CN111766189A - Three-dimensional chromatographic scanning method for dike hidden leakage channel based on hydraulic stimulation - Google Patents
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Abstract
The invention provides a three-dimensional chromatographic scanning method for an embankment hidden leakage channel based on hydraulic stimulation. The method comprises the steps of laying a netted hydraulic parameter detection well, measuring the natural potential of a region to be measured, connecting and laying a measuring device, measuring potential response, carrying out inversion of the three-dimensional structure of the stratum of the detection region, feeding back and monitoring in real time and the like. According to the method, efficient chromatographic scanning of the permeability coefficient of the underground aquifer can be carried out by utilizing the permeability coefficient change data measured by the water head sensing device, and the reaction speed and the calculation precision of the traditional monitoring scheme are greatly improved by implementing the development process of the leakage channel.
Description
Technical Field
The invention relates to the field of geophysical exploration of stratum aquifers and geological structures, in particular to a three-dimensional chromatographic scanning method for an embankment hidden leakage channel based on hydraulic stimulation.
Background
According to 2016 national water conservancy development statistics bulletin, 98460 reservoirs are built in China, the total length of river dams is 29.9 kilometers, and each sea dam is 2 kilometers. The hydraulic engineering generates huge economic and social benefits in the aspects of flood control, power generation, water supply, irrigation and the like. However, due to low engineering design standards, poor construction quality, aging over time, etc., more than 90% of reservoirs have leakage, and 30% of them have more serious leakage. When the water level in the reservoir rises, the reservoir water may run off along fault cracks of the mountain or dam foundations of the dam. The problem of dam seepage is a problem faced by all countries in the world, and seepage not only causes waste of water resources, but also directly relates to safe operation of dams. The key technical problem to treat dam leakage diseases is how to accurately diagnose leakage positions and leakage paths.
Because the hydraulic parameters (such as permeability coefficient) in the leakage channel are obviously different from the non-channel area, if the change rule of the hydraulic parameters in the dam can be obtained, the position of the hidden leakage channel can be carved, and the leakage amount can be calculated by utilizing the underground water movement theory. The hydraulic chromatography scanning is an effective method for characterizing the heterogeneous characteristics of the aquifer by utilizing monitoring data. Hydrographic scanning the hydraulic properties of saturated aquifers are often estimated by the water pumping test. The hydrotomography is a data fusion and inversion algorithm for reversely deducing the possible distribution rule of the heterogeneous parameters through the observed value. The water pumping test is to pump water through one well of the experimental site, and the other wells observe the water level response, so that one time of scanning the aquifer can be obtained; by continuously changing the depth of the pumping well or the pumping section, a series of observation data under different stimuli can be collected to obtain aquifer scanning images at different angles. And integrating the images through a data fusion method to obtain the spatial distribution form of the aquifer hydraulic parameters. From the initial virtual ideal calculation example, to the indoor test verification and then to the field test verification, the method proves that the method can effectively depict the spatial distribution of the hydraulic parameters of the saturated aquifer. Since the concept of hydrographic scanning, mathematical models and numerical algorithms have been proposed, the concept and technique of hydrographic scanning has been widely applied in the field of hydrogeology. In the hydraulic tomography scanning method, the traditional inversion model only divides the stratum into a plurality of regions with undetermined parameters, and the observation-simulation error is minimized through adjustment to obtain a unique group of parameter values. The observation data quantity of the inverse problem is larger than the number of parameters to be solved, the algorithm requirement is low, but the small-scale heterogeneity is ignored, and a large amount of information collected by the hydraulic chromatography survey cannot be fully mined. And the other model, namely a statistical model based on Bayes, considers the prior parameters as spatially-correlated random fields, and describes the spatial distribution law and uncertainty of the spatially-correlated random fields by means of mean values and covariance. After the absorption hydrotomography scanning observation, the posterior mean value and the covariance can be obtained by updating. Such models have sufficient degrees of freedom to absorb large amounts of hydrographic scan data. However, the method has the advantages of multiple unknown parameters, large calculation amount, strong nonlinearity of inverse problem, easy trapping in local optimal solution and high requirement on the numerical optimization algorithm.
Therefore, on the basis of the traditional hydraulic chromatography scanning method, it is very important to develop a dam hidden leakage channel hydraulic chromatography scanning technology with higher precision.
