A method for analyzing the stability of a liquid breaker for fracturing

Abstract

The present invention discloses a method for analyzing the stability of a liquid breaker for fracturing, which relates to the technical field of analyzing the stability of a liquid breaker, and specifically includes the following steps: dynamically obtaining in real time the injection process dynamic information of each region in a heterogeneous formation during the injection of a fracturing fluid, and analyzing it after obtaining, respectively generating the diffusion equilibrium coefficient and the diffusion response index of each region; constructing a diffusion uniformity evaluation model for the generated diffusion equilibrium coefficient and diffusion response index of each region, generating the diffusion uniformity coefficient of each region, and analyzing it after generating, evaluating the diffusion uniformity degree of the breaker in each region during the injection of the fracturing fluid, and dividing each region into a high-diffusion region, a uniform-diffusion region, and a low-diffusion region according to the evaluation results. The present invention solves the problem of uneven diffusion of the breaker in a heterogeneous formation and realizes precise control and optimization of the diffusion process of the breaker.

Description

Technical Field

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

[0002] A liquid breaker is a chemical agent used in the process of oil and gas exploitation. Its main function is to reduce the viscosity of the fracturing fluid to promote its fluidity in the formation, thereby enhancing the fracturing effect. The liquid breaker for fracturing specifically refers to the breaker used in the process of hydraulic fracturing, which is usually composed of a high molecular polymer and other additives, aiming to effectively open the formation fractures and improve the permeability and recovery rate of oil and gas. Analyzing the stability of the liquid breaker for fracturing is crucial 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, stratifies or has other stability problems before or during use, it will directly affect the fracturing effect and the output of oil and gas, and thus lead to economic losses. Therefore, systematic stability analysis can provide important basis for selecting the appropriate breaker and optimizing the fracturing design to ensure the success and safety of the entire fracturing operation.

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

[0004] The existing technology has the following deficiencies:

[0005] When conducting fracturing operations in heterogeneous formations, there will be sharp changes in formation permeability and porosity. Due to these changes, during the injection process of the fracturing fluid, it will experience significant changes in flow velocity and direction, resulting in the phenomenon that the breaker diffuses too fast in the high-permeability area and accumulates in the low-permeability area. Due to the influence of the non-uniformity of formation resistance, the diffusion rate of the breaker cannot be kept consistent in these areas. Existing stability analysis techniques are usually only tested under homogeneous formation conditions and cannot accurately simulate the non-uniformity of the flow and diffusion of the breaker in such heterogeneous formations, which will lead to the inability to predict the distribution of the breaker in advance during actual operations. This unpredictable diffusion non-uniformity will cause an imbalance in the viscosity adjustment of the fracturing fluid in the formation, thereby affecting the shape and propagation effect of the fracture, resulting in the ineffective formation of fractures in some areas, ultimately leading to a decrease in oil and gas recovery rate, while increasing the operation cost and complexity.

[0006] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0007] The object of the present invention is to provide a method for analyzing the stability of a liquid breaker for fracturing to solve the problems in the above background art.

[0008] To achieve the above object, the present invention provides the following technical solution: A method for analyzing the stability of a liquid breaker for fracturing, specifically including the following steps:

[0009] When conducting fracturing operations in heterogeneous formations, according to the changes in permeability, porosity, and lithology of the heterogeneous formation, the heterogeneous formation is evenly divided into several independent regions, and a real-time analysis framework for evaluating diffusion uniformity is established based on the diffusion and flow conditions of the breaker during the injection process in each region.

[0010] Obtain in real time the dynamic information of the injection process in each region of the heterogeneous formation during the injection process of the fracturing fluid, and analyze it after obtaining, and generate the diffusion equilibrium coefficient and diffusion response index of each region respectively.

[0011] Construct a diffusion uniformity evaluation model for the diffusion equilibrium coefficient and diffusion response index of each generated region, generate the diffusion uniformity coefficient of each region, and analyze it after generating, evaluate the diffusion uniformity degree of the breaker in each region during the injection process of the fracturing fluid, and divide each region into a high-diffusion region, a uniform-diffusion region, and a low-diffusion region according to the evaluation results.

[0012] According to the division results of each region in the heterogeneous formation, corresponding measures for adjusting the injection amount of the breaker, optimizing the injection pressure, and adjusting the breaker formula are taken respectively.

[0013] Continuously monitor the dynamic information of the injection process in each area, and dynamically adjust the gel breaker injection strategy and parameter settings according to the real-time analysis results, and regularly update the diffusion uniformity evaluation model.

[0014] Preferably, the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection process is obtained in real time, and after being obtained, it is analyzed to generate the diffusion equilibrium coefficient and diffusion response index of each area respectively, specifically including the following steps:

[0015] Obtain the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection process in real time, and perform preprocessing after being obtained;

[0016] Extract the diffusion dynamic information and response adjustment information in the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection process after preprocessing;

[0017] Analyze the diffusion dynamic information and response adjustment information in the dynamic information of the injection process in each area extracted, and generate the diffusion equilibrium coefficient and diffusion response index of each area respectively.

