Intelligent determination method for grouting time between frozen shaft walls based on multi-source information fusion

Abstract

The application discloses a frozen well shaft wall interlayer grouting opportunity intelligent judgment method based on multi-source information fusion, and relates to the technical field of mine construction; through the multi-source monitoring unit arranged on the inner layer well wall, the interlayer and the outer layer well wall, four types of parameters of the frozen wall thermal state, the interlayer hydrology, the well wall structure response and the construction state are collected, and after pretreatment, four intermediate characteristic quantities of the frozen wall remelting index, the water seepage risk index, the structure sensitive index and the grouting suitable index are constructed; the four characteristic quantities are weighted and fused to obtain the opportunity judgment value, and compared with the preset judgment interval; if the judgment value is lower than the lower limit, the output is the instruction of not grouting for the time being, and the monitoring frequency is encrypted in stages; if it is in the interval, the output is the instruction of starting the interlayer grouting, the grouting is executed according to the standard parameters, and real-time monitoring is carried out; if it is higher than the upper limit, the output is the emergency grouting instruction, the reinforced pressure parameters and the multi-mode emergency grouting process are adopted, and the auxiliary measures are linked to quickly seal.

Description

Technical Field

[0001] This invention relates to the field of mine construction technology, specifically to an intelligent method for determining the timing of grouting between frozen shaft walls based on multi-source information fusion. Background Technology

[0002] In mine construction, the freezing method is a common technique for drilling deep topsoil layers. The shaft typically employs a double-wall structure, consisting of inner and outer walls. Once the frozen wall begins to thaw, the original impermeable curtain disappears, and water-bearing layers can form seepage channels through the construction joints of the outer wall. Therefore, selecting the optimal timing for inter-wall grouting is crucial for ensuring shaft safety and forming a unified load-bearing structure between the inner and outer walls. If grouting is done too early, the frozen wall has not yet fully thawed, resulting in insufficient grout diffusion and limited grouting effectiveness; if grouting is done too late, seepage or even a sudden water inrush may have already occurred. Summary of the Invention

[0003] To address the problems in related technologies, this invention provides an intelligent method for determining the timing of grouting between frozen well walls based on multi-source information fusion, thereby overcoming the aforementioned technical problems in existing related technologies.

[0004] To solve the aforementioned technical problem, the present invention is achieved through the following technical solution: an intelligent determination method for the timing of grouting between frozen well walls based on multi-source information fusion, comprising the following steps:

[0005] Step 1: Collect frozen wall thermal state parameters, inter-wall hydrological parameters, well wall structural response parameters, and construction status parameters according to the sampling cycle;

[0006] Step 2: Based on the thermal state parameters of the frozen wall, the hydrological parameters between the walls, the structural response parameters of the well wall, and the construction state parameters, four intermediate characteristic quantities are constructed: the thawing index of the frozen wall, the seepage risk index, the structural sensitivity index, and the grouting suitability index.

[0007] Step 3: Weighted fusion of the intermediate feature quantities to obtain the timing determination value, compare the timing determination value with the preset determination interval, and output a command to temporarily stop grouting, start wall grouting, or emergency grouting based on the comparison result, and adjust the sampling cycle to update Step 1 in a coordinated manner.

[0008] Step four: Based on the received grouting instructions, perform corresponding grouting monitoring and control.

[0009] Preferably, the thermal state parameters of the frozen wall include the temperature at each temperature monitoring point and the aquifer thickness at the location of the temperature monitoring point; the hydrological parameters between the walls include the water level between the walls, pore water pressure, and seepage flow rate; the structural response parameters of the well wall include the strain at each stress monitoring point, the joint opening, and the spacing of symmetrical positions of the wellbore; and the construction state parameters include the thickness of the space between the walls.

[0010] The preferred method for constructing the freeze-wall melting index is as follows:

[0011] Location-related weights are assigned based on the radial position of temperature monitoring points within the frozen wall, and depth-related weights are assigned based on the ratio of the aquifer thickness to the total frozen layer thickness at each temperature monitoring point. The location-related weights and depth-related weights are multiplied and normalized to obtain the base weights. A dynamic factor is then constructed based on the temperature change rate at each monitoring point, and this dynamic factor is multiplied by the base weights and normalized to obtain the final weights. Based on the temperature, freezing critical temperature, and reference temperature at each monitoring point, the frozen wall thaw index is calculated using a weighted average. Specifically, this includes:

[0012] Extract the temperature T at each temperature monitoring point. i 'i' represents the index of the temperature monitoring point; in the initial stage, each temperature monitoring point is assigned a location-related weight. The location-related weight is determined by spatial position, with the rule being that the closer the temperature monitoring point is to the frozen wall area inside the well wall, the greater the corresponding location-related weight. In this embodiment, if temperature monitoring point i is located in the inner well wall, which is the key monitoring area closest to the potential seepage channel, the location-related weight ranges to 0.5. If temperature monitoring point i is located in the interlayer between the inner and outer well walls, which is the direct space for grout diffusion, the location-related weight ranges to 0.3. If temperature monitoring point i is located in the outer well wall, indicating that it is close to the undisturbed layer, the location-related weight is 0.2. Then, a depth-related weight is assigned to monitoring point i based on its depth. Obtain the aquifer thickness at monitoring point i and the total thickness of the entire frozen layer, and denote them as H. w And H; the specific formula for calculating the depth-related weights is:

[0013]

[0014] Where k1 is the depth adjustment coefficient, with a value range between 0.5 and 1, used to control the magnitude of dynamic correction and avoid over-adjustment; then the position-related weight and depth-related weight of each temperature monitoring point i are multiplied to obtain the basic weight of each temperature monitoring point due to its location, and the basic weight of all temperature monitoring points is normalized so that the sum of their weights is one.

