Method for analyzing stability of liquid gel breaker for fracturing

Abstract

The invention discloses a stability analysis method of a liquid gel breaker for fracturing, and relates to the technical field of stability analysis of liquid gel breakers, and the stability analysis method specifically comprises the following steps: acquiring dynamic information of an injection process of each area in a heterogeneous stratum in a fracturing fluid injection process in real time, and analyzing after acquisition to obtain a dynamic information of the injection process; respectively generating a diffusion equilibrium coefficient and a diffusion response index of each region; and constructing a diffusion uniformity degree evaluation model for the generated diffusion equilibrium coefficient and diffusion response index of each region, generating the diffusion uniformity coefficient of each region, analyzing after generation, and evaluating the diffusion uniformity degree of the gel breaker in each region in the fracturing fluid injection process. And each region is divided into a high diffusion region, a uniform diffusion region and a low diffusion region according to an evaluation result. According to the invention, the problem of non-uniform diffusion of the gel breaker in a heterogeneous stratum is solved, and accurate control and optimization of the diffusion process of the gel breaker are realized.

Description

Technical Field

[0001] The invention relates to the technical field of liquid breaker stability analysis, and in particular to a stability analysis method for a liquid breaker used for fracturing. Background Art

[0002] Liquid breaker is a chemical agent used in the process of oil and gas extraction. Its main function is to reduce the viscosity of the fracturing fluid to promote its fluidity in the formation, thereby enhancing the fracturing effect. Liquid breaker for fracturing refers specifically to the breaker used in the hydraulic fracturing process. It is usually composed of high molecular polymers and other additives, and is designed to effectively open formation cracks and increase the permeability and recovery rate of oil and gas. It is very important to analyze the stability of liquid breaker for fracturing, because in practical applications, the breaker needs to maintain its physical and chemical properties under high temperature, high pressure and complex geological environments to ensure its effectiveness and reliability during the construction process. If the breaker degrades, delaminates or has other stability problems before or during use, it will directly affect the fracturing effect and oil and gas production, leading to economic losses. Therefore, the stability analysis of the system can provide an important basis for selecting suitable breaker and optimizing fracturing design, ensuring the success and safety of the entire fracturing operation.

[0003] The existing stability analysis technology of liquid breakers for fracturing is mainly evaluated through a series of systematic experimental methods. First, researchers will test the physical properties of the breakers, including viscosity and density, which helps to understand their flow characteristics at different temperatures and shear rates. Next, the chemical stability analysis will ensure that the breakers do not chemically degrade during storage and use by measuring pH and chemical composition. In addition, thermal stability testing usually involves aging the breakers under high temperature conditions to observe the trend of their performance changes over time, and thermal cycling tests are also conducted to simulate the impact of temperature changes on the breakers in actual operations. Environmental stability analysis focuses on the performance of breakers in water environments with different salt concentrations and hardness to ensure their reliability under complex geological conditions. Finally, field simulation tests simulate real fracturing environments under laboratory conditions to comprehensively evaluate the application performance and stability of breakers. These comprehensive technical means provide important data support for the selection of breakers and the optimization of fracturing operations, thereby improving the efficiency and safety of oil and gas production.

[0004] The prior art has the following deficiencies: When fracturing in heterogeneous formations, the formation permeability and porosity will change dramatically. Due to these changes, the fracturing fluid will experience significant changes in flow rate and flow direction during the injection process, causing the breaker to diffuse too quickly in the high permeability area and be retained in the low permeability area. Due to the unevenness of the formation resistance, the diffusion rate of the breaker in these areas cannot be kept consistent. The existing stability analysis technology is usually only tested under homogeneous formation conditions, and it is impossible to accurately simulate the uneven flow and diffusion of the breaker in such a heterogeneous formation, which will lead to the inability to predict the distribution of the breaker in advance in actual operations. This unpredictable diffusion heterogeneity will lead to unbalanced viscosity adjustment of the fracturing fluid in the formation, which will affect the morphology and expansion effect of the cracks, resulting in the inability to effectively form cracks in some areas, ultimately leading to a decrease in oil and gas recovery, while increasing operating costs and complexity.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a stability analysis method for a liquid breaker for fracturing to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a stability analysis method of a liquid breaker for fracturing, specifically comprising the following steps: When fracturing in heterogeneous formations, the heterogeneous formations are evenly divided into several independent areas according to the permeability, porosity and lithology changes of the heterogeneous formations, and a real-time analysis framework for diffusion uniformity evaluation is established based on the diffusion and flow of the breaker during the injection process in each area; Real-time acquisition of dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, and analysis after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each area respectively; A diffusion uniformity evaluation model is constructed for the generated diffusion equilibrium coefficient and diffusion response index of each region, and the diffusion uniformity coefficient of each region is generated. After the generation, the diffusion uniformity of the breaker in each region during the fracturing fluid injection process is evaluated, and each region is divided into a high diffusion region, a uniform diffusion region and a low diffusion region according to the evaluation results; According to the division results of each area in the heterogeneous formation, corresponding measures are taken to adjust the injection amount of the breaker, optimize the injection pressure and adjust the formula of the breaker; Continuously monitor the dynamic information of the injection process in each area, dynamically adjust the breaker injection strategy and parameter settings based on real-time analysis results, and regularly update the diffusion uniformity assessment model.

[0008] Preferably, the injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process is acquired in real time, and analyzed after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each region respectively, which specifically includes the following steps: Real-time acquisition of injection process dynamic information of each area in the heterogeneous formation during fracturing fluid injection, and pre-processing after acquisition; Extracting diffusion dynamic information and response adjustment information from the preprocessed injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process; The diffusion dynamic information and response adjustment information in the extracted injection process dynamic information of each region are analyzed to generate the diffusion equilibrium coefficient and diffusion response index of each region respectively.

