallel or in reverse order.

[0024] S101: Install the API flow chamber 1 on the experimental platform and use the hydraulic press 2 to apply pressure to the upper and lower pistons simultaneously to simulate the closing pressure of the fracture in the formation.

[0025] Specifically, this application sets the outlet diameter of the improved API flow chamber 1 to 6 mm. This size ensures both experimental accuracy and ease of operation. The API flow chamber 1 can withstand a maximum pressure of 120 MPa, which is sufficient to simulate the closure pressure of most formation fractures. Simultaneously, the maximum temperature can reach 90℃, and the maximum flow rate can reach 1 L / min; these technical parameters meet the requirements of the experimental conditions. The API flow chamber 1 used in this application has a length of 17.78 cm and a width of 3.81 cm. The flow chamber is filled with proppant, and pistons are located at both the upper and lower ends. By using a hydraulic press 2 to simultaneously apply pressure to the upper and lower pistons, the closure pressure of fractures in the formation can be simulated, thus more realistically reproducing the actual situation of formation fractures.

[0026] Furthermore, after fracturing operations are completed, the fracturing fluid within the fracture gradually filters out and diffuses, and the fracture gradually closes. To accurately simulate the closure pressure of the fracture in the formation, multiple factors need to be considered. At the end of fracturing, the fluid pressure within the fracture is composed of the pump shutdown pressure, the fluid column pressure, and the frictional pressure loss. However, when the well is opened for flowback, the fluid pressure within the fracture becomes the sum of the wellhead pressure, the fluid column pressure, and the frictional pressure loss. Therefore, the effective closure pressure exerted on the proppant during well opening for flowback can be estimated by calculating the difference between the pump shutdown pressure and the flowback wellhead pressure. It should be noted that when the plunger pump 3 stops working, the fluid within the fracture, i.e., the fracturing fluid, maintains a certain pressure due to inertia, formation resistance, and the fluid's own compressibility; this pressure is the pump shutdown pressure.

[0027] The formula for calculating the effective closure pressure is as follows: the effective closure pressure exerted by the fracture wall on the proppant at the instant the fracturing pump is shut down. It can be done through formula The calculation yielded the following result. The crack closure pressure, For instantaneous pump stop pressure, This refers to the liquid column pressure. This represents the frictional pressure loss. However, in practice, since the fractures often do not completely close at the moment the pump is stopped, the effective closing pressure exerted by the fracture wall on the proppant at this time is considered to be 0. The effective closing pressure exerted by the formation fractures on the proppant during well opening and flowback is... It can be done through formula Calculation. Among them, This represents the return wellhead oil pressure. Considering the possibility that the fracture may not be completely closed at the moment of pump shutdown, the formula can be simplified as follows: This allows for a more direct estimation of the effective closure pressure. All pressure values ​​in the formula are in MPa.

[0028] Table 1 presents a statistical table of pressure data for horizontal wells in the Changqing shale oil field provided in the embodiments of this application. To verify the above theory and design a reasonable proppant backflow experiment, fracturing operation data from 31 horizontal wells in the Changqing oilfield were collected, including instantaneous pump shutdown pressure and flowback wellhead oil pressure. By calculating the differences in these data, the effective closure pressure of each well was estimated, and it was found that the effective fracture stress in most wells was between 10 and 20 MPa. Based on these findings, a proppant backflow experiment was designed, simulating experimental conditions with closure pressures of 10 MPa, 15 MPa, and 20 MPa. Furthermore, to observe the backflow state of the proppant within the fracture when the fracture is not completely closed, a comparative experimental group with a closure stress of 0 MPa was also set up. Through these experiments, a deeper understanding of the proppant backflow behavior under different closure pressures can be obtained, providing a useful reference for actual fracturing operations.

[0029] Table 1

[0030] Table 1 (continued)

[0031] S102: Close the valves on the first pipeline 11, the second pipeline 12, the third pipeline 13 and the fifth pipeline 15, open the valve on the fourth pipeline 14, and use the vacuum pump 10 to evacuate the API flow chamber 1 to remove air and impurities from inside the API flow chamber 1.

[0032] Specifically, during the evacuation process, a vacuum gauge or other monitoring equipment can be used to monitor the vacuum level inside API flow chamber 1. Ensure the vacuum level reaches the required level for the experiment to effectively remove air and impurities.

[0033] S103: Fill the inside of API flow chamber 1 with a layer of quartz sand with the same preset median particle size and sand concentration as a proppant, and calculate the required mass of proppant.

[0034] Specifically, the preset median particle size can be 0.65mm and 0.32mm, respectively, and the preset range of sand concentration is [8kg / m³]. 2 12kg / m 2 The formula for calculating the required mass of proppant is as follows: .in, For the required quality of the proppant, The area of ​​API flow chamber 1, The proppant concentration is specified. The mass of the proppant required in this application is expressed in grams (g), and the area of ​​the API flow chamber 1 is expressed in centimeters (cm²). 2 The unit for sand concentration is kg / m³. 2 .