[0015] Based on the basic weights of each temperature monitoring point i, the weights are dynamically updated in each sampling period; specifically, this includes calculating the temperature change rate of each temperature monitoring point i and constructing a dynamic factor using a formula. :

[0016]

[0017] Where k2 is the temperature rate adjustment coefficient, ranging from 0.3 to 0.8, used to control the contribution of aquifer thickness to the weighting, v i Let v represent the rate of temperature change at temperature monitoring point i, and max(v) represent the maximum rate of temperature change among all monitoring points; then, the dynamic factor of each temperature monitoring point i... Multiplying by its corresponding base weight yields the dynamic weight. Finally, the dynamic weights of all temperature monitoring points i are normalized to obtain the final weight. ;

[0018] Real-time acquisition of temperature T at each temperature monitoring point i，以及 The freezing critical temperature and the reference temperature close to the natural stratum temperature are used to calculate the freeze-thaw index F for each temperature monitoring point i using the following formula:

[0019]

[0020] Where T f The freezing critical temperature (T) is the critical temperature used to characterize the transition of soil from a frozen state to a thawed state. It is generally taken as 0℃ or a freezing temperature corrected for geological conditions. n It serves as a reference temperature close to the natural formation temperature, used to characterize the state of the frozen wall after complete thawing, which is close to the original formation temperature. It can usually be taken as the stable formation temperature of the area or the maximum temperature value in the monitoring data.

[0021] The preferred method for constructing the seepage risk index is as follows:

[0022] The seepage risk index is obtained by weighted summation of inter-wall water level, pore water pressure, seepage flow rate, and seepage increment per unit time. The seepage increment per unit time is calculated as the ratio of the difference in seepage flow rate between two adjacent sampling times to the time difference. Specifically, it includes:

[0023] The seepage increment is obtained by subtracting the seepage flow rate from the previous time from the current time. This increment is then divided by the time difference between the current and previous times to obtain the seepage increment per unit time. When the seepage increment per unit time is greater than zero, it indicates that the seepage is increasing and seepage channels may be forming or expanding. When the seepage increment per unit time is equal to zero, it indicates that the seepage is basically stable. When the seepage increment per unit time is less than zero, it indicates that the seepage is decreasing.

[0024] The seepage risk index S is obtained by calculating the inter-wall water level, pore water pressure, seepage flow rate, and seepage increment per unit time. The calculation formula is as follows:

[0025]

[0026] Where L is the inter-wall water level, P is the pore water pressure, Q is the seepage flow rate at the current time, and ΔQ is the seepage increment per unit time; b1, b2, b3, and b 4分别为 The corresponding weight coefficients satisfy b1+b2+b3+b4=1.

[0027] The preferred method for constructing the structural sensitivity index is as follows:

[0028] The strain at multiple stress monitoring points on the outer wellbore is acquired, and the original structural strain value is calculated using the root mean square method. The current spacing between symmetrical positions in the wellbore is acquired, and the original wellbore convergence value is calculated based on the initial spacing. The current joint opening is acquired, and the original joint opening value is calculated based on the initial opening value. The original structural strain value, the original wellbore convergence value, and the original joint opening value are normalized and then weighted and summed to obtain the structural sensitivity index. Specifically, this includes:

[0029] Extract the strain ε at each stress monitoring point j The parameters are: wellbore convergence amount u, and joint opening change amount δ, where j represents the strain monitoring point index. To avoid excessive interference from single-point anomalies, the strain values ​​of multiple strain monitoring points can be summarized to obtain the original structural strain value ε. raw The calculation formula is:

[0030]

[0031] Where m represents the total number of stress monitoring points. This represents the initial strain reference value at stress monitoring point j;

[0032] Extract the current spacing of the symmetrical position of the wellbore, subtract the current spacing from the initial spacing of the symmetrical position of the wellbore, and then divide by the initial spacing to obtain the original convergence value of the wellbore;

[0033] Extract the current joint opening, subtract the initial opening from it, and then divide it by the initial opening to obtain the original value of the joint opening;

[0034] Since the changes in strain, convergence, and joint opening are of different orders of magnitude, normalization is required to obtain the standard values ​​of structural strain, wellbore convergence, and joint opening. These are then weighted and summed to calculate the structural sensitivity index G. The calculation formula is as follows:

[0035]

[0036] Where c1, c2 and c3 represent the weighting coefficients of strain, convergence amount and joint opening change amount, respectively, and satisfy c1+c2+c3=1.

[0037] The preferred method for constructing the grouting suitability index is as follows:

[0038] The thickness adaptation factor is calculated based on the inter-wall space thickness; the temperature suitability factor is calculated based on the local temperature within the inter-wall; an effective diffusion radius prediction model is constructed based on preset grouting pressure, preset grout viscosity, preset formation permeability coefficient, and preset grouting duration, and the grout diffusion factor is obtained by dividing the effective diffusion radius by the target diffusion radius; the grouting suitability index is obtained by weighted fusion of the thickness adaptation factor, temperature suitability factor, and grout diffusion factor; specifically including:

[0039] Extract the inter-wall space thickness and convert it into a thickness adaptation factor Y using a formula. D The calculation formula is:

[0040]

[0041] Where D opt The optimal inter-wall space thickness is determined empirically, with Dmax and Dmin being the upper and lower limits of the allowable range, respectively.

[0042] The temperatures at various monitoring points within the wall were acquired, and the average value was calculated to obtain the local temperature. To reflect the suitability of the local temperature for grouting, the temperature suitability factor Y was calculated using a formula. T The calculation formula is:

[0043]

[0044] Where T is the local temperature between the walls, T opt The optimal temperature for slurry diffusion is Tmax, and Tmin is the upper and lower limits of the allowable temperature, respectively.

[0045] The diffusion process of the slurry in the inter-wall medium is approximated as a radial seepage expansion process, and a prediction model for the effective diffusion radius is constructed:

[0046]

[0047] Where λ is the model correction coefficient, Z is the preset grouting pressure, is the effective confining pressure or equivalent back pressure of the formation, μ is the preset grout viscosity, K is the preset formation permeability coefficient, and C is the preset grouting duration; the effective diffusion radius within the grouting time per unit time is predicted, and the target diffusion radius required to complete the inter-wall sealing is determined through trial injection experiments. The grout diffusion factor is obtained by dividing the effective diffusion radius by the target diffusion radius.

