Intelligent testing method and system for fracturing proppant conductivity

Abstract

This invention relates to the field of oil and gas field development technology, and discloses an intelligent testing method and system for the flow conductivity of fracturing proppant. The method includes: Step S1, constructing a simulated fracture unit; Step S2, filling the simulated fracture unit with a target fracturing proppant; Step S3, applying multi-level closure stress to the filled simulated fracture unit; Step S4, during the application of each level of closure stress, real-time acquisition of fluid dynamic data flowing through the simulated fracture unit; Step S5, calculating the real-time flow conductivity of the proppant based on the fluid dynamic data; Step S6, after applying each level of closure stress, calculating the breakage rate of the proppant in real-time through image analysis; Step S7, correcting the real-time flow conductivity calculated in Step S5 based on the breakage rate to obtain a corrected flow conductivity; Step S8, outputting the test results based on the corrected flow conductivity.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, specifically to an intelligent testing method and system for the conductivity of fracturing proppant. Background Technology

[0002] Fracturing proppant is an indispensable key material in oil and gas extraction. Its core function is to "open up" channels in the fractures formed by fracturing, preventing the fractures from closing, thereby providing a stable flow path for oil and gas to flow from the formation to the wellbore.

[0003] Before use, fracturing proppant needs to have its conductivity tested to ensure its performance. However, in simulated tests, changes in rock stress can cause proppant to fracture, which directly affects conductivity. Traditional testing methods mostly test the conductivity of proppant directly, and the final test result is the original test result, which cannot be corrected, thus affecting the overall test accuracy.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] To address the aforementioned problems, this invention proposes an intelligent testing method and system for the conductivity of fracturing proppant, solving the issue that existing testing methods cannot correct the conductivity test results in real time based on the proppant's breakage during the testing process. Specifically, the following technical solution is adopted:

[0006] A smart testing method for the conductivity of fracturing proppant includes:

[0007] Step S1: Construct simulated crack elements;

[0008] Step S2: Fill the simulated fracture unit with the target fracturing proppant;

[0009] Step S3: Apply multi-level closing stress to the filled simulated crack element;

[0010] Step S4: During the application of various levels of closure stress, real-time fluid dynamic data flowing through the simulated crack element is collected.

[0011] Step S5: Calculate the real-time flow-carrying capacity value K of the proppant based on the fluid dynamic data. W ;

[0012] Step S6: After applying various levels of closure stress, the breakage rate β of the proppant is calculated in real time through image analysis;

[0013] Step S7: Calculate the real-time flow diversion capacity value K obtained in step S5. WThe broken rate β calculated in step S6 is input into the correction model to generate a corrected flowability value. The calculation formula for the corrected flowability value is as follows:

[0014] K E =K W ×e -kβ Where e is a natural constant and k is a proppant type correction coefficient, the value of which is determined based on the type of the target fracturing proppant;

[0015] Step S8: Output the test results based on the corrected flow guidance capability.

[0016] As an optional embodiment of the present invention, in a smart testing method for the flow-carrying capacity of fracturing proppant, step S4 involves real-time acquisition of fluid dynamic data flowing through the simulated fracture unit, including: inlet pressure P1 and outlet pressure P2 flowing through the simulated fracture unit, and fluid mass flow rate Qm flowing through the simulated fracture unit.

[0017] As an optional embodiment of the present invention, in a smart testing method for the flow conductivity of fracturing proppant, step S5, calculating the real-time flow conductivity of the proppant based on the fluid dynamic data, includes:

[0018] Based on the inlet pressure P1, outlet pressure P2, and fluid mass flow rate Qm obtained in step S4, the conductivity value is calculated using the following formula:

[0019] K W = ;

[0020] in, For fluid viscosity, The length of the crack cavity. The width of the crack cavity;

[0021] The fluid viscosity corresponding to the real-time test temperature was obtained by consulting a temperature-fluid viscosity lookup table. .

[0022] As an optional embodiment of the present invention, in a smart testing method for the conductivity of fracturing proppant, step S6, after applying various levels of closure stress, involves calculating the breakage rate of the proppant in real time through image analysis, including:

[0023] After each stage of closed stress loading, images of proppant particles were acquired using a microscopic imaging device. The proportion of broken particles was identified based on a neural network, and the breakage rate was output. The breakage rate was calculated using the following formula:

[0024] β = ×100%;

[0025] Where N1 is the total number of particles and N2 is the number of broken particles.

