Method for evaluating the duration of stability of a bentonite colloid

Abstract

The application provides a bentonite colloid stability duration evaluation method, which comprises the following steps: monitoring the dissolved oxygen concentration and the iron ion concentration in the solution, simultaneously acquiring Zeta potential monitoring data of a Zeta potential instrument on the bentonite colloid, and carrying out denoising processing on the acquired data; inferring the generation state of the iron hydroxide colloid through the corrosion release activity of the iron ion, analyzing the flocculation morphology of the heterogeneous aggregation of the positive electric iron hydroxide colloid and the negative electric bentonite colloid in the solution, and obtaining the flocculation structure characteristics of the heterogeneous aggregation; carrying out cross verification of the bentonite colloid instability state through preliminary evaluation of the bentonite colloid stability duration and the flocculation structure characteristics of the heterogeneous aggregation, and outputting the evaluation result of the bentonite colloid stability duration.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for evaluating the duration of stability of bentonite colloids. Background Technology

[0002] Bentonite, as a high-performance clay mineral, plays a crucial role in industrial fields such as drilling fluids, waterproofing materials, and casting binders. Its hydration expansion properties directly determine product quality and application effectiveness. Accurately assessing the expansion capacity of bentonite is of great significance for ensuring the stability and economy of downstream industrial processes. Current assessment methods typically rely on multiple expansion indicators, such as expansion force, free expansion rate, and water absorption rate, to comprehensively judge bentonite quality. However, when the content of non-montmorillonite mineral impurities, especially quartz and feldspar fragments, changes in the sample, the degree of interference to different expansion indicators varies significantly. Quartz and feldspar are the most common rock-forming minerals in the Earth's crust and are often mixed in as surrounding rock fragments during the formation of bentonite deposits. Especially in mining areas with incomplete weathering or complex sedimentary environments, complete separation is difficult. Therefore, almost all natural bentonite contains a certain proportion of non-expansive impurities such as quartz and feldspar. In actual industrial procurement and batch inspection, the proportion of quartz and feldspar fragments in bentonite samples from different mining areas, different mining layers, and even different mining faces of the same ore body naturally fluctuates. When the content of these two types of impurities changes between batches, an increase in quartz content usually simultaneously lowers the values ​​of swelling force, free swelling rate, and water absorption rate. However, the intensity of this lowering effect is inconsistent across different indicators, causing a drastic change in the degree of inter-sample difference originally used for comprehensive scoring. This severely distorts the evaluation method that originally relied on the degree of dispersion to allocate weights. The core assumption of this method is that the greater the difference between samples, the better the indicator can distinguish between good and bad quality, and therefore it is given a higher weight. However, impurity interference precisely breaks this assumption—the comprehensive score and ranking of the same batch of samples may be fundamentally reversed, failing to truly reflect the relative quality of bentonite's intrinsic qualities. The root cause of this phenomenon lies in the extremely different selective interference intensity of non-montmorillonite mineral impurities on different swelling indicators. When quartz and feldspar fragments are mixed in, they occupy the space between montmorillonite particles, directly hindering the outward expansion of montmorillonite lamellae after absorbing water. Therefore, the inhibitory effect on indicators such as swelling force, which depend on the overall coordinated expansion of particles, is particularly severe. Water absorption rate, on the other hand, mainly depends on the speed at which water penetrates along the mineral surface and pore channels. Although impurity particles may partially block the pores, they do not fundamentally change the hydrophilic adsorption capacity of the montmorillonite surface, and therefore the inhibition is relatively mild. As the impurity content gradually increases from low to high, the dispersion trajectories of each indicator show opposite trends, directly causing the traditional assessment mechanism that relies on dispersion to allocate weights to fail, thus failing to truly reflect the relative quality of the montmorillonite content within the bentonite. For example, in a set of actual mineral samples from different mining areas, when the quartz content increased from 8% to 25%, the standard deviation of swelling force decreased from the highest among the groups to the lowest, while the standard deviation of water absorption rate jumped from the lowest to the highest. This caused the high-quality montmorillonite sample, which originally ranked high under low impurity conditions, to suddenly fall to the bottom in the comprehensive score, seriously interfering with the judgment of the true quality differences between bentonite batches.How to accurately identify and resist the selective interference caused by impurities on the dispersion of different expansion indicators under the condition of varying non-montmorillonite mineral impurity content, so as to obtain a stable and reliable comprehensive quality classification, has become a key issue in the evaluation of bentonite hydration expansion performance. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method for evaluating the duration of stability of bentonite colloids, which solves the problem of stable and reliable comprehensive quality grading in the existing technology.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for assessing the duration of bentonite colloidal stability mainly includes:

[0006] Dissolved oxygen concentration and iron ion concentration in the solution were monitored. Simultaneously, Zeta potential data of bentonite colloids were acquired using a Zeta potential meter, and the acquired data were denoised. The invasive activity of dissolved oxygen in the solution was analyzed based on the denoised dissolved oxygen concentration, and the time period when the dissolved oxygen invasive activity exceeded a preset criterion was identified. Based on the relationship between the corrosion release activity of iron ions and the increased dissolved oxygen level during this period, it was confirmed that iron ions hydrolyze under high pH conditions to form ferric hydroxide colloids. The formation state of ferric hydroxide colloids was inferred from the corrosion release activity of iron ions. The flocculation morphology of heterogeneous aggregation of positively charged ferric hydroxide colloids and negatively charged bentonite colloids in the solution was analyzed, and the flocculation structure characteristics of heterogeneous aggregation were obtained. Based on the flocculation structure characteristics of heterogeneous aggregation, and referring to the Zeta potential of bentonite colloids... The intrinsic decay baseline of the ta potential is used to restore the Zeta potential. The portion of the accelerated decay towards zero in the restored Zeta potential that exceeds the intrinsic decay range of bentonite colloid is marked as an intrinsic deviation phenomenon caused by heterogeneous aggregation. Based on the identification results of the intrinsic deviation phenomenon, the oxidative corrosion promoting characteristics of dissolved oxygen are incorporated into the dynamic update of the stability termination judgment condition and applied to the restored Zeta potential. The time span during which the Zeta potential decays to the termination judgment condition is calculated to obtain a preliminary assessment of the duration of bentonite colloid stability. The preliminary assessment of the duration of bentonite colloid stability is cross-validated with the flocculation structure characteristics of heterogeneous aggregation to determine the instability state of bentonite colloid, and the assessment result of the duration of bentonite colloid stability is output.

[0007] Furthermore, the dissolved oxygen concentration and iron ion concentration in the solution were monitored, and the zeta potential monitoring data of the bentonite colloid was obtained using a zeta potential meter, including:

[0008] A continuous signal of dissolved oxygen concentration in the solution is obtained by a dissolved oxygen probe, a signal of change in iron ion concentration in the solution is collected by an iron ion sensor, and a zeta potential measurement signal of bentonite colloid is obtained by a potentiometer. The lowest sampling frequency among the dissolved oxygen probe, the iron ion sensor and the potentiometer is used as a unified time reference interval. Signals with sampling frequencies higher than this time reference interval are downsampled in an equal-interval decimation manner to obtain three sets of original time-series data after frequency synchronization.