[0048] A weighting factor is assigned to each of the thickness adaptation factor, temperature suitability factor, and grout diffusion factor, and the sum of the weighting factors is one. The grouting suitability index Y is obtained by weighted fusion calculation of the thickness adaptation factor, temperature suitability factor, and grout diffusion factor using the assigned factors.

[0049] Preferably, in step three, the preset judgment interval includes a lower limit and an upper limit, which correspond to the opening and closing boundaries of the grouting window, respectively; when the timing judgment value is less than the lower limit of the interval, a command to temporarily stop grouting is output, and the monitoring frequency is encrypted using a graded incremental method.

[0050] Preferably, the monitoring frequency is increased in a tiered manner:

[0051] Let the basic sampling period be Δt0, and m be the cumulative number of consecutive outputs of the "temporarily not grouting" command. Then the formula for calculating the sampling period is:

[0052]

[0053] When m≥5, the sampling period is fixed. When the timing judgment value exceeds the upper limit of the interval, an emergency grouting command is output, and the monitoring frequency is increased accordingly. .

[0054] Preferably, in step four, when a command to start wall grouting is received, the grouting working pressure, final grouting pressure, initial setting time of grout, two-liquid grout ratio, and multi-hole grouting sequence are automatically calculated based on the current monitoring data, and the grouting pressure and grouting flow rate curves are monitored in real time during the grouting process; when an emergency grouting command is received, emergency grouting parameters are automatically pushed and grouting is performed using methods such as segmented, graded pressurization, dual-pump linkage, or multi-hole synchronous grouting.

[0055] The present invention has the following beneficial effects:

[0056] 1. The raw monitoring data is further transformed into the frozen wall thawing index, seepage risk index, structural sensitivity index, and grouting suitability index, completing the transformation from raw parameters to engineering criteria. Among them, the frozen wall thawing index, through location-related weights, depth-related weights, and a dynamic correction mechanism based on the rate of temperature change, gives higher influence weights to monitoring points near potential seepage channels and active thawing zones, improving the accuracy of identifying frozen wall failure trends. The seepage risk index jointly characterizes the inter-wall water level, pore water pressure, seepage flow rate, and seepage increment per unit time, enabling earlier detection of signs of seepage channel formation. The structural sensitivity index incorporates changes in strain, convergence, and joint opening into a unified evaluation, directly reflecting whether the well wall structure has entered an unfavorable stress stage. The grouting suitability index combines the thickness of the inter-wall space, local temperature, and grout diffusion capacity, ensuring that grouting judgment is related to both risk and construction feasibility, thereby improving the pertinence and reliability of subsequent fusion judgments.

[0057] 2. The four types of features are further integrated into a timing judgment value, and a hierarchical control system based on a dual-threshold judgment range is adopted to upgrade the grouting timing judgment from a single-point threshold judgment to a multi-factor collaborative decision-making. When the timing judgment value is below the lower limit, it is identified that the frozen wall has not fully thawed, avoiding premature grouting that would result in insufficient grout diffusion. When the timing judgment value is within the range, it is identified as the optimal grouting window, and grouting is carried out in a timely manner when the frozen wall begins to weaken but seepage has not yet developed significantly. When the timing judgment value is above the upper limit, it is identified as a significant increase in the risk of seepage or sudden water inrush, and emergency treatment can be initiated immediately. At the same time, the sampling cycle in the state of not grouting is shortened in stages, so as to achieve a synchronous increase in monitoring frequency and risk evolution, enhance the ability to capture critical changes, and avoid missing the optimal window.

[0058] 3. The two types of commands—initiating inter-wall grouting and emergency grouting—are mapped to differentiated grouting parameters and execution strategies, enabling direct conversion of judgment results into on-site construction actions. During normal initiation, the working pressure and final pressure are automatically generated based on hydrostatic pressure, and the initial setting time of the grout and the two-component grout ratio are pushed in conjunction with the rate of change of inter-wall temperature and water pressure, balancing grout diffusivity and early curing capability. By advancing the multi-hole grouting sequence from low-water-pressure holes to high-water-pressure holes, grout backflow and localized grout leakage are reduced, improving the uniformity of inter-wall filling. During the grouting process… Real-time monitoring of the pressure-flow curve and early warning mechanisms for pipe blockage and grout leakage enable timely identification and correction of abnormal operating conditions. Termination conditions are based on both pressure stabilization time and zero seepage, ensuring that the grouting effect reaches the expected level before ending the operation. In emergency mode, the upper limit of pressure is increased, the grouting interval is shortened, and segmented, staged, and graded pressurization and dual-pump linkage or multi-hole synchronous grouting methods are adopted. When necessary, drainage, pressure relief, and temporary support measures are linked to quickly seal the seepage channel when the risk increases significantly, thereby improving wellbore safety and emergency response capabilities.

[0059] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0060] To more clearly illustrate the technical solutions of the embodiments of the invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For those skilled in the art, the drawings can be obtained from these drawings without creative effort.

[0061] Figure 1 The flowchart of the intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion is provided for the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] Application Scenario: In mine construction, the freezing method is a common technique for drilling through deep topsoil layers. The shaft typically employs a double-wall structure, consisting of inner and outer walls. Once the frozen wall begins to thaw, the original impermeable curtain disappears, and aquifers can form seepage channels through the construction joints of the outer wall. Therefore, selecting the optimal timing for interwall grouting is crucial for ensuring shaft safety and ensuring the inner and outer walls form a unified load-bearing structure. If grouting is done too early, the frozen wall has not fully thawed, resulting in insufficient grout diffusion and limited grouting effectiveness; if grouting is done too late, seepage or even water inrush risks may occur. This invention proposes an intelligent method for determining the timing of interwall grouting in frozen shafts based on multi-source information fusion. This method intelligently identifies and dynamically controls the timing of interwall grouting during the freezing wall thawing stage in mine drilling, avoiding insufficient grout diffusion and poor grouting effect due to premature grouting, or seepage or even water inrush risks due to late grouting. This improves the overall load-bearing capacity and construction safety of the double-walled shaft.

