A method for predicting land subsidence based on a three-dimensional monitoring network

Abstract

The present invention belongs to the technical field of ground subsidence monitoring and early warning, and relates to a ground subsidence prediction method based on a three-dimensional monitoring network, including: S1, generalizing the hydrogeological structure and quantifying the volume compression coefficient of each layer based on the test data of geological identification holes and the observation data of groundwater level monitoring holes, layered marking holes, and pore water pressure monitoring holes; S2, constructing a three-dimensional groundwater seepage model, and calculating the groundwater level spatial distribution data of each aquifer; S3, fitting the groundwater level monitoring hole observation data with the calculation results, and inverting the parameters in the three-dimensional groundwater seepage model; S4, running the inverted groundwater seepage model to obtain the groundwater level drop and pore water pressure difference spatial distribution data of each aquifer and aquiclude. The ground subsidence prediction method provided by the present application can effectively, quickly and intuitively judge the severity of ground subsidence, the prediction result is highly accurate, and supports the prediction of ground subsidence caused by groundwater exploitation at different depths.

Description

Technical Field

[0001] The present invention belongs to the technical field of land subsidence monitoring and early warning, and relates to a land subsidence prediction method based on a three-dimensional monitoring network. Background Art

[0002] At present, means such as InSAR, surface markers, layered marker groups, fuzzy analytic hierarchy process, machine learning algorithms, etc. are commonly used for subsidence monitoring, analysis and prediction. However, in the application process, basically one or two of them are mainly used, and the cooperation and complementarity between different technologies are insufficient. Moreover, subsidence monitoring can only reflect the settlement changes of single points or local areas. In addition to not being able to show the spatio-temporal distribution of land subsidence in the overall area, it also lacks the ability to judge the dynamic changes of land subsidence from a developmental perspective. Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a land subsidence prediction method based on a three-dimensional monitoring network.

[0004] In order to achieve the above purpose, the present invention provides the following technical solutions:

[0005] A land subsidence prediction method based on a three-dimensional monitoring network, comprising:

[0006] S1, based on the test data of geological identification holes and the observation data of groundwater level monitoring holes, layered marker holes, and pore water pressure monitoring holes, generalize the hydrogeological structure and quantify the volume compressibility coefficients of each layer;

[0007] S2, construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of groundwater levels in each aquifer;

[0008] S3, fit the observation data of the groundwater level monitoring holes with the calculation results to invert the parameters in the three-dimensional groundwater seepage model;

[0009] S4, run the inverted groundwater seepage model to obtain the spatial distribution data of the groundwater level drawdown and pore water pressure difference in each aquifer and aquitard;

[0010] S5, under the condition of one-dimensional nonlinear consolidation, superimpose the deformations generated by the action of water level differences or pore water pressure differences at different spatial positions to obtain the final ground settlement value.

[0011] In the present invention, preferably, S1 includes:

[0012] S11, based on the test data of geological identification holes, judge the distribution of the thickness of formation particles, and divide the lithological layers of the whole well section. The test data of the geological identification holes include geophysical logging data, geological columnar diagrams, and core test data;

[0013] S12 uses the equivalent permeability coefficient method to draw the cumulative change curve of the hydraulic conductivity with depth, combines the lithologic layers of the entire well section according to the slope change of the curve, and generalizes the spatial distribution of the aquifer medium in the site, including quantifying the burial depth, thickness of the aquifer and aquitard, and the permeability zoning of each layer;

[0014] S13. According to the final settlement formula of the top surface of one-dimensional non-linear finite strain consolidation of soil layer:

[0015]

[0016] Derive the formula for the volume compressibility coefficient of the soil skeleton as:

[0017]

[0018] Where m v is the volume compressibility coefficient of the soil skeleton, S is the final settlement of the top surface of the corresponding soil layer, H is the thickness of the aquifer or aquitard, q u is the change in vertical stress caused by the change in water pressure, q u = ×S w , where is the unit weight of water, S w is the change in water level or pore water pressure of the corresponding soil layer;

[0019] S14. According to the measured groundwater level drawdown data, pore water pressure difference data, and top surface settlement data of each layer within the same time period, use the formula for the volume compressibility coefficient of the soil skeleton to solve the volume compressibility coefficients of each aquifer and aquitard.

[0020] In the present invention, preferably, the aquifer described in S12 refers to a formation composed of at least one medium of gravel soil, sandy soil, and silty soil that can give out and transmit water.