Disclosure of Invention
The invention aims to provide a three-dimensional chromatographic scanning method for an embankment hidden leakage channel based on hydraulic stimulation, and the method is used for solving the problems in the prior art.
The technical scheme adopted for achieving the aim of the invention is that the three-dimensional chromatographic scanning method for the dike hidden leakage channel based on hydraulic stimulation comprises the following steps:
1) and laying netted hydraulic parameter detection wells in the area to be detected, and arranging a plurality of detection points at intervals in each detection well. Wherein, a water pressure sensing device is arranged at the detection point.
2) Randomly selecting a certain detection point as a stimulation point, and the other detection points as observation points.
3) And pumping water or injecting water at the stimulation point by using a water pump. Wherein, the water pump is arranged on the ground surface. The liquid outlet end of the water pump is arranged in the detection well. When water is pumped or injected, the liquid outlet end moves to the detection points with different elevations in the well.
4) And (3) acquiring water head response data of each observation point by using a water pressure sensor, and transmitting the water head response data to a data processing and analyzing system.
5) And (5) exchanging the stimulus points and the observation points, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in a data processing and analyzing system, calculating the permeability coefficient value of the response by adopting a continuous linear estimation algorithm according to the water head response data, and performing inversion of the stratum three-dimensional structure of the detection area.
7) And updating and perfecting the structural characteristics of the stratum by utilizing the three-dimensional distribution rule of the permeability coefficient in the stratum and the corresponding relation between other stratum parameters and the permeability coefficient, and analyzing the possible development condition of the leakage channel.
8) And after the inversion is finished, feeding back the inversion result to a display terminal in real time.
Further, the step 6) specifically comprises the following steps:
6.1) according to the previous exploration data, providing the mean value, the variance and the relevant scale parameters of the formation permeability coefficient.
6.2) assigning the mean value of the permeability coefficients to each grid within the analysis area. And calculating the water head of each detection position under the condition of estimation parameters under each water head stimulation by combining boundary conditions and utilizing a three-dimensional permeability coefficient forward analysis model of the detection region.
6.3) estimating the permeability coefficient value of the point to be estimated in the detection area by utilizing a continuous linear estimation algorithm. The iterative calculation formula of the unknown permeability coefficient is shown as formula (1). The formula for calculating the weight coefficient matrix ω is shown in equation (2).
In the formula, r is the number of iterations. T is the transposed symbol. u. ofcAnd the permeability coefficient parameter vector of the detection area to be estimated. u (r +1) c is a parameter vector ucCondition estimate at time r + 1. d*The observed value of the water head is acted on by the water head. d(r)The simulated value of the water head under the water head effect is obtained by utilizing a three-dimensional permeability coefficient positive analysis model.
[dd+λdiag(dd)]ω=du(2)
In the formula (I), the compound is shown in the specification,ddis a covariance matrix between observed data.duIs a covariance matrix between the observed data and the parameter. Lambda is the Levenberg-Marquardt algorithm dynamic multiplier. The diag () function is used to construct a diagonal matrix.
6.4) repeating the iteration process of the step (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is less than an error allowable value or reaches a certain iteration step number.
Further, in step 6.3), the covariance matrix is obtained from the sensitivities:
in the formula, JduIs a sensitivity matrix of the water head observation data to the permeability coefficient change of the detection area. Parameter covariance matrixuuGiven by the prior geological information when r is 0, then each iteration is updated gradually according to equation (4):
further, the display terminal adopts mobile equipment. The mobile device has a computer program stored therein. The computer program is used for realizing the steps 2) to 7) when being executed, and realizing the real-time monitoring dynamic scanning of the embankment.
Further, after the step 7), a correlation step of obtaining three-dimensional distribution of the geological parameters of the stratum by using the relation between the unknown stratum structure parameters and the permeability coefficients is also provided.
The technical effects of the invention are undoubted: the water head change data measured by the water head sensing device can be used for carrying out efficient underground permeability coefficient chromatographic scanning, the obtained result can absorb various detection data source information, the nonlinear estimation of unknown permeability coefficient parameters by using observation data is realized, and the accuracy effect of improving the simulation of the dike buried leakage channel is obvious.