[0064] To address the problems mentioned in the background art, such as Figure 1 As shown, this embodiment of the invention provides an intelligent method for determining the timing of grouting between frozen well walls based on multi-source information fusion, specifically including:

[0065] Step 1: Deploy multi-source monitoring units within the influence range of the inner and outer well walls and the frozen wall to form a surrounding monitoring network. Collect the following parameters according to the sampling cycle: frozen wall thermal state parameters, inter-wall hydrological parameters, well wall structural response parameters, and construction state parameters. The frozen wall thermal state parameters include the temperature at each monitoring point and the aquifer thickness at the location of the monitoring point. Temperature monitoring is specifically distributed in the inner well wall, outer well wall, and the inter-wall layer between them. Inter-wall hydrological parameters include inter-wall water level, pore water pressure, and seepage flow rate. Well wall structural response parameters include the strain at each stress monitoring point, joint opening, and spacing at symmetrical positions within the well. Specifically, stress monitoring points are set on the outer well wall. Symmetrical positions within the well refer to points on the same cross-section of the well, along the path passing through the center of the well. Two measuring points are symmetrically arranged on opposite sides of the wellbore along the same diameter direction of the axis or centerline. Construction status parameters include the thickness of the inter-wall space, which is the actual distance between the inner and outer well walls. This thickness is calculated by comprehensively considering the cross-sectional position corresponding to the current excavation depth, the length of the completed well section, and the geometric dimensions and deformation monitoring data of the well wall at that cross-section. Data uploaded by different monitoring units are uniformly mapped to the same time series window to form a parameter group at the same time. Short-term missing data is filled using linear interpolation or moving average, while long-term missing data is marked as low confidence and its fusion weight is reduced. Parameters of different dimensions are dimensionless according to a preset interval so that they can be uniformly compared in subsequent fusion.

[0066] Step 2: After completing the preprocessing, corresponding characteristic indicators are constructed for different types of parameters to form intermediate characteristic quantities for determining the timing of grouting. The specific intermediate characteristic quantities include the frozen wall thawing index, the seepage risk index, the structural sensitivity index, and the grouting suitability index.

[0067] The calculation process for the frozen wall melting index is as follows:

[0068] Extract the temperature T at each temperature monitoring point. i 'i' represents the index of the temperature monitoring point; in the initial stage, each temperature monitoring point is assigned a location-related weight. The location-related weight is determined by spatial position, with the rule being that the closer the temperature monitoring point is to the frozen wall area inside the well wall, the greater the corresponding location-related weight. In this embodiment, if temperature monitoring point i is located in the inner well wall, which is the key monitoring area closest to the potential seepage channel, the location-related weight ranges to 0.5. If temperature monitoring point i is located in the interlayer between the inner and outer well walls, which is the direct space for grout diffusion, the location-related weight ranges to 0.3. If temperature monitoring point i is located in the outer well wall, indicating that it is close to the undisturbed layer, the location-related weight is 0.2. Then, a depth-related weight is assigned to monitoring point i based on its depth. Obtain the aquifer thickness at monitoring point i and the total thickness of the entire frozen layer, and denote them as H. w And H; the specific formula for calculating the depth-related weights is:

[0069]

[0070] Where k1 is the depth adjustment coefficient, ranging from 0.5 to 1, used to control the magnitude of dynamic correction and avoid over-adjustment; then, the location-related weight and depth-related weight of each temperature monitoring point i are multiplied to obtain the basic weight of each temperature monitoring point due to its location. The basic weights of all temperature monitoring points are then normalized so that their sum is one. It should be noted that the reason for setting the above location-related weights is as follows: the core objective of grouting between the walls of the frozen well is to seal potential seepage channels and improve the overall synergistic bearing capacity of the inner and outer well walls. Therefore, the closer the monitoring point is to the inner side of the well wall and the seepage-sensitive area, the more direct its temperature change has on the judgment of the grouting timing, and it should be given a higher weight; the interlayer between the walls is the main space for grout diffusion and filling, and its influence is secondary; the outer well wall is closer to the original stratum and reflects more the state of the outer edge of the frozen wall, and its indication of the final seepage breakthrough is relatively weak, so its weight is lower.

[0071] In actual operation, relying solely on static basic weights cannot accurately quantify the real-time changes of each monitoring point during the thawing process of the frozen wall. Therefore, it is necessary to further dynamically adjust the basic weights so that monitoring points with faster heating and more active thawing have a higher weight in the comprehensive judgment, thereby improving the real-time performance and accuracy of grouting timing determination. Based on the basic weights of each temperature monitoring point i, the weights are dynamically updated in each sampling period. Specifically, this includes calculating the temperature change rate of each temperature monitoring point i, which is obtained by subtracting the temperature of the previous moment from the current moment's temperature and dividing by the time difference between the two moments. It should be noted that thawing is essentially a temperature rise process. The faster the heating, the more active the thawing in the region of temperature monitoring point i, and the higher its weight should be.

[0072] Constructing dynamic factors using formulas :

[0073]

[0074] Where k2 is the temperature rate adjustment coefficient, ranging from 0.3 to 0.8, used to control the contribution of aquifer thickness to the weighting, v i Let v represent the rate of temperature change at temperature monitoring point i, and max(v) represent the maximum rate of temperature change among all monitoring points; then, the dynamic factor of each temperature monitoring point i... Multiplying by its corresponding base weight yields the dynamic weight. Finally, the dynamic weights of all temperature monitoring points i are normalized to obtain the final weight. In this embodiment, the weight of each temperature monitoring point is determined by a combination of spatial distribution and dynamic response. First, a basic weight is assigned based on the radial position of the temperature monitoring point in the frozen wall and the distribution of its corresponding aquifer. Then, the weight is dynamically corrected based on the rate of temperature change, so that the active area and critical melting area of ​​the thawing process have higher weight in the comprehensive judgment, thereby improving the accuracy and real-time performance of the assessment of the degree of thawing of the frozen wall.