[0009] Preferably, the logic for obtaining the diffusion equilibrium coefficient of each region is as follows: Extract the diffusion dynamic information from the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, specifically including the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, the average concentration of the breaker in each area, and the permeability and viscosity of the fracturing fluid in each area, and the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, and the average concentration of the breaker in each area are respectively calculated according to the time series by using the function , and To express, is a time point, and the time period is defined as , Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration in the region near the injection point is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration at the boundary of the region, Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration in the area, , is a positive integer; The permeability of each area and the viscosity of the fracturing fluid during the fracturing fluid injection process are calibrated as and , Indicates the first The permeability of the area, Indicates the first The viscosity of the fracturing fluid in each area; Calculate the diffusion equilibrium coefficient of each area. The specific calculation formula is as follows:

[0010] In the formula, For the The diffusion equilibrium coefficient of a region.

[0011] Preferably, the logic for obtaining the diffusion response index of each region is as follows: The response adjustment information in the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process is extracted, specifically including the injection pressure change rate in each area at different times during a period of time during the fracturing fluid injection process, the average concentration change rate of the breaker in each area, and the average flow rate change rate of the breaker in each area, and they are calibrated as , and , Indicates that during the injection of fracturing fluid, Moment The injection pressure change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average flow velocity change rate in the area is , , and All are positive integers; Calculate the diffusion response index of each area. The specific calculation formula is as follows:

[0012] In the formula, For the The diffusion response index of a region.

[0013] Preferably, a diffusion uniformity evaluation model is constructed based on the generated diffusion equilibrium coefficient and diffusion response index of each region to generate the diffusion uniformity coefficient of each region, specifically comprising the following steps: The diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time are collected and calibrated as , and , Indicates the diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time. , is a positive integer, and the data collected in the past period of time forms a historical data set; The multivariate regression model is selected as the diffusion uniformity evaluation model, and the historical data set is used for training to determine the value of the regression coefficient according to the formula: In the formula, , and is the regression coefficient; By minimizing the error between the predicted value and the actual value, the regression coefficient is optimized and finally determined. , and The value of Using the final regression coefficient, the diffusion uniformity evaluation model constructed is input with the diffusion equilibrium coefficient of each area generated in real time. and diffusion response index , real-time generation of diffusion uniformity coefficients for each region .

[0014] Preferably, the diffusion uniformity coefficient of each region generated is The pre-set diffusion uniformity coefficient threshold range The comparison is carried out, and the diffusion uniformity of the gel breaker in each area during the fracturing fluid injection process is evaluated according to the comparison results. According to the evaluation results, each area is divided into a high diffusion area, a uniform diffusion area and a low diffusion area. The specific comparison analysis and division are as follows: like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is low, then the area is classified as a low diffusion area; like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is normal, then the area is divided into a uniform diffusion area; like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in this area is high, then this area is divided into a high diffusion area.

[0015] Preferably, according to the division results of each area in the heterogeneous formation, corresponding measures of adjusting the injection amount of the breaker, optimizing the injection pressure and adjusting the formula of the breaker are respectively taken, specifically: For the areas classified as low diffusion areas, the specific measures taken are: increase the injection amount of the breaker and increase the injection pressure to increase the diffusion rate of the breaker in the area and maintain the original formula of the breaker; For the area divided into uniform diffusion areas, the specific measures taken are: maintain the current injection volume and injection pressure of the breaker and continue to monitor; For the areas classified as high diffusion areas, the specific measures taken are: reducing the injection amount of the breaker and lowering the injection pressure to reduce the diffusion rate in the area, and adjusting the breaker formula to enhance its stability in the area.

[0016] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. In practical applications, the present invention realizes accurate analysis and control of the diffusion process of the gel breaker in the heterogeneous formation, thereby effectively solving the problem of uneven diffusion of the gel breaker caused by changes in the permeability and porosity of the formation. By dividing the heterogeneous formation into regions and combining the real-time data acquisition and analysis method, the dynamic information of each region can be obtained in time during the injection of the gel breaker. The diffusion state of each region is evaluated using the diffusion equilibrium coefficient and the diffusion response index, and the diffusion uniformity is modeled and optimized through a multivariate regression model, so that the diffusion behavior of the gel breaker can be dynamically adjusted. This method ensures that during the fracturing operation, the phenomenon of the gel breaker diffusing too quickly in the high permeability area or being retained in the low permeability area can be quickly discovered and corrected, so that the effect of the gel breaker is more balanced.

[0017] 2. The present invention can automatically adjust the injection strategy of the breaker according to different diffusion states, including injection volume, pressure regulation and formula optimization, through real-time monitoring and analysis of the diffusion process of the breaker. It can adapt to the dynamic changes of formation conditions without frequent manual intervention, reduce the complexity of operation, and improve the diffusion effect of the breaker in various regions. In addition, the combination of real-time analysis and regular model update ensures that the diffusion uniformity assessment model is always optimized based on the latest data, with strong adaptability, so that it can maintain high accuracy in different oil fields and geological environments, and improve the reliability of fracturing operations.

[0018] 3. The present invention also significantly improves oil and gas recovery and operating efficiency. Through precise diffusion analysis and optimization, it can ensure that the breaker can fully exert its viscosity regulating effect in the formation, thereby improving the morphology and expansion effect of the cracks, so that more oil and gas can enter the wellbore through the cracks. At the same time, through targeted adjustments to areas with different diffusion degrees, the waste of breaker caused by uneven diffusion is reduced, and resource utilization is optimized. This not only reduces operating costs, but also reduces the impact on the environment, improves economic benefits and sustainability, and is an important innovative method to improve oil and gas extraction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0020] Figure 1 The present invention is a schematic flow diagram of a method for analyzing the stability of a liquid breaker for fracturing. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0022] The present invention provides Figure 1 A stability analysis method for a liquid breaker for fracturing is shown, which specifically includes the following steps: When fracturing in heterogeneous formations, the heterogeneous formations are evenly divided into several independent areas according to the permeability, porosity and lithology changes of the heterogeneous formations, and a real-time analysis framework for diffusion uniformity evaluation is established based on the diffusion and flow of the breaker during the injection process in each area; When fracturing operations are carried out in heterogeneous formations, the heterogeneous formations are divided into several independent areas according to the changes in the permeability, porosity and lithology of the heterogeneous formations. This can be achieved through formation imaging technology, logging data analysis and 3D geological modeling software. Specifically, logging tools (such as nuclear magnetic resonance logging and acoustic logging) are first used to obtain data such as permeability, porosity and lithology. These data are input into the 3D geological modeling software to construct a 3D model of the formation. Then, the software uses clustering algorithms (such as K-means clustering) or regional partitioning algorithms (such as Voronoi diagrams) for data analysis, and divides areas with similar permeability and porosity characteristics into an independent unit, thereby forming several divided areas. In this way, complex heterogeneous formations can be refined and processed, laying the foundation for subsequent dynamic analysis.

