CN111766189B - Three-dimensional chromatographic scanning method for embankment hidden seepage channel based on hydraulic stimulation - Google Patents
Three-dimensional chromatographic scanning method for embankment hidden seepage channel based on hydraulic stimulation Download PDFInfo
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Abstract
The invention provides a three-dimensional chromatographic scanning method for a hidden leakage channel of a dyke based on hydraulic stimulation. The method comprises the steps of arranging a netlike hydraulic parameter detection well, measuring the natural potential of a region to be detected, connecting a measuring device, measuring potential response, inverting the three-dimensional structure of a stratum of the detection region, feeding back and monitoring in real time and the like. The method can perform high-efficiency chromatographic scanning of the osmotic coefficient of the underground aquifer by utilizing the osmotic coefficient change data measured by the water head sensing device, and greatly improves the reaction speed and the calculation accuracy of the traditional monitoring scheme by implementing the development process of displaying the seepage channel.
Description
Technical Field
The invention relates to the field of geophysical exploration of stratum aquifer and geological structure, in particular to a three-dimensional chromatographic scanning method for a embankment hidden seepage channel based on hydraulic stimulation.
Background
According to the national water conservancy development statistical publication of 2016, various reservoirs 98460 are built in China at present, the total length of river dikes is 29.9 ten thousand kilometers, and various sea dikes are nearly 2 ten thousand kilometers. The hydraulic engineering has great economic and social benefits in aspects of flood control, power generation, water supply, irrigation and the like. However, more than 90% of reservoirs have leakage due to low engineering design standards, poor construction quality, aged deterioration over time, etc., with 30% having more severe leakage. When the water level in the reservoir rises, the reservoir water may run off along the fault fissures of the mountain or the dam foundation of the dam. The dam seepage problem is a problem faced by countries around the world, and the seepage not only causes the waste of water resources, but also directly relates to the safe operation of the dam. To treat the leakage diseases of the dam, the key technical problem is how to accurately diagnose the 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 drawn, and the leakage quantity can be calculated by utilizing the ground water movement theory. The hydraulic chromatography scanning is an effective method for describing the heterogeneous characteristics of the aquifer by using the monitoring data. Hydraulic chromatography scanning is often used in pumping tests to estimate the hydraulic properties of saturated aquifers. The hydraulic tomography scanning is a data fusion and inversion algorithm for reversely deducing possible distribution rules of heterogeneous parameters through observation values. The pumping test is to pump water through one well of an experimental site, and other wells observe water level response, so that one-time scanning of an aquifer can be obtained; by continuously changing the depth of the pumping well or the pumping section, a series of observation data under different stimulations can be collected, and the aquifer scanning images with different angles can be obtained. And integrating the images through a data fusion method to obtain the spatial distribution form of the hydraulic parameters of the aquifer. From the initial virtual ideal calculation example, through indoor test verification and then through field test verification, the method is proved to be capable of effectively describing the spatial distribution of the hydraulic parameters of the saturated aquifer. Since the concept, mathematical model and numerical algorithm of the hydraulic tomography are proposed, the concept and technique of the hydraulic tomography have been widely used in the field of hydrogeology. In the hydraulic tomography method, the traditional inversion model only divides the stratum into a plurality of areas with undetermined parameters, and a unique set of parameter values is obtained by adjusting to minimize the observation-simulation error. The observed data quantity of the inverse problem is larger than the number of parameters to be solved, the algorithm requirement is low, but the method ignores the heterogeneity of a small scale and cannot fully mine a large amount of information collected by the water chromatography investigation. The other model, a Bayesian-based statistical model, regards the prior parameters as spatially dependent random fields, describing their spatial distribution laws and uncertainties with means and covariances. After absorption water power chromatographic scanning observation, the posterior mean value and covariance can be updated. Such models have sufficient degrees of freedom to absorb large amounts of data from the hydraulic tomography scan. However, the method has the advantages of more unknown parameters, large calculated amount, strong anti-problem nonlinearity, easy sinking into a local optimal solution and higher requirement on a logarithmic optimization algorithm.
Therefore, on the basis of the traditional hydraulic chromatography scanning method, the development of the dam hidden leakage channel hydraulic chromatography scanning technology with higher precision is particularly important.
Disclosure of Invention
The invention aims to provide a three-dimensional chromatographic scanning method for a embankment hidden seepage channel based on hydraulic stimulation, which aims to solve the problems in the prior art.