[0035] Furthermore, this application selected two types of quartz sand as proppant, namely 20 / 40 mesh and 40 / 70 mesh. Both proppants underwent performance testing, including the determination of proppant density and particle size parameters, to provide data support for subsequent numerical simulation studies.

[0036] Figure 3 A photograph of a sample of quartz sand provided for an embodiment of this application. Figure 3 (a) is a sample photograph of 20 / 40 mesh quartz sand. Figure 3 Photograph (b) in the image shows a sample of 40 / 70 mesh quartz sand. Figure 3 As shown, these samples have few impurities, but their sphericity is not ideal due to the natural formation of the quartz sand. To more accurately understand the particle size distribution of the proppant, this application conducted bulk density testing and particle size analysis. The bulk density test results show that the bulk density of 20 / 40 mesh quartz sand is 1.52 g / cm³. 3 The bulk density of 40 / 70 mesh quartz sand is 1.45 g / cm³. 3 Their actual density is 2.51 g / cm³. 3 .

[0037] It should be noted that 20 / 40 mesh means that quartz sand can pass through a 20-mesh sieve but not a 40-mesh sieve. Therefore, the particle size of 20 / 40 mesh quartz sand falls between the aperture sizes of a 40-mesh and a 20-mesh sieve. Similarly, 40 / 70 mesh means that quartz sand can pass through a 40-mesh sieve but not a 70-mesh sieve. Therefore, the particle size of 40 / 70 mesh quartz sand falls between the aperture sizes of a 70-mesh and a 40-mesh sieve.

[0038] Particle size analysis was performed using a sieve analysis method, which determined the particle size distribution of the proppant by testing the proportion of proppant in different particle size ranges. Figure 4 A diagram showing the particle size distribution of the proppant provided in the embodiments of this application. Figure 4 (a) in the figure shows the particle size distribution of 20 / 40 mesh quartz sand proppant. Figure 4 Figure (b) shows the particle size distribution of 40 / 70 mesh quartz sand proppant. Figure 4 As shown, the particle sizes of the 20 / 40 mesh and 40 / 70 mesh quartz sand proppants are mainly concentrated in the middle three sieve particle size ranges, accounting for more than 95% of the total. Furthermore, it was found that the sieve particle sizes are not strictly limited to the predetermined range, but rather have a certain degree of expansion. Through particle size analysis, the median particle sizes of the 20 / 40 mesh and 40 / 70 mesh quartz sand proppants during the numerical simulation were determined to be 0.65 mm and 0.32 mm, respectively, meaning that the preset median particle sizes can be 0.65 mm and 0.32 mm, respectively.

[0039] Specifically, the preset range for the sand concentration in this application is [8 kg / m³]. 2 12kg / m 2 This means that in actual fracturing operations, 8 to 12 kilograms of proppant should be laid per square meter of wellbore area. The average proppant concentration observed in horizontal well fracturing operations is 11.15 kg / m². 2 This value indicates that in actual operation, the sand concentration is close to the upper limit of the preset range, but still within the specified preset range. This application considered three sand concentrations in the experimental design: 8 kg / m³. 2 10kg / m 2 12kg / m 2 These concentration points cover the entire specified range of sand concentrations.

[0040] S104: Prepare fracturing fluid as a fluid, place it in intermediate container 4, heat it to the preset temperature through preheater 5 and maintain it at a constant temperature.

[0041] Specifically, this application uses two fracturing fluids as the fluids. In each experiment, only one type of fracturing fluid is placed in the intermediate container 4 and heated to a preset temperature by the preheater 5 and maintained at a constant temperature. The fracturing fluids used are water and a fracturing fluid with a crosslinking ratio of 0.01%.

[0042] Furthermore, the fracturing fluid used in this application is EM30S fracturing fluid. Before the formal experiment, a detailed viscosity analysis of the EM30S fracturing fluid was conducted to select a suitable fracturing fluid concentration and set accurate numerical simulation parameters. In field fracturing operations, the crosslinking ratio of the fracturing fluid is typically 0.3%–0.6%. Therefore, during the experimental preparation stage, EM30S fracturing fluid experimental reagents were prepared, and fracturing fluids were formulated according to different crosslinking ratios (0.1%, 0.2%, 0.3%, 0.4%, 0.5%, and 0.6%). Each fracturing fluid was stirred for 2 hours using a six-speed rotator to ensure its homogeneity. The viscosity of the fracturing fluids with different crosslinking ratios was measured at room temperature (25°C). The experimental results showed that the viscosity of the fracturing fluid with a crosslinking ratio of 0.1% was 8.1 mPa·s, far lower than the viscosity required for actual flowback fluid. Therefore, the crosslinking ratio was further reduced, and the viscosity at even lower crosslinking ratios such as 0.01%, 0.02%, and 0.05% was tested.