[0023] According to the diffusion and flow of the breaker during the injection process in each area, a real-time analysis framework for diffusion uniformity evaluation is established, which can be achieved through a real-time data acquisition system and fluid dynamics simulation software. The specific operation is to deploy pressure sensors, flow rate sensors and breaker concentration monitoring equipment in each independent area to collect dynamic information of the breaker during the injection process, such as pressure changes, flow rate and concentration data, in real time, and transmit the data to the analysis software through a wireless transmission system. The fluid dynamics simulation software performs CFD simulation based on the Navier-Stokes equation, and simulates the diffusion behavior of the breaker in each area in combination with real-time data. Then, a diffusion uniformity evaluation model is constructed using multivariate regression analysis and machine learning algorithms to perform real-time analysis of the diffusion rate and flow trend of the breaker, and generate a diffusion evaluation report to optimize the diffusion effect.

[0024] The reason for doing this is to better solve the problem of uneven diffusion of breakers in heterogeneous formations. Due to the large differences in permeability and porosity of the formation, the diffusion behavior of the breakers in different areas is significantly affected, which can easily lead to excessive diffusion of breakers in high permeability areas, while retention may occur in low permeability areas, thus affecting the overall fluidity and effect of the fracturing fluid. By dividing the formation into multiple independent analysis areas, the diffusion behavior of the breakers in each area can be finely monitored, allowing us to make precise injection adjustments for each area. Establishing a real-time analysis framework can dynamically monitor the diffusion state of the breakers and adjust the injection strategy in time according to real-time data, thereby improving the uniformity of the distribution of breakers in various areas, optimizing crack formation and oil and gas flow paths, and improving the fracturing effect and oil and gas recovery rate. Doing so can not only overcome the problem that the existing technology cannot accurately predict the distribution of breakers, but also significantly improve the efficiency and effectiveness of the operation.

[0025] Real-time acquisition of dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, and analysis after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each area respectively; In this embodiment, the injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process is obtained in real time, and analyzed after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each region respectively, which specifically includes the following steps: Real-time acquisition of injection process dynamic information of each area in the heterogeneous formation during fracturing fluid injection, and pre-processing after acquisition; Real-time acquisition of dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process can be achieved through the combination of sensor networks and data acquisition systems with cloud data platforms. Specifically, high-precision pressure sensors, flow rate sensors and concentration monitoring equipment are deployed in each independent area of ​​the heterogeneous formation. These sensors can monitor the injection pressure, flow rate and concentration changes of the fracturing fluid and debonding agent in real time. The sensor network transmits the collected data to the data acquisition system in real time through wired or wireless means, and uploads it to the cloud data platform. The cloud platform will perform preliminary verification and storage of the data to ensure that all information is complete and correct during the transmission process. At the same time, the data acquisition system supports multi-threaded data synchronization and remote access, which is convenient for real-time acquisition of dynamic information in each area, and stores this information in the background for subsequent analysis.

[0026] The purpose of preprocessing is to improve the quality of data and ensure the accuracy and reliability of the diffusion equilibrium coefficient and diffusion response index generated by subsequent analysis. The preprocessing steps mainly include data cleaning, denoising, data normalization and data integrity check. Specifically, data cleaning is first used to remove outliers and obviously erroneous data points that may be generated by sensors, such as sudden extreme values ​​or missing data caused by communication errors. Next, a filtering algorithm (such as Kalman filtering or low-pass filtering) is applied to denoise the data to eliminate high-frequency interference in the signal and make the data smoother and more stable. Then, data normalization is performed to convert the data collected by different sensors to the same scale to facilitate comparison and calculation in subsequent analysis. Finally, a data integrity check is performed to ensure that the data of each time period has been fully collected. If missing data is found, it is supplemented by interpolation. All these preprocessing processes can be implemented through the data analysis software platform to ensure that the evaluation parameters generated subsequently are more accurate.

[0027] Extracting diffusion dynamic information and response adjustment information from the preprocessed injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process; Extracting the diffusion dynamic information and response regulation information from the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process can be achieved by combining the feature extraction algorithm and the data classification model through the data analysis software platform. Specifically, the pre-processed data is first imported into the data analysis platform, and the platform uses the feature extraction algorithm (such as principal component analysis PCA or cluster analysis) to identify the parameters related to the diffusion characteristics (such as the change of breaker concentration, flow rate, permeability, etc.) from the dynamic information and classify them as diffusion dynamic information. Then, the classification model (such as support vector machine SVM or decision tree) is used to classify the data, identify the parameters related to the pressure change response and flow rate regulation (such as pressure fluctuation, flow rate change, etc.), and classify these data as response regulation information. In this way, the data analysis software can automatically classify and extract the parts related to the diffusion and response characteristics in the dynamic information, making the subsequent analysis more targeted and ensuring the accuracy and efficiency of the evaluation model. This method can effectively automate the data processing process, making the extraction process efficient and without manual intervention.

[0028] The diffusion dynamic information and response adjustment information in the extracted injection process dynamic information of each region are analyzed to generate the diffusion equilibrium coefficient and diffusion response index of each region respectively.