[0026] As an optional embodiment of the present invention, in a smart testing method for the conductivity of fracturing proppant, step S8, outputting test results based on the corrected conductivity, includes:

[0027] Plot the closure stress on the x-axis and the K output in step S7 on the y-axis. E Plot the conductivity curve with the vertical axis as the ordinate, and overlay the contour lines of temperature T.

[0028] As an optional embodiment of the present invention, a smart testing method for the conductivity of fracturing proppant includes:

[0029] Step S9: Monitor the corrected flow guidance capability K E The system monitors changes in the data and automatically triggers an early warning mechanism when the rate of decline exceeds a set threshold.

[0030] The decrease rate is under the closure stress of two adjacent stages, and the corrected conductivity K E The decrease in value and K under the previous stage closure stress E The ratio of values;

[0031] The set threshold is set according to different types of proppant.

[0032] As an optional embodiment of the present invention, in a smart testing method for the conductivity of fracturing proppant, step S1, constructing a simulated fracture element includes:

[0033] A high-temperature and high-pressure core holder is used to construct an adjustable fracture cavity. The initial width of the fracture cavity is set to 2-8 mm, and the surface roughness of the cavity simulates the mineral composition of the target reservoir rock.

[0034] As an optional embodiment of the present invention, in a smart testing method for the conductivity of fracturing proppant, step S2, filling the simulated fracture unit with the target fracturing proppant includes:

[0035] A closed stress of 10-100MPa is applied by a hydraulic servo system, with each stress level stabilizing for ≥30 minutes and the stress interval between adjacent levels being 5-15MPa.

[0036] This invention also provides an intelligent testing system for the conductivity of fracturing proppant, comprising:

[0037] The simulated crack element construction module is used to construct simulated crack elements.

[0038] A fracturing proppant filling module fills the simulated fracture unit with the target fracturing proppant.

[0039] The multi-level closed stress application module applies multi-level closed stress to the filled simulated crack elements;

[0040] The fluid dynamic data acquisition module collects fluid dynamic data flowing through the simulated crack unit in real time during the application of various levels of closing stress.

[0041] The real-time flow-guiding capacity calculation module calculates the real-time flow-guiding capacity value K of the proppant based on the fluid dynamic data. W ;

[0042] The proppant breakage rate calculation module calculates the proppant breakage rate β in real time through image analysis after applying various levels of closing stress.

[0043] The flow guidance capability correction module will calculate the real-time flow guidance capability value K. W The brokenness ratio β is input into the correction model to generate a corrected conductivity value. The calculation formula for the corrected conductivity value is as follows:

[0044] K E =K W ×e -kβ Where e is a natural constant and k is a proppant type correction coefficient, the value of which is determined based on the type of the target fracturing proppant;

[0045] The test result output module outputs the test results based on the corrected flow guidance capability.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] 1. The present invention provides an intelligent testing method for the conductivity of fracturing proppant. By simulating the real scenario of oilfield exploitation formations, the method can increase the realism of testing the actual use of fracturing proppant. At the same time, by outputting the fracture rate and substituting it into the calculation formula for correcting conductivity, the conductivity of the proppant can be corrected in real time, thereby increasing the accuracy and effectiveness of the test.

[0048] 2. The present invention provides an intelligent testing method for the flowability of fracturing proppant. During testing, the breakage rate of the fracturing proppant can be detected in real time, thereby detecting the compressive strength of the fracturing proppant and the effect of the fracturing proppant particles on the flow rate after breakage, thus enhancing the functionality of the method.

[0049] 3. The present invention provides an intelligent testing method for the conductivity of fracturing proppant. It can detect the real-time conductivity information and compare it with a predetermined threshold. When the conductivity is lower than the predetermined threshold, an early warning message can be triggered, which makes it easier for personnel to judge whether the monitoring process is misjudged due to external forces or other factors, or whether the actual conductivity of the fracturing proppant body is lower than the predetermined threshold. This allows personnel to judge whether to end the test to prevent wasting test time. Attached Figure Description

[0050] Figure 1 This is a flowchart illustrating an intelligent testing method for the conductivity of fracturing proppant according to an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the corrected conductivity calculation process in an intelligent testing method for the conductivity of fracturing proppant according to an embodiment of the present invention;

[0052] Figure 3 This is a framework diagram of an intelligent testing system for the flowability of fracturing proppant according to an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0054] Therefore, the following detailed description of embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely illustrates some embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0055] It should be noted that, unless otherwise specified, the embodiments and features and technical solutions in the present invention can be combined with each other.