Drawings
FIG. 1 is a work flow diagram;
FIG. 2 solves for domain and grid partitioning;
FIG. 3 is a graph of an iterative process of permeability coefficient tomography;
FIG. 4 is a comparison graph of real value simulation values;
FIG. 5 development of latent leak channel over time;
fig. 6 is a comparison of the true leak path and the leak path obtained by inversion.
Detailed Description
The present invention is further illustrated by the following examples, but it should not be construed that the scope of the above-described subject matter is limited to the following examples. Various substitutions and alterations can be made without departing from the technical idea of the invention and the scope of the invention is covered by the present invention according to the common technical knowledge and the conventional means in the field.
Example 1:
referring to fig. 1, the present embodiment discloses a three-dimensional tomographic scanning method for an embankment hidden leakage channel based on hydraulic stimulation, which includes the following steps:
1) the surface of the dike and the nearby area are divided into areas to be detected. According to the detection precision requirement, a plurality of hydraulic parameter detection wells are distributed in the area to be detected according to reasonable intervals. Probe points are arranged at different elevation intervals within each probe well. Wherein, the hydraulic parameter detecting well can be a vertical well or an inclined well. The hydraulic parameter detection well extends into the interior of the dike soil body. The diameter of the hydraulic parameter detection well is 20-30 mm. And a water pressure sensing device is arranged at the detection point.
2) Randomly selecting a certain detection point as a stimulation point, and the other detection points as observation points.
3) And pumping water or injecting water at the stimulation point by using a water pump. Wherein, the water pump is arranged on the ground surface. The liquid outlet end of the water pump is arranged in the detection well. When water is pumped or injected, the liquid outlet end moves to the detection points with different elevations in the well.
4) And (3) acquiring water head response data of each observation point by using a water pressure sensor, and transmitting the water head response data to a data processing and analyzing system.
5) And (5) exchanging the stimulus points and the observation points, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in a data processing and analyzing system. The continuous linear estimation algorithm linearizes the data information by an iterative method, and adopts a simultaneous absorption mode in time in the iterative process, so that the nonlinear problem can be effectively solved, and the problem of parameter-observation inconsistency possibly occurring in the traditional data assimilation algorithm and the like is avoided. And calculating the permeability coefficient value of the response by adopting a continuous linear estimation algorithm according to the water head response data, and performing inversion of the stratum three-dimensional structure of the detection area.
6.1) according to the previous exploration data, providing the mean value, the variance and the relevant scale parameters of the formation permeability coefficient.
6.2) assigning the mean value of the permeability coefficients to each grid within the analysis area. And calculating the water head of each detection position under the condition of estimation parameters under each water head stimulation by combining boundary conditions and utilizing a three-dimensional permeability coefficient forward analysis model of the detection region.
6.3) estimating the permeability coefficient value of the point to be estimated in the detection area by utilizing a continuous linear estimation algorithm. The iterative calculation formula of the unknown permeability coefficient is shown as formula (1). The formula for calculating the weight coefficient matrix ω is shown in equation (2).
In the formula, r is the number of iterations. T is the transposed symbol. u. ofcAnd the permeability coefficient parameter vector of the detection area to be estimated. u (r +1) c is a parameter vector ucCondition estimate at time r + 1. d*The observed value of the water head is acted on by the water head. d(r)The simulated value of the water head under the water head effect is obtained by utilizing a three-dimensional permeability coefficient positive analysis model.
[dd+λdiag(dd)]ω=du(2)
In the formula (I), the compound is shown in the specification,ddis a covariance matrix between observed data.duIs a covariance matrix between the observed data and the parameter. Lambda is the Levenberg-Marquardt algorithm dynamic multiplier. The diag () function is used to construct a diagonal matrix.
The covariance matrix is derived from the sensitivity:
in the formula, JduIs the water head observation data to the detection areaA sensitivity matrix of permeability coefficient changes. Parameter covariance matrixuuGiven by the prior geological information when r is 0, then each iteration is updated gradually according to equation (4):
6.4) repeating the iteration process of the step (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is less than an error allowable value or reaches a certain iteration step number.
7) And updating and perfecting the structural characteristics of the stratum by utilizing the three-dimensional distribution rule of the permeability coefficient in the stratum and the corresponding relation between other stratum parameters and the permeability coefficient, and analyzing the possible development condition of the leakage channel.
8) And obtaining the three-dimensional distribution of the geological parameters of the stratum by utilizing the relation between the unknown stratum structure parameters and the permeability coefficients.