[0029] In this embodiment, the logic for obtaining the diffusion balance coefficient of each region is as follows: Extract the diffusion dynamic information from the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, specifically including the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, the average concentration of the breaker in each area, and the permeability and viscosity of the fracturing fluid in each area, and the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, and the average concentration of the breaker in each area are respectively calculated according to the time series by using the function , and To express, is a time point, and the time period is defined as , Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration in the region near the injection point is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration at the boundary of the region, Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration in the area, , is a positive integer; The pre-processed diffusion dynamic information of each area in the heterogeneous formation during the fracturing fluid injection process is extracted, including the actual concentration of the breaker near the injection wellbore in each area, the actual concentration of the breaker at the boundary of each area, the average concentration of the breaker in each area, the permeability of each area and the viscosity of the fracturing fluid. The acquisition of these quantitative data mainly depends on the synergy of sensor networks, logging technology and data analysis software platforms. First, by deploying concentration monitoring sensors near the injection wellbore and at the boundaries of each area, the concentration changes of the breaker at different times during the injection process are recorded in real time. These sensors can detect the actual concentration data of the breaker during the flow process. The actual concentration data near the injection wellbore reflects the concentration state of the breaker when it just enters the formation, while the actual concentration at the boundary of the area shows the diffusion state of the breaker when it reaches the outer edge of the area when flowing through the formation. The data collected by the sensor is sent to the data analysis software platform through a wireless transmission system. The platform can calculate the average concentration of the breaker in each area through the time-weighted average algorithm based on these time-series concentration data. For permeability data, logging technology (such as nuclear magnetic resonance logging and sonic logging) is used to collect detailed data on the pore structure of the formation, and the spatial distribution of permeability is analyzed through the formation model in the data platform to obtain the permeability values ​​of each area. The viscosity of the fracturing fluid is obtained through laboratory measurements and real-time correction data of formation temperature and pressure changes. The viscosity value is automatically updated on the data platform by combining the temperature and pressure change model. All of these data are finally integrated and processed in the data analysis software to generate diffusion dynamic information for subsequent calculations, ensuring that the diffusion behavior of the breaker in different areas and its influencing factors can be accurately reflected. In this way, not only the real-time collection and dynamic update of data are realized, but also efficient analysis and prediction can be carried out according to the data changes at different time points.

[0030] The permeability of each area and the viscosity of the fracturing fluid during the fracturing fluid injection process are calibrated as and , Indicates the first The permeability of the area, Indicates the first The viscosity of the fracturing fluid in each area; Calculate the diffusion equilibrium coefficient of each area. The specific calculation formula is as follows:

[0031] In the formula, For the The diffusion equilibrium coefficient of a region.

[0032] This formula calculates the diffusion equilibrium coefficient of each region. The purpose of this is to quantify the diffusion uniformity of the breaker in a specific area, and to evaluate it by combining the time variation and various influencing factors. Specifically, the integral form is used in the formula to The diffusion changes of the breaker at different time points are comprehensively analyzed. The time trend can be accumulated through integration to capture the overall dynamics of concentration changes over time. It is used to normalize the time interval, converting the integral result into the average diffusion characteristic within the time period, so as to avoid the distortion of the result caused by different time lengths. It represents the rate of change of the concentration of the breaker near the injection point over time, reflecting the initial diffusion rate of the breaker during the injection process. It indicates the rate of change of the concentration of the breaker at the boundary of the region over time, reflecting the rate at which the breaker diffuses to the outer edge in the region. The relative change of these two parts indicates whether the process from injection to diffusion of the breaker in the region is balanced. By comparing the internal concentration change with the overall diffusion trend, we can evaluate the difference between the internal concentration change and the overall diffusion trend. If the difference between the two change rates is large, it means that the diffusion of the breaker in the area is uneven. represents the permeability, and Indicates viscosity, its ratio This is to correct the physical properties of the diffusion process, because the breaker is easier to diffuse in the area with higher permeability, while the higher viscosity will inhibit the flow of the breaker. This correction part ensures that the results under different permeability and viscosity conditions are comparable. The overall calculation formula combines these influencing factors to obtain the diffusion equilibrium of the breaker in each time period, and finally generates the diffusion equilibrium coefficient of the area. , which is used to evaluate the diffusion uniformity of the breaker, thus providing a scientific basis for the optimization of fracturing operations.

[0033] No. Diffusion equilibrium coefficient of the region The size of directly reflects the diffusion uniformity of the breaker in the area, and is then used to evaluate the diffusion uniformity of the breaker in each area during the fracturing fluid injection process. When the value is large, it means that the concentration change of the breaker from the injection point to the regional boundary is relatively balanced, that is, the breaker can diffuse relatively evenly in the entire region without obvious retention or over-diffusion; this means that the diffusion state of the region is good and the role of the breaker can be fully exerted. When the value is small, it indicates that the concentration change rate of the breaker in the area is uneven. The concentration may be too high in the area close to the injection point and low at the boundary, or the breaker diffuses too fast or too slow in some local areas, resulting in uneven diffusion. This uneven diffusion will affect the overall fluidity and effect of the fracturing fluid in the formation, making the fracturing effect in some areas poor. Therefore, The value of can be used as a key indicator to measure the uniformity of breaker diffusion in each area, which helps to identify areas where the breaker injection strategy needs to be adjusted, thereby optimizing the overall fracturing operation effect.

