Underground karst reservoir capacity curve calculation method based on hydrogeological parameters

Abstract

Disclosed in the present invention is an underground karst reservoir capacity curve calculation method based on hydrogeological parameters. The method comprises: performing hydrogeological exploration, determining the range of an underground reservoir, determining a water storage space, determining relevant hydrogeological parameters on the basis of hydrogeological tests, and performing underground reservoir capacity analysis. In the present invention, a unit water permeability and an encounter rate of karst cavities in boreholes, which are extremely easily obtained by means of borehole water pressure / water injection tests, are used in combination with a few pumping tests, so as to obtain, by means of performing regression analysis with the unit water permeability or a permeability coefficient, a correlation function relationship for a specific yield and a karstification rate, which are difficult to obtain. The method for obtaining an underground reservoir capacity curve by means of calculating underground reservoir capacities at corresponding elevations on the basis of a specific yield or a karstification rate can not only improve accuracy and reduce errors, but can also function as a guide for the water storage, scheduling, and flood control of underground reservoirs.

Description

A calculation method for karst underground storage capacity curve based on hydrogeological parameters Technical Field

[0001] The present invention relates to the technical field of karst underground reservoir capacity calculation, and in particular to a karst underground reservoir capacity curve calculation method based on hydrogeological parameters. Background Art

[0002] Underground storage capacity refers to the pores, cracks and karst cave aquifer cavities below the ground that have water storage and utilization value. There is no relevant literature at home and abroad that systematically discusses the underground reservoir storage capacity, and it has always been a blank area in theoretical research. The lag in theoretical research has restricted the rational development and utilization of aquifers.

[0003] Research on the storage capacity of karst caves relative to pore and fissure-type groundwater reservoirs, especially underground storage capacity curves, is of great significance for the effective implementation of reservoir planning and scheduling plans. Due to the extremely heterogeneous storage medium, the analysis is relatively difficult. The following methods are generally used to calculate the storage capacity of groundwater reservoirs:

[0004] (1) Groundwater balance method

[0005] Based on the measured runoff of the karst underground river, the annual distribution analysis of the designed annual runoff (P=75%) was carried out, and the runoff in April, the driest period, was taken as the stable runoff, and the underground storage capacity was not less than the sum of the stable runoff and the seasonal increase in runoff during the dry period (January to May) as the karst underground storage capacity.

[0006] (2) Plotnikov method for groundwater runoff

[0007] Plotnikov classified groundwater reserves as follows:

[0008] Dynamic reserves are the volume of groundwater flowing through a certain water-passing section of the aquifer per unit time under natural conditions; regulating reserves are the volume of water stored in the aquifer between the highest and lowest water levels under natural conditions; static reserves are the part of the storage volume that needs to be extracted by wells; the regulating reserves of the underground storage capacity, which is the volume of water stored in the aquifer between the highest and lowest water levels under natural conditions, are the underground storage capacity.

[0009] (3) Other methods

[0010] There are also the following methods for calculating underground reservoir capacity based on the few domestic and foreign literature:

[0011] 1. Water supply method: For porous and fractured underground storage capacity, water supply obeys different probability distributions (normal distribution) in space. Based on the determined water supply distribution, the spatial overlay function of ArcGIS software is used to overlay the water supply zoning map of the study area's phreatic aquifer with the average groundwater level and surface elevation of a certain year. The dewatering storage capacity of the phreatic aquifer in that year is calculated. The entire area is then divided into rectangles, and the buried depth of each cell is calculated based on the surface elevation and the average groundwater level of that year. Based on the actual analysis needs, the Monte Carlo method is used to perform multiple random simulations (fuzzy method). Each simulation generates several water supply values ​​that meet a certain distribution, and the corresponding multiple dewatering storage capacity values ​​are obtained.

[0012] 2. Water content method: The water content of the karst body is affected by the porosity and water absorption of the rock mass. It is determined by the weighted average of the water content of the cross section. The volume of the underground system (underground storage capacity) is determined by the product of the underground rock volume and the average water content.

[0013] 3. Mathematical modeling of tracer detection: For complex karst seepage fields with dissolution gaps, two karst hydrogeological models can be generalized: a dual parallel flow field of pipes and dissolution gaps and a single-pipe series pool flow field. Calculations are based on the average groundwater flow rate, the total mass of the tracer, the average or peak concentration, and the time required to achieve half or full recovery.

[0014] 4. Water storage space geometric morphology generalization method:

[0015] The volume of karst caves was calculated based on actual measurements.