The technical scheme adopted for realizing the purpose of the invention is that the method for three-dimensional chromatographic scanning of the embankment hidden seepage channel based on hydraulic stimulation comprises the following steps:
1) And arranging a net-shaped hydraulic parameter detection well in the region to be detected, and arranging a plurality of detection points in each detection well at intervals. Wherein, the detection point is provided with a water pressure sensing device.
2) And randomly selecting a certain detection point as a stimulation point, and the rest 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 pumping or injecting water, the liquid outlet end moves to detection points at different heights in the well.
4) And 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) Exchanging the stimulation point and the observation point, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in the data processing and analysis system, calculating a response permeability coefficient value by adopting a continuous linear estimation algorithm according to the water head response data, and inverting 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 seepage channel.
8) And feeding back the inversion result to the display terminal in real time after the inversion is finished.
Further, the step 6) specifically includes the following steps:
6.1 According to the earlier exploration data, the mean value, variance and relevant scale parameters of the stratum permeability coefficient are given.
6.2 A mean value of the permeability coefficient is assigned to each grid in the analysis area. And calculating the water head of each detection position under each water head stimulus under the condition of estimating parameters by using a positive analysis model of the three-dimensional permeability coefficient of the detection area in combination with the boundary conditions.
6.3 Using a continuous linear estimation algorithm to estimate the permeability coefficient value of the point to be estimated in the detection area. The iterative calculation formula of the unknown permeability coefficient is shown as formula (1). The calculation formula of the weight coefficient matrix omega is shown in formula (2).
Where r is the number of iterations. T is the transposed symbol. u (u) c And the permeability coefficient parameter vector is the detection area to be estimated. u (r+1) c is a parameter vector u c Condition estimation at the r+1st time. d, d * Is the observed value of the water head under the action of the water head. d, d (r) The simulation value of the water head under the action of the water head is obtained by utilizing a three-dimensional permeability coefficient positive analysis model.
[ε dd +λdiag(ε dd )]ω＝ε du (2)
Wherein ε dd Is the covariance matrix between the observed data. Epsilon du Is the covariance matrix between the observed data and the parameters. Lambda is the dynamic multiplier of the Levenberg-Marquardt algorithm. The diag () function is used to construct a diagonal matrix.
6.4 Repeating the iterative process of the formula (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is smaller than the error allowable value or a certain iterative step number is reached.
Further, in step 6.3), the covariance matrix is derived from the sensitivity:
wherein J is du Is a sensitivity matrix of the water head observation data to the change of the permeability coefficient of the detection area. Parameter covariance matrix epsilon uu Given by a priori geological information at r=0, each iteration is then updated step by step according to equation (4):
further, the display terminal adopts a mobile device. 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 step 7), there is a correlation step of obtaining a three-dimensional distribution of the formation geological parameters using the relationship between the unknown formation structural parameters and the permeability coefficients.
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 high-efficiency chromatographic scanning of the underground permeability coefficient, the obtained result can absorb various detection data source information, nonlinear estimation of unknown permeability coefficient parameters by using observation data is realized, and the simulation precision effect on the hidden leakage channel of the lifting embankment is obvious.
Drawings
FIG. 1 is a workflow diagram;
FIG. 2 solves a domain and grid division;
FIG. 3 is a graph of an iterative process of permeation coefficient tomography;
FIG. 4 is a graph of true value modeling versus value;
FIG. 5 development of the stealth leak path over time;
FIG. 6 is a graph of true leak path versus inverted leak path.
Detailed Description
The present invention is further described below with reference to examples, but it should not be construed that the scope of the above subject matter of the present invention is limited to the following examples. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.
Example 1:
referring to fig. 1, the embodiment discloses a three-dimensional chromatographic scanning method of a embankment hidden seepage channel based on hydraulic stimulation, which comprises the following steps:
1) Dividing the surface of the embankment and the nearby area into areas to be detected. And arranging a plurality of hydraulic parameter detection wells in the region to be detected according to the detection precision requirement and a reasonable interval. Detection points are spaced at different elevations within each detection well. Wherein, the hydraulic parameter detecting well can be a vertical well or an inclined well. The hydraulic parameter detection well penetrates into the soil body of the embankment. 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) And randomly selecting a certain detection point as a stimulation point, and the rest 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 pumping or injecting water, the liquid outlet end moves to detection points at different heights in the well.