[0056] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0057] In the description of this invention, it should be noted that the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. These terms are only for the convenience of describing this invention and 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, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0058] like Figure 1 As shown in this embodiment, an intelligent testing method for the conductivity of fracturing proppant includes:

[0059] Step S1: Construct simulated crack elements;

[0060] Step S2: Fill the simulated fracture unit with the target fracturing proppant;

[0061] Step S3: Apply multi-level closing stress to the filled simulated crack element;

[0062] Step S4: During the application of various levels of closure stress, real-time fluid dynamic data flowing through the simulated crack element is collected.

[0063] Step S5: Calculate the real-time flow-carrying capacity value K of the proppant based on the fluid dynamic data. W ;

[0064] Step S6: After applying various levels of closure stress, the breakage rate β of the proppant is calculated in real time through image analysis;

[0065] Step S7: Calculate the real-time flow diversion capacity value K obtained in step S5. W The broken rate β calculated in step S6 is input into the correction model to generate a corrected flowability value. The calculation formula for the corrected flowability value is as follows:

[0066] K E =K W ×e -kβ Where e is a natural constant and k is a proppant type correction coefficient, the value of which is determined based on the type of the target fracturing proppant;

[0067] Step S8: Output the test results based on the corrected flow guidance capability.

[0068] This embodiment provides an intelligent testing method for the conductivity of fracturing proppant. By constructing a closed-loop intelligent testing process, it achieves a more realistic, accurate, and efficient evaluation of the proppant conductivity. The specific technical effects are as follows:

[0069] 1. Significantly improved the authenticity and reliability of the test.

[0070] By constructing simulated fracture elements that can mimic reservoir rock composition and roughness (step S1) and applying multi-level closure stresses under high temperature and high pressure (step S3), this method highly replicates the actual loading environment of proppant in downhole fractures. Simultaneously, using a KCl solution with a composition similar to formation water as the test fluid further ensures the consistency between the experimental conditions and actual oilfield production scenarios, giving the test results extremely high reference value and reliability.

[0071] 2. Dynamic and precise correction of the flow guidance capacity test results has been achieved.

[0072] The core innovation of this method lies in the introduction of real-time calculation of the breakage rate based on image analysis (step S6) and dynamic correction of the flowability (step S7). Traditional methods only test the initial flowability, ignoring the blockage effect of stress-induced proppant breakage on the flow channels. This invention effectively eliminates the test error caused by proppant breakage by detecting the breakage rate in real time and calculating the real-time flowability using an established correction model. This makes the final corrected flowability closer to the actual performance of the proppant in the crack, greatly improving the accuracy of the test data and its engineering guidance value.

[0073] 3. It enhances the intelligence and automation level of the testing process.

[0074] From real-time data acquisition (step S4) and automatic calculation (step S5) to intelligent image recognition (step S6) and model correction (step S7), the entire process achieves a high degree of automation and intelligence. This method can automatically output test reports based on the corrected results (step S8) and can be further extended with early warning functions to alert operators when the throughput capacity drops sharply, effectively avoiding unnecessary continued testing and saving time and resources. This integrated intelligent testing solution reduces reliance on operator experience and improves testing efficiency and result consistency.

[0075] In summary, the intelligent testing method for the flowability of fracturing proppant provided in this embodiment integrates environmental simulation, real-time monitoring, intelligent identification, and dynamic correction, overcoming the industry pain point that traditional testing methods cannot reflect the impact of proppant breakage. This provides a more advanced, accurate, and reliable technical means for the performance evaluation, selection, and quality control of fracturing proppant.

[0076] Specifically, in the intelligent testing method for the conductivity of fracturing proppant provided in this embodiment, step S1 includes: constructing an adjustable fracture cavity using a high-temperature and high-pressure core holder, with the initial width of the fracture cavity set to 2-8 mm, and the surface roughness of the cavity simulating the mineral composition of the target reservoir rock.