[0016] 5. Water tank model simulation method (inversion method): In the evaluation of underground storage capacity, it is usually obtained by inverting the original data of the reservoir operation and scheduling records after the underground reservoir is filled with water. By releasing water (water release test) in the underground river retaining space and water storage space (water tank), the water flowing out of the water tank is the underground storage capacity. The storage and release of the water tank can be linear or nonlinear, usually linear.

[0017] In summary, a review of existing research on karst underground reservoir capacity demonstrates, primarily from a macroscopic perspective, that all methods involve certain errors and inaccuracies, and only yield a single estimate of total underground reservoir capacity. Determining water content, karstification rate, and water content is challenging, especially for measuring large numbers of karst fractures. Tracer detection methods suffer from tracer adsorption loss and are difficult to estimate for unfilled cavities. Water tank simulation methods are conducted after reservoir filling and offer little guidance for preliminary survey and design. Furthermore, their guidance for underground reservoir storage, scheduling, and flood control is limited, making it difficult to understand underground reservoir capacity characteristics at varying elevations.

[0018] Summary of the Invention

[0019] In order to guide the survey, design, water storage, scheduling and flood control of underground reservoirs, it is necessary to understand more about the water storage capacity at different water storage elevations, so as to determine the corresponding water storage and water use plans according to different elevations and formulate corresponding flood control measures. It is necessary not only to obtain the total storage capacity, but also to understand the storage capacity characteristics under different water storage level conditions.

[0020] The technical solution provided by the present invention is:

[0021] A method for calculating a karst underground storage capacity curve based on hydrogeological parameters, characterized by comprising the following steps:

[0022] S1. Hydrogeological Exploration: Conduct hydrogeological exploration of the target underground reservoir, including exploring the dam site area, reservoir area karst conditions, and karst groundwater distribution;

[0023] S2. Determine the scope of the underground reservoir: Based on the hydrogeological conditions of the target underground reservoir's basin, as well as the groundwater overflow elevation at the karst watershed, groundwater springs, and hydrogeological drilling data, obtain the groundwater level during the dry season and draw an isowater level map based on this to determine the boundary and bottom conditions of the underground reservoir capacity;

[0024] S3. Determine water storage space: Through ground geological mapping, calculate the karst fracture rate at multiple points, further survey the karst caves between the highest water storage level and the lowest groundwater level, and focus on identifying the volume and elevation distribution of the karst caves that can be explored. At the same time, calculate the volume distribution of water-storing rock masses and karst caves that can be explored at different elevations above the lowest groundwater level.

[0025] S4. Determine relevant hydrogeological parameters based on hydrogeological testing: Arrange multiple groups of exploratory boreholes and pumping test holes within the catchment area of ​​the target underground reservoir, and conduct a large number of borehole pressure / water injection tests to obtain hydrogeological parameters, including the borehole void encounter rate and specific water permeability. Based on the drawdown curve and drawdown funnel drainage volume and water supply degree obtained from the pumping test, analyze the water supply degree at various elevations of the underground reservoir basin;

[0026] S5. Underground reservoir capacity curve analysis: Based on the borehole data, the encounter rate of karst caves, including filled and unfilled types, and the unit water permeability of each borehole are statistically analyzed according to the elevation distribution. The weighted average of the relevant section length is used to calculate the encounter rate of karst caves and unit water permeability of the comprehensive boreholes at each elevation;

[0027] According to the regression relationship between karst water supply rate, comprehensive drilling karst cave encounter rate and unit water permeability μ=0.525n+0.088q, the water supply degree of each elevation involved in the underground reservoir capacity is calculated;

[0028] For underground storage capacity, the underground storage capacity should be the volume of all karst caves that can be filled with water in the underground karst body, which is the volume of karst caves that can be explored and measured.洞 Add the remaining soluble rock volume v after deducting the karst caves that can be explored and measured 溶隙 The product of the above karst water supply degree V 溶隙 To determine, the underground karst reservoir volume V=V 洞 +V 溶隙 ;

[0029] Among them, V 洞 It is a relatively large unfilled karst cave; v 溶隙 =V 总 -V 洞 ; V 溶隙 =μv 溶隙 .

[0030] The advantages of the present invention over the prior art are: the present invention uses the unit water permeability and the borehole karst cave encounter rate, which are very easy to obtain through borehole pressure (injection) water tests, combined with a small amount of pumping tests, to perform regression analysis on the water supply degree and karst rate, which are difficult to obtain, with the unit water permeability or the permeability coefficient to obtain a related functional relationship. The method calculates the underground storage capacity at the corresponding elevation based on the water supply degree or the karst rate and obtains the underground storage capacity curve, which can improve accuracy and reduce errors, and can play a guiding role in underground reservoir water storage, scheduling and flood control. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] FIG1 is a diagram showing the annual distribution of underground river runoff P=75% of the designed annual runoff in the method of the present invention.