[0034] In this embodiment, the logic for obtaining the diffusion response index of each region is as follows: The response adjustment information in the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process is extracted, specifically including the injection pressure change rate in each area at different times during a period of time during the fracturing fluid injection process, the average concentration change rate of the breaker in each area, and the average flow rate change rate of the breaker in each area, and they are calibrated as , and , Indicates that during the injection of fracturing fluid, Moment The injection pressure change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average flow velocity change rate in the area is , , and are all positive integers; Extract the response adjustment information of each area in the heterogeneous formation during the injection of fracturing fluid after preprocessing, including the injection pressure change rate, the average concentration change rate of the breaker and the average flow rate change rate of the breaker in each area at different times within a period of time. First, the injection pressure change rate is obtained by high-precision pressure sensors deployed in each area. These sensors monitor the pressure data of fracturing fluid and breaker in real time during the injection process. The data acquisition system records the pressure values ​​at different times, and the data analysis software performs time series analysis on these pressure data to calculate the pressure change rate in each time period, reflecting the pressure fluctuation caused by the change of formation conditions during the injection of fracturing fluid. The pressure change rate data helps to understand how the diffusion and flow behavior of the breaker are driven by pressure during the injection of fracturing fluid. Secondly, the average concentration change rate of the breaker in each area is obtained by concentration monitoring equipment, which is deployed at key locations in each area to measure the concentration values ​​of the breaker at different time points in real time. By inputting these concentration values ​​into the data analysis software and applying statistical methods such as moving average method or difference method, the concentration change rate of each area in different time periods can be calculated. The concentration change rate describes the trend of the concentration of the breaker in the area over time, and is a key indicator for evaluating the diffusion rate of the breaker. Finally, the average flow rate change rate of the breaker is calculated using the real-time flow rate data collected by the flow sensors, which record the flow rate of the breaker at different times in the area. The data analysis software calculates the rate of change of the flow rate in different time periods by performing time series analysis on the flow rate data, reflecting the change of the flow state of the breaker in the area over time. The flow rate change rate can help evaluate the adaptability of the flow behavior of the breaker when it is affected by pressure and geological resistance in the formation. These data are automatically processed by the data acquisition system and the analysis platform to form complete response adjustment information, providing an accurate basis for the subsequent calculation of the diffusion response index. In this way, the dynamic information of each area can be obtained in real time and accurately, ensuring that the diffusion behavior of the breaker in complex formations is fully evaluated.

[0035] Calculate the diffusion response index of each area. The specific calculation formula is as follows:

[0036] In the formula, For the The diffusion response index of a region.

[0037] This formula is used to calculate the Diffusion response index of the region The purpose of this formula is to quantify the dynamic response of the breaker to pressure fluctuations and flow rate changes during injection, so as to evaluate the adaptability of the breaker in this area. The summation symbol used in the formula is to accumulate the data at each time point in the time period, indicating the response changes of the breaker at different time points. This summation process can capture all the changes in pressure, concentration and flow rate in the time interval, and provide an overall response characteristic. Indicates the time period The injection pressure change rate reflects the driving force on the breaker. It is The average concentration change rate of the breaker in the region indicates the change of the concentration of the breaker over time during the period. By multiplying these two parameters, the concentration response intensity of the breaker under pressure can be evaluated. Represents the average velocity change rate of the breaker in this area, which is used to adjust the concentration response result. A higher velocity change rate means that the fluid flow has a more significant effect on the diffusion of the breaker, so by dividing the concentration response intensity by the velocity change rate, the breaker's response ability under the flow state can be more accurately evaluated. The final normalization factor It is used to calculate the average response index within a time period, so that the calculation results of different time periods are consistent and comparable. This calculation method can fully reflect the adaptability of the breaker to different external conditions during the injection process, thus providing a scientific basis for optimizing the injection strategy.

[0038] No. Diffusion response index of the region The size of directly reflects the dynamic adaptability of the breaker to pressure changes and flow rate changes in this area, and is therefore used to assess the degree of uneven diffusion of the breaker in this area. When the value is large, it means that the breaker shows a strong concentration response ability when the pressure fluctuates, and can better adapt to the change of flow rate, indicating that the diffusion of the breaker in this area is more balanced and can quickly adjust its diffusion path to adapt to the dynamically changing environment. When the value is small, it indicates that the breaker has a weak response and poor adaptability to changes in pressure and flow rate, which may lead to uneven diffusion of the breaker in the area, prone to local retention or excessive diffusion, thus affecting the overall fluidity and effect of the fracturing fluid. The value can effectively judge the diffusion equilibrium state of the breaker in different formation areas and provide an important reference for optimizing the injection strategy.

[0039] A diffusion uniformity evaluation model is constructed for the generated diffusion equilibrium coefficient and diffusion response index of each region, and the diffusion uniformity coefficient of each region is generated. After the generation, the diffusion uniformity of the breaker in each region during the fracturing fluid injection process is evaluated, and each region is divided into a high diffusion region, a uniform diffusion region and a low diffusion region according to the evaluation results; In this embodiment, a diffusion uniformity evaluation model is constructed based on the generated diffusion equilibrium coefficient and diffusion response index of each region to generate the diffusion uniformity coefficient of each region, which specifically includes the following steps: The diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time are collected and calibrated as , and , Indicates the diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time. , is a positive integer, and the data collected in the past period of time forms a historical data set; The diffusion equilibrium coefficient, diffusion response index and corresponding diffusion uniformity coefficient of several regions generated in the past period of time can be collected by combining the data acquisition system, the database management platform and the data analysis software platform. Specifically, first, during the fracturing operation, the diffusion equilibrium coefficient and diffusion response index of each region are monitored in real time by the sensor network deployed on site, and are automatically calculated and generated by the data acquisition system. These parameters generated in real time are uploaded to the cloud or local server through the wireless data transmission system. The data management platform is responsible for storing these data in time series and establishing labels in the database to mark the diffusion coefficients of each region in each time period. Then, the data analysis software platform regularly accesses the database, extracts all the stored diffusion equilibrium coefficients, diffusion response indexes and their corresponding diffusion uniformity coefficients in the past period of time, and archives them according to the specified time period and region. In this way, the continuity and integrity of the data can be ensured, and the subsequent data analysis and model training process can be facilitated, providing a stable and accurate data basis.

[0040] limited The value of is a positive integer greater than or equal to 3 to ensure that when constructing the diffusion uniformity evaluation model, sufficient data samples can be obtained to accurately calculate the regression coefficient. , and The regression model involves three regression coefficients, and each data sample provides an equation, so at least 3 different sample data are required (i.e. ), in order to form a system of three equations, so as to solve the specific values ​​of the three regression coefficients. This not only ensures that the system of equations has a solution, but also provides sufficient input data for model training, so that the regression coefficient can better reflect the influence of the diffusion equilibrium coefficient and the diffusion response index on the diffusion uniformity coefficient. In addition, when When the value of is larger, it means that more historical data is used for model training, which can improve the stability and prediction accuracy of the regression model and make the model more robust and reliable during application.