[0021] In the present invention, preferably, the aquitard described in S12 refers to a formation composed of at least one medium of clay and silty clay that can neither give out nor transmit water.

[0022] In the present invention, preferably, the S2 includes:

[0023] S21. According to the quantified burial depths of the aquifer and aquitard and the permeability zoning of each layer, establish a hydrogeological structure model;

[0024] S22. Input the permeability coefficient, specific yield, elastic water release rate, recharge amount, and extraction amount into the hydrogeological structure model;

[0025] S23. Calculate the spatial contour map of the groundwater level of each aquifer in the site.

[0026] In the present invention, preferably, the method for inverting the parameters in the three-dimensional groundwater seepage model in S3 is as follows:

[0027] Compare the deviation between the calculated groundwater level value and the observed groundwater level value at the site. By continuously adjusting the values of the permeability coefficient, specific yield, and elastic water release rate, and repeatedly running the model until the trend of the calculated groundwater level value and the observed groundwater level value can be completely fitted and the root mean square error is not greater than 2%, the parameters in the model at this time are the hydrogeological parameters suitable for this site.

[0028] In the present invention, preferably, in S4, the planned extraction amounts under different rainfall environments are substituted into the inverted groundwater seepage model, and the inverted groundwater seepage model is run to obtain the groundwater level drawdown values or pore water pressure differences at different spatial positions.

[0029] In the present invention, preferably, the different rainfall environments refer to the dry season, wet season, normal season, and the rainfall period with an average of N years.

[0030] In the present invention, preferably, S5 includes:

[0031] S51, export the groundwater level difference or pore water pressure difference data of each layer after the model runs, and the export data arrangement format is X, Y, S’ w , under the one-dimensional nonlinear consolidation condition, use the layer-wise summation method to calculate the final ground settlement values at different spatial positions. The calculation formula is as follows:

[0032]

[0033] Where S 总 is the final ground settlement value; H i is the thickness of the i-th layer of aquifer medium; q ui is the vertical stress change caused by the water pressure change in the i-th layer of aquifer medium, q ui = ×S’ wi , where is the unit weight of water, S’ wi is the water level or pore water pressure change in the i-th layer of aquifer medium; m vi is the volume compressibility coefficient of the soil skeleton in the i-th layer of aquifer medium, X, Y are plane coordinates, S’ w is the water level change or pore water pressure change of the aquifer medium;

[0034] S52, import the final ground settlement values at different spatial positions into the geographic data gridding drawing software Sufer to obtain the ground settlement contour map within the site range.

[0035] Compared with the prior art, the beneficial effects of the present invention are:

[0036] The present invention introduces the technology of a three-dimensional ground settlement monitoring network and the principle of one-dimensional non-linear finite strain consolidation of soil layers, effectively improving the accuracy of ground settlement prediction. The present invention utilizes groundwater seepage simulation technology to obtain the dynamic spatio-temporal variation values of groundwater levels under different conditions, and then intuitively presents the spatio-temporal distribution characteristics of ground settlement, which has strong guidance and is convenient for taking targeted anti-settlement measures, saving the time and economic costs of disaster prevention and control. Brief Description of the Drawings

[0037] Figure 1 It is a flowchart of the ground settlement prediction method based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0038] Figure 2 It is a flowchart of S1 in the ground settlement prediction method based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0039] Figure 3 It is a flowchart of S2 in the ground settlement prediction method based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0040] Figure 4 It is a flowchart of S5 in the ground settlement prediction method based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0041] Figure 5 It is the upper half of the comprehensive columnar diagram of the geological identification borehole at a certain site according to an embodiment of the present invention.

[0042] Figure 6 It is the lower half of the comprehensive columnar diagram of the geological identification borehole at a certain site according to an embodiment of the present invention.

[0043] Figure 7 It is a curve diagram showing the variation of the cumulative water conductivity coefficient with depth of the geological identification borehole at a certain site according to an embodiment of the present invention.

[0044] Figure 8 It is a diagram of the grid division of the groundwater seepage model and the calculated groundwater level distribution at a certain site according to an embodiment of the present invention.

[0045] Figure 9 It is a fitting comparison diagram of the calculated groundwater level and the observed groundwater level at a certain site according to an embodiment of the present invention.

[0046] Figure 10 It is a spatial distribution diagram of the groundwater level drawdown after 10 years of current groundwater extraction under the N-year average rainfall environment at a certain site according to an embodiment of the present invention.