[0077] Specifically, based on data from rock samples of the target reservoir, such as mineral composition, porosity, permeability, rock mechanical strength parameters, and the viscosity, density, and pH value of fracturing fluid, a fracture model of the rock formation is constructed. A digital model of the fracture surface morphology is then built using 3D scanning and image reconstruction technology, thereby obtaining a simulation model of the target rock formation. The acquisition, scanning, and construction technologies used above are all mature techniques, so their specific principles will not be elaborated on here. The high-temperature and high-pressure core holder can simulate the high-temperature and high-pressure environment downhole, increasing the realism of the test.

[0078] Furthermore, since the width of natural fractures or hydraulically fractured fractures in shale and tight sandstone reservoirs is typically in the range of 1–10 mm, the initial width of the fracture cavity is set to 2–8 mm, where 2 mm corresponds to narrow fractures, such as deep high-temperature reservoirs, and 8 mm corresponds to wide fractures, such as large fracture networks in brittle shale. This range covers the measured fracture width distribution of mainstream shale reservoirs, ensuring the universality of the experimental scenario.

[0079] Specifically, in the intelligent testing method for the conductivity of fracturing proppant provided in this embodiment, step S2 includes:

[0080] The proppant to be tested is filled into the fractures of the simulated rock formation model constructed above, thereby simulating the downhole support state of the proppant. Different types of proppant, such as quartz sand, ceramsite, and resin sand, can be simulated.

[0081] Specifically, in the intelligent testing method for the flowability of fracturing proppant provided in this embodiment, step S3 includes: applying a closing stress of 10-100MPa through a hydraulic servo system, with each stress level stabilizing for ≥30 minutes, and the stress interval gradient between adjacent levels being 5-15MPa.

[0082] Specifically, see Table 1:

[0083]

[0084] According to Table 1, the stress range applied by the hydraulic servo system of this equipment is 10-100MPa. Different closed stress ranges can be simulated according to different burial depths, thereby testing the stress limit of the proppant under different application environments. At the same time, according to different types of proppant, various parameters of the proppant under ultimate stress can be tested, such as the breakage rate of quartz sand under stress of 60-80MPa, the flowability of ceramsite at 100MPa, and the peeling of the resin coating of resin sand above 80MPa.

[0085] Table 2:

[0086]

[0087] Based on Table 2, the stress gradient between adjacent levels can be controlled according to the different types of proppant. Since quartz sand, as a low-strength material, is commonly used in shallow reservoirs, a small gradient of 5-10 MPa can facilitate the capture of the breakage inflection point of the proppant under ultimate stress. A medium gradient of 10-12 MPa can facilitate the monitoring of the critical stress of resin peeling. High gradient stress testing can increase the testing efficiency of high-strength materials such as ceramsite. Graded testing can increase the intelligence of the test and the accuracy of the data.

[0088] Specifically, this embodiment provides an intelligent testing method for the flow conductivity of fracturing proppant. In step S4, the real-time acquisition of fluid dynamic data flowing through the simulated fracture unit includes: the inlet pressure P1 and outlet pressure P2 of the simulated fracture unit, and the fluid mass flow rate Qm. The test fluid is a 2% KCl solution, and the temperature is controlled between 90-180℃.

[0089] Specifically, pressure sensors P1 and P2 are used to calculate the pressure difference between the inlet and outlet. A 2% KCl solution can simulate formation water. A mass flow meter detects the fluid mass flow rate Qm. The temperature range of 90-180℃ covers medium and high temperature reservoirs, such as shale gas reservoirs where the temperature often reaches 120-180℃. Temperature control ensures that fluid viscosity and proppant performance are tested in a real environment.

[0090] Table 3:

[0091]

[0092] Table 3 shows that the formation water K in shale reservoirs + The concentrations are generally 15,000–40,000 mg / L, with a KCl equivalent of 1.5–4%. Here, a 2% KCl concentration is used, falling within the midpoint of this range, ensuring the accuracy of the test. +The double electric layer of compressible clay particles reduces particle shedding and minimizes fluid viscosity interference. Furthermore, KCL exhibits no phase change under conditions of 90–180℃ and 100MPa, maintaining a single-phase liquid state, thus ensuring stable testing.