[0041] In the formula, , and is the regression coefficient; The multiple regression model is a statistical analysis method used to establish a linear relationship between a dependent variable and multiple independent variables. In this model, the dependent variable is the result we want to predict or explain, and the independent variable is the factor that affects the change of the dependent variable. The multiple regression model is selected in the diffusion uniformity assessment because the diffusion uniformity coefficient is affected by multiple factors, including the diffusion equilibrium coefficient and the diffusion response index. Through the multiple regression model, the influence of these two independent variables on the diffusion uniformity coefficient can be considered at the same time, so as to more accurately predict or explain its changes. The three regression coefficients in the model , and They have different meanings: is a constant term, indicating that and All are zero hours Basic level of yes The regression coefficient of represents the effect of a unit increase in the diffusion equilibrium coefficient on the diffusion uniformity coefficient when other conditions remain unchanged; yes The regression coefficients represent the effect of each unit increase in the diffusion response index on the diffusion uniformity coefficient. By training the model and determining the optimal values ​​of these three regression coefficients, we can better describe and How to jointly influence , thus providing a scientific basis for the evaluation of diffusion uniformity in actual operations.

[0042] By minimizing the error between the predicted value and the actual value, the regression coefficient is optimized and finally determined. , and The value of The process of optimizing the regression coefficient is to ensure that the multivariate regression model can accurately reflect the actual impact of the diffusion equilibrium coefficient and the diffusion response index on the diffusion uniformity coefficient, thereby improving the predictive ability and accuracy of the model. Specifically, by minimizing the error between the predicted value and the actual value, the regression coefficient value that best fits the historical data can be found, so that the model can make more accurate predictions when applied in the future. This process is usually implemented using the Ordinary Least Squares (OLS), which is a commonly used method in regression analysis. Historical data is imported into the model through data analysis software (such as R, Python's scikit-learn library or professional statistical software such as SPSS). The software automatically calculates the sum of squared errors between the predicted value and the actual observed value of each data point, and continuously adjusts the regression coefficients. , and The value of is used to find the coefficient combination that minimizes the sum of squared errors. This process is automatically iterated until the error reaches the minimum value, and the final regression coefficient value is determined. This method ensures that the model performs best on the training data and can more accurately predict the diffusion uniformity coefficient in future applications.

[0043] Using the final regression coefficient, the diffusion uniformity evaluation model constructed is input with the diffusion equilibrium coefficient of each area generated in real time. and diffusion response index , real-time generation of diffusion uniformity coefficients for each region .

[0044] In this embodiment, the diffusion uniformity coefficient of each region is generated The pre-set diffusion uniformity coefficient threshold range The comparison is carried out, and the diffusion uniformity of the gel breaker in each area during the fracturing fluid injection process is evaluated according to the comparison results. According to the evaluation results, each area is divided into a high diffusion area, a uniform diffusion area and a low diffusion area. The specific comparison analysis and division are as follows: like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is low, then the area is classified as a low diffusion area; This means that the diffusion of the breaker is relatively uneven in this area, and the breaker may be retained in some locations and difficult to penetrate in other areas. Due to insufficient diffusion, the breaker cannot fully play its role in this area, which may lead to unsatisfactory viscosity adjustment of the fracturing fluid in this area, thereby affecting the formation and expansion of cracks. This unevenness will cause some cracks in the formation to fail to open effectively, thereby reducing the permeability of oil and gas, and ultimately leading to a decrease in oil and gas recovery, increasing the difficulty and cost of subsequent operations.

[0045] like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is normal, then the area is divided into a uniform diffusion area; In this case, the diffusion of the breaker in the area is relatively balanced, with moderate concentration and flow rate, which can well adapt to the changes in the permeability of the formation. This means that the effect of the breaker in this area has reached the expected level, and it can effectively adjust the viscosity of the fracturing fluid and ensure uniform expansion of the cracks. This can make the fracturing operation more stable and efficient, and the crack morphology more regular, thereby improving the fluidity and output efficiency of oil and gas, and reducing the uncertainty and adjustment needs during the operation.

[0046] like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in this area is high, then this area is divided into a high diffusion area.

[0047] This situation means that the breaker diffuses too fast in the area, which may cause the breaker concentration in the local area to be too low and excessive diffusion. Although the distribution of the breaker is relatively uniform in space, this high diffusivity may cause the breaker to be exhausted prematurely in some areas, thus affecting its continuous effect during the entire injection process. Such a situation will lead to insufficient viscosity adjustment of the fracturing fluid in local areas, which may cause excessive or uneven expansion of cracks, increase operational risks, and may lead to the need to adjust the overall injection strategy to avoid waste of breaker and reduced operational efficiency.

[0048] Pre-set diffusion uniformity coefficient threshold range It can be determined through a combination of historical data analysis, machine learning model training, and simulation experimental results. First, a large amount of historical data from past fracturing operations is analyzed using data analysis software (such as Python's pandas, R language, etc.) to extract the statistical characteristics of the diffusion uniformity coefficient of each region under different formation conditions, including the mean, median, and standard deviation. Based on these statistical characteristics, a preliminary setting can be made. and The range of values ​​is usually the 25th and 75th percentiles of the data distribution as the preliminary intervals. Subsequently, simulation experiments and numerical simulation software (such as COMSOL, ANSYS) are used to simulate the diffusion behavior of the gel breaker under different formation conditions, and the rationality of these thresholds is adjusted and verified to ensure that they can accurately reflect the diffusion state of the gel breaker in actual operations. Finally, machine learning algorithms (such as linear regression or decision trees) are used to train these data, and the threshold range that can best predict the diffusion effect is found through model optimization. The model will automatically adjust according to the input formation characteristics and injection parameters and The value of can make the set threshold range adapt to different geological conditions and ensure the best diffusion effect of the breaker in each area. In this way, the threshold range of the diffusion uniformity coefficient can be accurately set, making it more scientific and adaptable in practical applications.