4) And 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) Exchanging the stimulation point and the observation point, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in the data processing and analysis system. The continuous linear estimation algorithm linearizes the information of the data by an iterative method, and in the iterative process, a simultaneous absorption mode is adopted in time, so that the nonlinear problem can be effectively solved, and the problem of inconsistent parameter-observation 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 carrying out inversion on the stratum three-dimensional structure of the detection area.
6.1 According to the earlier exploration data, the mean value, variance and relevant scale parameters of the stratum permeability coefficient are given.
6.2 A mean value of the permeability coefficient is assigned to each grid in the analysis area. And calculating the water head of each detection position under each water head stimulus under the condition of estimating parameters by using a positive analysis model of the three-dimensional permeability coefficient of the detection area in combination with the boundary conditions.
6.3 Using a continuous linear estimation algorithm to estimate the permeability coefficient value of the point to be estimated in the detection area. The iterative calculation formula of the unknown permeability coefficient is shown as formula (1). The calculation formula of the weight coefficient matrix omega is shown in formula (2).
Where r is the number of iterations. T is the transposed symbol. u (u) c And the permeability coefficient parameter vector is the detection area to be estimated. u (r+1) c is a parameter vector u c Condition estimation at the r+1st time. d, d * Is the observed value of the water head under the action of the water head. d, d (r) The simulation value of the water head under the action of the water head is obtained by utilizing a three-dimensional permeability coefficient positive analysis model.
[ε dd +λdiag(ε dd )]ω＝ε du (2)
Wherein ε dd Is the covariance matrix between the observed data. Epsilon du Is the covariance matrix between the observed data and the parameters. Lambda is the dynamic multiplier of the Levenberg-Marquardt algorithm. The diag () function is used to construct a diagonal matrix.
The covariance matrix is derived from sensitivity:
wherein J is du Is a sensitivity matrix of the water head observation data to the change of the permeability coefficient of the detection area. Parameter covariance matrix epsilon uu Given by a priori geological information at r=0, each iteration is then updated step by step according to equation (4):
6.4 Repeating the iterative process of the formula (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is smaller than the error allowable value or a certain iterative step number is reached.
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 seepage channel.
8) And obtaining the three-dimensional distribution of the stratum geological parameters by utilizing the relation between the unknown stratum structural parameters and the permeability coefficients.
9) And feeding back the inversion result to the display terminal in real time after the inversion is finished. 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 chromatography scanning method for a large-scale geological structure with a water head as a stimulus source, which comprises the following steps:
1) And arranging a net-shaped hydraulic parameter detection well in the region to be detected, and arranging a plurality of detection points in each detection well at intervals. Wherein, water pump and water pressure sensing device are arranged at the detection point.
2) And randomly selecting a certain detection point as a stimulation point, and the rest detection points as observation points.
3) And pumping water or injecting water at the stimulation point by using a water pump.
4) And 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) Exchanging the stimulation point and the observation point, and repeating the steps 2) to 4).
6) And establishing a three-dimensional geological forward and backward analysis model of the detection area in the data processing and analysis system, calculating a response permeability coefficient value by adopting a continuous linear estimation algorithm according to the water head response data, and inverting 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 seepage channel.
Example 3:
in the embodiment, a 40m multiplied by 60m aquifer region is selected as a research region and is subjected to numerical modeling, and a chromatographic scanning method is utilized to describe the permeability coefficient distribution of the aquifer. And assuming that a high water head area exists at the left boundary of the model, namely the water level boundary in the embankment, a seepage field from left to right is simulated. The method comprises the steps of carrying out unit grid division in a solution domain surrounded by boundaries, wherein the grids are square, the scale is 1m multiplied by 1m, 56 hydraulic parameter detection wells are arranged in total, and a 9-time water head stimulus-response test scheme is preset, and the grid division situation is shown in figure 2:
the calculation is carried out every other hour, the model initiation and boundary conditions are given, a hidden leakage channel is manually set, the homogeneity, variance and relevant scale of the internal structure of the embankment are regulated, and the hidden leakage channel in the simulation field is detected through 9 water head stimulus-response tests. The iteration curve of the scanning process is shown in fig. 3. It can be seen that the piping channels are approximately formed after t=20h. The true value is taken as an abscissa, the analog value is taken as an ordinate, and a relation diagram is drawn to obtain a straight line with a slope of approximately 1, so that the simulation result is better, and a hidden leakage channel can be better detected.