[0018] Preferably, the acquisition logic of the diffusion equilibrium coefficient of each area is as follows:

[0019] Extract the diffusion dynamic information in the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection process after preprocessing, specifically including the actual concentration of the gel breaker near the injection point in each area at different times within a period of time during the fracturing fluid injection process, the actual concentration of the gel breaker at the boundary of each area, the average concentration of the gel breaker in each area, and the permeability of each area and the viscosity of the fracturing fluid, and use functions , and to represent the actual concentration of the gel breaker near the injection point in each area at different times within a period of time during the fracturing fluid injection process, the actual concentration of the gel breaker at the boundary of each area, and the average concentration of the gel breaker in each area respectively according to the time series, is the time point, define the time period as , represents the actual concentration of the gel breaker near the injection point in the th area at the th moment within a period of time during the fracturing fluid injection process, represents the actual concentration of the gel breaker at the boundary of the th area at the th moment within a period of time during the fracturing fluid injection process, represents the actual concentration of the gel breaker in the The average concentration of the delayed breaker in the th region, , being a positive integer;

[0020] And calibrate the permeability of each region and the viscosity of the fracturing fluid during the fracturing fluid injection process as and , indicating the permeability of the th region during the fracturing fluid injection process, indicating the viscosity of the fracturing fluid in the th region during the fracturing fluid injection process;

[0021] Calculate the diffusion equilibrium coefficient of each region. The specific calculation formula is as follows:

[0022]

[0023] In the formula, is the diffusion equilibrium coefficient of the th region.

[0024] Preferably, the acquisition logic of the diffusion response index of each region is as follows:

[0025] Extract the response adjustment information in the dynamic information of the injection process of each region in the heterogeneous formation during the fracturing fluid injection process after preprocessing, specifically including the injection pressure change rate, the average concentration change rate of the delayed breaker in each region, and the average flow rate change rate of the delayed breaker in each region at different times during a period of time in the fracturing fluid injection process, and calibrate them as , and , indicating the injection pressure change rate in the th region at time during a period of time in the fracturing fluid injection process, indicating the average concentration change rate of the delayed breaker in the th region at time during a period of time in the fracturing fluid injection process, indicating the average flow rate change rate of the delayed breaker in the th region at time during a period of time in the fracturing fluid injection process, , , and are all positive integers;

[0026] Calculate the diffusion response index of each region. The specific calculation formula is as follows:

[0027]

[0028] In the formula, is the diffusion response index of the th region.

[0029] Preferably, a diffusion uniformity evaluation model is constructed for the diffusion equilibrium coefficients and diffusion response indices of each generated region, and the diffusion uniformity coefficients of each region are generated, specifically including the following steps:

[0030] Collect the diffusion equilibrium coefficients, diffusion response indices, and corresponding diffusion uniformity coefficients of several regions generated in the past period of time, and label them respectively as , and , represents the number of the diffusion equilibrium coefficients, diffusion response indices, 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 is formed into a historical data set;

[0031] Select a multiple regression model as the diffusion uniformity evaluation model, and train it through the historical data set to determine the values of the regression coefficients, according to the formula:

[0032] In the formula, , and are the regression coefficients;

[0033] Optimize the regression coefficients by minimizing the error between the predicted value and the actual value, and finally determine the values of the regression coefficients , and ;

[0034] Use the finally determined regression coefficients to input the diffusion equilibrium coefficients and diffusion response indices of each region generated in real time into the constructed diffusion uniformity evaluation model, and generate the diffusion uniformity coefficients of each region in real time.

[0035] Preferably, compare the generated diffusion uniformity coefficients of each region with the preset diffusion uniformity coefficient threshold interval , evaluate the diffusion uniformity of the breaker in each region during the fracturing fluid injection process according to the comparison result, and divide each region into a high diffusion region, a uniform diffusion region, and a low diffusion region according to the evaluation result. The specific comparison analysis and division are as follows:

[0036] If and the degree of gel breaker diffusion in this area is low during the fracturing fluid injection process, then this area is classified as a low-diffusion area;

[0037] If and the degree of gel breaker diffusion in this area is normal during the fracturing fluid injection process, then this area is classified as a uniform-diffusion area;

[0038] If and the degree of gel breaker diffusion in this area is high during the fracturing fluid injection process, then this area is classified as a high-diffusion area.

[0039] Preferably, according to the classification results of each area in the heterogeneous formation, corresponding measures for adjusting the gel breaker injection volume, optimizing the injection pressure, and adjusting the gel breaker formula are taken respectively, specifically:

[0040] For the area classified as a low-diffusion area, the specific measures taken are: increasing the injection volume of the gel breaker, raising the injection pressure to improve the diffusion rate of the gel breaker in this area, and maintaining the original formula of the gel breaker;

[0041] For the area classified as a uniform-diffusion area, the specific measures taken are: maintaining the current gel breaker injection volume and injection pressure, and continuously monitoring;

[0042] For the area classified as a high-diffusion area, the specific measures taken are: reducing the injection volume of the gel breaker, lowering the injection pressure to reduce the diffusion rate in this area, and at the same time adjusting the gel breaker formula to enhance its stability in this area.