[0043] Figure 5 This is a schematic diagram illustrating the viscosity test results of fracturing fluids with different crosslinking ratios at 25°C and 60°C, as provided in the embodiments of this application. Figure 5As shown, the viscosity of the fracturing fluid increases with the increase of the crosslinking ratio. For example, the viscosity of the fracturing fluid with a 0.6% crosslinking ratio reaches 47.2 mPa·s. However, when the fracturing fluid is placed in a 60℃ constant temperature water bath for 12 hours, its viscosity decreases significantly. Through this series of experiments, not only were the accurate viscosity values ​​of fracturing fluids with different crosslinking ratios determined, but the law of viscosity change with crosslinking ratio and temperature was also discovered. Finally, in the reflow experiment, this application selected EM30S fracturing fluid with a 0.01% crosslinking ratio because its viscosity is approximately 2 mPa·s, which meets the experimental requirements and has good fluidity. At the same time, clean water was also determined as another fracturing fluid for the reflow experiment, with a viscosity of 1 mPa·s.

[0044] S105: Close the valve on the fourth pipeline 14, and open the valves on the first pipeline 11, second pipeline 12, third pipeline 13, and fifth pipeline 15. Use the flow chamber heating device to heat the API flow chamber 1 to the preset experimental temperature. Inject the fracturing fluid in the intermediate container 4 into the flow chamber 1 through the plunger pump 3 at a preset initial flow rate. S106: The first pressure sensor 8 and the second pressure sensor 9 monitor the flow state of the fluid in the API flow chamber 1. The preset experimental temperature can be 60℃.

[0045] S107: When the readings of the first pressure sensor 8 and the second pressure sensor 9 remain stable, the flow rate is gradually increased by a preset gradient value based on the preset initial flow rate. At the same time, the back pressure valve 7 is observed and adjusted to maintain the stability of the outflow fluid pressure.

[0046] S108: Each time the flow rate is increased, the data of the first pressure sensor 8 and the second pressure sensor 9 are recorded at a second preset time interval, and the changes in the proppant in the sand collection filter 6 are observed.

[0047] S109: When the proppant begins to flow back from the outlet end of the API flow chamber 1, the injection flow rate at the inlet end of the API flow chamber 1 is recorded. This injection flow rate is taken as the critical backflow flow rate of the proppant, and the critical backflow velocity of the proppant is determined based on the critical backflow flow rate of the proppant.

[0048] It should be noted that since the width of the flow chamber is fixed, the thickness of the proppant filling layer will decrease under the pressure of closure during the experiment. Therefore, the equipment is equipped with a laser rangefinder to calculate the thickness of the proppant filling layer. When the proppant starts to flow back at the outlet end, the flow rate on the constant flow pump is the critical backflow flow rate of the proppant in the experiment. Then, based on the thickness and width of the proppant, the area of ​​the flow cross section is calculated to further determine the critical backflow velocity of the proppant.

[0049] S110: Collect the proppant that flows back into the sand filter 6 until the proppant no longer flows back into the outlet of the API flow chamber 1, and calculate the proppant backflow sand rate.

[0050] The formula for calculating the proppant return sand ratio is: ;in, The reflux sand discharge rate of the proppant, The mass of the proppant returning in the sand collection filter 6, The required mass of proppant. The mass of proppant returned to the sand filter 6 is in grams.

[0051] S111: After collecting the proppant that has returned in the sand filter 6, continue to increase the flow rate by the preset gradient value until the pressure in the API flow chamber 1 changes abruptly, at which point the experiment is stopped.

[0052] Specifically, to accurately determine the critical backflow velocity of the proppant within the fracture, this application employed a variable flow rate method. The experiment started with a preset initial flow rate of 1 ml / min, increasing by a preset gradient value of 0.1 ml / min each time. At the outlet of API flow chamber 1, proppant backflowed at different flow rates was collected, and these proppant samples were dried and weighed after the experiment. The purpose of this step was to analyze the proppant backflow at different flow rates, thereby determining the critical backflow velocity.

[0053] This experiment aimed to comprehensively investigate the effects of proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure on proppant recirculation. To gain a deeper understanding of these factors, 48 ​​experimental groups were designed, each considering different combinations of the four variables. Two different proppant particle sizes, 20 / 40 mesh and 40 / 70 mesh, were selected to explore the influence of particle size on proppant recirculation. The experimental setup was 8 kg / m³. 2 10kg / m 2 and 12kg / m 2 Three proppant concentrations were used to evaluate the effect of concentration variation on proppant recirculation. Two fracturing fluids with different viscosities, 1 mPa·s and 2 mPa·s, were selected to investigate the effect of viscosity on proppant recirculation. Four different closure pressure conditions were considered: 0 MPa (no closure pressure, used to observe the change in proppant morphology at the outlet during recirculation in API flow chamber 1), 10 MPa, 15 MPa, and 20 MPa, to analyze the effect of closure pressure on proppant recirculation.

[0054] Table 2 presents the experimental design table for proppant recirculation in the API flow chamber. Table 2 lists the key parameters for each experimental group, including the experimental number, proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure. Through these 48 experimental groups, the influence of different factors on the proppant recirculation state can be systematically analyzed, providing strong data support for subsequent fracture management and fluid optimization.