[0049] According to the division results of each area in the heterogeneous formation, corresponding measures are taken to adjust the injection amount of the breaker, optimize the injection pressure and adjust the formula of the breaker; In this embodiment, according to the division results of each area in the heterogeneous formation, corresponding measures of adjusting the injection amount of the breaker, optimizing the injection pressure and adjusting the formula of the breaker are taken respectively, specifically: For the areas classified as low diffusion areas, the specific measures taken are: increase the injection amount of the breaker and increase the injection pressure to increase the diffusion rate of the breaker in the area and maintain the original formula of the breaker; Measures for low diffusion areas: Increasing the injection volume of the breaker and raising the injection pressure can be achieved through the on-site monitoring system and the automated control platform. First, the monitoring system collects the concentration, pressure and flow rate data of the breaker in the area in real time, and analyzes the lack of diffusion uniformity in the area. Based on this information, the data analysis software can calculate the appropriate injection volume and pressure increase, and automatically send adjustment instructions to the injection equipment. Through the automated control platform, adjust the flow parameters of the injection pump, increase the injection volume of the breaker, and adjust the output pressure of the booster pump to increase the injection pressure. This is done to speed up the diffusion rate of the breaker in the low diffusion area so that it can be more evenly distributed in the area, thereby improving the overall adjustment effect of the fracturing fluid and ensuring that the cracks are fully expanded in the low permeability area.

[0050] For the area divided into uniform diffusion areas, the specific measures taken are: maintain the current injection volume and injection pressure of the breaker and continue to monitor; Measures for uniform diffusion areas: Maintain the current injection volume and injection pressure of the gel breaker, and continue to monitor, which can be achieved through the data acquisition and real-time monitoring system. The data acquisition system will continuously record the concentration of the gel breaker, injection pressure and flow rate changes, and continuously evaluate these data through data analysis software to ensure that they are within the preset target range. The software can automatically set warning thresholds. When the monitoring data exceeds these thresholds, it will automatically issue reminders or suggest adjustments so that operators can intervene in time. Maintaining the current injection parameters without adjustment is because the diffusion state of the area has reached the ideal state. Maintaining the existing injection parameters can maintain the uniform diffusion effect of the gel breaker in the area, thereby ensuring the stability and continuity of the fracturing process and avoiding unnecessary risks caused by excessive adjustments.

[0051] For the areas classified as high diffusion areas, the specific measures taken are: reducing the injection amount of the breaker and lowering the injection pressure to reduce the diffusion rate in the area, and adjusting the breaker formula to enhance its stability in the area.

[0052] Measures for high diffusion areas: reducing the injection volume of breaker, lowering the injection pressure, and adjusting the breaker formula can be achieved through an automated formula management system and an injection control system. First, the concentration and diffusion rate of the area are evaluated through data analysis software to determine the specific reasons why the breaker diffuses too quickly in the area. Then, the injection control system automatically adjusts the flow of the injection pump according to the analysis results, reduces the injection volume of the breaker, and gradually reduces the injection pressure through the pressure reducing device to inhibit the excessive diffusion of the breaker. At the same time, the formula management system will automatically optimize the formula of the breaker according to the changes in formation conditions and the analysis results of the diffusion rate, and adjust the proportion of the auxiliary ingredients therein to improve the stability of the breaker in the area. The purpose of this is to avoid excessive dilution and waste of the breaker in the high diffusion area, thereby ensuring the concentration and effect of the breaker in other areas, while optimizing the cost of using the breaker and improving the efficiency and effect of the overall fracturing operation.

[0053] Continuously monitor the dynamic information of the injection process in each area, dynamically adjust the breaker injection strategy and parameter settings based on real-time analysis results, and regularly update the diffusion uniformity assessment model.

[0054] To achieve "continuously monitor the dynamic information of the injection process in each area, dynamically adjust the injection strategy and parameter settings of the gel breaker according to the real-time analysis results, and regularly update the diffusion uniformity assessment model", this can be accomplished through the collaborative work of the data acquisition system, real-time analysis platform, automated control system and model optimization platform.

[0055] First, the sensor network on site will monitor the dynamic information of each area in real time, including key parameters such as breaker concentration, injection pressure, flow rate and formation temperature. These data are uploaded to the cloud data platform or local server through the wireless transmission system for storage and preliminary processing. The data acquisition system will filter and standardize the information to ensure the accuracy and consistency of the data. The goal of continuous monitoring is to obtain high-frequency real-time data, so that the changing trends of various areas during the fracturing process can be reflected immediately, especially when the formation pressure fluctuates or the diffusion of the breaker is abnormal, so that the abnormal signal can be captured at the first time.

[0056] Next, the data analysis platform will process the real-time collected data and apply machine learning models or preset analysis algorithms to quickly evaluate the diffusion status of each area. Based on these real-time analysis results, the platform will determine whether the current diffusion uniformity of each area is within the expected range. If the diffusion speed in a certain area is too fast or too slow, the system will automatically generate adjustment suggestions and directly issue commands to the injection equipment through the automated control system to adjust the injection volume and injection pressure of the breaker in that area or change the injection rate. This dynamic adjustment mechanism ensures that the diffusion of the breaker can maintain the best state under different geological conditions, thereby avoiding waste of breaker or poor fracturing effect caused by uneven diffusion.

[0057] In addition, in order to ensure that the analysis model can adapt to changes in formation conditions, the data analysis platform will regularly use the collected historical data to update the diffusion uniformity assessment model. The historical data will be input into the model training module, and the model parameters will be optimized through machine learning algorithms to improve the accuracy of the model in predicting diffusion uniformity. The updated model will automatically replace the old model and be used in real-time analysis to ensure that the model's predictive ability is always at a high level. The purpose of this is to ensure that the model can adapt to the dynamic changes in geological conditions, make the analysis results more accurate, and ultimately provide reliable data support for the optimization of the breaker injection strategy.

[0058] This intelligent and automated management method can monitor and optimize the entire process of breaker injection, reduce errors caused by manual adjustments, and improve the efficiency and success rate of fracturing operations. The combination of real-time monitoring and dynamic adjustment ensures that the effect of breaker use can be continuously optimized according to the formation conditions, ultimately improving the economic benefits and production safety of oil and gas production.