[0075] Real-time acquisition of temperature T at each temperature monitoring point i，以及 The freezing critical temperature and the reference temperature close to the natural stratum temperature are used to calculate the freeze-thaw index F for each temperature monitoring point i using the following formula:

[0076]

[0077] Where T f The freezing critical temperature (T) is the critical temperature used to characterize the transition of soil from a frozen state to a thawed state. It is generally taken as 0℃ or a freezing temperature corrected for geological conditions. n The reference temperature is close to the natural formation temperature and is used to characterize the state of the frozen wall after complete thawing, which is close to the original formation temperature. It can usually be taken as the stable formation temperature of the area or the maximum temperature value in the monitoring data. The thawing index F reflects the overall decline in the water-proofing capacity of the frozen wall and realizes the quantitative characterization of the overall thawing degree of the frozen wall.

[0078] The calculation process for the seepage risk index is as follows:

[0079] The seepage increment is obtained by subtracting the seepage flow rate from the previous time from the current time. This increment is then divided by the time difference between the current and previous times to obtain the seepage increment per unit time. When the seepage increment per unit time is greater than zero, it indicates that the seepage is increasing and seepage channels may be forming or expanding. When the seepage increment per unit time is equal to zero, it indicates that the seepage is basically stable. When the seepage increment per unit time is less than zero, it indicates that the seepage is decreasing.

[0080] The seepage risk index S is obtained by calculating the inter-wall water level, pore water pressure, seepage flow rate, and seepage increment per unit time. The calculation formula is as follows:

[0081]

[0082] Where L is the inter-wall water level, P is the pore water pressure, Q is the seepage flow rate at the current time, and ΔQ is the seepage increment per unit time; b1, b2, b3, and b 4分别为The corresponding weighting coefficients must satisfy b1+b2+b3+b4=1; the inter-wall water level reflects the water accumulation and head rise in the inter-wall area. A higher water level indicates poor drainage or increased infiltration, thus increasing the risk of seepage; pore water pressure reflects the pressure state in the inter-wall and surrounding media. Higher pressure makes it easier for water to penetrate into weak parts of the well wall; seepage flow rate reflects the current scale of seepage. A larger flow rate indicates that seepage channels are more likely to have formed; seepage increment per unit time reflects the speed of seepage development. A larger increment indicates faster seepage expansion and a higher urgency for grouting.

[0083] The calculation process for the structural sensitivity index is as follows:

[0084] Extract the strain ε at each stress monitoring point j The strain values ​​are: wellbore convergence (u) and joint opening change (δ), where j represents the strain monitoring point index. It should be noted that wellbore convergence is the shrinkage deformation of the wellbore's inner diameter or the control section between the walls, while joint opening change refers to the change in the current joint opening relative to the initial opening. The outer wellbore strain reflects the internal stress state of the wellbore material; wellbore convergence reflects the overall geometric deformation of the wellbore; and joint opening change reflects whether weak points are opening and forming seepage channels. To avoid excessive interference from single-point anomalies, the strain values ​​from multiple strain monitoring points can be summarized to obtain the original structural strain value ε. raw The calculation formula is:

[0085]

[0086] Where m represents the total number of stress monitoring points. This represents the initial strain reference value at stress monitoring point j; the original strain value of the structure is calculated using the root mean square form, which can simultaneously reflect the overall strain level of multiple monitoring points, avoid excessive amplification of the results by a single local peak value, and also better reflect the overall stress level of the structure than a simple average value.

[0087] Extract the current spacing at the symmetrical position of the wellbore, subtract the current spacing from the initial spacing at the symmetrical position of the wellbore, and then divide by the initial spacing to obtain the original value of wellbore convergence. When the inner diameter of the wellbore decreases, that is, the spacing decreases, the wellbore convergence increases, indicating that the well wall is shrinking inward and the structure is in a more sensitive state.

[0088] Extract the current joint opening, subtract the initial opening from it, and then divide it by the initial opening to obtain the original value of the joint opening. When the original value of the joint opening increases, it indicates that the joint is opening and the risk of seepage in the weak part increases.

[0089] Since the changes in strain, convergence, and joint opening are of different orders of magnitude, normalization is required to obtain the standard values ​​of structural strain, wellbore convergence, and joint opening. These are then weighted and summed to calculate the structural sensitivity index G. The calculation formula is as follows:

[0090]

[0091] Where c1, c2 and c3 represent the weighting coefficients of strain, convergence and joint opening change, respectively, and satisfy c1+c2+c3=1; when the structural sensitivity index increases, it indicates that the strain level of the outer well wall increases, the wellbore convergence intensifies and the joint opening trend is enhanced, indicating that the well wall has entered the stress-sensitive stage, promoting the further development of seepage channels.

[0092] The calculation process for the grouting suitability index is as follows:

[0093] The thickness of the inter-wall space is extracted. If the inter-wall space is too small, it will restrict grout injection and diffusion, resulting in insufficient sealing; however, if the space is too large, it means that a larger grout volume and a longer diffusion time are required. The thickness of the inter-wall space is converted into a thickness adaptation factor Y using a formula. D The calculation formula is:

[0094]

[0095] Where D opt The optimal inter-wall space thickness is determined empirically, and Dmax and Dmin are the upper and lower limits of the allowable range, respectively. The suitability is highest when the inter-wall space thickness is close to the optimal value; the greater the deviation from the optimal value, the lower the suitability.

[0096] The temperatures at various monitoring points within the wall are acquired, and the average value is calculated to obtain the local temperature. When the local temperature within the wall is too low, the grout viscosity increases, the fluidity decreases, and the diffusion radius shrinks, which can easily lead to discontinuous grouting or insufficient sealing. To reflect the degree of adaptability of the local temperature to the grouting, the temperature suitability factor Y is calculated using a formula. T The calculation formula is:

[0097]

[0098] Where T is the local temperature between the walls, T opt The optimal temperature for grout diffusion is Tmax, and the upper and lower limits of the allowable temperature are Tmin, respectively. The closer the local temperature between the walls is to the optimal grouting temperature, the higher the temperature suitability; the greater the deviation, the worse the suitability.