[0055] Table 2

[0056] Table 2 (continued)

[0057] Table 3 shows the proppant reflux test results when the closing pressure is 0 MPa. Figure 6 This is a schematic diagram of the critical backflow rate of the proppant when the closing pressure is 0 MPa, as provided in the embodiments of this application. Figure 7 This is a schematic diagram showing the proppant backflow sand discharge rate when the closing pressure is 0 MPa, as provided in the embodiments of this application. (See Table 3.) Figure 6 and Figure 7 As shown, the smaller the proppant particle size, the lower the critical backflow rate. This is because small-particle-size proppant requires less flow energy, making backflow more likely to occur at lower flow rates. The higher the proppant concentration, the lower the critical backflow rate. This is because the fracture width increases with increasing proppant concentration, leading to poorer stability of proppant accumulation and making backflow more likely during fracturing fluid flow. Experimental results show that fracturing fluid viscosity has a relatively small effect on the critical backflow rate. However, with increasing proppant concentration, the influence of fracturing fluid viscosity on the proppant return rate increases, especially when using small-particle-size proppant (e.g., 40 / 70 mesh quartz sand) and high proppant concentrations (e.g., 12 kg / m³). 2 At a critical flow rate, increased fracturing fluid viscosity significantly improves proppant return. After reaching the critical velocity, proppant backflow at the outlet creates a depression, which may lead to unfilled fractures near the perforation in the formation. These unfilled fractures may reclose after fracturing, thus reducing fracture conductivity. Experiments showed that a proppant concentration of 12 kg / m³ was optimal. 2 When 20 / 40 mesh silica sand proppant reaches the critical backflow velocity, the proppant at the outlet becomes unstable and a significant amount of proppant flows back. This further emphasizes the importance of maintaining proppant stability at the fracture site. Using large-diameter proppant can better prevent proppant backflow, but the difficulty of pumping large-diameter proppant into microfractures during fracturing and sand delivery needs to be considered. Therefore, backflow and pumpability must be comprehensively considered when selecting proppant particle size. When using small-diameter proppant, the amount of breaker should be considered, and a fracturing fluid system with more complete breaker should be used as much as possible to reduce the sand yield from the fracture.

[0058] Table 3

[0059] Table 4 shows the orthogonal experimental design for proppant recirculation in the API flow chamber. This design aims to study the influence of different factors on the proppant recirculation characteristics within the fracture. The experiment employed a four-factor, three-level orthogonal design, comprising nine experimental groups. The four factors were closure pressure, proppant particle size, fracturing fluid viscosity, and proppant concentration. The proppant particle size was measured in mesh. Each factor was set with three different levels to comprehensively examine its influence on proppant recirculation. Specifically, the closure pressure was set at three levels: 10 MPa, 15 MPa, and 20 MPa. The proppant particle size was selected from three specifications: 20 / 40 mesh, 30 / 50 mesh, and 40 / 70 mesh. The fracturing fluid viscosity was divided into three levels: 1 mPa·s, 5 mPa·s, and 10 mPa·s. The proppant concentration was 8 kg / m³. 2 10kg / m 2 and 12kg / m 2 Based on the results of the API proppant reflow experiment at three concentrations and four factors at three levels, the following conclusions were drawn: as the closure pressure increases, the critical reflow velocity of the proppant within the fracture also increases.

[0060] Figure 8 This is a schematic diagram illustrating the critical reflux flow rate of 20 / 40 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 9 This is a schematic diagram showing the reflux sand discharge rate of 20 / 40 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 10 This is a schematic diagram showing the critical reflux flow rate of 40 / 70 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 11 This is a schematic diagram showing the reflux sand discharge rate of 40 / 70 mesh proppant under different closing pressures, as provided in the embodiments of this application. Figure 9 and Figure 11 The return sand discharge rate is the reflux sand discharge rate. See Table 4 and... Figures 8 to 11 As shown in the experiment, during the closure pressure, the proppant at the fracture opening is squeezed and expelled. To determine the critical backflow velocity of the proppant within the fracture under closure pressure, the flow rate was gradually increased from 1 ml / min after the pressure stabilized. For quartz sand proppant with particle sizes of 20 / 40 mesh and 40 / 70 mesh, the closure pressure significantly affected the critical backflow velocity and backflow sand yield under pressurized conditions. Specifically, the higher the sand concentration, the lower the stability of the sand embankment when the critical backflow velocity is reached. For example, under the same conditions, a sand concentration of 12 kg / m³... 2 The sand output rate at that time was compared to 10kg / m 2The yield increased by 11.9%. Furthermore, the reflow characteristics of 20 / 40 mesh and 40 / 70 mesh quartz sand were compared. Under the same conditions, the critical reflow velocity of 40 / 70 mesh quartz sand was significantly lower than that of 20 / 40 mesh quartz sand, and its sand yield was also significantly increased. This indicates that small-diameter proppant at the joint opening is more prone to reflow. To improve this phenomenon, a method of tailing large-diameter proppant was adopted in field practice. When the closing pressure was 20 MPa, this method reduced the sand yield by 18.6%, and the effect of improving the sand yield was more significant with the increase of the proppant concentration.