[0093] Table 4:

[0094] reservoir types Burial depth (m) Geothermal gradient (°C / 100m) Temperature range (°C) Conventional shallow oil and gas 800-2000 2.5-3.0 50-80 Shale reservoirs 2000-3500 3.0-3.5 90-130 Deep high temperature reservoir 4000-6000 3.5-4.0 150-180

[0095] As shown in Table 4, 90℃ is the lower limit of the temperature range for shale reservoirs, which meets the initial temperature requirements of the main shale reservoirs. 180℃ is the upper limit of the temperature range for deep reservoirs, covering ultra-deep reservoirs. By simulating the temperatures of different reservoirs, the conductivity and high-temperature state of fracturing proppant can be tested. For example, when testing resin sand, the resin types include phenolic resin, whose glass transition temperature is 140-160℃, and epoxy resin, whose glass transition temperature is 180-200℃. By simulating different temperature changes, the glass transition limit temperature of the resin can be tested.

[0096] Table 5:

[0097]

[0098] As shown in Table 5, based on the simulation of different ambient temperatures, the phenomena of different types of fracturing proppant at different temperatures can be monitored, thereby increasing the means and accuracy of monitoring fracturing proppant.

[0099] Specifically, this embodiment provides an intelligent testing method for the conductivity of fracturing proppant, wherein the step...

[0100] In step S5, calculating the real-time flow-carrying capacity of the proppant based on the fluid dynamics data includes:

[0101] Based on the inlet pressure P1, outlet pressure P2, and fluid mass flow rate Qm obtained in step S4, the flow carrying capacity value is calculated according to the following formula:

[0102] K W = ;

[0103] in, For fluid viscosity, The length of the crack cavity. The width of the crack cavity;

[0104] The fluid viscosity corresponding to the real-time test temperature was obtained by consulting a temperature-fluid viscosity lookup table. .

[0105] Specifically, U is obtained by referring to the pre-stored ASTM D445 standard calibration table and determining the viscosity of the 2% KCl solution based on the corresponding temperature.

[0106] According to the original form of Darcy's Law:

[0107] V = × ;

[0108] Where V is the fluid permeation velocity and K is the rock permeability. For pressure gradient;

[0109] The conductivity K of proppant-filled fractures W = Permeability K × Crack Width W

[0110] In a physical sense, the flow rate through a unit crack width under a unit pressure difference represents the crack's ability to transport fluid.

[0111] Based on Darcy's Law, the following derivation can be made:

[0112] Step 1: Convert the mass flow rate Q m Convert to Q v :

[0113] Q u = , where ρ is the fluid density;

[0114] Step 2: The cross-sectional area of ​​the crack is A = W × H, where H is the crack height and this is the core diameter;

[0115] Step 3: Substitute the above formula and rewrite Darcy's Law as follows:

[0116] Q u = ;

[0117] Step 4: Substitute A = W × H, and define K W =K×W;

[0118] Q u = ;

[0119] Step 5: The expression for the diversion capacity is obtained as follows:

[0120] K W = ;

[0121] Step 6: In the experiment, the crack height H was normalized to a unit height of 1 cm, i.e., H = 1, and because =ρQ u The final form is:

[0122] K W = ;

[0123] Since the density of a 2% KCl solution in practical applications is ρ≈1.0-1.1 g / m³, ρ can be simplified to 1, and the formula can be simplified to K... W = ;

[0124] Now, let's substitute the actual test scenario into the above formula;

[0125] For example, when testing quartz sand proppant under a closure stress of 60 MPa.

[0126]

[0127] Calculations show that: K W = =0.3375u㎡, from which the value of the flow conduction capacity can be calculated.

[0128] Specifically, this embodiment provides an intelligent testing method for the conductivity of fracturing proppant. In step S6, after applying various levels of closure stress, the proppant breakage rate is calculated in real time through image analysis, including:

[0129] After each stage of closed stress loading, images of proppant particles were acquired using a microscopic imaging device. The proportion of broken particles was identified based on a neural network, and the breakage rate was output. The breakage rate was calculated using the following formula:

[0130] β = ×100%;

[0131] Where N1 is the total number of particles and N2 is the number of broken particles.