[0043] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0044] 1. The present invention realizes the precise analysis and control of the gel breaker diffusion process in the heterogeneous formation in practical applications, thus effectively solving the problem of uneven gel breaker diffusion caused by changes in formation permeability and porosity. By dividing the heterogeneous formation into regions and combining real-time data acquisition and analysis methods, the dynamic information of each region can be obtained in a timely manner during the gel breaker injection process. The diffusion state of each region is evaluated using the diffusion equilibrium coefficient and the diffusion response index, and the diffusion uniformity degree is modeled and optimized through a multiple regression model, enabling dynamic adjustment of the gel breaker diffusion behavior. Such a method ensures that during the fracturing operation, the phenomenon of excessive diffusion of the gel breaker in the high-permeability area or retention in the low-permeability area can be quickly discovered and corrected, making the action of the gel breaker more balanced.

[0045] 2. By means of real-time monitoring and analysis of the breaker diffusion process, the present invention can automatically adjust the injection strategy of the breaker according to different diffusion states, including injection volume, pressure regulation, and formulation optimization, etc. It can adapt to the dynamic changes of formation conditions, without frequent manual intervention, reducing the operation complexity and improving the diffusion effect of the breaker in each area. In addition, the combination of real-time analysis and regular model update ensures that the diffusion uniformity evaluation model is always optimized based on the latest data, with strong adaptability, so that it can maintain high accuracy in different oilfields and geological environments, improving the reliability of the fracturing operation.

[0046] 3. The present invention also significantly improves the oil and gas recovery rate and operation efficiency. Through precise diffusion analysis and optimization, it can ensure that the breaker can fully play its viscosity adjustment role in the formation, thereby improving the shape and propagation effect of the fracture, enabling more oil and gas to enter the wellbore through the fracture. At the same time, through targeted adjustment of different diffusion degree areas, the waste of the breaker caused by uneven diffusion is reduced, and the resource utilization rate is optimized. This not only reduces the operation cost, but also reduces the impact on the environment, improving the economic benefits and sustainability, and is an important innovative method for improving the oil and gas recovery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0048] Figure 1 It is a schematic flow chart of a method for analyzing the stability of a liquid breaker for fracturing according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] Now, the exemplary embodiments will be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these exemplary embodiments are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art.

[0050] The present invention provides a method for analyzing the stability of a liquid breaker for fracturing as shown in Figure 1 and specifically includes the following steps:

[0051] When performing a fracturing operation in a heterogeneous formation, according to the permeability, porosity, and lithology changes of the heterogeneous formation, the heterogeneous formation is evenly divided into several independent regions, and a real-time analysis framework for evaluating diffusion uniformity is established according to the diffusion and flow conditions of the breaker during the injection process in each region.

[0052] When conducting a fracturing operation in a heterogeneous formation, according to the changes in permeability, porosity, and lithology of the heterogeneous formation, the heterogeneous formation can be divided into several independent regions, which can be achieved through formation imaging technology, logging data analysis, and 3D geological modeling software. Specifically, first, logging tools (such as nuclear magnetic resonance logging and acoustic logging) are used to obtain data such as permeability, porosity, and lithology, and these data are input into 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 division algorithms (such as Voronoi diagrams) for data analysis, and divides regions with similar permeability and porosity characteristics into an independent unit, thus forming several divided regions. In this way, the complex heterogeneous formation can be refined, laying a foundation for subsequent dynamic analysis.

[0053] And according to the diffusion and flow conditions of the breaker during the injection process in each region, a real-time analysis framework for evaluating diffusion uniformity can be 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 devices inside each independent region, and collect the dynamic information of the breaker during the injection process in real time, such as pressure changes, flow rate, and concentration data, and transmit the data to the analysis software through a wireless transmission system. The fluid dynamics simulation software performs CFD simulations based on the Navier-Stokes equations, and combines the real-time data to simulate the diffusion behavior of the breaker in each region. Then, using multivariate regression analysis and machine learning algorithms, a diffusion uniformity evaluation model is constructed to perform real-time analysis on the diffusion rate and flow trend of the breaker, and generate a diffusion evaluation report for optimizing the diffusion effect.

[0054] The reason for doing this is to better solve the problem of uneven diffusion of the breaker in the heterogeneous formation. Due to the large differences in permeability and porosity of the formation, the diffusion behavior of the breaker in different regions is significantly affected, which easily leads to excessive diffusion of the breaker in the high-permeability region, while there may be retention phenomena in the low-permeability region, thus affecting the overall fluidity and effect of the fracturing fluid. By dividing the formation into multiple independent analysis regions, the diffusion behavior of the breaker in each region can be monitored in detail, enabling us to make precise injection adjustments for each region. Establishing a real-time analysis framework can dynamically monitor the diffusion state of the breaker and adjust the injection strategy in a timely manner according to the real-time data, thereby improving the distribution uniformity of the breaker in each region, optimizing the fracture formation and oil-gas flow path, and enhancing the fracturing effect and oil-gas recovery rate. Doing so can not only overcome the problem of being unable to accurately predict the distribution of the breaker in the existing technology, but also significantly improve the efficiency and effect of the operation.

[0055] Obtain in real time the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection, and analyze it after obtaining, and respectively generate the diffusion equilibrium coefficient and diffusion response index of each area;

[0056] In this embodiment, obtaining in real time the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection, and analyzing it after obtaining, and respectively generating the diffusion equilibrium coefficient and diffusion response index of each area, specifically includes the following steps:

[0057] Obtain in real time the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection, and perform preprocessing after obtaining;

[0058] Obtaining in real time the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection can be achieved by combining a sensor network and a data acquisition system with a cloud data platform. Specifically, in each independent area of the heterogeneous formation, high-precision pressure sensors, flow rate sensors, and concentration monitoring devices are deployed. These sensors can monitor in real time the injection pressure, flow rate, and concentration changes of the fracturing fluid and breaker. 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 error-free during the transmission process. At the same time, the data acquisition system supports multi-threaded data synchronization and remote access, facilitating the real-time acquisition of the dynamic information of each area and storing this information in the background for subsequent analysis.