9) And after the inversion is finished, feeding back the inversion result to a display terminal in real time. The display terminal adopts mobile equipment. The mobile device has a computer program stored therein. The computer program is used for realizing the steps 2) to 7) when being executed, and realizing the real-time monitoring dynamic scanning of the embankment.
Example 2:
the embodiment discloses a basic three-dimensional tomographic scanning method for a large-scale geological structure by taking a water head as a stimulus source, which comprises the following steps of:
1) and laying netted hydraulic parameter detection wells in the area to be detected, and arranging a plurality of detection points at intervals in each detection well. Wherein, a water pump and a water pressure sensing device are arranged at the detection point.
2) Randomly selecting a certain detection point as a stimulation point, and the other detection points as observation points.
3) And pumping water or injecting water at the stimulation point by using a water pump.
4) And (3) acquiring water head response data of each observation point by using a water pressure sensor, and transmitting the water head response data to a data processing and analyzing system.
5) And (5) exchanging the stimulus points and the observation points, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in a data processing and analyzing system, calculating the permeability coefficient value of the response by adopting a continuous linear estimation algorithm according to the water head response data, and performing inversion of the stratum three-dimensional structure of the detection area.
7) And updating and perfecting the structural characteristics of the stratum by utilizing the three-dimensional distribution rule of the permeability coefficient in the stratum and the corresponding relation between other stratum parameters and the permeability coefficient, and analyzing the possible development condition of the leakage channel.
Example 3:
in this example, a 40m × 60m aquifer area is selected as a study area and numerically modeled, and the distribution of permeability coefficients of the aquifer is characterized by using a tomography method. And a left boundary of the model is assumed to have a high water head area, namely a water level boundary in the dike, and a left-to-right seepage field is simulated. Unit grid division is carried out in a solving domain surrounded by boundaries, the grid is square, the size is 1m multiplied by 1m, 56 hydraulic parameter detection wells are arranged in total, a 9-time water head stimulation-response test scheme is preset, and the grid division condition is shown in figure 2:
the calculation is carried out every hour, initial and boundary conditions of the model are given, a hidden leakage channel is manually set, the homogeneity, variance and relevant scale of the internal structure of the dike are specified, and the hidden leakage channel in the simulated field is detected through 9 water head stimulation-response tests. The iteration curve of the scanning process is shown in fig. 3. It can be seen that the piping channel is approximately formed after t-20 h. And the real value is taken as an abscissa, the analog value is taken as an ordinate, and the relation graph is drawn to obtain a straight line with the slope of about 1, so that the simulation result is better, and the hidden leakage channel can be better detected.
The measurement time was set to 1 hour, and inversion simulation was performed every T ═ 1 h. Fig. 5 represents a process in which the leak path is gradually formed in a plurality of simulations, wherein 5a represents t-0 h, 5b represents t-12 h, 5c represents t-18 h, and 5d represents t-20 h. It can be seen from the figure that the development process of the latent leakage channel is gradually detected along with the increase of the number of test measurements. The permeability coefficient value in the calculation area gradually changes from an initial uniform guess value to obvious heterogeneity, and a piping channel is approximately formed by the time t is equal to 20 h.
Figure 6 represents a comparison of the distribution of real leak paths over simulated leak paths. 6a is an artificial leakage channel modeling grid, 6b is the true leakage channel distribution, and 6c is the inverted leakage channel distribution. Comparing the real distribution condition of the leakage channel with the distribution of the leakage channel obtained by utilizing the chromatography scanning, it can be seen that the distribution of the piping channel obtained by the back analysis can better reflect the real condition.
It is worth to say that the three-dimensional tomography is an advanced means for obtaining high-resolution aquifer characteristics by utilizing limited monitoring data inversion. Through contrastive analysis, it can be seen that the water head change data measured by the hydraulic sensing device can be used for carrying out efficient chromatographic scanning on the permeability coefficient of the underground aquifer, and the obtained result is greatly improved in the aspects of accurate positioning, real-time feedback and the like compared with the traditional monitoring mode.