[0032] FIG2 is a schematic diagram of the hydrogeology and exploration drilling arrangement of the Shilin underground reservoir in the method of the present invention.

[0033] FIG3 is a cross-sectional view of the pumping hole in the method of the present invention.

[0034] FIG4 is a graph showing the underground reservoir capacity in the method of the present invention. DETAILED DESCRIPTION

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0036] Example:

[0037] This plan takes the Shilin underground reservoir as an example. The Shilin underground reservoir is located in the Shilin karst area of ​​the Yunnan Plateau at the source of the Bajiang River, a tributary of the Nanpan River in the Xijiang River system in the Pearl River Basin. The karst is very developed. The total underground and surface runoff area is 26.63km 2The average annual groundwater runoff P = 50% is 12.98 million m 3 , P = 75% is 9.41 million m 3 , flow rate 0.044~4.35m 3 / s, as shown in Figure 1.

[0038] The reservoir consists of two surface basins (the Xiangshuidong karst funnel basin and the Qingshikan karst basin) and one underground basin. The main structures include the Qingshikan karst basin dam, a connecting tunnel between the reservoirs, a water transfer culvert, a water collection corridor, and a subterranean river dredging tunnel. The inlet floor elevation of the water transfer culvert (high culvert) is 1851.50 meters. The gate bottom width of the subterranean river dredging tunnel is 1.6 meters, and the floor elevation is 1822.50 meters.

[0039] Groundwater reservoirs located in karst areas face complex hydrogeological conditions. The reservoir basin is composed of underground rivers, caves, rock cavities, and fissures. To intercept and fully utilize these karst caves to form and regulate underground reservoirs, it is essential to study the characteristics of underground reservoir capacity, with a particular focus on reservoir capacity at different elevations.

[0040] With reference to Figures 1-4 , the working method of this embodiment includes the following steps:

[0041] S1. Brief Introduction to Hydrogeology and Exploration

[0042] The Shilin Underground Reservoir is located on the karst platform of eastern Yunnan. Since 1966, a groundwater observation station has been established, and project demonstration, feasibility studies, preliminary design, and construction have been carried out. The karst strata involved in the Shilin Underground Reservoir are limestones of the Qixia Formation of the Carboniferous and Lower Permian systems. The dam site is located between two layers of limestone, in a zone of sandstone and mudstone interbedded with argillaceous limestone of the Daoshitou Formation of the Lower Permian system. As shown in Figure 2, the underground reservoir area was formed by intercepting and sealing underground rivers, karst caves, and dissolution fissures. This raised the groundwater level, built a dam in the hub area, and stored water in the upstream karst depression to form a surface reservoir, achieving gravity water supply.

[0043] According to the karst development characteristics of the Shilin underground reservoir and the layout of engineering buildings, a total of 47 exploration drilling holes were completed, with a drilling footage of 3,319 meters and 567 sections of pressure (injection) water tests; 18 underground reservoir basin drilling holes were involved (including 6 pumping holes and monitoring holes). In order to find out the karst conditions of the dam site and reservoir area, and the distribution of karst groundwater, the drilling holes were mainly arranged in the dam site and the curtain anti-seepage axis. At the same time, according to the karst characteristics of the reservoir area, two pumping test areas were arranged in the karst developed and less developed areas of the reservoir area. Each pumping test area was arranged with a pumping hole, and two groundwater level observation holes were arranged about 15 to 20 meters and 50 meters outside the pumping hole.

[0044] S2. Determination of the scope of underground reservoir:

[0045] Based on the hydrogeological conditions of the underground reservoir basin, the groundwater overflow elevation (karst lake) in the karst watershed, groundwater springs and hydrogeological drilling data, a more detailed groundwater level in the dry season is obtained and a groundwater level line map is drawn based on this to determine the boundary and bottom conditions of the underground storage capacity.

[0046] S3. Determination of water storage space:

[0047] Through ground geological mapping, the karst fissure rate at multiple points was counted, and the karst caves between the highest water storage level and the lowest groundwater level were further surveyed, with a focus on identifying the volume and elevation distribution of the explorable karst caves. At the same time, the volume distribution of water-storage rock bodies and explorable karst caves at different elevations above the lowest groundwater level was calculated.