[0059] The purpose of performing preprocessing is to improve the quality of the 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, first, remove the outliers and obvious error data points that may be generated by the sensors through data cleaning, such as sudden extreme values or missing data caused by communication errors. Next, apply a filtering algorithm (such as Kalman filtering or low-pass filtering) to perform denoising on the data to eliminate the high-frequency interference in the signal and make the data smoother and more stable. Then, perform data normalization processing to convert the data collected by different sensors to the same scale, facilitating comparison and calculation in subsequent analysis. Finally, through data integrity check, ensure that the data in each time period has been completely collected. If missing data is found, it is supplemented by interpolation method. All these preprocessing processes can be realized through a data analysis software platform to ensure that the subsequent generated evaluation parameters are more accurate.

[0060] Extract the diffusion dynamic information and response adjustment information from the dynamic information of the injection process in each area of the heterogeneous formation during the fracturing fluid injection after preprocessing;

[0061] To extract the diffusion dynamic information and response regulation information from the injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process after preprocessing, it can be achieved through a data analysis software platform combined with a feature extraction algorithm and a data classification model. Specifically, first, import the preprocessed data into the data analysis platform. The platform uses a feature extraction algorithm (such as principal component analysis PCA or clustering analysis) to identify the parameters related to diffusion characteristics (such as breaker concentration change, flow rate, permeability, etc.) from the dynamic information and classify them as diffusion dynamic information. Then, use a classification model (such as support vector machine SVM or decision tree) to classify the data and identify the parameters related to 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 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.

[0062] Analyze the diffusion dynamic information and response regulation information in the injection process dynamic information of each extracted region, and generate the diffusion equilibrium coefficient and diffusion response index of each region respectively.

[0063] In this embodiment, the acquisition logic of the diffusion equilibrium coefficient of each region is as follows:

[0064] Extract the diffusion dynamic information from the injection process dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process after preprocessing, specifically including the actual concentration of the breaker near the injection point in each region at different times within a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each region, the average concentration of the breaker in each region, as well as the permeability of each region and the viscosity of the fracturing fluid. And represent the actual concentration of the breaker near the injection point in each region at different times within a period of time during the fracturing fluid injection process, the actual concentration of the breaker at the boundary of each region, and the average concentration of the breaker in each region according to the time series with functions , and respectively. is the time point, define the time period as , represents within a period of time during the fracturing fluid injection process the actual concentration of the breaker near the injection point in the th region at time represents within a period of time during the fracturing fluid injection process the actual concentration of the breaker at the boundary of the th region at time Indicates the average concentration of the breaker within a certain period during the fracturing fluid injection process at the moment in the th region, , where is a positive integer;

[0065] Extract the diffusion dynamic information of each region in the heterogeneous formation during the fracturing fluid injection process, specifically including the actual concentration of the breaker near the injection wellbore in each region, the actual concentration of the breaker at the boundary of each region, the average concentration of the breaker in each region, the permeability of each region, and the viscosity of the fracturing fluid. The acquisition of these quantitative data mainly relies on the collaborative action of a sensor network, logging technology, and a data analysis software platform. First, through the concentration monitoring sensors deployed near the injection wellbore and at the boundaries of each region, the concentration changes of the breaker at different moments 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 first enters the formation, while the actual concentration at the region boundary shows the diffusion state of the breaker when it reaches the outer edge of the region during the flow through the formation. The data collected by the sensors 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 region through a time-weighted average algorithm based on these time-series concentration data. For the permeability data, detailed data on the formation pore structure is collected using logging technologies (such as nuclear magnetic resonance logging, acoustic logging), and the spatial distribution of the permeability is analyzed through a formation model in the data platform to obtain the permeability values of each region. The viscosity of the fracturing fluid is obtained through laboratory measurements and real-time correction data of formation temperature and pressure changes, and the viscosity value is automatically updated on the data platform by combining temperature and pressure change models. All these data are finally integrated and processed in the data analysis software to generate the diffusion dynamic information for subsequent calculations, ensuring that it can accurately reflect the diffusion behavior of the breaker in different regions and its influencing factors. In this way, not only the real-time acquisition and dynamic update of data are achieved, but also efficient analysis and prediction can be carried out based on the data changes at different time points.

[0066] And calibrate the permeability of each region and the viscosity of the fracturing fluid during the fracturing fluid injection process as and , Indicates the permeability of the th region during the fracturing fluid injection process, Indicates the viscosity of the fracturing fluid in the th region during the fracturing fluid injection process;

[0067] Calculate the diffusion equilibrium coefficient of each region. The specific calculation formula is as follows:

[0068]

[0069] In the formula, is the diffusion equilibrium coefficient of the th region.