[0061] Table 4

[0062] Furthermore, to delve into the specific influences of proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure on the critical backflow velocity, grey relational analysis was employed. This method uses the critical backflow velocity as the core evaluation criterion, and through a series of calculation steps, transforms each influencing factor into a comprehensive coefficient, i.e., a comprehensive evaluation value, which serves as the basis for classification and ranking.

[0063] The critical backflow velocity of the proppant was determined as the reference sequence, and four factors—proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure—were determined as the comparison sequence. The comparison sequence was sorted based on weighting coefficients to reflect the degree of influence of each factor on the critical backflow velocity of the proppant.

[0064] The calculation method for the comprehensive evaluation value includes: calculating the correlation coefficient between the comparison sequence and the reference sequence; calculating the correlation degree of each comparison sequence based on the correlation coefficient between the comparison sequence and the reference sequence; calculating the weight coefficient of each comparison sequence based on the correlation degree of each comparison sequence; and calculating the comprehensive evaluation value based on the weight coefficient of each comparison sequence.

[0065] To ensure the comparability and accuracy of the data, the data from these reference sequences were standardized, i.e., normalized.

[0066] According to the formula Calculate the correlation coefficient between the comparison sequence and the reference sequence. Wherein, To compare the correlation coefficient between the sequence and the reference sequence, For comparing sequences With reference sequence In the The absolute value of the difference at each data point. For all comparison sequences Compare sequences across all data points With reference sequence The minimum absolute value of the difference between them. For all comparison sequences Compare sequences across all data points With reference sequence The maximum absolute value of the difference between them. The resolution coefficient. It can take the value 0.52.

[0067] It should be noted that the comparison sequence middle The value of can be 1, 2, 3, or 4, representing the four factors: proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure, respectively. The value can be an integer.

[0068] The correlation degree of each comparison sequence is calculated based on the correlation coefficient between the comparison sequence and the reference sequence. The calculation formula is as follows: .in, The correlation between each comparison sequence, In the first For each data point, the correlation coefficient between the comparison sequence and the reference sequence is calculated, where n is the number of data points. This is an index variable used to iterate through all data points in the dataset.

[0069] The weight coefficients of each comparison sequence are calculated based on the correlation degree of each comparison sequence, reflecting the relative importance of each factor influencing the critical backflow velocity. By comparing the weight coefficients, it can be determined which factors have a more significant impact on the critical backflow velocity.

[0070] The weight coefficient of each comparison sequence is calculated based on the correlation of each comparison sequence. The calculation formula is as follows: .in, These are the weighting coefficients for each comparison sequence.

[0071] The comprehensive evaluation value is calculated based on the weighting coefficients of each comparison sequence. The formula for calculating the comprehensive evaluation value is: .in, This is the comprehensive evaluation value. Figure 12This diagram illustrates the influence of proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure on the critical backflow velocity, as provided in the embodiments of this application. Table 5 shows the ranking of the influence of proppant particle size, proppant concentration, fracturing fluid viscosity, and closure pressure on the critical backflow velocity. According to the ranking, closure pressure has the greatest impact on the critical backflow velocity, followed by proppant concentration and proppant particle size, while the impact of fracturing fluid viscosity is relatively small. This conclusion provides a useful reference for optimizing fracturing design and improving oil and gas well productivity. It is also noted that increasing the proppant particle size increases the difficulty of pumping it into the fracture, which should be fully considered during field operations. The ranking of weighting coefficients reflects the importance of each indicator, i.e., which factor is more likely to cause backflow, while the comprehensive evaluation value is the final evaluation result of the experimental scheme considering multiple factors, reflecting which scheme is better. Since this application does not evaluate each experimental scheme individually, but aims to find the factors with the greatest influence to provide guidance for future experiments or field parameter design, the ranking is based on weighting coefficients.

[0072] Table 5

[0073] Furthermore, in experiments involving proppant backflow within fractures, it was observed that proppant backflow led to a reduction in the effective width at the fracture opening. This phenomenon, in turn, affected the effective conductivity of the fracture. To quantify this effect, a conductivity testing method based on Darcy's law was employed, applicable to laminar flow liquids. The formula for calculating conductivity is as follows: .in, The liquid permeability is expressed in μm. 2 , The thickness of the proppant is in cm. The value is the liquid flow rate, in ml / s. The viscosity of the liquid is given in mPa·s. The lengths at both ends of the test point are in cm. Width of the guide channel, in cm. To test the differential pressure between two points, 10 -1 MPa.

[0074] Under standard API flow chamber 1 conditions, with a width of 3.81 cm and a distance of 12.7 cm between pressure test points, the formula for calculating the flow capacity can be simplified to: During proppant reflow testing, the crack closure pressure becomes unstable as the flow rate increases. When reflow occurs, the high closure pressure makes it difficult to maintain an effective closure pressure, resulting in a decrease in crack closure pressure as shown in pressure tests. Therefore, by monitoring changes in closure pressure, it is possible to determine whether reflow has occurred and to ascertain the critical reflow velocity.