[0009] Furthermore, the analysis of the intrusive activity of dissolved oxygen in the solution based on the denoised dissolved oxygen concentration includes:

[0010] Based on the denoised dissolved oxygen concentration data, the difference in dissolved oxygen concentration between adjacent sampling times is calculated and divided by the sampling time interval to obtain the rate of change of dissolved oxygen concentration. This rate of change is used as the invasive activity of dissolved oxygen in the solution. The invasive activity is compared with a preset activity criterion. If the invasive activity exceeds the preset activity criterion, the sampling time is marked as a high invasive activity time. Consecutive high invasive activity times constitute an invasive activity exceeding the standard period. The denoised iron ion concentration data corresponding to the invasive activity exceeding the standard period is extracted, and the ratio of the cumulative increase of iron ion concentration in that period to the duration of the period is calculated to obtain the corrosion release activity of iron ions.

[0011] Furthermore, the step of confirming that iron ions undergo hydrolysis and generate ferric hydroxide colloid under high pH conditions based on the relationship between the corrosion release activity of iron ions and the increased dissolved oxygen state during that period includes: if the corrosion release activity of iron ions and the intrusion activity of dissolved oxygen show a synchronous response, then combining the solution pH data collected by the pH sensor and processed by noise reduction to confirm that the solution is under high pH conditions, the iron ions undergo hydrolysis reaction and generate ferric hydroxide colloid under high pH conditions.

[0012] Furthermore, the method of inferring the formation state of ferric hydroxide colloid through the corrosion release activity of iron ions, and analyzing the flocculation morphology of the heterogeneous aggregation of positively charged ferric hydroxide colloid and negatively charged bentonite colloid in solution, includes:

[0013] Based on the corrosion release activity of iron ions and the pH conditions of the solution, the formation state of ferric hydroxide colloid is inferred. The formation concentration of ferric hydroxide colloid is calculated by converting the cumulative increase in iron ion concentration during the period of excessive invasive activity, according to the molar conversion relationship of one iron ion hydrolyzing to form one ferric hydroxide molecule. The formation rate of ferric hydroxide colloid is calculated by converting the corrosion release activity of iron ions according to the same molar conversion relationship, thus obtaining the formation concentration and formation rate of ferric hydroxide colloid. Based on the formation concentration of ferric hydroxide colloid, the surface positive charge of positively charged ferric hydroxide colloid is determined by combining the degree of protonation of hydroxyl groups on the surface of ferric hydroxide colloid under alkaline conditions. Simultaneously, the surface negative charge of negatively charged bentonite colloid is determined based on the cation exchange capacity of bentonite particles. The adsorption binding strength between the two colloids is obtained by dividing the product of the surface positive charge of positively charged ferric hydroxide colloid and the surface negative charge of negatively charged bentonite colloid by the square of the average distance between the two colloids. Based on the adsorption binding strength and the formation rate of ferric hydroxide colloid, the aggregation rate of positively charged ferric hydroxide colloid and negatively charged bentonite colloid ...

[0014] Furthermore, the portion of the accelerated decay towards zero in the baseline-restored Zeta potential that exceeds the intrinsic decay range of bentonite colloids is marked as an intrinsic deviation phenomenon caused by heterogeneous aggregation, including:

[0015] Identify the time periods in the baseline-restored Zeta potential sequence that deviate towards zero at a rate exceeding a preset intrinsic decay range threshold, and mark the Zeta potential changes within these time periods as intriguing deviations caused by heterogeneous aggregation.

[0016] Furthermore, based on the identification results of intriguing deviations, the oxidative corrosion promoting characteristics of dissolved oxygen are incorporated into the dynamic update of the stability termination criteria. An application is made to the Zeta potential after baseline reduction, and the time span during which the Zeta potential decays to the termination criteria is calculated to obtain a preliminary assessment of the duration of bentonite colloidal stability, including:

[0017] Based on the identification results of extrinsic deviations, the cumulative increase in dissolved oxygen concentration during the period of occurrence of the extrinsic deviation is extracted. This cumulative increase is used as an indicator of the oxidative corrosion promoting characteristics of dissolved oxygen. A preset stability termination threshold is dynamically updated based on this indicator. The stability termination threshold is the lower limit of the absolute value of the Zeta potential. If the oxidative corrosion promoting characteristic indicator exceeds a preset promoting characteristic benchmark value, the stability termination threshold is adjusted upwards according to the ratio of the oxidative corrosion promoting characteristic indicator to the promoting characteristic benchmark value, resulting in an updated stability termination threshold. The updated stability termination threshold is then applied to... The Zeta potential sequence after baseline restoration is used to track the decay process of the absolute value of the Zeta potential at each time step, starting from the beginning of the baseline restored Zeta potential sequence. It is determined whether the absolute value of the Zeta potential at each time step is lower than the updated stability termination threshold. The moment when the absolute value of the Zeta potential first falls below the stability termination threshold is recorded as the stability termination moment. Based on the difference between the stability termination moment and the beginning of the baseline restored Zeta potential sequence, the time span during which the Zeta potential decays to the stability termination threshold is calculated. This time span is used as a preliminary assessment result of the duration of bentonite colloidal stability.

[0018] Furthermore, the evaluation results of the duration of bentonite colloidal stability are output, including: based on the confirmation markers that have passed cross-validation, the preliminary evaluation results of the duration of bentonite colloidal stability are output as the final evaluation results, wherein the final evaluation results characterize the duration of time that the bentonite colloidal maintains a dispersed and stable state under the current test conditions.

[0019] Compared to existing technologies, this invention offers the following advantages: By monitoring dissolved oxygen concentration, iron ion concentration, and bentonite colloid Zeta potential data, and integrating noise reduction processing, heterogeneous aggregation and flocculation structure characteristic analysis, and charge neutralization adsorption strength assessment, it systematically solves the instability problem of bentonite colloids caused by dissolved oxygen oxidation corrosion under high pH conditions. This invention first analyzes the relationship between dissolved oxygen intrusion activity and iron ion corrosion release, confirming the formation of ferric hydroxide colloids and their heterogeneous aggregation characteristics with bentonite colloids. Then, it identifies intriguing deviations through Zeta potential baseline restoration, dynamically updates the stability termination criteria, and finally, combines flocculation structure characteristics with decay time history cross-validation to accurately assess the duration of stability. The core innovation of this invention lies in combining the dissolved oxygen oxidation effect with colloidal aggregation characteristics, achieving a comprehensive quantitative description of the bentonite colloid instability process, and providing a scientific basis and predictive tool for related fields. Attached Figure Description

[0020] Figure 1 This is a flowchart of a method for evaluating the duration of bentonite colloidal stability according to the present invention.