[0070] The purpose of calculating the diffusion equilibrium coefficient of each region by this formula is to quantify the diffusion uniformity of the breaker in a specific region, and to evaluate it by combining the time variation and various influencing factors. Specifically, the integral form is used in the formula to comprehensively analyze the diffusion changes of the breaker at different time points within the time interval . Through integration, the change trend over time can be accumulated, and the overall dynamics of the concentration change with time can be captured. The in the formula is used for the normalization of the time interval, converting the integral result into the average diffusion characteristics within this time period, so as to avoid the distortion of the results caused by different time lengths. The in the formula represents the change rate of the breaker concentration near the injection point with time, reflecting the initial diffusion rate of the breaker during the injection process. While represents the change rate of the breaker concentration at the region boundary with time, reflecting the rate when the breaker diffuses to the outer edge in this region. The relative change of these two parts indicates whether the diffusion process of the breaker in the region from injection to diffusion is balanced. Comparing the ratio of these two with (i.e., the change rate of the average concentration in this region) can evaluate the difference between the internal concentration change and the overall diffusion trend. If the change rates of the two are quite different, it means that the diffusion of the breaker in the region is uneven. The in the formula represents the permeability, while represents the viscosity, and their ratio is used to correct the physical properties during the diffusion process, because the breaker is more likely to diffuse in regions with higher permeability, while higher viscosity will inhibit the flow of the breaker. This correction part ensures the comparability of the results under different permeability and viscosity conditions. 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 this region, which is used to evaluate the diffusion uniformity of the breaker, so as to provide a scientific basis for the optimization of the fracturing operation.

[0071] The th region's diffusion equilibrium coefficient directly reflects the diffusion uniformity of the breaker in this region, and is then used to evaluate the diffusion uniformity of the breaker in each region during the fracturing fluid injection process. When When the value is large, it means that the concentration change of the breaker from the injection point to the regional boundary in this area is relatively balanced, that is, the breaker can diffuse more evenly throughout the area without obvious retention or excessive diffusion; this indicates that the diffusion state of this area is good and the function of the breaker can be fully exerted. When the value is small, it indicates that the concentration change rate of the breaker in this area is unbalanced. The concentration may be too high in the area near the injection point and too 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 evenness of the breaker diffusion in each area, which helps to identify the areas where the breaker injection strategy needs to be adjusted, so as to optimize the overall fracturing operation effect.

[0072] In this embodiment, the acquisition logic of the diffusion response index of each area is as follows:

[0073] Extract the response adjustment information in the dynamic information of the injection process of each area in the heterogeneous formation during the fracturing fluid injection process after preprocessing, specifically including the injection pressure change rate at different times within 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 calibrate them respectively as 、 and , represents the injection pressure change rate in the th area at the th moment during a period of time in the fracturing fluid injection process, represents the average concentration change rate of the breaker in the th area at the th moment during a period of time in the fracturing fluid injection process, represents the average flow rate change rate of the breaker in the th area at the th moment during a period of time in the fracturing fluid injection process, , , and are all positive integers;

[0074] Extract the response adjustment information of each region in the heterogeneous formation during the fracturing fluid injection process after preprocessing, specifically including the injection pressure change rate, the average concentration change rate of the breaker, and the average flow rate change rate of the breaker at different times within a period. First, the injection pressure change rate is obtained through high-precision pressure sensors deployed in each region, which monitor the pressure data of the fracturing fluid and the 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 within each time period, reflecting the pressure fluctuations caused by changes in formation conditions during the fracturing fluid injection process. The pressure change rate data helps to understand how the diffusion and flow behavior of the breaker are driven by pressure during the fracturing fluid injection process. Second, the average concentration change rate of the breaker in each region is obtained through concentration monitoring devices, which are deployed at key positions in each region 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 the moving average method or the difference method, the concentration change rate in each region within different time periods can be calculated. The concentration change rate describes the trend of the concentration of the breaker changing with time in the region 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 from the real-time flow rate data collected by the flow rate sensors, which record the flow rates of the breaker at different times in the region. The data analysis software performs time series analysis on the flow rate data to calculate the change rate of the flow rate within different time periods, reflecting the change of the flow state of the breaker in the region over time. The flow rate change rate can help to 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 calculating the diffusion response index subsequently. In this way, the dynamic information of each region can be obtained in real time and accurately, ensuring a comprehensive evaluation of the diffusion behavior of the breaker in the complex formation.

[0075] Calculate the diffusion response index of each region. The specific calculation formula is as follows:

[0076]

[0077] In the formula, is the diffusion response index of the th region.

[0078] This formula is used to calculate the diffusion response index of the th region , whose purpose is to quantify the dynamic response ability of the breaker during the injection process to pressure fluctuations and flow rate changes, so as to evaluate the adaptability of the breaker in this area. The summation symbol used in the formula is to accumulate data at each time point within the time period, indicating the response changes of the breaker at different time points. This summation process can capture all the pressure, concentration, and flow rate changes within the time interval, providing an overall response characteristic. In the formula, represents the injection pressure change rate within the time period , reflecting the magnitude of the driving force received by the breaker; while is the average concentration change rate of the breaker in the th area, indicating the change of the breaker's concentration over time during this time period. Multiplying these two parameters can evaluate the concentration response intensity of the breaker under pressure drive. The in the denominator represents the average flow rate change rate of the breaker in this area, which is used to adjust the result of the concentration response. A higher flow rate change rate means that the fluid flow has a more significant impact on the diffusion of the breaker. Therefore, by dividing the concentration response intensity by the flow rate change rate, the response ability of the breaker in the flowing state can be evaluated more precisely. The final normalization factor is used to calculate the average response index within the time period, making the calculation results of different time periods consistent and comparable. Such a calculation method can comprehensively reflect the adaptability of the breaker to different external conditions during the injection process, thus providing a scientific basis for optimizing the injection strategy.