[0075] Figure 13 This is a schematic diagram illustrating the effect of proppant backflow on closure pressure, provided in an embodiment of this application. Figure 14 This is a schematic diagram illustrating the effect of proppant refluxing on the conductivity of the fluid, provided in an embodiment of this application. Figure 13 and Figure 14 As shown, under stable closure pressure, with the increase of the backflow rate, the proppant within the fracture gradually flows back, leading to a change in fracture morphology and a reduction in the effective fracture width at the fracture opening. Comparative testing of the fracture's conductivity revealed that after backflow, the effective conductivity of the fracture significantly decreased under a closure pressure of 20 MPa. Specifically, for 20 / 40 mesh proppant, the conductivity reduction reached 19.6%, and for 40 / 70 mesh proppant, the reduction was 17.7%.

[0076] Figure 15 This diagram illustrates the linear regression results of the critical backflow velocity of proppant within fractures, as provided in an embodiment of this application. Based on test data from API flow chamber 1, this application investigates the pattern of proppant backflow within fractures. To predict the critical backflow velocity of proppant under different conditions, a prediction model for the critical backflow rate of proppant was established. Considering the complexity of field fracture conditions, the experimental results were further analyzed in depth, aiming to convert experimental conditions into field fracture parameters to guide the prediction of the critical backflow rate at the wellhead. A prediction model was established using linear regression, with proppant concentration, proppant particle size, fracturing fluid viscosity, and closure pressure as independent variables, and critical backflow rate as the dependent variable. The F-test results show that the model is significant at a significance level of 0.000, and the predicted results have high accuracy compared to measured values. R0 2 =0.966. Furthermore, grey relational analysis was used to determine the degree of influence of different factors on the critical backflow velocity, in descending order of importance: closure pressure, proppant concentration, proppant particle size, and fracturing fluid viscosity. Figure 15 The critical sand discharge flow rate is the critical reflux flow rate.

[0077] Specifically, a critical backflow velocity prediction model is established to predict the critical backflow velocity of proppant under different conditions. Based on the critical backflow velocity prediction model, a formula for calculating the critical backflow flow rate at the wellhead under field formation fracture conditions is obtained.

[0078] The expression for the critical backflow velocity prediction model is: .in, The critical reflux velocity of the proppant. Where φ is the particle size of the proppant, and φ is the sand concentration. For backflow viscosity, This is the closing pressure.

[0079] Figure 16This image shows a comparison of the prediction results of the critical backflow velocity prediction model provided in this application. This application successfully constructed a critical backflow velocity prediction model using a linear regression method. By comparing the prediction results with actual data, the model's fitting effect is found to be quite excellent. Furthermore, grey relational analysis was used to evaluate the influence of different factors on the critical backflow velocity. The results show that the closure pressure and proppant concentration have the most significant impact on the critical backflow velocity, exceeding the importance of proppant particle size and fracturing fluid viscosity. This finding provides strong support for a deeper understanding of the proppant flowback mechanism within fractures and helps to more accurately predict and control the critical backflow velocity in practical engineering.

[0080] Furthermore, this application aims to apply the critical backflow velocity prediction model to actual field fracture conditions to better control post-fracturing backflow discharge and effectively prevent sand production from fractures. To achieve this goal, the calculation formula for the critical backflow velocity in the wellbore is combined with the effective circumferential area at the perforation point, rather than the cross-sectional area of ​​the entire fracture, thus deriving a calculation formula for the critical backflow discharge under single-fracture conditions in the field. The calculation formula for the critical backflow discharge under single-fracture conditions is as follows: .in, This represents the critical backflow discharge rate of the crack under single-crack conditions. The critical reflux velocity of the proppant. The width of the crack. The wellbore diameter is given. The critical backflow velocity for proppant is measured in meters per second. The fracture width is measured in meters. The wellbore diameter is measured in meters.

[0081] Furthermore, in order to apply the critical backflow velocity prediction model to more complex in-situ formation fracture conditions, it was substituted and the number of segments was introduced. ) and number of clusters ( These two new parameters were then used to derive a formula for calculating the critical wellhead backflow rate under field formation fracture conditions.

[0082] The formula for calculating the critical wellhead backflow rate under field formation fracture conditions is as follows: .in, The critical wellhead backflow rate under field formation fracture conditions. The critical reflux velocity of the proppant. The width of the crack. The diameter of the wellbore. For the number of segments, This refers to the number of clusters. This application utilizes 20 / 40 mesh quartz sand proppant obtained from experimental testing, under specific closure pressure (10 MPa) and sand concentration (10 kg / m³). 2Under the conditions of 0.5 mm and crack width (6 mm), the critical backflow velocity was determined to be 4.9 × 10⁻⁶ mm using the critical backflow velocity prediction model. -2 m / min, which is converted to a critical reflux flow rate of 11.2 ml / min.

[0083] To verify the accuracy of the established critical backflow velocity prediction model, several wells on the HuaH100 platform were used as examples, and a detailed analysis was conducted combining actual fracturing operation parameters, backflow data, and wellbore cleaning data. By comparing the backflow parameters from the field wells with the results calculated by the model, it was found that the critical backflow rate calculated by the model has good consistency with the actual field conditions. Table 6 shows a comparison between the backflow parameters from the field wells and the critical backflow velocity prediction model calculations.