[0048] S4. Determine relevant hydrogeological parameters based on hydrogeological testing:

[0049] To analyze underground reservoir capacity curves, it is important to obtain the water supply at relevant elevations, which in turn involves a number of relevant hydrogeological parameters. Because a large number of exploratory boreholes and pumping test holes are arranged within the groundwater reservoir catchment area, and a large number of borehole pressure (injection) water tests have been conducted, it is easy to obtain relevant hydrogeological parameters such as the unit permeability of the rock mass and the encounter rate of karst cavities in the boreholes.

[0050] 1. Easily accessible hydrogeological parameters

[0051] (1) The encounter rate of karst caves in the borehole (n:%) is the ratio of the total length of karst caves seen in the borehole (l(m)) to the drilling footage of the section (L(m)):

[0052] (2) Unit water permeability (q: lu): The amount of water injected (Q: l / min) under unit pressure (P: MPa) and unit test section length (L: m):

[0053] (3) Permeability coefficient

[0054] The permeability coefficient is mainly obtained from the two pumping test wells ZK114 and ZK111. There are many methods for calculating the permeability coefficient. According to the "Water Supply Hydrogeological Survey Code GB50027-2001" and the "Hydropower and Water Conservancy Project Drilling Pumping Test Code DL / T5213-2005", there are mainly water supply code formulas, Qiu Buyi, Babushkin, Skabalanovich and other formulas. The results obtained by analysis are 8.355 to 23.022 times different. The average value of various methods is close to the Babushkin formula, that is:

[0055] In the above formula: K is the permeability coefficient m / d, Q is the water inflow m 3 / d, l is the filter length m, s is the drawdown m, and r is the drilling radius m.

[0056] 2. Descent curve and drainage volume

[0057] (1) Pumping test and related results are shown in Table 1;

[0058] (2) Calculated according to the Kusakin influence radius formula and the Weber water supply formula:

[0059] According to the Kusakin influence radius formula:

[0060] Where: s is the influence radius of the drop funnel in m, K is the permeability coefficient in m / d, and H is the thickness of the phreatic aquifer in m. The influence radius is calculated to be 26m to 206m, which is somewhat different from the measured data.

[0061] Table 1 Comprehensive results of pumping test

[0062] According to the Weber formula: Transformed into

[0063] Where: μ is the water supply rate (%), t is the pumping time d, and the water supply rate calculated using the Kusakin formula influence radius is 0-5%, with an average of 1.98%, which is difficult to correlate with the karst development at various elevations of the underground reservoir basin and the water supply rate; the water supply rate calculated according to the measured influence radius is 0.4-4989%, which varies greatly.

[0064] (3) Drainage volume of the drop funnel

[0065] Fitting is performed based on the observation results of the groundwater drawdown curve of ZK111 and 114 wells (as shown in Figure 3):

[0066] Assume: R is the maximum radius of the falling funnel m, s is the maximum depth of groundwater drop m, r i is the distance from the pumping hole axis in m, h i For r i The water level is m above the maximum drawdown elevation from the pumping hole, and K is the permeability coefficient m / d;

[0067] According to the observation of the falling curve, h i , K and s, and h i For the closest exponential function relationship: set r i for K β 、s γ The composite function of K β 、s γA trial calculation shows that when α, β, and γ are 3.5, 0.46, and 1.02 respectively, the correlation coefficients between the calculated and measured values ​​are 0.99, 0.95, and 0.97 respectively. The equation for the drop curve is:

[0068] Due to the small sample size, the regression coefficient is 0.96, which is highly correlated.

[0069] The coefficient ξ is adjusted according to the corresponding drop curve shape, and its value is 0.49~1.16 (still waiting for further discussion in more pumping tests), s and K are fixed values, so the comprehensive coefficient is set as m=ξs 1.02 K 0.46 .

[0070] The volume of the body of rotation of this falling curve around the h(y) axis is:

[0071] For 114 holes ξ = 1.04 ~ 1.16, 111 holes ξ = 0.49 ~ 0.75, the calculation results are shown in Table 2;

[0072] 3. Water supply degree correlation analysis

[0073] (1) Water supply rate μ / %: the amount of water discharged by the drop funnel Q / m 3 The volume of the falling funnel V / m 3 The ratio is determined;

[0074] Right now:

[0075] (2) Correlation analysis of water supply at different elevations of underground reservoir basins

[0076] To determine the water supply at different elevations of the underground reservoir basin, we first conduct a regression analysis using the relevant hydrogeological parameters obtained from the pumping test wells. For two related parameters, a simple linear regression can be used; for two or more parameters, a binary or multiple regression analysis can be used.