[0059] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0060] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0061] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0062] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0063] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0064] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0065] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0066] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for analyzing the stability of a liquid breaker for fracturing, characterized in that: The specific steps include: When fracturing in heterogeneous formations, the heterogeneous formations are evenly divided into several independent areas according to the permeability, porosity and lithology changes of the heterogeneous formations, and a real-time analysis framework for diffusion uniformity evaluation is established based on the diffusion and flow of the breaker during the injection process in each area; Real-time acquisition of dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, and analysis after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each area respectively; A diffusion uniformity evaluation model is constructed for the generated diffusion equilibrium coefficient and diffusion response index of each region, and the diffusion uniformity coefficient of each region is generated. After the generation, the diffusion uniformity of the breaker in each region during the fracturing fluid injection process is evaluated, and each region is divided into a high diffusion region, a uniform diffusion region and a low diffusion region according to the evaluation results; According to the division results of each area in the heterogeneous formation, corresponding measures are taken to adjust the injection amount of the breaker, optimize the injection pressure and adjust the formula of the breaker; Continuously monitor the dynamic information of the injection process in each area, dynamically adjust the breaker injection strategy and parameter settings based on real-time analysis results, and regularly update the diffusion uniformity assessment model.

2. The stability analysis method of a liquid breaker for fracturing according to claim 1, characterized in that: The dynamic information of the injection process of each area in the heterogeneous formation during the fracturing fluid injection process is obtained in real time, and analyzed after acquisition to generate the diffusion equilibrium coefficient and diffusion response index of each area respectively, which specifically includes the following steps: Real-time acquisition of injection process dynamic information of each area in the heterogeneous formation during fracturing fluid injection, and pre-processing after acquisition; Extracting diffusion dynamic information and response adjustment information from the preprocessed injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process; The diffusion dynamic information and response adjustment information in the extracted injection process dynamic information of each region are analyzed to generate the diffusion equilibrium coefficient and diffusion response index of each region respectively.

3. The stability analysis method of a liquid breaker for fracturing according to claim 2, characterized in that: The logic for obtaining the diffusion balance coefficient of each region is as follows: Extract the diffusion dynamic information from the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process, specifically including the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, the average concentration of the breaker in each area, and the permeability and viscosity of the fracturing fluid in each area, and the actual concentration of the breaker near the injection point in each area at different times during a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each area, and the average concentration of the breaker in each area are respectively calculated according to the time series by using the function , and To express, is a time point, and the time period is defined as , Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration in the region near the injection point is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The actual concentration at the boundary of the region, Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration in the area, , is a positive integer; The permeability of each area and the viscosity of the fracturing fluid during the fracturing fluid injection process are calibrated as and , Indicates the first The permeability of the area, Indicates the first The viscosity of the fracturing fluid in each area; Calculate the diffusion equilibrium coefficient of each area. The specific calculation formula is as follows: In the formula, For the The diffusion equilibrium coefficient of a region.

4. The stability analysis method of a liquid breaker for fracturing according to claim 3, characterized in that: The acquisition logic of the diffusion response index of each region is as follows: The response adjustment information in the pre-processed dynamic information of the injection process in each area of ​​the heterogeneous formation during the fracturing fluid injection process is extracted, specifically including the injection pressure change rate in each area at different times during a period of time during the fracturing fluid injection process, the average concentration change rate of the breaker in each area, and the average flow rate change rate of the breaker in each area, and they are calibrated as , and , Indicates that during the injection of fracturing fluid, Moment The injection pressure change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average concentration change rate in the region is Indicates that during the injection of fracturing fluid, At the moment the gel breaker The average flow velocity change rate in the area is , , and All are positive integers; Calculate the diffusion response index of each area. The specific calculation formula is as follows: In the formula, For the The diffusion response index of a region.

5. The stability analysis method of a liquid breaker for fracturing according to claim 4, characterized in that: A diffusion uniformity evaluation model is constructed based on the generated diffusion equilibrium coefficient and diffusion response index of each region to generate the diffusion uniformity coefficient of each region, which specifically includes the following steps: The diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time are collected and calibrated as , and , Indicates the diffusion equilibrium coefficients, diffusion response indexes and corresponding diffusion uniformity coefficients of several regions generated in the past period of time. , is a positive integer, and the data collected in the past period of time forms a historical data set; The multivariate regression model is selected as the diffusion uniformity evaluation model, and the historical data set is used for training to determine the value of the regression coefficient according to the formula: In the formula, , and is the regression coefficient; By minimizing the error between the predicted value and the actual value, the regression coefficient is optimized and finally determined. , and The value of Using the final regression coefficient, the diffusion uniformity evaluation model constructed is input with the diffusion equilibrium coefficient of each area generated in real time. and diffusion response index , real-time generation of diffusion uniformity coefficients for each region .

6. The stability analysis method of a liquid breaker for fracturing according to claim 5, characterized in that: The diffusion uniformity coefficient of each region generated The pre-set diffusion uniformity coefficient threshold range The comparison is carried out, and the diffusion uniformity of the gel breaker in each area during the fracturing fluid injection process is evaluated according to the comparison results. According to the evaluation results, each area is divided into a high diffusion area, a uniform diffusion area and a low diffusion area. The specific comparison analysis and division are as follows: like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is low, then the area is classified as a low diffusion area; like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in the area is normal, then the area is divided into a uniform diffusion area; like , during the fracturing fluid injection process, if the diffusion uniformity of the gel breaker in this area is high, then this area is divided into a high diffusion area.

7. The stability analysis method of a liquid breaker for fracturing according to claim 6, characterized in that: According to the division results of each area in the heterogeneous formation, corresponding measures are taken to adjust the injection amount of the breaker, optimize the injection pressure and adjust the formula of the breaker, specifically: For the areas classified as low diffusion areas, the specific measures taken are: increase the injection amount of the breaker and increase the injection pressure to increase the diffusion rate of the breaker in the area and maintain the original formula of the breaker; For the area divided into uniform diffusion areas, the specific measures taken are: maintain the current injection volume and injection pressure of the breaker and continue to monitor; For the areas classified as high diffusion areas, the specific measures taken are: reducing the injection amount of the breaker and lowering the injection pressure to reduce the diffusion rate in the area, and adjusting the breaker formula to enhance its stability in the area.

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