[0084] Table 6

[0085] Table 6 lists key parameters for several wells, including the number of fracturing stages, closure pressure, nozzle diameter, venting discharge rate, venting regime, and critical backflow rate, and records the sand flushing results. Comparison reveals that when the on-site backflow velocity exceeds the critical backflow rate predicted by the critical backflow velocity prediction model, sand production from the fractures is severe. For example, well number 1 achieved a maximum discharge rate of 102.2 m³ / s within the first 5 days of venting. 3 / d, with an average displacement of 83.7m³. 3 / d, this displacement is greater than the critical backflow rate of 75.97m³ predicted by the critical backflow velocity prediction model. 3 / d, leading to proppant backflow. Subsequently, by replacing the nozzle and adjusting the flow rate to below the critical backflow rate, sand production from the fractures was effectively controlled. Furthermore, for wells with high sand production data, wells numbered 4 and 19 had lower critical backflow rates. The flow rates during the initial blowout and backflow of these two wells were both greater than the critical backflow rate, resulting in higher sand production from the fractures. This observation is consistent with the critical backflow velocity prediction model, further demonstrating the accuracy of the critical backflow velocity prediction model in field applications.

[0086] In summary, by comparing the predicted results with the actual sand flushing results after backflow, the accuracy of the critical backflow velocity prediction model was verified. When the actual backflow velocity exceeds the predicted critical backflow discharge rate, the sand discharge situation is quite severe.

[0087] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, please refer to each other. Each embodiment focuses on describing the differences from other embodiments.

[0088] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. An API flow-by-frac proppant flowback apparatus, characterized in that, The API flow channel (1), the hydraulic machine (2), the plunger pump (3), the intermediate container (4), the preheater (5), the sand collecting filter (6), the back pressure valve (7), the first pressure sensor (8), the second pressure sensor (9) and the vacuum pump (10) are connected through the first pipeline (11), the second pipeline (12), the third pipeline (13), the fourth pipeline (14), the fifth pipeline (15) and the sixth pipeline (16). The upper and lower ends of the API flow channel (1) are respectively provided with upper and lower pistons, and the hydraulic machine (2) is connected with the upper and lower pistons, respectively. The plunger pump (3) is connected with the inlet end of the API flow channel (1), and is used for pumping fluid into the API flow channel (1) to simulate the fluid flowing in the fracture. The intermediate container (4) is arranged between the plunger pump (3) and the API flow channel (1), and is used for storing and adjusting the pressure and flow of the fluid. The preheater (5) is arranged between the intermediate container (4) and the API flow channel (1), and is used for heating the fluid. The sand collecting filter (6) is connected with the outlet end of the API flow channel (1), and is used for collecting the proppant flowing back from the API flow channel (1). The back pressure valve (7) is connected with the outlet end of the API flow channel (1), and is used for adjusting and controlling the fluid pressure flowing out of the API flow channel (1). The first pressure sensor (8) is arranged at the inlet end of the API flow channel (1), and the second pressure sensor (9) is arranged at the outlet end of the API flow channel (1). The vacuum pump (10) is connected with the outlet end of the API flow channel (1), and is used for vacuumizing the API flow channel (1) before the experiment.

2. The API flow-by-formation proppant flowback test apparatus of claim 1, wherein, The plunger pump (3) and the intermediate container (4) are connected through the first pipeline (11). The intermediate container (4) and the preheater (5) are connected through the second pipeline (12). The preheater (5) and the inlet end of the API flow channel (1) are connected through the third pipeline (13). The outlet end of the API flow channel (1) and the vacuum pump (10) are connected through the fourth pipeline (14). The outlet end of the API flow channel (1) and the sand collecting filter (6) are connected through the fifth pipeline (15). The outlet end of the API flow channel (1) and the back pressure valve (7) are connected through the sixth pipeline (16).

3. The API flow-by-frac proppant flowback apparatus of claim 2, wherein, Valves are arranged on the first pipeline (11), the second pipeline (12), the third pipeline (13), the fourth pipeline (14) and the fifth pipeline (15).

4. The API flow-by-formation proppant flowback test apparatus of claim 1, wherein, The differential pressure gauge (17) is connected with the inlet end and the outlet end of the API flow channel (1) through the seventh pipeline (18) and the eighth pipeline (19). The API flow channel proppant backflow experiment device is applied to the API flow channel proppant backflow experiment device.