[0079] The th area's diffusion response index directly reflects the dynamic adaptability of the breaker to pressure changes and flow rate changes in this area, thus being used to evaluate the degree of diffusion non-uniformity of the breaker in this area. When has a large value, it means that the breaker shows a strong concentration response ability during pressure fluctuations and can better adapt to the change of the flow rate, indicating that the diffusion of the breaker in this area is relatively balanced and can quickly adjust its diffusion path to adapt to the dynamically changing environment. On the contrary, when has a small value, it indicates that the breaker has a weak response and poor adaptability when facing pressure and flow rate changes, which may lead to non-uniform diffusion of the breaker in this area, prone to local retention or excessive diffusion, thus affecting the overall fluidity and effect of the fracturing fluid. Therefore, the size of the value can effectively judge the diffusion equilibrium state of the breaker in different formation areas, providing an important reference for optimizing the injection strategy.

[0080] Construct a diffusion uniformity evaluation model for the diffusion equilibrium coefficient and diffusion response index of each generated region, generate the diffusion uniformity coefficient of each region, and perform analysis after generation to evaluate the diffusion uniformity of the breaker in each region during the fracturing fluid injection process, and divide each region into a high-diffusion region, a uniform-diffusion region, and a low-diffusion region according to the evaluation results;

[0081] In this embodiment, constructing a diffusion uniformity evaluation model for the diffusion equilibrium coefficient and diffusion response index of each generated region, and generating the diffusion uniformity coefficient of each region specifically includes the following steps:

[0082] Collect a number of diffusion equilibrium coefficients, diffusion response indices, and corresponding diffusion uniformity coefficients of each region generated in the past period of time, and calibrate them respectively as 、 and , represents the number of a number of diffusion equilibrium coefficients, diffusion response indices, and corresponding diffusion uniformity coefficients of each region generated in the past period of time, , is a positive integer, and form a historical data set with the data collected in the past period of time;

[0083] The diffusion equilibrium coefficient and diffusion response index of each region can be collected by combining a data acquisition system, a database management platform, and a data analysis software platform. Specifically, first, during the fracturing operation, the diffusion equilibrium coefficient and diffusion response index of each region monitor relevant data in real time through a sensor network deployed on site, and are automatically calculated and generated by the data acquisition system. These real-time generated parameters are uploaded to the cloud or local server through a wireless data transmission system. The data management platform is responsible for storing these data in time series and establishing tags in the database to mark the diffusion coefficients of each region within each time period. Then, the data analysis software platform regularly accesses the database, extracts all stored diffusion equilibrium coefficients, diffusion response indices, and their corresponding diffusion uniformity coefficients in the past period of time, and files and organizes them according to the specified time period and region. In this way, the continuity and integrity of the data can be ensured, and it can facilitate the subsequent data analysis and model training process, providing a stable and accurate data basis.

[0084] Limit to be a positive integer greater than or equal to 3, in order to ensure that when constructing the diffusion uniformity evaluation model, sufficient data samples can be obtained to accurately calculate the regression coefficients 、 and . There are three regression coefficients involved in the regression model, and each data sample provides one equation. Therefore, at least 3 different sample data (i.e., ), are required to form a system of equations consisting of three equations, so as to solve the specific values of these three regression coefficients. Doing so can not only ensure that the system of equations has a solution, but also provide sufficient input data for the training of the model, enabling the regression coefficients to better reflect the influence of the diffusion equilibrium coefficient and the diffusion response index on the diffusion uniformity coefficient. In addition, when takes a larger value, it means using more historical data for model training, which can improve the stability and prediction accuracy of the regression model, making the model more robust and reliable during the application process.

[0085] In the formula, , and are regression coefficients;

[0086] 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 variables are the factors that affect the change of the dependent variable. The multiple regression model is selected in the evaluation of diffusion uniformity because the diffusion uniformity coefficient is jointly 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 simultaneously, so as to more accurately predict or explain its change. The three regression coefficients , and in the model have different meanings respectively: is the constant term, indicating the basic level of and when both are zero; ; is the regression coefficient of , indicating the influence on the diffusion uniformity coefficient when the diffusion equilibrium coefficient increases by one unit under other unchanged conditions; is the regression coefficient of , indicating the influence on the diffusion uniformity coefficient when the diffusion response index increases by one unit. By training the model to determine the optimal values of these three regression coefficients, the way and jointly affect can be better described, thus providing a scientific basis for the evaluation of diffusion uniformity in actual operations.