[0077] Table 2 Calculation results of falling funnel

[0078] (2.1) The linear regression formula is y = a + bx (linear function) or y = 10 a x b (exponential function),

[0079] but in: is the average

[0080] Correlation coefficient:

[0081] (2.2) Multiple linear regression

[0082] set up

[0083] The regression coefficient Regression equation y = β0 + β1x1 + β2x2 + … + β n x n (linear function), or (Exponential function), multiple correlation coefficient:

[0084] (2.3) Correlation coefficients r and r xy Both are dimensionless values, r and r xy The value range is [-1,1]; when r = 1, it is completely positively correlated; when r = -1, it is completely negatively correlated, where:

[0085] When |r| or |r xy |>0.8, there is a high or significant correlation; when 0.5<|r| or |r xy |≤0.8, there is a moderate correlation; when 0.3<|r| or |r xy |≤0.5, there is a low correlation; when |r| or |r xy |≤0.3, there is no linear correlation;

[0086] (2.4) According to the existing data, the water supply degree μ s A univariate linear correlation analysis was conducted between the average borehole karst cave encounter rate n / %, permeability coefficient K / m / d and unit water permeability q / lu within the corresponding drop depth; the results are shown in Table 3.

[0087] Table 3 Correlation analysis results of water supply degree, borehole karst cave encounter rate and unit water permeability

[0088] In drilling pressure (injection) water tests, the more developed the karst, the greater the unit permeability. For unfilled karst caves, pressure (injection) water tests are impossible when they are within a certain width. During pressure (injection) water tests, it is difficult to calculate the borehole hole encounter rate for locations with low unit permeabilities. Therefore, to examine the karst development intensity and karst rate of a location, it is necessary to analyze both the borehole karst hole encounter rate and the unit permeability. Filled karst caves are primarily filled with gravel clay or gravel sandy clay. Physical property tests of the filling soil show an average porosity of 0.51. Therefore, the porosity of filled karst caves is calculated as 51%. The comprehensive karst hole encounter rate should be determined by adding the 51% filled karst hole encounter rate to the 100% unfilled karst hole encounter rate.

[0089] (2.5) According to the binary regression of the karst water supply rate of ZK114 and ZK111 holes, the encounter rate of karst holes in the comprehensive boreholes and the unit water permeability, the relationship is μ'=-4.18+1.32n+0.21q, and the multiple correlation coefficient is 0.89, which is highly correlated. After canceling the coefficient -4.18, the water supply rate μ' calculated by the binary regression is consistent with the actual water supply rate μ s A simple regression analysis was performed again to obtain the relationship μ = 0.525n + 0.088q, and the correlation coefficient was 0.94, which is highly correlated. The results are shown in Table 4.

[0090] Table 4 Water supply calculation results

[0091] S5. Underground storage capacity curve analysis

[0092] The karst bodies in the area involve the Qixia Formation limestone of the Carboniferous and Lower Permian. Statistical analysis shows the average encounter rate of karst caves and the weighted average unit permeability of the Carboniferous and Permian limestone boreholes in this area, as shown in Table 5.

[0093] Based on the drilling data, the karst cave encounter rate (according to filled and unfilled types) and unit water permeability of each hole were statistically analyzed according to the elevation distribution. The weighted average of the relevant section length was used to calculate the karst cave encounter rate and unit water permeability of the comprehensive drilling holes at each elevation.

[0094] Underground storage capacity only involves Carboniferous limestone above the lowest groundwater level, so only this rock mass is considered in the statistics. Because karst cavities in limestone with highly permeable units (q ≥ 1000 lu) often open to more than 3 mm, these cavities are easily measured as their width increases. However, during pressure (injection) water testing, the test water level in test sections above the groundwater level cannot usually be raised to the top of the test section. These units have permeabilities as high as tens of thousands of lu, making accurate results impossible. The resulting water content often exceeds 100%, so the data for highly permeable sections are excluded. Based on the regression relationship between the karst water supply rate, the comprehensive borehole karst cave encounter rate, and the unit permeability (μ = 0.525n + 0.088q), the results of the calculation of water supply at various elevations involved in underground storage capacity are shown in Table 6.

[0095] Table 5 Average encounter rate of karst caves in boreholes and weighted average length of unit permeability

[0096] Table 6 Calculation results of karst water supply rate

[0097] For underground storage capacity, it should be the volume of all karst caves that can be filled with water in the underground karst body. It is the volume of karst caves that can be explored and measured (V caves - larger unfilled karst caves) plus the volume of soluble rock remaining after deducting the karst caves that can be explored and measured (v溶隙 =V 总 -V 洞 ) and the product of the above karst water supply degree (V 溶隙 =μv 溶隙 ) is determined by the underground karst reservoir volume V=V 洞 +V 溶隙 The calculated storage capacity curve is shown in Table 7 and Illustration 4.