5. A method of conducting a flowback experiment on API diversion-chamber proppant, characterized by, The API flow channel (1) is installed on the experimental platform, and the hydraulic machine (2) is used to simultaneously apply pressure to the upper and lower pistons to simulate the closure pressure of the fracture in the formation. ​ Close the valves on the first pipeline (11), the second pipeline (12), the third pipeline (13) and the fifth pipeline (15), open the valve on the fourth pipeline (14), and use the vacuum pump (10) to perform vacuumizing treatment on the API flow conduit (1) to remove air and impurities inside the API flow conduit (1); Fill a layer of quartz sand with the same preset median particle size and sand concentration as the proppant in the API flow conduit (1), and calculate the required mass of the proppant; Configure the fracturing fluid as the fluid, place it in the intermediate container (4), heat it to a preset temperature through the preheater (5) and keep it at a constant temperature; Close the valve on the fourth pipeline (14), open the valves on the first pipeline (11), the second pipeline (12), the third pipeline (13) and the fifth pipeline (15), use the flow conduit heating device to heat the API flow conduit (1) to a preset experimental temperature, and use the plunger pump (3) to inject the fracturing fluid in the intermediate container (4) into the API flow conduit (1) at a preset initial flow rate; The first pressure sensor (8) and the second pressure sensor (9) monitor the flow state of the fluid in the API flow conduit (1); When the readings of the first pressure sensor (8) and the second pressure sensor (9) remain stable, gradually increase the flow rate at a preset gradient value on the basis of the preset initial flow rate, and at the same time, observe and adjust the back pressure valve (7) to maintain the stability of the outflow fluid pressure; Each time the flow rate is increased, stay for a first preset time, record the data of the first pressure sensor (8) and the second pressure sensor (9) every second preset time, and observe the changes of the proppant in the sand collecting filter (6); When the outlet end of the API flow conduit (1) starts to backflow the proppant, record the injection flow rate of the inlet end of the API flow conduit (1), take the injection flow rate as the critical backflow flow rate of the proppant, and determine the critical backflow flow rate of the proppant based on the critical backflow flow rate of the proppant; Collect the backflow proppant in the sand collecting filter (6) until the outlet end of the API flow conduit (1) no longer backflows the proppant, and calculate the backflow sand production rate of the proppant; After the collection of the backflow proppant in the sand collecting filter (6) is completed, continue to increase the flow rate at a preset gradient value until the experiment is stopped when the pressure of the API flow conduit (1) changes abruptly.

6. The API flow-by-liquid experiment method for proppant of a flow-by-liquid chamber according to claim 5, wherein, The formula for calculating the mass of proppant required is: ; where, is the mass of proppant required, is the area of the API flow cell (1), is the sand placement concentration.

7. The API divertor pack flowback test method of claim 6, wherein, The formula for calculating the flowback proppant flowback rate is: ; wherein, is the flowback proppant flowback rate, is the mass of the proppant flowed back in the sand collection filter (6), is the mass of the proppant required.

8. The API flow-by-liquid experiment method for proppant pack in a flow conduit of claim 5, wherein, Further comprising: Determine the critical backflow flow rate of the proppant as a reference sequence, determine the particle size, sand concentration, fracturing fluid viscosity and closure pressure of the proppant as a comparison sequence, sort the comparison sequence based on the weight coefficient to reflect the influence degree of each factor on the critical backflow flow rate of the proppant; The calculation method of the comprehensive evaluation value includes: calculating the correlation coefficient between the comparison sequence and the reference sequence, calculating the correlation degree of each comparison sequence based on the correlation coefficient between the comparison sequence and the reference sequence, calculating the weight coefficient of each comparison sequence based on the correlation degree of each comparison sequence, and calculating the comprehensive evaluation value based on the weight coefficient of each comparison sequence. According to the formula Calculate the correlation coefficient between the comparison sequence and the reference sequence; where, To compare the correlation coefficient between the sequence and the reference sequence, For comparing sequences With reference sequence In the The absolute value of the difference at each data point. For all comparison sequences Compare sequences across all data points With reference sequence The minimum absolute value of the difference between them. For all comparison sequences Compare sequences across all data points With reference sequence The maximum absolute value of the difference between them. The resolution coefficient; The correlation degree of each comparison sequence is calculated based on the correlation coefficient between the comparison sequence and the reference sequence. The calculation formula is as follows: ;in, The correlation between each comparison sequence, In the first For each data point, the correlation coefficient between the comparison sequence and the reference sequence is calculated, where n is the number of data points. This is an index variable used to iterate through all data points in the dataset. The weight coefficient of each comparison sequence is calculated based on the correlation degree of each comparison sequence, and the calculation formula is: ; wherein, is the weight coefficient of each comparison sequence. The comprehensive evaluation value is calculated based on the weight coefficient of each comparison sequence, and the calculation formula is: ; wherein, is the comprehensive evaluation value.

9. The API divertor pack flowback test method of claim 8, wherein, Also comprising: establishing a critical backflow flow rate prediction model to predict the critical backflow flow rate of the proppant under different conditions, and obtaining a wellhead critical backflow flow rate calculation formula under the field formation fracture conditions based on the critical backflow flow rate prediction model; The expression of the critical flowback flow rate prediction model is: ; wherein, is the critical flowback flow rate of the proppant, is the particle size of the proppant, is the sand placement concentration, is the flowback viscosity, is the closure pressure; The wellhead critical flowback flow rate under the field formation fracture condition is calculated by the formula: ; wherein, is the wellhead critical flowback flow rate under the field formation fracture condition, is the critical flowback flow rate of the proppant, is the fracture width, is the borehole diameter, is the number of segments, is the number of clusters.

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