[0047] Figure 11 It is a spatial distribution diagram of ground settlement after 10 years of current groundwater extraction under the N-year average rainfall environment at a certain site according to an embodiment of the present invention. Detailed Embodiments

[0048] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention.

[0050] Please also refer to Figures 1 to 4 , a ground settlement prediction method based on a three-dimensional monitoring network provided by a preferred embodiment of the present invention includes:

[0051] S1. Based on the test data of geological identification holes and the observation data of groundwater level monitoring holes, layer markers, and pore water pressure monitoring holes, generalize the hydrogeological structure and quantify the volume compressibility coefficients of each layer.

[0052] Specifically, as Figure 2 shown, the generalization of the hydrogeological structure and the quantification of the volume compressibility coefficients of each layer in S1 may include:

[0053] S11. Based on the test data of geological identification holes (including geophysical logging data, geological histograms, and core test data), judge the distribution of the thickness of formation particles, and divide the lithologic layers of the entire well section.

[0054] As Figure 5 and Figure 6 shown in the comprehensive histogram of a geological identification hole at a certain site, through the geophysical logging data in the geological identification hole, combined with the core sampling of the entire well section and the local hydrogeological data, judge the distribution of the thickness of formation particles, the buried depth of different lithologies, porosity, permeability, etc.

[0055] S12. Use the equivalent permeability coefficient method to draw the cumulative change curve of the hydraulic conductivity with depth, and combine the lithologic layers of the entire well section according to the slope change of the curve to generalize the spatial distribution of the aquifer medium in the site, including quantifying the buried depth, thickness of the aquifer and aquitard, and the permeability zoning of each layer.

[0056] Among them, an aquifer refers to a formation composed of at least one of gravel, sand, and silt that can give out and transmit water, and an aquitard refers to a formation composed of at least one of clay and silty clay that can neither give out nor transmit water. As Figure 7As shown in the curve of the cumulative hydraulic conductivity varying with depth of a geological identification borehole at a certain site, by calculating the product of the permeability coefficient and the layer thickness of each layer of lithology in the geological identification borehole and accumulating them the cumulative hydraulic conductivity is obtained, and a curve of the cumulative hydraulic conductivity varying with depth is plotted. From Figure 7 it can be seen that the slope of the curve changes significantly with depth. A large slope indicates good permeability and can be generalized as an aquifer, while a small slope indicates poor permeability and can be generalized as an aquitard. According to the changing trend of the slope of the curve, the water-bearing medium of the geological identification borehole is generalized into 5 layers. The horizontal permeability coefficient of each layer of water-bearing medium can be calculated using the following formula:

[0057]

[0058] where: K h is the horizontal permeability coefficient of the generalized water-bearing rock formation (m / d); K hi is the horizontal permeability coefficient of the i-th stratum (m / d); M i is the thickness of the i-th stratum (m).

[0059] S13. According to the formula for the final settlement of the top surface of one-dimensional non-linear finite strain consolidation of soil layers:

[0060]

[0061] the formula for the volume compressibility coefficient of the soil skeleton is derived as:

[0062]

[0063] where m v is the volume compressibility coefficient of the soil skeleton; S is the final settlement of the top surface of the corresponding soil layer; H is the thickness of the aquifer or aquitard; q u is the change in vertical stress caused by the change in water pressure, q u = ×S w , where is the unit weight of water, and S w is the change in water level or pore water pressure of the corresponding soil layer.

[0064] S14. According to the measured data of the water level drawdown, pore water pressure difference, and settlement data of the top surface of each layer within the same time period, the volume compressibility coefficients of each aquifer and aquitard are solved using the formula for the volume compressibility coefficient of the soil skeleton.

[0065] As shown in Table 1 below, by reading the relevant data of the groundwater level monitoring borehole, layer mark borehole, and pore water pressure monitoring borehole, the water level drawdown data, pore water pressure difference data, and settlement data of the top surface of each layer within the same time period are obtained, and substituting them into the above formula for solving the volume compressibility coefficient of the soil skeleton, the volume compressibility coefficients of the soil skeletons of different water-bearing media are obtained.

[0066] Table 1 Calculation process of volume compressibility of different water-containing media

[0067]

[0068] S2. Construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of the groundwater levels in each aquifer.

[0069] Specifically, as Figure 3 shown, S2 includes:

[0070] S21. Establish a hydrogeological structure model based on the quantified burial depths of aquifers and aquitards and the permeability zoning of each layer.

[0071] S22. Input the permeability coefficient, specific yield, elastic water release rate, recharge amount, and extraction amount into the hydrogeological structure model.