[0087] By minimizing the error between the predicted value and the actual value, the regression coefficients are optimized, and finally the values of the regression coefficients , and are determined;

[0088] The process of optimizing the regression coefficients is to ensure that the multiple 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 prediction ability and accuracy of the model. Specifically, by minimizing the error between the predicted value and the actual value, the regression coefficient values that best fit the historical data can be found, so that the model can make more accurate predictions in future applications. This process is usually achieved using the Ordinary Least Squares (OLS) method, which is a commonly used method in regression analysis. Through data analysis software (such as R, the scikit-learn library in Python, or professional statistical software such as SPSS), historical data is imported into the model, and the software automatically calculates the sum of the squared errors between the predicted value and the actual observed value for each data point, and continuously adjusts the regression coefficients , and to find the coefficient combination that minimizes the sum of the squared errors. This process automatically iterates until the error reaches the minimum value, and the final regression coefficient values can be determined. Such a method ensures that the model performs best on the training data and can predict the diffusion uniformity coefficient more accurately in future applications.

[0089] Using the finally determined regression coefficients, input the diffusion equilibrium coefficients of each region generated in real time into the constructed diffusion uniformity evaluation model and the diffusion response index to generate the diffusion uniformity coefficients of each region in real time .

[0090] In this embodiment, the generated diffusion uniformity coefficients of each region are compared with the pre-set diffusion uniformity coefficient threshold interval . According to the comparison results, evaluate the diffusion uniformity degree of the breaker in each region during the fracturing fluid injection process, and divide each region into a high-diffusion region, a uniform-diffusion region, and a low-diffusion region according to the evaluation results. The specific comparison analysis and division are as follows:

[0091] If , the diffusion uniformity degree of the breaker in this region during the fracturing fluid injection process is low, then this region is divided into a low-diffusion region;

[0092] This situation means that within this area, the non-uniformity of the breaker diffusion is relatively large. The breaker may accumulate at certain positions and be difficult to penetrate into other areas. Due to insufficient diffusion, the breaker cannot fully play its role within this area, which may lead to unsatisfactory viscosity adjustment of the fracturing fluid in this area, thereby affecting the formation and propagation of fractures. This non-uniformity will cause some fractures in the formation to fail to open effectively, reducing the permeability of oil and gas, ultimately resulting in a decrease in oil and gas recovery rate, and increasing the difficulty and cost of subsequent operations.

[0093] If , during the injection process of the fracturing fluid, the degree of uniform diffusion of the breaker in this area is at a normal level, then this area is classified as a uniformly diffused area;

[0094] In this case, the diffusion of the breaker within this area is relatively balanced, with moderate concentration and flow rate, and it can well adapt to the change of formation permeability. This means that the effect of the breaker within this area reaches the expectation, and it can effectively adjust the viscosity of the fracturing fluid to ensure uniform fracture propagation. This can make the fracturing operation more stable and efficient, with a more regular fracture shape, thereby enhancing the fluidity and production efficiency of oil and gas, and reducing the uncertainty and adjustment requirements during the operation process.

[0095] If , during the injection process of the fracturing fluid, the degree of uniform diffusion of the breaker in this area is at a high level, then this area is classified as a highly diffused area.

[0096] This situation means that the diffusion rate of the breaker within this area is too fast, which may lead to too low concentration of the breaker in some local areas, showing an over-diffusion phenomenon. 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 throughout the injection process. Such a situation will lead to insufficient viscosity adjustment of the fracturing fluid in local areas, and there may be over-propagation or non-uniform propagation of fractures, increasing the operation risk, and may require adjustment of the overall injection strategy to avoid waste of the breaker and reduction of operation efficiency.

[0097] The preset threshold interval of the diffusion uniformity coefficient can be determined by a comprehensive method of historical data analysis, machine learning model training, and simulation experiment results. First, use data analysis software (such as pandas in Python, R language, etc.) to analyze the historical data of a large number of past fracturing operations, and extract the statistical characteristics of the diffusion uniformity coefficients of each area under different formation conditions, including mean, median, and standard deviation. Based on these statistical characteristics, the and The value range is usually selected as the 25th percentile and the 75th percentile of the data distribution as the initial interval. Subsequently, through simulation experiments and numerical simulation software (such as COMSOL, ANSYS), the diffusion behavior of the breaker under different formation conditions is simulated multiple times to adjust and verify the rationality of these thresholds to ensure that they can accurately reflect the diffusion state of the breaker in actual operations. Finally, machine learning algorithms (such as linear regression or decision tree) are applied to train these data, and through model optimization, the threshold range that can best predict the diffusion effect is found. The model will automatically adjust and the values of, so that the set threshold interval can adapt to different geological conditions and ensure the best diffusion effect of the breaker in each area. In this way, the threshold interval of the diffusion uniformity coefficient can be accurately set, making it more scientific and adaptable in practical applications.

[0098] According to the division results of each area in the heterogeneous formation, corresponding measures for adjusting the breaker injection volume, optimizing the injection pressure, and adjusting the breaker formula are taken respectively;

[0099] In this embodiment, according to the division results of each area in the heterogeneous formation, corresponding measures for adjusting the breaker injection volume, optimizing the injection pressure, and adjusting the breaker formula are taken respectively. Specifically:

[0100] For the area with the division result of the low-diffusion area, the specific measures are: increasing the injection volume of the breaker and raising the injection pressure to increase the diffusion rate of the breaker in this area and maintaining the original formula of the breaker;

[0101] Measures for the low-diffusion area: 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 this area in real time and analyzes that the diffusion uniformity in this area is insufficient. The data analysis software can calculate the appropriate injection volume and pressure increase based on this information and automatically send adjustment instructions to the injection equipment. Through the automated control platform, the flow parameters of the injection pump are adjusted to increase the injection volume of the breaker, and at the same time, the output pressure of the booster pump is adjusted to increase the injection pressure. This is done to accelerate the diffusion speed of the breaker in the low-diffusion area so that it can be more evenly distributed in this area, thereby improving the overall adjustment effect of the fracturing fluid and ensuring that the fractures are fully extended in the low-permeability area.