[0132] Specifically, the use of microscopic imaging combined with neural networks for intelligent identification of broken particles, such as identifying fragment contours or particle size changes, and calculating the breakage rate β, is a common technique in existing technologies. Therefore, its specific structure and principle will not be elaborated on here. When different stresses are applied to different types of fracturing proppant and when tested at different temperatures, the breakage rate of different fracturing proppants can be detected, thereby increasing the means of monitoring fracturing proppants and providing a basis for subsequent corrections.

[0133] Specifically, such as Figure 2 As shown in the figure, this embodiment provides an intelligent testing method for the conductivity of fracturing proppant. In step S7, the conductivity value K calculated in step S5 is used... W The broken rate β calculated in step S6 is input into the correction model to generate a corrected flowability value. The calculation formula for the corrected flowability value is as follows:

[0134] K E =K W ×e -kβ Where e is a natural constant, and k is a proppant type correction coefficient, the value of which is determined based on the type of the target fracturing proppant. Specifically, the proppant type correction coefficient k is 0.25 for quartz sand, 0.12 for ceramsite, and 0.18 for resin sand.

[0135] Specifically, traditional flow capacity calculations do not consider the influence of broken particles. If broken particles clog pores, the actual flow capacity will be lower than the calculated value. This method uses K to correct this, e -kβ This is the breakage correction factor, where the larger β is, the smaller the factor, and the corrected K E The closer it is to the true value; the K value is set according to the proppant's anti-fracture ability, as shown in Table 6 below.

[0136] Table 6:

[0137] proppant type <![CDATA[K W Value Compressive strength (MPa) breakage sensitivity Quartz sand 0.25 35-50 High (high brittleness) Expanded clay 0.12 70-100 Low (high toughness) Resin Sand 0.18 50-80 Middle (resin-encapsulated)

[0138] As shown in Table 6, quartz sand has poor resistance to breakage (k=0.25), and its breakage has a significant impact on its conductivity. Ceramsite has strong resistance to breakage (k=0.12), and its breakage has a small impact on it. This makes the modification more in line with the characteristics of different proppants.

[0139] First, substitute the parameters of the flow-guiding capacity value measured in actual use into the modified flow-guiding capacity calculation formula, and then conduct the following test.

[0140] Table 7:

[0141] parameter Quartz sand Expanded clay <![CDATA[K W ]]> 1200 1800 β 38％ 12％ <![CDATA[K E ]]> 326 1480 Actual flow diversion capacity 310 1520

[0142] Table 7 shows that the correction value of quartz sand is closer to the true value than the first measured conductivity value, which reflects that the test method is more applicable to actual conditions. In addition to measuring the breakage rate of different types of fracturing proppant under different stresses and temperatures, it can also measure the actual impact of the fracturing proppant on conductivity after breakage.

[0143] Specifically, this embodiment provides an intelligent testing method for the conductivity of fracturing proppant. In step S8, the output of test results based on the corrected conductivity includes: plotting the closure stress as the abscissa and using K output in step S7 as the coordinate. E Plot the conductivity curve with the vertical axis as the ordinate, and overlay the contour lines of temperature T.

[0144] Specifically, to simulate actual fracturing operations, closure stress is the core control variable and a major factor in the attenuation of proppant conductivity during fracturing. Excessive closure stress can lead to proppant breakage, indirectly affecting its conductivity. Therefore, closure stress is used as the principal variable on the x-axis, while K... E With the dependent variable as the ordinate, K changes with the closing stress during the test. E The trend may change accordingly, making it easier to intuitively judge the trend of the test data. The temperature contour lines can intuitively judge the direct impact of different temperatures on fracturing proppant.

[0145] Specifically, this embodiment provides an intelligent testing method for the conductivity of fracturing proppant, including:

[0146] Step S9: Monitor the corrected flow guidance capability K E The system monitors changes in the data and automatically triggers an early warning mechanism when the rate of decline exceeds a set threshold.

[0147] The decrease rate is under the closure stress of two adjacent stages, and the corrected conductivity K E The decrease in value and K under the previous stage closure stress E The ratio of values;

[0148] The set threshold is set according to different types of proppant.