[0072] S23. Calculate the spatial contour map of the groundwater levels in each aquifer of the site.

[0073] As Figure 8 shown, based on the quantified burial depths of aquifers and aquitards and the permeability zoning of each layer, establish a hydrogeological structure model. Input data such as the permeability coefficient, specific yield, elastic water release rate, recharge amount, and extraction amount into the model to obtain a three-dimensional groundwater seepage model. Solve this model by the discretization method to obtain the contour map of the groundwater level of the site (i.e., Figure 8 the solid line with data in).

[0074] S3. Fit the observed data of the groundwater level monitoring wells with the calculation results and invert the parameters in the three-dimensional groundwater seepage model.

[0075] Specifically, compare the deviation between the calculated groundwater level value and the observed groundwater level value of the site. By continuously adjusting the values of the permeability coefficient, specific yield, and elastic water release rate, repeat running the model until the trend of the calculated groundwater level value can be completely fitted with the observed groundwater level value (the observed value of the groundwater level monitoring well). Figure 9 is a comparison diagram of the calculated contour map of the groundwater level (solid line) and the observed contour map of the groundwater level (dashed line) of a certain site including geological identification wells. It can be seen that the calculated contour map of the groundwater level fits the macroscopic shape well, not only correctly reflects the recharge-discharge characteristics of groundwater, but also has a high fitting accuracy with the measured water level values in most areas, with an absolute error less than 1 m and the root mean square error also meeting the research requirements, that is, the root mean square error is not greater than 2%. At this time, the parameters in the model are the hydrogeological parameters suitable for this site.

[0076] S4. Run the inverted groundwater seepage model to obtain the spatial distribution data of the groundwater level drawdown and pore water pressure difference in each aquifer and aquitard.

[0077] The change in the groundwater level or pore water pressure causes a change in the vertical stress of each soil layer in the field area, which in turn induces ground settlement. The dynamic change of the water level is affected by rainfall and the local groundwater extraction volume. According to the abundance of rainfall, the rainfall environment is divided into several specific rainfall periods, namely the dry season, the wet season, the normal season, and the N-year average. Among them, the rainfall period of the N-year average is rainfall data obtained through calculation, and N years can be any number of years set as needed.

[0078] Specifically, substitute the planned extraction volume under different rainfall environments into the inverted groundwater seepage model, and run it to obtain the spatial distribution data of the groundwater level drawdown and / or the pore water pressure difference of each aquifer and aquitard. As Figure 10 shown, it is the spatial distribution map of the groundwater level drawdown calculated after 10 years of groundwater extraction in a certain site containing geological identification holes under the N-year average rainfall environment according to the current situation.

[0079] S5. Under the condition of one-dimensional nonlinear consolidation, superimpose the deformations generated by the water level difference or pore water pressure difference at different spatial positions to obtain the final ground settlement value.

[0080] Specifically, as Figure 4 shown, calculating the final ground settlement value at different spatial positions in S5 may include

[0081] S51. Export the groundwater level difference or pore water pressure difference data of each layer after the model runs. The export data arrangement format is X, Y, S’. w , under the condition of one-dimensional nonlinear consolidation, use the layer-wise summation method to calculate the final ground settlement value at different spatial positions. The calculation formula is as follows:

[0082]

[0083] where S 总 is the final ground settlement value; H i is the thickness of the i-th layer of water-bearing medium; q ui is the change in vertical stress caused by the change in water pressure of the i-th layer of water-bearing medium. q ui = ×S’ wi , where is the unit weight of water, S’ wi is the change in water level or pore water pressure of the i-th layer of water-bearing medium; m vi is the volume compressibility coefficient of the soil skeleton of the i-th layer of water-bearing medium, X and Y are plane coordinates, and S’ w is the change in water level or pore water pressure of the water-bearing medium. When the position is an aquifer, measure the change in water level of the water-bearing medium, that is, S’ wIndicates the change in the water level of the water-bearing medium (or the water level difference of the water-bearing medium). When this position is an aquitard, the change in pore water pressure is measured, that is, S’ w Indicates the change in pore water pressure (or the pore water pressure difference).

[0084] S52. Import the final ground settlement values at different spatial positions into the geographic data gridding and mapping software Surfer to obtain the ground settlement contour map within the site. As Figure 11 shown, based on this, the severity of ground settlement can be effectively, quickly and intuitively judged.