The measurement time was set to 1 hour, and inversion simulation was performed every t=1h. Fig. 5 represents a process in which a leak path is gradually formed in a plurality of simulation processes, in which 5a represents t=0h, 5b represents t=12h, 5c represents t=18h, and 5d represents t=20h. The graph shows that the development process of the hidden leakage channel is gradually ascertained along with the increase of the test measurement times. The osmotic coefficient values in the calculated area gradually change from the initial unified guess value to obvious heterogeneity, and piping channels are approximately formed by the time t=20h.
Figure 6 represents a comparison of the actual leak path distribution over the simulated leak path distribution. 6a is an artificial leak path modeling grid, 6b is a true leak path distribution, and 6c is an inverted leak path distribution. Comparing the true distribution of the leak channels with the distribution of the leak channels obtained by using the chromatographic scanning, it can be seen that the distribution of piping channels obtained by the inverse analysis can better reflect the true situation.
It is worth noting that the three-dimensional tomographic scanning technique is an advanced means for obtaining high-resolution aquifer characteristics by using limited monitoring data inversion. Through comparative analysis, the water head change data measured by the hydraulic sensing device can be used for high-efficiency chromatographic scanning of the permeability coefficient of the underground aquifer, and compared with the traditional monitoring mode, the obtained result is greatly improved in the aspects of accurate positioning, real-time feedback and the like.
Claims (2)
1. The three-dimensional chromatographic scanning method for the embankment hidden seepage channel based on hydraulic stimulation is characterized by comprising the following steps of:
1) Arranging netlike hydraulic parameter detection wells in a region to be detected, and arranging a plurality of detection points in each detection well at intervals; 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 rest 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 moves to detection points at different heights 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 the stimulation point and the observation point, 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 analysis system, calculating a response permeability coefficient value by adopting a continuous linear estimation algorithm according to water head response data, and inverting the stratum three-dimensional structure of the detection area; step 6) comprises the following sub-steps:
6.1 According to the earlier exploration data, the mean value, variance and relevant scale parameters of the stratum permeability coefficient are given;
6.2 Assigning a mean value of the permeation coefficients to each of the grids in the analysis region; calculating the water head of each detection position under each water head stimulus under the condition of estimating parameters by utilizing a positive analysis model of the three-dimensional permeability coefficient of the detection area in combination with the boundary conditions;
6.3 Estimating the permeability coefficient value of the point to be estimated in the detection area by using a continuous linear estimation algorithm; the iterative calculation formula of the unknown permeability coefficient is shown in formula (1); the calculation formula of the weight coefficient matrix omega is shown in formula (2);
wherein r is the iteration number; t is a transposed symbol; u (u) c A permeability coefficient parameter vector for a detection area to be estimated; u (r+1) c is a parameter vector u c Condition estimation at the (r+1) th time; d, d * Is the observed value of the water head under the action of the water head; d, d (r) The simulation value of the water head under the action of the water head obtained by utilizing the three-dimensional permeability coefficient positive analysis model;
[ε dd +λdiag(ε dd )]ω＝ε du (2)
wherein ε dd A covariance matrix between observation data; epsilon du A covariance matrix between the observed data and the parameters; lambda is a dynamic multiplier of a Levenberg-Marquardt algorithm; the diag () function is used to construct a diagonal matrix;
the covariance matrix is derived from sensitivity:
wherein J is du Is a sensitivity matrix of the water head observation data to the change of the permeability coefficient of the detection area; parameter covariance matrix epsilon uu Given by a priori geological information when r=0, followed byEach iteration is updated step by step according to equation (4):
6.4 Repeating the iterative process of the formula (1) until the difference between the calculated value and the detected value obtained under the condition of the obtained parameter estimated value is smaller than the error allowable value or a certain iterative step number is reached;
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 the seepage channel;
8) Obtaining three-dimensional distribution of stratum geological parameters by utilizing the relation between unknown stratum structural parameters and permeability coefficients;
9) And feeding back the inversion result to the display terminal in real time after the inversion is finished.
2. The method for three-dimensional chromatographic scanning of the embankment blind seepage channel based on hydraulic stimulation according to claim 1, which is characterized by comprising the following steps of: 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.
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