[0098] Table 7 Storage capacity characteristics of Shilin underground reservoir

[0099] S6. Results:

[0100] According to the analysis, the total storage capacity of Shilin underground reservoir is 6.4882 million m 3 (of which the ground storage capacity is 3.7548 million m 3 , underground storage capacity 2.7334 million m 3 ), which is a fully annual regulation reservoir, and the underground storage capacity under different characteristic water levels can be obtained. The normal water level is 1864.58m, and the corresponding storage capacity is 5.9229 million m 3 , Xingli reservoir capacity is 4.8718 million m 3 , flood control storage capacity 468,500 m 3 , dead water level 1853.01m (reservoir capacity 722,400m 3 ).

[0101] 1. Beneficial technical effects of the technical solution of this application

[0102] Through the trial water storage operation of the Shilin underground reservoir, based on the upstream inflow (incoming water) and outflow (discharge) observations (water tank model simulation method), the following calculations were made:

[0103] (1) Inflow analysis

[0104] According to the water storage test on August 15, 2017, the measured upstream water flow during the same period was 0.21~1.79m 3 / s, average flow rate 0.455m 3 / s. During the trial storage period, the water level rose from 1823.04m to 1857.32m, and the storage capacity was 2.1335 million m 3 , minus the surface storage capacity of 694,600 m 3 The underground storage capacity is 1.4389 million m 3 , the reservoir capacity calculated for the preliminary design stage is 1.4278 million m 3 The underground storage capacity is 103.2% of that below the elevation of 1856.37m, and the calculated underground storage capacity is too small. Above this elevation, it is 2% to 4% larger. When the underground storage capacity is less than 1 million m 3 When the value is below , the smaller the storage capacity, the greater the deviation, see Table 8.

[0105] Table 8 Inflow analysis summary

[0106] (2) Outflow analysis

[0107] After the trial water storage, the gate was opened to release water on October 9. According to the observation of the underground river dredging tunnel and the high culvert opening, the outflow volume and the drop in elevation were adjusted until the outflow flow reached the natural base flow of the underground river (flow rate 0.11~0.09m) on November 29. 3 / s). After releasing water, an underground cave was explored on November 7. Observations revealed that many cracks with a width of less than 3mm and karst cracks with fillings still showed water slowly seeping out. The total outflow of the tunnels and high culverts dredged from October 9 to November 29 was 2.1453 million m3. 3 and 239,500 m 3 , minus the natural base flow of the underground river of 386,600 m 3 The water volume it can supply is 1.9983 million m 3 , continue to deduct the surface storage capacity of 694,600 m 3 , then the underground storage capacity is 1.3037 million m 3 , the reservoir capacity calculated for the preliminary design stage is 1.4278 million m 3 The observed cumulative storage capacity is much larger than the calculated cumulative storage capacity due to the rapid water release below the elevation of 1850 m. However, the outflow volume between the elevations above 1831.20 m is 40% to 110% of the calculated underground storage capacity at the corresponding elevations. The results are shown in Table 9.

[0108] Table 9 Outflow analysis summary

[0109] (3) Conclusion

[0110] The actual cavity volume of the karst cave can be calculated by deducting the surface volume from the actual inflow and outflow. The average volume karst rates below the elevation of 1857.34 m are 4.22% and 3.83%, respectively, which are 103% and 92% of the average value of 4.01% predicted in the preliminary design.

[0111] 2. Comparison based on several currently suitable methods:

[0112] (1) Using the groundwater balance method, the groundwater hydrological observation results, the annual distribution analysis of the groundwater reservoir design annual runoff (P ​​= 75%), the runoff in April, the driest period, is 203,000 m 3 As a stable runoff, the stable runoff of Shilin underground reservoir is 2.436 million m 3The runoff volume increased by 543,000 m3 from January to May during the dry season. 3 , the underground storage capacity will not be less than the stable runoff (2.436 million m 3 ) and the seasonal increase in runoff during the dry season (January to May) (547,000 m 3 ) total, the underground storage capacity is 2.983 million m 3 .

[0113] (2) According to the Plotnikov method for groundwater runoff analysis, the dynamic reserve of groundwater flowing through a certain water-passing section of the aquifer per unit time under natural conditions is 8.973 million m 3 / year, under natural conditions, the regulating reserve (underground storage capacity) in the aquifer between the highest and lowest water levels is 2.0201 million m 3 / year, the static reserves that need to be extracted by mining wells are approximately 30.15 million m 3 .