[0149] When K E When the rock pressure drops to the set threshold, a warning will be triggered. At this point, hydraulic loading should be stopped immediately to prevent overpressure damage to the core holder. The warning mechanism used in this equipment is consistent with that of K... E The real-time calculated values ​​are linked, and the early warning mechanism used in this device is a commonly used early warning mechanism in existing systems. It has an internal counting mechanism, and when K... E When the predetermined value is reached, the early warning mechanism will be triggered. When the early warning mechanism is activated, it indicates that the fracturing proppant tested at the field has reached the critical point for use and can no longer meet the actual required flow capacity. At this time, it is convenient for the staff to judge whether the test process is affected by external factors or whether the fracturing proppant can no longer meet the flow capacity. This allows the staff to make judgments and adjustments. When the fracturing proppant itself cannot meet the flow capacity, the staff can end the test, thus avoiding the problem of wasting experimental time due to lack of prompts.

[0150] Furthermore, the rate of decrease specifically refers to K under adjacent stress levels. E The ratio of the difference to the previous level KE, such as from 50MPa to 60MPa, K EThe decrease rate is 30% from 100 to 70. The early warning mechanism can be implemented through audio-visual prompts or system pop-ups to promptly remind testers to avoid continuing to apply ineffective stress, thus saving test time or misjudging the proppant performance.

[0151] Threshold settings should be based on different types of proppant. Specifically, different thresholds should be set for different types of fracturing proppant to meet the actual testing requirements and avoid issuing warnings too early or too late, which could affect the testing process.

[0152] This embodiment provides an intelligent testing method for the conductivity of fracturing proppant, including: step S10, outputting various parameters.

[0153] Specifically, step S10 includes: during the test, the calculated data, the stress data of the simulated rock layer applied to the model by the external pressure device, and various parameters can be output, so as to facilitate the staff to make intuitive judgments. Moreover, this method can not only test the above three types of fracturing proppant, but also flexibly adjust the threshold parameters according to different types of fracturing proppant.

[0154] like Figure 3 As shown, this embodiment also provides an intelligent testing system for the conductivity of fracturing proppant, including:

[0155] The simulated crack element construction module is used to construct simulated crack elements.

[0156] A fracturing proppant filling module fills the simulated fracture unit with the target fracturing proppant.

[0157] The multi-level closed stress application module applies multi-level closed stress to the filled simulated crack elements;

[0158] The fluid dynamic data acquisition module collects fluid dynamic data flowing through the simulated crack unit in real time during the application of various levels of closing stress.

[0159] The real-time flow-guiding capacity calculation module calculates the real-time flow-guiding capacity of the proppant based on the fluid dynamic data.

[0160] The proppant breakage rate calculation module calculates the proppant breakage rate in real time through image analysis after applying various levels of closing stress.

[0161] The flow guidance capability correction module will calculate the real-time flow guidance capability value K. W The brokenness ratio β is input into the correction model to generate a corrected conductivity value. The calculation formula for the corrected conductivity value is as follows:

[0162] K E =K W ×e -kβWhere e is a natural constant and k is a proppant type correction coefficient, the value of which is determined based on the type of the target fracturing proppant;

[0163] The test result output module outputs the test results based on the corrected flow guidance capability.

[0164] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent testing of fracture proppant conductivity, characterized by, The method comprises the following steps: S1, constructing a simulated fracture unit; S2, filling target fracturing proppants in the simulated fracture unit; S3, applying multi-stage closure stress to the filled simulated fracture unit; S4, collecting fluid dynamic data flowing through the simulated fracture unit in real time during the application of each stage of closure stress; Step S5, calculating the real-time conductivity value K of the proppant according to the fluid dynamic data W ; S6, calculating the breakage rate β of the proppants in real time through image analysis after the application of each stage of closure stress; Step S7: Calculate the real-time flow diversion capacity value K obtained in step S5. W The broken rate β calculated in step S6 is input into the correction model to generate a corrected flowability value. The calculation formula for the corrected flowability value is as follows: K E = K W × e -kβ ; wherein e is a natural constant, k is a proppant type correction coefficient, and the value of the proppant type correction coefficient k is determined based on the type of the target fracturing proppant; Step S8, output the test result based on the corrected discharge capacity value, taking the closure stress as the abscissa, and K E draw the discharge capacity curve, and superimpose the contour lines of temperature T for marking; Step S9, monitoring the changes of the modified flow capacity K and automatically triggering a warning mechanism when its decreasing rate exceeds a set threshold value. E of the flow capacity K and automatically triggering a warning mechanism when its decreasing rate exceeds a set threshold value. The decreasing rate is the ratio of the decreasing value of the modified flow conductivity K E at the closing stress of the two adjacent levels to the K E value at the closing stress of the previous level. The set threshold is set according to different types of proppants.