[0021] Figure 2 This is a schematic diagram of a method for evaluating the duration of bentonite colloidal stability according to the present invention.

[0022] Figure 3 This is another schematic diagram of a method for evaluating the duration of bentonite colloidal stability according to the present invention. Detailed Implementation

[0023] The present invention will now be described in detail through specific embodiments:

[0024] like Figures 1-3 This embodiment of a method for evaluating the duration of bentonite colloidal stability may specifically include:

[0025] This disclosure first provides an exemplary embodiment of a method for monitoring the stability of bentonite colloids. One step of this method may include the following steps S101 to S106. Step S101 involves monitoring the dissolved oxygen concentration and the iron ion concentration in the solution, simultaneously acquiring the Zeta potential monitoring data of the bentonite colloid using a Zeta potential meter, and then performing noise reduction processing on the acquired data. For example, in the process of monitoring the stability of bentonite colloids, the simultaneous acquisition of three parameters—dissolved oxygen concentration, iron ion concentration, and Zeta potential—is a fundamental step in assessing the colloidal state. A continuous signal of dissolved oxygen concentration in the solution can be acquired using a dissolved oxygen probe, a change signal of iron ion concentration in the solution can be acquired using an iron ion sensor, and the Zeta potential measurement signal of the bentonite colloid can be acquired using a Zeta potential meter. The dissolved oxygen probe typically employs an electrochemical sensing principle, characterizing the dissolved oxygen concentration level in the solution through the current signal generated by the reduction reaction of oxygen on the surface of the working electrode. The iron ion sensor, based on the principle of ion-selective electrodes, generates a response signal to free iron ions in the solution. The potentiometer measures the electrophoretic migration rate of bentonite particles under an electric field and calculates the Zeta potential value on the particle surface. Addressing the difference in the original sampling frequencies of the dissolved oxygen probe, the iron ion sensor, and the Zeta potentiometer, the lowest sampling frequency among the three can be used as a unified time reference frequency. Signals with sampling frequencies higher than this time reference frequency are downsampled at equal intervals to obtain three sets of original time-series data after frequency synchronization. For example, in one embodiment, the sampling frequency of the dissolved oxygen probe is set to once per second, the sampling frequency of the iron ion sensor is set to once every two seconds, and the sampling frequency of the potentiometer is set to once every five seconds. Since the original sampling frequencies of the three instruments differ, directly comparing and analyzing the three sets of data will result in a time-scale misalignment. To address this problem, the lowest sampling frequency among the three is used as a unified time reference interval, and the dissolved oxygen concentration signal and iron ion concentration signal with higher sampling frequencies are downsampled at equal intervals. Specifically, equal-interval decimation refers to selecting data points from the original high-frequency signal sequence at fixed intervals, discarding other data points within the interval, thereby ensuring that the decimated signal sequence has the same time resolution as the low-frequency signal. It should be noted that although the three sets of original time-series data after frequency synchronization have the same sampling interval, the starting acquisition times of each set of data may differ. In one embodiment, the dissolved oxygen probe starts acquiring data at time zero, while the iron ion sensor starts acquiring data at 0.3 seconds and the potentiometer starts acquiring data at 0.5 seconds. This difference in starting times will cause the three sets of data within the same time reference interval to actually correspond to different physical times. Further, based on the three sets of original time-series data after frequency synchronization, the starting timestamp of each set of data is extracted, and the timestamp difference between the dissolved oxygen concentration data, the iron ion concentration data, and the Zeta potential measurement data is calculated.If a timestamp discrepancy exists between any two sets of data, the data with the lagging timestamp is shifted forward along the time axis until it aligns with the earliest timestamp, resulting in three sets of time-corrected measurement data. In one optional implementation, the first timestamp of each data sequence is extracted, and the earliest timestamp is used as the reference time. The delay of the other two data sets relative to the reference time is calculated, and the data sequences with delays are shifted forward along the time axis by the corresponding delay amount, ensuring complete alignment of the timestamps of the three sets of data. It is understood that the time-corrected measurement data still contains noise interference introduced during the acquisition process. For the three sets of time-corrected measurement data, a sliding window midpoint filter with a window size of five is used to filter out abnormal jump points that deviate from adjacent values ​​in each set of data. The working principle of the sliding window midpoint filter is to set a fixed-length window in the data sequence, sort all data points within the window by value, and take the value at the middle position as the filter output of the window center point. The window slides point by point along the time axis until it traverses the entire data sequence. This method has a suppressive effect on abnormal jump points that deviate from adjacent values, while preserving the overall trend of data variation. Optionally, after filtering out abnormal jump points, a Butterworth low-pass filter is applied to the data after filtering out abnormal jump points to suppress high-frequency fluctuation components. The cutoff frequency is 0.1 Hz, resulting in denoised dissolved oxygen concentration, iron ion concentration, and bentonite colloidal Zeta potential monitoring data. Specifically, a Butterworth low-pass filter is used, with the input being the original data sequence after time-series correction and median filtering. The cutoff frequency is set to 0.1 Hz based on the signal sampling rate, and a smooth sequence is output after calculating the filter coefficients. This filter allows low-frequency signal components to pass through while attenuating high-frequency fluctuation components above the cutoff frequency, thus making the filtered dissolved oxygen concentration, iron ion concentration, and bentonite colloidal Zeta potential monitoring data present smooth change curves. In step S102, the invasive activity of dissolved oxygen in the solution is analyzed based on the denoised dissolved oxygen concentration, and the time period when the dissolved oxygen invasive activity exceeds the preset criterion is identified. Based on the relationship between the corrosion release activity of iron ions and the increased dissolved oxygen state during this time period, it is confirmed that iron ions undergo hydrolysis under high acidity and alkalinity conditions to generate ferric hydroxide colloid. During the monitoring of bentonite colloidal stability, dissolved oxygen slowly infiltrates the solution system through tiny gaps or the lid of the container, and its infiltration intensity dynamically changes over time. Infiltration activity is a quantitative indicator characterizing the rate at which dissolved oxygen enters the solution, obtained by calculating the ratio of the change in dissolved oxygen concentration between adjacent sampling times to the time interval. Based on the denoised dissolved oxygen concentration data, the difference in dissolved oxygen concentration between adjacent sampling times is calculated and divided by the sampling time interval to obtain the rate of change of dissolved oxygen concentration. This rate of change is used as the infiltration activity of dissolved oxygen in the solution, and the infiltration activity is compared with a preset activity criterion. A large infiltration activity value indicates that dissolved oxygen is rapidly entering the solution. When the infiltration activity value approaches zero, it indicates that the dissolved oxygen concentration is in a relatively stable state.If the intrusion activity exceeds a preset activity criterion, the sampling time is marked as a high intrusion activity time. At least three consecutive high intrusion activity times constitute an intrusion activity exceeding the standard period. For example, in a long-term static stability test of drilling fluid, the preset activity criterion is set based on the container sealing performance and the test environment. If the intrusion activity at a certain sampling time exceeds the activity criterion, that time is marked as a high intrusion activity time. Consecutive high intrusion activity times constitute an intrusion activity exceeding the standard period, which reflects the time interval of concentrated dissolved oxygen infiltration. For each intrusion activity exceeding the standard period, the corresponding denoised iron ion concentration data is extracted, the difference in iron ion concentration between adjacent sampling times is calculated and divided by the sampling time interval to obtain the iron ion corrosion release activity at each time, forming a corrosion release activity curve. The iron ion concentration data within the intrusion activity exceeding the standard period is extracted. The cumulative increase in iron ion concentration characterizes the total amount of ferrous ions released into the solution after oxidation in bentonite. This cumulative increase is divided by the duration of the period to obtain the iron ion corrosion release activity. A higher corrosion release activity value indicates a faster rate of iron ion release from the bentonite crystal structure. Further, the time when the corrosion release activity curve reaches its maximum value and the time when the intrusion activity reaches its maximum value are extracted. The deviation between the two times is calculated, and it is determined whether this deviation is within a preset synchronization tolerance range, i.e., not exceeding two sampling intervals. This yields the result of determining the synchronization relationship between iron ion corrosion release activity and dissolved oxygen intrusion activity. Specifically, determining whether a synchronous response relationship exists between iron ion corrosion release activity and dissolved oxygen intrusion activity is a crucial step in confirming their causal association. The specific process for determining the synchronization relationship includes extracting the times when the corrosion release activity curve reaches its maximum value and the time when the intrusion activity curve reaches its maximum value, calculating the absolute deviation between the two times, and comparing this deviation value with a preset synchronization tolerance range. If the deviation value is within the synchronization tolerance range, it is determined that the two exhibit synchronous responses. If the deviation value exceeds the synchronization tolerance range, it is determined that the two do not have a synchronous relationship. The setting of the synchronization tolerance range is related to the sampling time interval and sensor response delay, and is usually set to several sampling periods in the