[0099] The diffusion process of the slurry in the inter-wall medium is approximated as a radial seepage expansion process, and a prediction model for the effective diffusion radius is constructed:

[0100]

[0101] Where λ is the model correction coefficient, Z is the preset grouting pressure, is the effective confining pressure or equivalent back pressure of the formation, μ is the preset grout viscosity, K is the preset formation permeability coefficient, and C is the preset grouting duration; the meaning of this model is: the higher the grouting pressure, the better the formation permeability, and the lower the grout viscosity, the faster the grout diffusion and the larger the radius; conversely, the higher the confining pressure and the thicker the grout, the smaller the diffusion radius; the effective diffusion radius is predicted within a unit time of grouting, and the target diffusion radius required to complete the inter-wall sealing is determined through trial grouting experiments. The grout diffusion factor is obtained by dividing the effective diffusion radius by the target diffusion radius;

[0102] A weighting factor is assigned to each of the thickness adaptation factor, temperature suitability factor, and grout diffusion factor, and the sum of the weighting factors is one. The grouting suitability index Y is obtained by weighted fusion calculation of the thickness adaptation factor, temperature suitability factor, and grout diffusion factor using the assigned factors.

[0103] The above calculation process yields intermediate characteristic quantities for each time point. These intermediate characteristic quantities include the thawing index of the frozen wall, the permeability risk index, the structural sensitivity index, and the grouting suitability index.

[0104] Step 3: Combine the above-mentioned frozen wall thawing index, seepage risk index, structural sensitivity index, and grouting suitability index to obtain the timing judgment value A; the calculation formula is:

[0105]

[0106] Where e1, e2, e3, and e4 are the fusion weights, and they satisfy e1+e2+e3+e4=1. The weight settings are based on historical wellbore monitoring data, expert experience, or sample training results, and are specifically set according to the scenario. For example, when more attention is paid to safety during grouting, the weights of the seepage risk index and the structural sensitivity index are increased; when more attention is paid to the grout diffusion effect during grouting, the weights of the frozen wall thawing index and the grouting suitability index are increased.

[0107] A preset judgment interval is used to define the engineering boundary for grouting timing. This interval is based on the physical laws governing the thawing process of the frozen wall and the evolution of seepage risk. The grouting window is divided into three consecutive stages: too early, suitable, and too late, enabling refined, graded control of grouting timing. The lower limit of the interval corresponds to the opening boundary of the grouting window, and the upper limit corresponds to the closing boundary. If the timing judgment value is less than the minimum value of the judgment interval, it indicates that the frozen wall has not thawed sufficiently, and suitable grout diffusion conditions have not yet formed between the walls. If grouting is performed at this time, the grout is easily affected by residual freezing, limiting diffusion and resulting in poor grouting effect. In this case, a command to temporarily refrain from grouting is output, and the monitoring frequency is increased to wait for further thawing of the frozen wall. Specifically, the increased monitoring frequency is achieved using a graded incremental method. If the basic sampling period is Δt0, the sampling period is adjusted to Δt after entering the waiting state. m , where Δt m ≤Δt0; The sampling period is adjusted sequentially to half, one-third, one-quarter of the original period, up to the minimum one-fifth; m is the cumulative number of consecutive outputs of the "temporarily not grouting" command, and its value range is greater than or equal to zero; when m=0, it means that no "temporarily not grouting" command has been output, i.e., the basic sampling period Δt0 is used; when m=1, i.e., Δt1 uses half of the basic sampling period Δt0; when m=2, i.e., Δt2 uses one-third of the basic sampling period Δt0; when m=3, i.e., Δt3 uses one-quarter of the basic sampling period Δt0; when m=4, i.e., Δt4 uses one-fifth of the basic sampling period Δt0; when m≥5, all use one-fifth of the basic sampling period Δt0; through the above method, the sampling period is shortened step by step, thereby improving the monitoring resolution of the frozen wall thawing process and changes in seepage risk;

[0108] If the timing judgment value is within the judgment range, it indicates that the frozen wall has entered the appropriate thawing stage and the seepage risk has not yet evolved to a dangerous level. This is the best window period for inter-wall grouting, and an inter-wall grouting start command is output. If the timing judgment value is greater than the maximum value of the judgment range, it indicates that the frozen wall has thawed sufficiently, and the seepage risk and structural sensitivity have increased significantly. If not dealt with in time, it may further develop into seepage or even water inrush risk. An emergency grouting command is output, and the monitoring frequency is simultaneously increased to the highest level, i.e., one-fifth of the basic sampling period Δt0.

[0109] Step four: Upon receiving the command to start inter-wall grouting, the grouting parameters are automatically calculated based on the current monitoring data and pushed to the mobile terminal to execute the grouting operation. Specifically: Grouting working pressure = q1 × P 静 P 静 The hydrostatic pressure at the current depth; final grouting pressure = q² × P 静Where q1 is the grouting working pressure coefficient, ranging from 1.2 to 1.5, used to ensure that the grout can overcome the inter-wall water pressure and diffuse sufficiently; q2 is the grouting final pressure coefficient, ranging from 2.0 to 2.5, used to ensure that the grout is fully compacted under pressure to form an effective seal; based on the current inter-wall temperature and water pressure change rate, the recommended initial setting time of the grout is usually set to 30 to 60 minutes. Based on the initial setting time requirement, the volume ratio of cement and water glass grout is automatically calculated. This ratio ensures that the grout has sufficient time to fill the inter-wall gap after injection and can solidify quickly after filling, preventing the grout from being diluted or washed away by groundwater; the specific calculation process includes:

[0110] The water pressure change is calculated based on the pore water pressure at the current time and the pore water pressure at the previous acquisition time. Dividing this by the difference between the two acquisition times yields the rate of water pressure change. Based on engineering experience, the suitable initial setting time for wall grouting is typically 30–60 minutes. Using this range as a basis, a preliminary adjustment is made based on the wall temperature to obtain the initial setting time. Specifically, the initial setting time is calculated as 45 × (reference wall temperature / current local wall temperature), where the reference wall temperature is typically taken as 15 degrees Celsius. When the wall temperature is lower than the reference temperature, the grout reaction rate slows down, and the initial setting time… The initial setting time should be appropriately extended when the temperature is high; conversely, when the temperature is high, the initial setting time should be appropriately shortened. Then, the initial setting time of the grout should be obtained by correcting the initial setting time of the foundation using the rate of change of water pressure. The initial setting time of the grout is calculated as: initial setting time of foundation × (1 - (α × rate of change of water pressure / preset upper limit of rate of change of water pressure)), where α is the correction coefficient, with a value range of 0.2 to 0.5. When the rate of change of water pressure is high, it indicates that the risk of seepage is rising rapidly, so the initial setting time is automatically shortened to allow the grout to solidify faster and form a seal. When the rate of change is low, a relatively sufficient initial setting time is maintained to ensure that the grout diffuses fully.