[0102] For the area with the division result of the uniform-diffusion area, the specific measures are: maintaining the current breaker injection volume and injection pressure and continuously monitoring;

[0103] Measures for the uniform diffusion area: Keep the current breaker injection volume and injection pressure and continuously monitor them, which can be achieved through a data acquisition and real-time monitoring system. The data acquisition system will continuously record the changes in breaker concentration, injection pressure, and flow rate, 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, and when the monitored data exceeds these thresholds, it will automatically send reminders or notifications for recommended adjustments so that operators can intervene in a timely manner. Keeping the current injection parameters without adjustment is because the diffusion state in this area has reached an ideal state, and maintaining the existing injection parameters can maintain the uniform diffusion effect of the breaker in the area, thus ensuring the stability and continuity of the fracturing process and avoiding unnecessary risks brought by excessive adjustment.

[0104] For the area with the division result of high diffusion area, the specific measures are as follows: Reduce the injection volume of the breaker and lower the injection pressure to reduce the diffusion rate in this area, and at the same time adjust the breaker formula to enhance its stability in this area.

[0105] Measures for the high diffusion area: Reduce the injection volume of the breaker, lower the injection pressure, and adjust the breaker formula, which can be achieved through an automated formula management system and an injection control system. First, evaluate the concentration and diffusion rate in this area through data analysis software to determine the specific reasons for the too-fast diffusion of the breaker in this area. Then, the injection control system automatically adjusts the flow rate of the injection pump according to the analysis results, reduces the injection volume of the breaker, and gradually reduces the injection pressure through a pressure reduction device to inhibit the too-fast diffusion of the breaker. At the same time, the formula management system will automatically optimize the breaker formula according to the changes in formation conditions and the analysis results of the diffusion rate, and adjust the proportion of the additives in it to improve the stability of the breaker in this area. The purpose of doing this is to avoid excessive dilution and waste of the breaker in the high diffusion area, thus ensuring the breaker concentration and action effect in other areas, while optimizing the use cost of the breaker and improving the efficiency and effect of the overall fracturing operation.

[0106] Continuously monitor the dynamic information of the injection process in each area, and dynamically adjust the breaker injection strategy and parameter settings according to the real-time analysis results, and regularly update the diffusion uniformity evaluation model.

[0107] To achieve "continuously monitor the dynamic information of the injection process in each area, and dynamically adjust the breaker injection strategy and parameter settings according to the real-time analysis results, and regularly update the diffusion uniformity evaluation model", it can be completed through the collaborative work of a data acquisition system, a real-time analysis platform, an automated control system, and a model optimization platform.

[0108] First, the on-site sensor network will monitor the dynamic information of each area in real time, including key parameters such as the concentration of the gel breaker, injection pressure, flow rate, and formation temperature. These data are uploaded to the cloud data platform or local server through a wireless transmission system for storage and preliminary processing. The data acquisition system will filter out noise and standardize these information to ensure the accuracy and consistency of the data. The goal of continuous monitoring is to obtain high-frequency real-time data, which can immediately reflect the change trends of each area during the fracturing process. Especially when abnormal fluctuations occur in formation pressure or gel breaker diffusion, abnormal signals can be captured in the first time.

[0109] 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 state of each area. The platform will judge whether the diffusion uniformity of each area is within the expected range according to these real-time analysis results. If the diffusion speed of 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 automatic control system to adjust the injection volume, injection pressure or change the injection rate of the gel breaker in this area. This dynamic adjustment mechanism ensures that the diffusion of the gel breaker can maintain the best state under different geological conditions, thus avoiding the waste of the gel breaker caused by uneven diffusion or poor fracturing effect.

[0110] In addition, in order to ensure that the analysis model can adapt to the changes in formation conditions, the data analysis platform will regularly update the diffusion uniformity evaluation model using the collected historical data. The historical data will be input into the model training module, and the parameters of the model 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, so as to ensure that the prediction ability of the model is always at a high level. The purpose of doing this is to ensure that the model can adapt to the dynamic changes of geological conditions, make the analysis results more accurate, and finally provide reliable data support for the optimization of the gel breaker injection strategy.

[0111] Through this intelligent and automated management method, the whole process monitoring and optimization of the gel breaker injection process can be realized, reducing the error of manual adjustment and improving the efficiency and success rate of the fracturing operation. The combination of real-time monitoring and dynamic adjustment ensures that the use effect of the gel breaker can be continuously optimized according to the formation conditions, and finally improves the economic benefits and production safety of oil and gas exploitation.

[0112] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation. The preset parameters in the formula are set by technicians in this field according to the actual situation.

[0113] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using 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 processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless (such as infrared, wireless, microwave, etc.) manner. 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 includes one or more collections of available media. The available media can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0114] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not imply the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0115] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0116] In 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 above-described embodiments are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can be in an electrical, mechanical, or other form.

[0117] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0118] In addition, each functional unit in various embodiments of the present application may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit.

[0119] As described above, the above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to 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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