stability test of waterproof materials. Based on the synchronization relationship determination results, if the iron ion corrosion release activity and dissolved oxygen intrusion activity show a synchronous response, then combined with the solution pH data collected by the pH sensor and processed by noise reduction, it is confirmed that the iron ions undergo a hydrolysis reaction under the high pH conditions and generate ferric hydroxide colloid. It should be noted that when the iron ion corrosion release activity and dissolved oxygen intrusion activity show a synchronous response, it indicates that the release of iron ions is triggered by the oxidation of ferrous iron in bentonite by dissolved oxygen. In the alkaline solution environment commonly found in drilling fluids and waterproofing materials, the released iron ions rapidly undergo a hydrolysis reaction under high pH conditions, generating ferric hydroxide precipitates. These precipitates are suspended in the solution in the form of tiny colloidal particles.In one embodiment, when the synchronization relationship determination result shows that the two respond synchronously and the solution pH value is in the alkaline range, it is confirmed that ferric hydroxide colloid has been generated in the solution. This confirmation result provides a basis for subsequent analysis of heterogeneous aggregation phenomena. Step S103: The formation state of ferric hydroxide colloid is inferred by the corrosion release activity of iron ions, and the flocculation morphology of the two colloids, positively charged ferric hydroxide colloid and negatively charged bentonite colloid, in heterogeneous aggregation in the solution is analyzed to obtain the flocculation structure characteristics of heterogeneous aggregation. In the process of bentonite colloid stability monitoring, the formation state of ferric hydroxide colloid directly affects the subsequent judgment of heterogeneous aggregation behavior. When iron ions undergo hydrolysis under high acidity and alkalinity conditions, a divalent or trivalent iron ion combines with a hydroxide ion to form a ferric hydroxide molecule. This molar conversion relationship shows that the cumulative increase in iron ion concentration is directly related to the formation concentration of ferric hydroxide colloid. The formation state of ferric hydroxide colloid is inferred based on the corrosion release activity of iron ions and the high acidity and alkalinity conditions of the solution. The concentration of ferric hydroxide colloid is calculated by converting the cumulative increase in iron ion concentration during the period of excessive intrusion activity, according to the molar conversion relationship of one iron ion hydrolyzing to generate one ferric hydroxide molecule. Simultaneously, the formation rate of ferric hydroxide colloid is calculated by converting the corrosion release activity according to the same molar conversion relationship, thus obtaining the formation concentration and rate of ferric hydroxide colloid. The period of excessive intrusion activity refers to the time when the iron ion corrosion release activity exceeds the threshold of 1.5 micromoles per liter. The formation rate of ferric hydroxide colloid per unit time is obtained by converting the corrosion release activity value according to the same ratio. For example, in drilling fluid stability testing, if the iron ion concentration cumulatively increases by a certain value during the period of excessive intrusion activity, the formation concentration of ferric hydroxide colloid is numerically equal to this cumulative increase according to a one-to-one molar conversion relationship. The calculation method for the formation rate is similar, directly reflecting the speed at which ferric hydroxide colloid enters the solution system. Based on the formation concentration of ferric hydroxide colloid, the surface positive charge of the positively charged ferric hydroxide colloid is determined by combining the degree of protonation of the hydroxyl groups on the surface of the ferric hydroxide colloid under alkaline conditions. Simultaneously, the surface negative charge of the negatively charged bentonite colloid is determined based on the cation exchange capacity of the bentonite particles. In an optional embodiment, the surface positive charge of the ferric hydroxide colloid is determined by the degree of protonation of its surface hydroxyl groups. Ferric hydroxide particles have a large number of hydroxyl functional groups distributed on their surface. In an alkaline solution environment, some hydroxyl groups will combine with hydrogen ions in the solution to undergo a protonation reaction, giving the particle surface a positive charge. The higher the degree of protonation, the greater the surface positive charge. This degree of protonation is closely related to the pH value of the solution; the lower the pH value, the higher the degree of protonation, and vice versa. In the slightly alkaline environment commonly found in drilling fluids and waterproofing materials, ferric hydroxide particles still maintain a certain degree of surface positive charge. It should be noted that the surface negative charge of the bentonite colloid is determined by the cation exchange capacity.Cation exchange capacity is an important indicator of the amount of negative charge on the surface of bentonite particles, reflecting the total amount of exchangeable cations that a unit mass of bentonite can adsorb. The isomorphic substitution of aluminum-oxygen octahedra in montmorillonite crystal layers creates a permanent negative charge on the crystal surface, and this negative charge density is positively correlated with the cation exchange capacity. Furthermore, dividing the product of the positive and negative charges by the square of the average distance between the two colloids yields the adsorption binding strength between them. Specifically, the adsorption binding strength between the two colloids is a core indicator for judging the degree of heterogeneous aggregation. There is a Coulomb attraction between the positively charged ferric hydroxide colloid and the negatively charged bentonite colloid. The strength of this attraction is directly proportional to the product of their surface charges and inversely proportional to the square of their average distance. When the concentration of ferric hydroxide colloid increases, the number of positively charged particles in the solution increases, increasing the probability of them encountering bentonite particles. The average distance between them decreases accordingly, and the Coulomb attraction strengthens. The higher the adsorption binding strength, the stronger the tendency for the two colloids to adhere and aggregate, and the easier it is for heterogeneous aggregation to occur. Based on the adsorption binding strength and the formation rate of ferric hydroxide colloid, the aggregation rate of positively charged ferric hydroxide colloid and negatively charged bentonite colloid ... The density of an aggregate is determined by the ratio of its particle size to the number of original particles it contains, thus obtaining the particle size, settling velocity, and density of the flocs during heterogeneous aggregation. It is understood that the settling velocity of an aggregate under gravity is related to its particle size and density. The density of an aggregate is determined by the ratio of its actual particle size to the number of original particles it contains; the smaller the ratio, the more tightly packed the same number of particles, and the denser the aggregate structure. The larger the ratio, the looser the particle arrangement and the looser the aggregate structure. Dense aggregates have a higher density and a faster settling velocity. Loose aggregates have a density close to that of the solution and a slower settling velocity. Based on the particle size, settling velocity, and density of the flocs, the spatial distribution density of the flocs at different depths in the solution is obtained by statistical analysis.Spatial distribution density, settling velocity, and compactness are used as flocculation structural characteristics of heterogeneous aggregation. Further, the quantity distribution of flocs at different depths in the solution is statistically analyzed to obtain the spatial distribution density of the flocs. Spatial distribution density, particle size growth rate, settling velocity, and compactness together constitute the flocculation structural characteristics of heterogeneous aggregation, which describes the flocculation morphology after heterogeneous aggregation of positively charged ferric hydroxide colloids and negatively charged bentonite colloids from multiple dimensions. The formation concentration of positively charged ferric hydroxide colloids and the surface charge density of negatively charged bentonite colloids are extracted. The adsorption binding strength and aggregation rate of the two colloids due to charge neutralization are analyzed to identify the particle size growth rate, settling velocity, and aggregate compactness of the flocs during heterogeneous aggregation. A quantitative description of the flocculation structure in terms of spatial distribution density and particle arrangement morphology is obtained as the flocculation structural characteristics of heterogeneous aggregation. The formation concentration of positively charged ferric hydroxide colloids is extracted, which is obtained by the cumulative increase in iron ion concentration during the period of excessive invasive activity according to the molar conversion relationship. Simultaneously, the surface charge density of negatively charged bentonite colloids is extracted. This surface charge density is determined based on the ratio of the cation exchange capacity to the specific surface area of ​​the bentonite particles. In the extraction of the flocculation structure characteristics of heterogeneous aggregation, the concentration of positively charged ferric hydroxide colloids and the surface charge density of negatively charged bentonite colloids are two core parameters. The concentration of positively charged ferric hydroxide colloids has been obtained through the aforementioned molar conversion of iron ion concentration; this value reflects the molar number of newly generated ferric hydroxide particles in the solution. The surface charge density of negatively charged bentonite colloids is directly related to its cation exchange capacity. Specifically, the cation exchange capacity is a key indicator characterizing the amount of negative charge on the surface of bentonite particles. Its determination method involves suspending bentonite in a specific cation solution, allowing the cations in the solution to replace the exchangeable cations between the bentonite crystal layers. The cation exchange capacity is obtained by measuring the total amount of cations displaced. Dividing the cation exchange capacity by the specific surface area of ​​the bentonite particles yields the amount of negative charge per unit area, which is the surface charge density. For example, in drilling fluid stability testing, bentonite from different origins exhibits significant differences in cation exchange capacity and surface charge density due to variations in montmorillonite content and isomorphic substitution. The total positive charge is calculated based on the generated concentration and the unit mass charge of the ferric hydroxide colloid, while the total negative charge is calculated based on the surface charge density and the total surface area of ​​the bentonite particles. In an optional embodiment, the total positive charge is calculated based on the generated concentration of the positively charged ferric hydroxide colloid