[0111] The setting time of cement-water glass grout is mainly determined by the amount of water glass added. The volume ratio of cement grout to water glass is calculated based on the determined initial setting time. Let the volume ratio of cement grout to water glass be 1:β, where the water-cement ratio of cement grout is 0.8-1.0, the modulus of water glass is 2.8-3.2, and the concentration is 35-45 Baume degrees; β is the ratio of the volume of water glass to the volume of cement grout. Engineering experience shows that the initial setting time of grouting is negatively correlated with β, which can be approximated by the following empirical formula: β=β0×(reference initial setting time / grout initial setting time); where the reference initial setting time is taken as 45 minutes, and β0 is the reference ratio, which is a value in the range of 0.3-0.5.

[0112] If multiple grouting holes are set up on site, the grouting sequence is automatically generated according to the real-time water pressure value monitored at each grouting hole, starting from the hole with lower water pressure and proceeding to the hole with higher water pressure. This sequence can avoid the grout flowing backward along the wall gap due to the high-pressure hole being grouted first, thereby ensuring that the grout is evenly filled from the low-pressure area to the high-pressure area, improving the integrity and density of the wall filling. After the grouting operation is started, the system automatically switches to the grouting process monitoring mode, and synchronously collects grouting pressure and grouting flow data at a frequency of no less than once every 10 seconds, draws pressure-time curves and flow-time curves in real time, and pushes them to the on-site operation screen to achieve visual monitoring. The system also automatically identifies and pushes early warning information for the following abnormal working conditions: (1) Pipe blockage risk warning: When the instantaneous value of the grouting pressure exceeds 1.2 times the final grouting pressure, and the grouting flow rate decreases by more than 50% / min during the same period, it is determined that pipe blockage may occur, and an early warning of possible pipe blockage is automatically generated to prompt the operator. (1) The grouting personnel shall suspend grouting, inspect the pipeline or adjust the grouting parameters; (2) Grout leakage risk warning: When the instantaneous value of grouting pressure drops significantly (the drop exceeds 20% of the current pressure) and the grouting flow increases synchronously, the system determines that grout leakage may occur, automatically generates a grout leakage warning, and prompts the operator to adjust the grout ratio, reduce the grouting rate or use intermittent grouting to control the grout diffusion range; Real-time monitoring of grouting pressure and wall water flow changes, when all of the following conditions are met at the same time, the system automatically determines that the grouting has reached the termination state and issues a grouting termination prompt: (1) The grouting pressure has reached the designed final grouting pressure and the pressure has been stabilized for no less than 10 minutes, indicating that the wall gap has been fully filled with grout and the grouting pressure can be maintained stably; (2) The wall water flow monitoring value (i.e. seepage flow) has dropped to zero and has been kept stable for no less than 5 minutes, indicating that the wall seepage channel has been effectively blocked; The operator can terminate the grouting operation according to the prompt;

[0113] Upon receiving an emergency grouting command, emergency grouting parameters will be immediately pushed out, where the grouting working pressure = 1.5 × P. 静 P 静 The hydrostatic pressure at the current depth; final grouting pressure = 2.5 × P 静Compared with the standard grouting process, the working pressure and final pressure of emergency grouting are increased by about 10% to 20%, which aims to enhance the diffusion driving force and compaction effect of the grout, enabling the grout to enter high-risk channels and weak points as soon as possible, quickly forming an effective sealing barrier and curbing the further development of seepage. For multi-hole grouting, a segmented operation is adopted; for single grouting holes, a segmented grouting method is adopted, and grouting is carried out step by step according to the depth range. Within each grouting segment, a graded pressurization strategy is adopted, starting from low pressure and gradually increasing to the design final pressure, with each pressure increase not exceeding 0.2 MPa. This method can avoid secondary damage to the well wall structure caused by a sudden increase in pressure, while ensuring that the grout gradually fills the inter-wall gaps under each pressure level. In cases where the seepage channel is clearly defined and the risk is high, dual-pump linkage or multi-hole synchronous grouting methods can be employed. Dual-pump linkage refers to two grouting pumps simultaneously injecting grout into different depth sections of the same grouting hole or alternating grouting into different grouting holes to maintain grouting continuity. Multi-hole synchronous grouting refers to simultaneously injecting grout into multiple adjacent grouting holes to quickly form regional sealing and improve instantaneous treatment capabilities. If necessary, emergency drainage, local pressure relief, or temporary support measures can be activated in a coordinated manner to prevent further expansion of the seepage channel. The role of the above-mentioned emergency coordination measures is to maximize the sealing window period by rapidly, frequently, and directionally controlling grouting, combined with auxiliary engineering measures, when the risk of seepage or water inrush has significantly increased, so as to complete the sealing and reinforcement before the accident escalates and reduce the safety risk of the wellbore. When the grouting pressure reaches the designed final grouting pressure and is stabilized for more than 5 minutes, or when the grouting volume reaches 120% of the designed grouting volume, the system determines that the emergency grouting is initially completed. After grouting is completed, the system automatically enters the emergency tracking mode to continuously monitor the water pressure and flow rate between the walls for no less than 72 hours. If the monitoring data remains stable during the tracking period, i.e., the water pressure drop does not exceed 10% and the water flow remains zero, the monitoring frequency will be gradually restored to the normal frequency. If abnormalities recur, a secondary emergency response will be triggered, and the emergency grouting process will be re-executed. By establishing differentiated grouting control strategies for the two commands of initiating wall grouting and emergency grouting, seamless connection between grouting operations and the timing determination results can be achieved. The standard grouting process ensures the grouting quality and efficiency within the optimal window period; the emergency grouting process provides enhanced pressure parameters, multi-mode process control, and coordinated measures for risk conditions, forming a closed-loop control from timing determination to grouting execution, thereby improving the intelligence level and engineering safety of wall grouting in frozen wells.