[0114] 3. The underground reservoir capacity obtained based on hydrogeological parameters is 2.733 million m 3 , between Plotnikov method 2.0201 million m 3 / year and groundwater balance method 2.983 million m 3 The underground storage capacity of the underground reservoir is determined to be 2.733 million m 3 .

[0115] By employing multiple methods to analyze and demonstrate the underground reservoir capacity, striving to objectively, accurately, and reliably produce results, this application highlights the use of a large number of readily available hydrogeological tests to generate a corresponding reservoir capacity curve based on the spatial distribution functions of unit permeability, permeability coefficient, karstity, and water supply. This curve, summarized through operational water storage tests, provides valuable guidance for underground reservoir storage, scheduling, and flood control. Due to recent decreases in precipitation in the reservoir area, to ensure water storage and drought resistance, the underground reservoir capacity between the 1857.34m water level and the normal water level of 1864.58m awaits further review and analysis during operational water use based on water release observations.

[0116] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A method for calculating karst underground reservoir capacity curve based on hydrogeological parameters, characterized in that: The following steps are involved: S1. Hydrogeological exploration: Conduct hydrogeological exploration of the target karst groundwater reservoir, including exploring the karst conditions of the dam site and reservoir area, and the distribution of karst groundwater; S2. Determine the scope of karst underground water reservoirs: According to the hydrogeological conditions of the underground water reservoir basin of the target underground water reservoir, as well as the groundwater overflow elevation, groundwater springs and hydrogeological drilling data at the karst watershed, obtain the groundwater level in the dry season and draw the isowater level map accordingly to determine the boundary and bottom boundary conditions of the underground water reservoir capacity; S3. Determine water storage space: Through ground geological mapping, calculate the karst fissure rate at multiple points, further survey the karst caves between the highest water storage level and the lowest groundwater level, focus on finding out the volume and elevation distribution of the karst caves that can be explored, and calculate the volume distribution of water storage rock bodies and karst caves that can be explored at different elevations above the lowest groundwater level; S4. Determine relevant hydrogeological parameters based on hydrogeological tests: arrange multiple groups of exploration boreholes and pumping test holes in the catchment area of ​​the target underground reservoir, and conduct a large number of borehole pressure / water injection tests to obtain hydrogeological parameters, including borehole void encounter rate, unit water permeability, and analyze the drawdown curve and drawdown funnel drainage volume and water supply degree obtained from the pumping test, as well as the water supply degree of each elevation of the underground reservoir basin; S5. Underground reservoir capacity analysis: Based on the borehole data, the encounter rate of karst caves in each borehole, including filled and unfilled types, and unit water permeability are counted according to the elevation distribution, and the weighted average is taken using the relevant section length to calculate the encounter rate of karst caves and unit water permeability of the comprehensive boreholes at each elevation; According to the regression relationship between karst water supply rate, comprehensive borehole karst cave encounter rate and unit water permeability μ=0.525n+0.088q, the water supply degree of each elevation involved in the underground reservoir capacity is calculated; For underground storage capacity, the underground storage capacity should be the volume of all karst caves that can be filled with water in the underground karst body, which is the volume of the karst caves that can be explored and measured. 洞 Add the remaining soluble rock volume v after deducting the karst caves that can be explored and measured 溶隙 The product of the above karst water supply degree V 溶隙 To determine, the underground karst reservoir volume V = V 洞 +V 溶隙 ; Among them, V 洞 It is a relatively large unfilled karst cave; v 溶隙 =V 总 -V 洞 ; V 溶隙 =μv 溶隙 .

2. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, the hydrogeological parameters obtained include the encounter rate of borehole karst caves, the unit water permeability of the relevant rock mass, and the permeability coefficient.

3. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 2, characterized in that: In step S4, the encounter rate of karst caves in the borehole n / % is the ratio of the total length of karst caves seen in the borehole l / m to the drilling footage L / m of the section:

4. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 2, characterized in that: In step S4, the unit water permeability q of the relevant rock mass is the amount of water Q / l / min injected under the unit pressure P / MPa and the unit test section length L / m:

5. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, the permeability coefficient is obtained according to the Babushkin formula: In the above formula: K is the permeability coefficient m / d, Q is the water inflow m 3 / d, l is the filter length m, s is the drawdown depth m, and r is the drilling radius.

6. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, the drop curve and the drainage volume are calculated according to the Kusakin influence radius formula and the Weber water supply degree formula: Kusakin influence radius formula: Where: s is the influence radius of the falling funnel m, K is the permeability coefficient m / d, H is the thickness of the phreatic aquifer m; The Wilbur formula: Transformed into: Where: μ is the water supply rate, t is the pumping time d. The water supply rate is calculated by using the influence radius of the Kusakin formula to be 0-5%, with an average of 1.98%, which is difficult to correlate with the karst development at each elevation of the underground reservoir basin and the water supply rate.

7. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, the method for calculating the drainage volume of the drop funnel comprises the following steps: (1) Assume: R is the maximum radius of the drop funnel m, s is the maximum groundwater drop depth m, r i is the distance from the pumping hole axis m, h i For r i The water level at the maximum drawdown elevation from the pumping hole is m, and K is the permeability coefficient m / d; (2) According to the observation of the falling curve, r i With h i , K and s, and h i For an obvious exponential function relationship: set r i for K β 、s γ The composite function of K β 、s γ The calculation results show that when α, β, and γ are 3.5, 0.46, and 1.02 respectively, the correlation coefficients between the calculated and measured values ​​are 0.99, 0.95, and 0.97 respectively. The equation of the drop curve is: (3) The coefficient ξ is adjusted according to the corresponding drop curve shape, and its value is 0.49~1.

16. s and K are fixed values, so the comprehensive coefficient is set to m=ξs 1.02 K 0.46 ; (4) The volume of the body rotating around the h(y) axis of the falling curve is:

8. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, water supply rate μ / %: the amount of water discharged by the drop funnel Q / m 3 The volume of the falling funnel is V / m 3 The ratio is determined, namely:

9. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 1, characterized in that: In step S4, the analysis of the water supply degree at each elevation of the underground reservoir basin includes the following steps: (1) Make full use of the relevant hydrogeological parameters obtained from the pumping test wells for regression analysis; for two relevant parameters, a univariate linear regression can be performed; if two or more parameters are involved, a binary or multivariate regression analysis can be used, specifically: Univariate linear regression uses a linear function formula: y = a + bx Or exponential function y = 10 a x b , but in: is the average The correlation coefficient is: (2) Multiple linear regression The regression coefficient The linear functional regression equation is: y=β0+β1x1+β2x2+…+β n x n Or, the exponential function regression equation is: The multiple correlation coefficient is: (3) Correlation coefficients r and r xy are dimensionless values, r and r xy The value range is [-1,1]; when r = 1, it is completely positively correlated; r = -1, it is completely negatively correlated, where: When |r| or |r xy |>0.8, there is a high or significant correlation; when 0.5<|r| or |r xy |≤0.8 has a moderate correlation; when 0.3<|r| or |r xy |≤0.5 has a low correlation; when |r| or |r xy |≤0.3There is no linear correlation; (4) According to the existing data, the water supply degree μ s / % and the average borehole karst cave encounter rate n / %, permeability coefficient K / m / d and unit permeability q / lu within the corresponding drop depth are subjected to a one-dimensional linear correlation analysis; 5) According to the existing data, the borehole karst water supply rate, the comprehensive borehole karst cave encounter rate and the unit water permeability are subjected to binary regression, and the relationship is: μ'=-4.18+1.32n+0.21q, The multiple correlation coefficient is 0.89, which is highly correlated. After canceling the coefficient -4.18, the water supply degree μ' calculated by binary regression is consistent with the actual water supply degree μ s Performing univariate regression analysis again yields the following relationship: μ=0.525n+0.088q, The correlation coefficient is 0.94, which is highly correlated.

10. The method for calculating karst underground reservoir capacity curve based on hydrogeological parameters according to claim 9, characterized in that: In step (4), in the drilling pressure / water injection test, the more developed the karst is, the greater its unit permeability is; usually, for unfilled karst caves, it is impossible to conduct pressure / water injection tests when they have a certain width. During the pressure / water injection test, it is difficult to conduct statistics on the borehole cave encounter rate for the parts with smaller unit permeability; therefore, to examine the karst development intensity and karst rate of a part, it is necessary to combine the borehole karst cave encounter rate and unit permeability for simultaneous analysis. The filling material of the filled karst cave is mainly gravel clay or gravel sandy clay. Through the physical property test of the filling soil, the average porosity of the filling soil is 0.

51. Therefore, the porosity of the filled karst cave is calculated as 51%. The comprehensive karst cave encounter rate should be determined by adding 51% of the filled karst cave encounter rate to 100% of the unfilled karst cave rate.

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