by multiplying the generated concentration by the unit mass charge of the ferric hydroxide colloid. The unit mass charge depends on the particle size and surface protonation degree of the ferric hydroxide particles; smaller particle sizes result in larger specific surface areas and carry a greater amount of positive charge. The total negative charge is calculated by multiplying the surface charge density by the total surface area of ​​the bentonite particles, which is obtained by multiplying the mass concentration of bentonite in the solution by its specific surface area.The charge neutralization ratio is calculated by dividing the total positive charge by the total negative charge. This ratio characterizes the degree to which the positively charged ferric hydroxide colloid neutralizes the surface charge of the negatively charged bentonite colloid. It should be noted that the charge neutralization ratio is an important indicator for judging the degree of heterogeneous aggregation. The charge neutralization ratio is calculated by dividing the absolute value of the total positive charge by the total negative charge. This ratio reflects the neutralizing ability of the positively charged ferric hydroxide colloid on the surface charge of the negatively charged bentonite colloid. When the charge neutralization ratio is less than one, the total positive charge is insufficient to neutralize all the negative charge, and some negative charge remains on the surface of the bentonite particles. Although the electrostatic repulsion between particles is weakened, it still exists. When the charge neutralization ratio is close to one, the positive and negative charges are basically balanced, the electrostatic repulsion between particles disappears, and the tendency for heterogeneous aggregation reaches its peak. When the charge neutralization ratio is greater than one, the excess positive charge causes the surface charge of the particles to reverse, and electrostatic repulsion reappears between the particles. The adsorption binding strength and aggregation rate of the two colloidal particles due to charge neutralization are calculated based on the charge neutralization ratio and the average distance between the two colloidal particles in the solution. In one embodiment, the adsorption binding strength is calculated based on the charge neutralization ratio and the average distance between the two colloidal particles. The average distance depends on the number concentration of the two colloidal particles in the solution; the higher the particle number concentration, the smaller the average distance. The adsorption binding strength is positively correlated with the charge neutralization ratio and inversely correlated with the square of the average distance. When the charge neutralization ratio is close to one and the average distance is small, the adsorption binding strength reaches a high level. The aggregation rate is determined by both the adsorption binding strength and the particle collision frequency. Based on the aggregation rate, the particle size of the flocs at different times during heterogeneous aggregation is tracked, and the difference between the particle size values ​​at adjacent times is calculated to obtain the particle size growth rate. The time taken for the flocs to sink from the solution surface to a preset depth is recorded and converted into the settling velocity. Optionally, the particle size growth rate of the flocs is tracked using dynamic light scattering or a laser particle size analyzer. The average particle size of the flocs is measured at different times, and the difference between the particle size values ​​at adjacent times is the particle size growth rate. The settling velocity is determined by recording the time it takes for the flocs to sink from the solution surface to a predetermined depth. The settling velocity is positively correlated with the particle size and density of the flocs. The density of the aggregates is determined by the ratio of the measured particle size of the flocs to the number of original colloidal particles they contain. It is understood that determining the density of the aggregates is fundamental to determining the particle arrangement morphology. Density is obtained by the ratio of the measured particle size of the flocs to the number of original colloidal particles they contain. A smaller ratio indicates that the same number of particles are packed in a smaller space, indicating dense packing. A larger ratio indicates loose particle distribution, indicating loose packing. Densely packed flocs have a higher density and a faster settling velocity, while loosely packed flocs have a density close to the solution's settling velocity and a slower settling velocity. Based on the particle size increase, settling velocity, and density, the spatial distribution density is obtained by statistically analyzing the number and volume percentage of flocs in different depth ranges of the solution.Based on the degree of compactness, the particle arrangement is determined to be either dense or loosely packed. The spatial distribution density and particle arrangement morphology are used as characteristics of the heterogeneous aggregation flocculation structure. Further, the spatial distribution density is obtained by statistically analyzing the number and volume percentage of flocs in different depth ranges of the solution; this density reflects the stratification state of the flocs under gravity. Integrating the spatial distribution density and particle arrangement morphology forms a quantitative description of the heterogeneous aggregation flocculation structure characteristics, encompassing both the spatial distribution pattern of the flocs and the internal structural compactness. In step S104, based on the heterogeneous aggregation flocculation structure characteristics, the Zeta potential is baseline-restored with reference to the intrinsic decay baseline of the bentonite colloid Zeta potential. The portion of the accelerated decay deviating from zero in the baseline-restored Zeta potential that exceeds the intrinsic decay range of the bentonite colloid is marked as an intriguing deviation caused by heterogeneous aggregation. In the process of assessing the stability of bentonite colloids, the intrinsic decay baseline is an important reference for distinguishing between the deterioration of the bentonite's own structure and the influence of external interference factors. Based on the flocculation structure characteristics of heterogeneous aggregation, the natural decay curve of the Zeta potential of bentonite colloid under dissolved oxygen-free conditions is obtained over time. This natural decay curve is used as the intrinsic decay baseline of the Zeta potential of bentonite colloid. The intrinsic decay baseline reflects the trend of a gradual decrease in the absolute value of the Zeta potential caused by the slow deterioration of the bentonite colloid's own structure. For example, in drilling fluid stability testing, a set of bentonite suspensions with the same proportions as the test sample are prepared in advance and placed in a sealed container under nitrogen protection for control testing. The change curve of the Zeta potential over time is recorded, and this curve is the intrinsic decay baseline. Under these conditions, there is no dissolved oxygen infiltration; therefore, the change in Zeta potential is only caused by the slow deterioration of the bentonite's own crystal structure. In an optional embodiment, the correction of the intrinsic decay baseline includes two steps: translation correction and slope scaling correction. The intrinsic attenuation baseline is shifted and corrected based on the spatial distribution density of the flocculated structure. Higher spatial distribution density indicates a denser distribution of flocs in the solution, resulting in greater background interference to the Zeta potential measurement. Consequently, the intrinsic attenuation baseline is shifted towards zero. Simultaneously, the slope of the intrinsic attenuation baseline is scaled and corrected based on the density, yielding the corrected intrinsic attenuation baseline. For densely packed flocs, the influence on the Zeta potential accumulates rapidly over time, leading to a correspondingly larger slope of the intrinsic attenuation baseline. For loosely packed flocs, the influence accumulates more slowly, resulting in a correspondingly smaller slope. It should be noted that the purpose of baseline restoration is to remove the contribution of bentonite's own structural degradation from the measured Zeta potential data, retaining only the potential changes caused by external factors. Based on the corrected intrinsic attenuation baseline, the noise-reduced bentonite colloidal Zeta potential monitoring data is compared with the corrected intrinsic attenuation baseline time-by-time, extracting the deviation of the measured Zeta potential value at each time point from the corresponding value of the corrected intrinsic attenuation baseline. The deviation is subtracted from the measured Zeta potential value to obtain the Zeta potential sequence after baseline restoration.Specifically, the baseline-restored Zeta potential sequence reflects the potential state after excluding its own degradation factors. For this sequence, the rate of deviation of the Zeta potential towards zero is calculated time-by-time, and this deviation rate is compared with a preset intrinsic decay range threshold. The intrinsic decay range threshold is set based on the potential fluctuation amplitude of bentonite colloid under normal conditions. In one embodiment, for the baseline-restored Zeta potential sequence, time periods in which the deviation towards zero occurs at a rate exceeding the preset intrinsic decay range threshold are identified. If the rate of deviation of the baseline-restored Zeta potential towards zero exceeds the intrinsic decay range threshold within a certain time period, the Zeta potential change within that time period is marked as an intrinsic deviation phenomenon caused by heterogeneous aggregation. This intrinsic deviation phenomenon characterizes the accelerated decay of the Zeta potential caused by heterogeneous aggregation of positively charged ferric hydroxide colloid and negatively charged bentonite colloid. Step S105: Based on the identification results of the extrinsic deviation phenomenon, the oxidative corrosion promoting characteristics of dissolved oxygen are incorporated into the dynamic update of the stability termination judgment condition, and applied to the Zeta potential after baseline restoration. The time span during which the Zeta potential decays to the termination judgment condition is calculated to obtain a preliminary assessment of the duration of bentonite colloidal stability. In the preliminary assessment of the duration of bentonite colloidal stability, the oxidative corrosion promoting characteristics of dissolved oxygen are a key factor affecting the accuracy of the assessment. Based on the identification results of the extrinsic deviation phenomenon, the cumulative increment of dissolved oxygen concentration during the period of the extrinsic deviation phenomenon is extracted, and this cumulative increment is used as an index of the oxidative corrosion promoting characteristics of dissolved oxygen. This cumulative increment reflects the total amount of dissolved oxygen participating in the oxidation reaction after penetrating the solution. For example, in drilling fluid stability testing, if the extrinsic deviation phenomenon lasts for several hours, and the dissolved oxygen concentration rises from the initial value to a certain peak and then tends to stabilize during this period, then the cumulative increment is the difference