[0114] Through the above steps, the present invention first integrates four types of characteristics: frozen wall thawing, water seepage risk, structural response, and grouting suitability, to form a tiered judgment value for timing. Then, based on the relationship between the judgment value and a preset threshold range, it outputs commands to temporarily suspend grouting, initiate inter-wall grouting, or perform emergency grouting. Finally, it adjusts the monitoring frequency and grouting strategy in conjunction with different commands, thereby forming a closed-loop control process of monitoring, judgment, execution, and feedback.

[0115] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0116] The preferred embodiments of the invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention.

Claims

1. A method for intelligently determining the timing of grouting between frozen well walls based on multi-source information fusion, characterized in that, Includes the following steps: Step 1: Collect frozen wall thermal state parameters, inter-wall hydrological parameters, well wall structural response parameters, and construction status parameters according to the sampling cycle; Step 2: Based on the thermal state parameters of the frozen wall, the hydrological parameters between the walls, the structural response parameters of the well wall, and the construction state parameters, four intermediate characteristic quantities are constructed: the thawing index of the frozen wall, the seepage risk index, the structural sensitivity index, and the grouting suitability index. Step 3: Weighted fusion of the intermediate feature quantities to obtain the timing determination value, compare the timing determination value with the preset determination interval, and output a command to temporarily stop grouting, start wall grouting, or emergency grouting based on the comparison result, and adjust the sampling cycle to update Step 1 in a coordinated manner. Step four: Based on the received grouting instructions, perform corresponding grouting monitoring and control.

2. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion as described in claim 1, characterized in that, The thermal state parameters of the frozen wall include the temperature at each temperature monitoring point and the aquifer thickness at the location of the temperature monitoring point; the hydrological parameters between the walls include the water level between the walls, pore water pressure and seepage flow rate; the structural response parameters of the well wall include the strain at each stress monitoring point, the joint opening and the spacing of the symmetrical positions of the wellbore; and the construction state parameters include the thickness of the space between the walls.

3. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 2, characterized in that, The method for constructing the freeze-wall melting index is as follows: The location-related weights are assigned based on the radial position of the temperature monitoring point in the frozen wall, and the depth-related weights are assigned based on the ratio of the aquifer thickness to the total thickness of the frozen layer at the location of the temperature monitoring point. The location-related weights and depth-related weights are multiplied and normalized to obtain the base weights. Then, a dynamic factor is constructed based on the temperature change rate of each temperature monitoring point. The dynamic factor is multiplied by the basic weight and normalized to obtain the final weight. Based on the temperature of each temperature monitoring point, the freezing critical temperature and the reference temperature, the frozen wall thaw index is obtained by weighted calculation.

4. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 3, characterized in that, The method for constructing the seepage risk index is as follows: The seepage risk index is obtained by weighted summation of the inter-wall water level, pore water pressure, seepage flow rate, and seepage increment per unit time. The seepage increment per unit time is calculated by the ratio of the difference in seepage flow rate between two adjacent sampling times to the time difference.

5. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 4, characterized in that, The method for constructing the structural sensitivity index is as follows: The strain at multiple stress monitoring points on the outer well wall is obtained, and the original value of structural strain is calculated using the root mean square method. The current spacing of the symmetrical positions of the wellbore is obtained, and the original value of wellbore convergence is calculated based on the initial spacing. The current joint opening is obtained, and the original value of joint opening is calculated based on the initial opening. The original values ​​of structural strain, wellbore convergence, and joint opening are normalized and then weighted and summed to obtain the structural sensitivity index.

6. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 5, characterized in that, The method for constructing the grouting suitability index is as follows: Calculate the thickness adaptation factor based on the inter-wall space thickness; The temperature suitability factor is calculated based on the local temperature between the walls; an effective diffusion radius prediction model is constructed based on the preset grouting pressure, preset grout viscosity, preset formation permeability coefficient and preset grouting duration, and the grout diffusion factor is obtained by dividing the effective diffusion radius by the target diffusion radius; the grouting suitability index is obtained by weighted fusion of the thickness suitability factor, temperature suitability factor and grout diffusion factor.

7. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 6, characterized in that, In step three, the preset judgment interval includes a lower limit and an upper limit, which correspond to the opening and closing boundaries of the grouting window, respectively. When the timing judgment value is less than the lower limit of the interval, a command to temporarily stop grouting is output, and the monitoring frequency is encrypted using a graded incremental method.

8. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 7, characterized in that, The monitoring frequency is encrypted using a tiered, incremental method. Let the basic sampling period be Δt0, and m be the cumulative number of consecutive outputs of the "temporarily not grouting" command. Then the formula for calculating the sampling period is: ， When m≥5, the sampling period is fixed. When the timing judgment value exceeds the upper limit of the interval, an emergency grouting command is output, and the monitoring frequency is increased accordingly. .

9. The intelligent determination method for grouting timing between frozen well walls based on multi-source information fusion according to claim 8, characterized in that, In step four, when a command to start wall grouting is received, the grouting working pressure, final grouting pressure, initial setting time of grout, two-liquid grout ratio, and multi-hole grouting sequence are automatically calculated based on the current monitoring data. The grouting pressure and grouting flow rate curves are monitored in real time during the grouting process. When an emergency grouting command is received, emergency grouting parameters are automatically pushed and grouting is performed using methods such as segmented, graded pressurization, dual-pump linkage, or multi-hole synchronous grouting.

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