Claims (5)
1. A three-dimensional chromatography scanning method for an embankment hidden leakage channel based on hydraulic stimulation is characterized by comprising the following steps:
1) laying netted hydraulic parameter detection wells in a region to be detected, and arranging a plurality of detection points at intervals in each detection well; wherein a water pressure sensing device is arranged at the detection point;
2) randomly selecting a certain detection point as a stimulation point, and taking the other detection points as observation points;
3) pumping water or injecting water at the stimulation point by using a water pump; wherein, the water pump is arranged on the ground surface; the liquid outlet end of the water pump is arranged in the detection well; when pumping water or injecting water, the liquid outlet end is moved to the detection points with different elevations in the well;
4) the water pressure sensor acquires water head response data of each observation point and transmits the water head response data to the data processing and analyzing system;
5) exchanging stimulation points and observation points, and repeating the steps 2) to 4);
6) establishing a three-dimensional geological forward and backward analysis model of a detection area in a data processing and analyzing system, calculating a permeability coefficient value of response by adopting a continuous linear estimation algorithm according to water head response data, and performing inversion of a stratum three-dimensional structure of the detection area;
7) updating and perfecting the structural characteristics of the stratum by utilizing the three-dimensional distribution rule of the permeability coefficient in the stratum and the corresponding relation between other stratum parameters and the permeability coefficient, and analyzing the possible development condition of a leakage channel;
8) and after the inversion is finished, feeding back the inversion result to a display terminal in real time.
2. The hydraulic stimulation-based three-dimensional tomographic scanning method for the embankment concealed leakage channel according to claim 1, wherein the step 6) comprises the following steps:
6.1) according to the early exploration data, providing the mean value, the variance and the relevant scale parameters of the formation permeability coefficient;
6.2) assigning the mean value of the permeability coefficient to each grid in the analysis area; calculating the water head of each detection position under the condition of estimation parameters under each water head stimulation by utilizing a three-dimensional permeability coefficient positive analysis model of the detection region in combination with boundary conditions;
6.3) estimating the permeability coefficient value of a point to be estimated in the detection region by utilizing a continuous linear estimation algorithm; wherein, the iterative calculation formula of the unknown permeability coefficient is shown as the formula (1); the calculation formula of the weight coefficient matrix omega is shown as formula (2);
in the formula, r is iteration times; t is a transposed symbol; u. ofcThe permeability coefficient parameter vector of the detection area to be estimated is obtained; u (r +1) c is a parameter vector ucCondition estimate at the r +1 th time; d*Applying the observed value of the water head to the water head; d(r)The simulated value of the water head under the water head effect is obtained by utilizing a three-dimensional permeability coefficient positive analysis model;
[dd+λdiag(dd)]ω=du(2)
in the formula (I), the compound is shown in the specification,ddis a covariance matrix between observed data;duis a covariance matrix between the observed data and the parameters; lambda is a Levenberg-Marquardt algorithm dynamic multiplier; the diag () function is used to construct a diagonal matrix;
6.4) repeating the iteration process of the step (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is less than an error allowable value or reaches a certain iteration step number.
3. The hydraulic stimulation-based three-dimensional tomography scanning method for the embankment hidden leakage passage is characterized in that in the step 6.3), the covariance matrix is obtained by sensitivity:
in the formula, JduThe sensitivity matrix of the water head observation data to the permeability coefficient change of the detection area; parameter covariance matrixuuGiven by the prior geological information when r is 0, then each iteration is updated gradually according to equation (4):
4. the three-dimensional chromatographic scanning method for the dike hidden leakage channel based on the hydraulic stimulation, which is characterized by comprising the following steps of: the display terminal adopts mobile equipment; the mobile device stores a computer program therein; the computer program is used for realizing the steps 2) to 7) when being executed, and realizing the real-time monitoring dynamic scanning of the embankment.
5. The hydraulic stimulation-based three-dimensional tomographic scanning method for the dike hidden leakage channel as claimed in claim 1, wherein: and 7) obtaining the three-dimensional distribution of the geological parameters of the stratum by utilizing the relation between the unknown stratum structure parameters and the permeability coefficients.
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CN113569444A (en) * | 2021-06-30 | 2021-10-29 | 南昌大学 | Random sequential inversion method for permeability coefficient of embankment body material |
CN113758645A (en) * | 2021-08-02 | 2021-12-07 | 重庆交通大学 | Dam leakage inlet detection device and detection method thereof |
CN116819647A (en) * | 2023-08-28 | 2023-09-29 | 北京建工环境修复股份有限公司 | Hydrologic geophysical data fusion method based on cross gradient structure constraint |
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