Claims

1. A method for predicting land subsidence based on a three-dimensional monitoring network, characterized in that: include: S1, generalize the hydrogeological structure and quantify the volume compression coefficient of each layer based on the experimental data of geological identification holes and the observation data of groundwater level monitoring holes, stratification marking holes, and pore water pressure monitoring holes; S2, construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of groundwater levels in each aquifer; S3, fitting the observation data of groundwater level monitoring holes with the calculation results, inverting the parameters in the three-dimensional groundwater seepage model; S4, running the inverted groundwater seepage model to obtain the groundwater level drawdown and pore water pressure difference spatial distribution data of each aquifer and aquitard; S5, under one-dimensional nonlinear consolidation conditions, the deformations caused by the water level difference or pore water pressure difference at different spatial positions are superimposed to obtain the final ground settlement value; The S1 includes: S11, based on the test data of the geological identification hole, determine the distribution of stratum grain size and divide the lithology layer of the entire well section; the test data of the geological identification hole includes geophysical logging data, geological columnar diagram and core test data; S12, using the equivalent permeability coefficient method to draw the cumulative change curve of water conductivity with depth, combining the lithology layers of the entire well section according to the change of the slope of the curve, generalizing the spatial distribution of the water-bearing media in the site, including quantifying the burial depth, thickness and permeability zoning of the aquifer and aquiclude; S13, according to the formula of the final settlement of the top surface of the one-dimensional nonlinear finite strain consolidation of the soil layer: The formula for the volume compression coefficient of the soil skeleton is derived as follows: Where m v is the volume compression coefficient of the soil skeleton, S is the final settlement of the top surface of the corresponding soil layer, H is the thickness of the aquifer or aquiclude, q u is the vertical stress change caused by the water pressure change, q u = ×S w ,in is the water density, S w To correspond to the change of soil water level or pore water pressure; S14, based on the measured water level drop data, pore water pressure difference data, and settlement data of the top surface of each layer in the same time period, the volume compression coefficient formula of the soil skeleton is used to solve the volume compression coefficient of each aquifer and aquiclude; The S5 includes: S51, export the groundwater level difference or pore water pressure difference data of each layer after the model is run, and the exported data is arranged in the format of X, Y, S' w Under one-dimensional nonlinear consolidation conditions, the final ground settlement values ​​at different spatial positions are calculated using the layered summation method. The calculation formula is as follows: ， in S 总 is the final ground settlement value, H i is the thickness of the i-th layer of water-containing medium, q ui is the vertical stress change caused by the water pressure change of the i-th layer of water-bearing medium, q ui = ×S' wi ,in is the water density, S' wi is the change in water level or pore water pressure of the i-th layer of water-bearing medium, m vi is the volume compression coefficient of the i-th layer of water-bearing soil skeleton, X and Y are plane coordinates, S' w It is the change of water level or pore water pressure in aquiferous medium; S52, importing the final ground settlement values ​​at different spatial locations into the geographic data gridding drawing software Sufer to obtain a ground settlement contour map within the site.

2. The method according to claim 1, characterized in that The aquifer refers to a stratum composed of at least one medium selected from gravel, sand and silt that can give out and pass water.

3. The method according to claim 1, characterized in that The aquiclude refers to a stratum composed of at least one medium selected from clay and silty clay that can neither give out nor pass through water.

4. The method according to claim 1, characterized in that The S2 includes: S21, establish a hydrogeological structure model based on the quantified burial depth of aquifers and impermeable layers and the permeability zoning of each layer; S22, input the permeability coefficient, water supply degree, elastic water release rate, recharge volume, and extraction volume into the hydrogeological structure model; S23, calculate the spatial contour map of groundwater levels in each aquifer on the site.

5. The method according to claim 1, characterized in that The method of inverting the parameters in the three-dimensional groundwater seepage model in S3 is: Compare the deviation between the calculated groundwater level value and the observed groundwater level value of the site, and repeatedly run the model by continuously adjusting the values ​​of the permeability coefficient, water supply degree, and elastic water release rate until the calculated groundwater level value and the observed groundwater level value trend can be completely fitted, and the root mean square error is no more than 2%. At this time, the parameters in the model are the hydrogeological parameters suitable for this site.

6. The method according to claim 1, characterized in that In S4, the planned extraction volume under different rainfall environments is substituted into the inverted groundwater seepage model, and the inverted groundwater seepage model is run to obtain groundwater level drop values ​​or pore water pressure difference values ​​at different spatial positions.

7. The method according to claim 6, characterized in that The different rainfall environments refer to the dry season, the flood season, the normal water season and the average rainfall period over N years.

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