2. The intelligent testing method of the fracture proppant conductivity according to claim 1, characterized in that, In the step S4, the real-time collection of fluid dynamic data flowing through the simulated fracture unit includes the inlet pressure P1 and the outlet pressure P2 of the simulated fracture unit, and the fluid mass flow rate Qm flowing through the simulated fracture unit.

3. The intelligent testing method of fracture proppant conductivity according to claim 2, characterized in that, In the step S5, the calculation of the real-time conductivity of the proppants according to the fluid dynamic data includes: Based on the inlet pressure P1, the outlet pressure P2 and the fluid mass flow rate Qm obtained in the step S4, the conductivity value is calculated according to the following formula: K W ＝ ； wherein, is the fluid viscosity, is the fracture cavity length, is the fracture cavity width; obtaining the fluid viscosity corresponding to the real-time test temperature by inquiring a temperature and fluid viscosity table .

4. The intelligent testing method of fracture proppant conductivity according to claim 3, characterized in that, In the step S6, the breakage rate of the proppants is calculated in real time through image analysis after the application of each stage of closure stress, which includes: After each stage of closure stress is loaded, a microscopic imaging device is used to obtain a proppant particle image, a neural network is used to identify the proportion of broken particles, and a breakage rate is output, which is calculated according to the following formula: β＝ ×100％； Wherein N1 is the total number of particles, and N2 is the number of broken particles.

5. The intelligent testing method of fracture proppant conductivity according to claim 1, characterized in that, In the step S1, the construction of the simulated fracture unit includes: A high-temperature and high-pressure core holder is used to construct a size-adjustable fracture cavity, the initial width of the fracture cavity is set to 2-8mm, and the surface roughness of the cavity simulates the mineral components of the target reservoir rock.

6. The intelligent testing method of fracture proppant conductivity according to claim 1, characterized in that, In the step S2, the target fracturing proppants are filled in the simulated fracture unit, which includes: A hydraulic servo system is used to apply a closure stress of 10-100MPa, each stage of stress is stable for ≥30 minutes, and the interval gradient between adjacent two stages of stress is 5-15MPa.

7. An intelligent testing system for fracture proppant conductivity, characterized by, The method comprises the following steps: A simulated fracture unit construction module is constructed to construct a simulated fracture unit; A fracturing proppant filling module is used to fill target fracturing proppants in the simulated fracture unit; A multi-stage closure stress application module is used to apply multi-stage closure stress to the filled simulated fracture unit; A fluid dynamic data collection module is used to collect fluid dynamic data flowing through the simulated fracture unit in real time during the application of each stage of closure stress; a real-time conductivity calculation module configured to calculate a real-time conductivity value K of the proppant based on the fluid dynamic data W ; A proppant breakage rate calculation module is used to calculate the breakage rate β of the proppants in real time through image analysis after the application of each stage of closure stress; The flow guiding capacity correction module corrects the calculated real-time flow guiding capacity value K W and the breakage rate β input correction model to generate a corrected flow guiding capacity value, and the calculation formula of the corrected flow guiding capacity value is as follows: K E = K W × e -kβ ; wherein e is a natural constant, k is a proppant type correction coefficient, and the value of the proppant type correction coefficient k is determined based on the type of the target fracturing proppant; a test result output module for outputting a test result based on the corrected discharge capacity value, taking the closure stress as the abscissa and K E taking the longitudinal coordinate, drawing a discharge capacity curve, and superimposing the contour lines of the temperature T. monitoring the changes in the modified discharge capacity K E and automatically triggering a warning mechanism when its rate of decrease exceeds a set threshold; The decrease rate is the ratio of the decrease value of the modified conductive capacity K E at the closing stress of the adjacent two levels to the K E value at the closing stress of the previous level. The set threshold is set according to different types of proppants.

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