between the peak value and the initial value. In one optional implementation, a preset stability termination threshold is dynamically updated based on the oxidation-corrosion promoting characteristic index, where the stability termination threshold is the lower limit of the absolute value of the Zeta potential. The promoting characteristic benchmark value is a pre-set reference value, characterizing the average intensity of the oxidation reaction induced by dissolved oxygen infiltration under typical test conditions. If the oxidation-corrosion promoting characteristic index exceeds the preset promoting characteristic benchmark value, the stability termination threshold is adjusted upwards according to the ratio of the oxidation-corrosion promoting characteristic index to the promoting characteristic benchmark value, resulting in an updated stability termination threshold. The adjusted threshold is more stringent, ensuring that the colloid is determined to have reached a stability termination state at a relatively high absolute value of the Zeta potential. It should be noted that the stability termination threshold characterizes the critical potential state at which bentonite colloids lose their dispersion stability. When the absolute value of the Zeta potential is below this threshold, the electrostatic repulsion between particles is insufficient to resist van der Waals attraction, and the colloid begins to aggregate. The updated stability termination threshold is applied to the baseline-restored Zeta potential sequence, and the decay process of the absolute value of the Zeta potential is tracked hourly, starting from the beginning of the baseline-restored Zeta potential sequence.Specifically, it is determined whether the absolute value of the Zeta potential at each moment is lower than the updated stability termination threshold, and the moment when the absolute value of the Zeta potential first falls below the stability termination threshold is recorded as the stability termination moment. Based on the difference between the stability termination moment and the starting moment of the baseline-restored Zeta potential sequence, the time span during which the Zeta potential decays to the stability termination threshold is calculated, and this time span is used as a preliminary assessment result of the duration of bentonite colloid stability. Further, the starting moment and cumulative deviation amplitude of intriguing deviation phenomena are retrieved, and the intensity of the oxidation-promoting effect of dissolved oxygen concentration on the continuous generation of ferric hydroxide colloid is analyzed to identify the remaining margin and expected decay time of the baseline-restored Zeta potential decaying from its current state to the stability termination threshold. The starting moment is the sampling moment when the rate of deviation to zero in the baseline-restored Zeta potential sequence first exceeds the intrinsic decay range threshold, marking the beginning of significant charge neutralization between positively charged ferric hydroxide colloid and negatively charged bentonite colloid. The cumulative deviation amplitude is the sum of the decrease in the absolute value of the baseline-restored Zeta potential from the starting moment to the current moment. The average deviation rate of the intriguing deviation is obtained by dividing the cumulative deviation amplitude by the duration from the start time to the current time. A larger cumulative deviation amplitude indicates a stronger charge neutralization effect of the positively charged ferric hydroxide colloid on the negatively charged bentonite colloid. The average deviation rate characterizes the average rate of decrease in the absolute value of the Zeta potential during heterogeneous aggregation. Based on the average deviation rate, the cumulative increment of dissolved oxygen concentration within the duration of the intriguing deviation phenomenon is extracted, and the ratio of the cumulative increment to the duration is taken as the dissolved oxygen infiltration rate per unit time. The ratio of the infiltration rate per unit time to the average deviation rate is taken as the intensity of the oxidation-promoting effect of dissolved oxygen concentration on the continuous generation of ferric hydroxide colloid, and the intensity of the oxidation-promoting effect characterizes the degree of Zeta potential deviation caused by the unit dissolved oxygen infiltration rate. Based on the intensity of the oxidation-promoting effect, the difference between the absolute value of the Zeta potential at the current time after baseline restoration and the updated stability termination threshold is obtained as the residual margin. A larger residual margin indicates that the current state of the bentonite colloid is further from the instability critical point. Dividing the remaining margin by the average deviation rate yields the expected decay time of the Zeta potential after baseline restoration from its current state to the stability termination threshold. Based on the expected decay time and the elapsed time from the start of the eigenvalue deviation to the current time, the total time span from the start of the test to the expected reaching of the stability termination threshold is calculated. This total time span is used as a preliminary assessment result of the duration of bentonite colloid stability. This result comprehensively considers the occurrence time of the eigenvalue deviation, the current deviation state, the intensity of the oxidation-promoting effect, and the remaining margin. Step S106 involves cross-validating the preliminary assessment of the duration of bentonite colloid stability with the flocculation structure characteristics of heterogeneous aggregation to determine the instability state of the bentonite colloid, and outputting the assessment result of the duration of bentonite colloid stability.In the final assessment of the duration of bentonite colloidal stability, cross-validation is a crucial step in confirming that intriguing deviations have been identified. Preliminary assessment results of the duration of bentonite colloidal stability are obtained along with the flocculation structure characteristics of heterogeneous aggregation, where the flocculation structure characteristics are derived from experimental observations of the heterogeneous aggregation process. The predicted instability time based on Zeta potential decay is determined based on the total time span in the preliminary assessment results. Simultaneously, the predicted time when the flocs complete settling is determined based on the ratio of settling velocity to solution depth in the flocculation structure characteristics. Cross-validation is achieved by comparing the instability prediction results of these two independent dimensions: one based on the decay trend of Zeta potential, and the other based on the settling behavior of the flocs. For example, in drilling fluid stability testing, the predicted instability time based on Zeta potential decay is obtained by adding the test start time to the total time span in the preliminary assessment results. The predicted time based on floc settling is obtained by dividing the effective depth of the solution container by the settling velocity in the flocculation structure characteristics; this time characterizes the predicted time point when the flocs completely settle from the solution surface to the bottom of the container. In one optional implementation, the time difference between two predicted moments is calculated to obtain the cross-validation deviation of the instability state. This deviation reflects the degree of agreement between predictions based on electrochemical characteristics and predictions based on physical sedimentation characteristics. If the instability moments obtained by the two independent prediction methods are similar, it indicates that the change in Zeta potential and the formation of flocs are consistent on a time scale. Based on the cross-validation deviation, if the deviation is within a preset consistency tolerance range, it is determined that the preliminary evaluation result is consistent with the floc structure characteristics, confirming that the non-intrinsic deviation phenomenon has been identified, and a confirmation mark indicating that cross-validation has passed is obtained. The consistency tolerance range is set to twice the sampling period; for example, if the sampling period is one hour, the tolerance is two hours. It should be noted that the confirmation mark indicating that cross-validation has passed is a prerequisite for outputting the final evaluation result. Based on the confirmation mark indicating that cross-validation has passed, the preliminary evaluation result of the duration of bentonite colloid stability is output as the final evaluation result. The final evaluation result characterizes the duration for which the bentonite colloid maintains a dispersed and stable state under the current test conditions. The final evaluation results are presented in the form of time values, which can serve as a quantitative indicator for evaluating material performance in drilling fluid formulation optimization and waterproofing material quality control. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications and substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for evaluating the duration of colloidal stability of bentonite, characterized in that, The method includes: Dissolved oxygen concentration and iron ion concentration in the solution were monitored. Simultaneously, Zeta potential data of bentonite colloids were acquired using a Zeta potential meter, and the acquired data were denoised. The invasive activity of dissolved oxygen in the solution was analyzed based on the denoised dissolved oxygen concentration, and the time period when the dissolved oxygen invasive activity exceeded a preset criterion was identified. Based on the relationship between the corrosion release activity of iron ions and the increased dissolved oxygen level during this period, it was confirmed that iron ions hydrolyze under high pH conditions to form ferric hydroxide colloids. The formation state of ferric hydroxide colloids was inferred from the corrosion release activity of iron ions. The flocculation morphology of heterogeneous aggregation of positively charged ferric hydroxide colloids and negatively charged bentonite colloids in the solution was analyzed, and the flocculation structure characteristics of heterogeneous aggregation were obtained. Based on the flocculation structure characteristics of heterogeneous aggregation, and referring to the Zeta potential of bentonite colloids... The intrinsic decay baseline of the ta potential is used to restore the Zeta potential. The portion of the accelerated decay towards zero in the restored Zeta potential that exceeds the intrinsic decay range of bentonite colloid is marked as an intrinsic deviation phenomenon caused by heterogeneous aggregation. Based on the identification results of the intrinsic deviation phenomenon, the oxidative corrosion promoting characteristics of dissolved oxygen are incorporated into the dynamic update of the stability termination judgment condition and applied to the restored Zeta potential. The time span during which the Zeta potential decays to the termination judgment condition is calculated to obtain a preliminary assessment of the duration of bentonite colloid stability. The preliminary assessment of the duration of bentonite colloid stability is cross-validated with the flocculation structure characteristics of heterogeneous aggregation to determine the instability state of bentonite colloid, and the assessment result of the duration of bentonite colloid stability is output.

2. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The monitoring of dissolved oxygen concentration and iron ion concentration in the solution, along with the acquisition of Zeta potential monitoring data of bentonite colloid using a Zeta potential meter, includes: A continuous signal of dissolved oxygen concentration in the solution is obtained by a dissolved oxygen probe, a signal of change in iron ion concentration in the solution is collected by an iron ion sensor, and a zeta potential measurement signal of bentonite colloid is obtained by a potentiometer. The lowest sampling frequency among the dissolved oxygen probe, the iron ion sensor and the potentiometer is used as a unified time reference interval. Signals with sampling frequencies higher than this time reference interval are downsampled in an equal-interval decimation manner to obtain three sets of original time-series data after frequency synchronization.

3. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The analysis of dissolved oxygen intrusion activity in solution based on the denoised dissolved oxygen concentration includes: Based on the denoised dissolved oxygen concentration data, the difference in dissolved oxygen concentration between adjacent sampling times is calculated and divided by the sampling time interval to obtain the rate of change of dissolved oxygen concentration. This rate of change is used as the invasive activity of dissolved oxygen in the solution. The invasive activity is compared with a preset activity criterion. If the invasive activity exceeds the preset activity criterion, the sampling time is marked as a high invasive activity time. Consecutive high invasive activity times constitute an invasive activity exceeding the standard period. The denoised iron ion concentration data corresponding to the invasive activity exceeding the standard period is extracted, and the ratio of the cumulative increase of iron ion concentration in that period to the duration of the period is calculated to obtain the corrosion release activity of iron ions.

4. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The method of confirming that iron ions undergo hydrolysis and generate ferric hydroxide colloid under high pH conditions based on the relationship between the corrosion release activity of iron ions and the increase in dissolved oxygen during this period includes: if the corrosion release activity of iron ions and the intrusion activity of dissolved oxygen show a synchronous response, then combined with the solution pH data collected by the pH sensor and processed by noise reduction, it is confirmed that iron ions undergo hydrolysis reaction and generate ferric hydroxide colloid under high pH conditions.

5. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The method of inferring the formation state of ferric hydroxide colloid by the corrosion release activity of iron ions, and analyzing the flocculation morphology of heterogeneous aggregation of positively charged ferric hydroxide colloid and negatively charged bentonite colloid in solution, includes: Based on the corrosion release activity of iron ions and the pH conditions of the solution, the formation state of ferric hydroxide colloid is inferred. The formation concentration of ferric hydroxide colloid is calculated by converting the cumulative increase in iron ion concentration during the period of excessive invasive activity, according to the molar conversion relationship of one iron ion hydrolyzing to form one ferric hydroxide molecule. The formation rate of ferric hydroxide colloid is calculated by converting the corrosion release activity of iron ions according to the same molar conversion relationship, thus obtaining the formation concentration and formation rate of ferric hydroxide colloid. Based on the formation concentration of ferric hydroxide colloid, the surface positive charge of positively charged ferric hydroxide colloid is determined by combining the degree of protonation of hydroxyl groups on the surface of ferric hydroxide colloid under alkaline conditions. Simultaneously, the surface negative charge of negatively charged bentonite colloid is determined based on the cation exchange capacity of bentonite particles. The adsorption binding strength between the two colloids is obtained by dividing the product of the surface positive charge of positively charged ferric hydroxide colloid and the surface negative charge of negatively charged bentonite colloid by the square of the average distance between the two colloids. Based on the adsorption binding strength and the formation rate of ferric hydroxide colloid, the aggregation rate of positively charged ferric hydroxide colloid and negatively charged bentonite colloid ...

6. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The portion of the accelerated decay towards zero in the baseline-restored Zeta potential that exceeds the intrinsic decay range of bentonite colloids is marked as an intrinsic deviation phenomenon caused by heterogeneous aggregation, including: Identify the time periods in the baseline-restored Zeta potential sequence that deviate towards zero at a rate exceeding a preset intrinsic decay range threshold, and mark the Zeta potential changes within these time periods as intriguing deviations caused by heterogeneous aggregation.

7. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, Based on the identification results of non-intrinsic deviation phenomena, the oxidative corrosion promoting characteristics of dissolved oxygen are incorporated into the dynamic update of the stability termination criteria. An application is made to the Zeta potential after baseline reduction, and the time span during which the Zeta potential decays to the termination criteria is calculated to obtain a preliminary assessment of the duration of bentonite colloidal stability, including: Based on the identification results of extrinsic deviations, the cumulative increase in dissolved oxygen concentration during the period of occurrence of the extrinsic deviation is extracted. This cumulative increase is used as an indicator of the oxidative corrosion promoting characteristics of dissolved oxygen. A preset stability termination threshold is dynamically updated based on this indicator. The stability termination threshold is the lower limit of the absolute value of the Zeta potential. If the oxidative corrosion promoting characteristic indicator exceeds a preset promoting characteristic benchmark value, the stability termination threshold is adjusted upwards according to the ratio of the oxidative corrosion promoting characteristic indicator to the promoting characteristic benchmark value, resulting in an updated stability termination threshold. The updated stability termination threshold is then applied to... The Zeta potential sequence after baseline restoration is used to track the decay process of the absolute value of the Zeta potential at each time step, starting from the beginning of the baseline restored Zeta potential sequence. It is determined whether the absolute value of the Zeta potential at each time step is lower than the updated stability termination threshold. The moment when the absolute value of the Zeta potential first falls below the stability termination threshold is recorded as the stability termination moment. Based on the difference between the stability termination moment and the beginning of the baseline restored Zeta potential sequence, the time span during which the Zeta potential decays to the stability termination threshold is calculated. This time span is used as a preliminary assessment result of the duration of bentonite colloidal stability.

8. The method for evaluating the duration of bentonite colloidal stability according to claim 1, characterized in that, The evaluation result of the duration of bentonite colloidal stability includes: outputting the preliminary evaluation result of the duration of bentonite colloidal stability as the final evaluation result based on the confirmation mark of cross-validation, wherein the final evaluation result characterizes the duration of time that the bentonite colloidal maintains a dispersed and stable state under the current test conditions.

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