A calculation method of karst underground reservoir capacity curve based on hydrogeological parameters

Abstract

The invention discloses a method for calculating a karst underground storage capacity curve based on hydrogeological parameters, comprising hydrogeological exploration, determining the scope of underground reservoirs, determining water storage space, determining relevant hydrogeological parameters according to hydrogeological tests, and performing underground storage capacity analysis. The invention uses unit water permeability and borehole karst cave encounter rate that are very easily obtained through borehole pressure / water injection tests and combines a small amount of water pumping tests to perform regression analysis on water supply degree and karst rate that are difficult to obtain with unit water permeability or permeability coefficient to obtain a related function relationship. The method calculates the underground storage capacity of the corresponding elevation according to the water supply degree or karst rate and obtains the underground storage capacity curve, which can improve accuracy, reduce errors, and play a guiding role in underground reservoir water storage, scheduling and flood control.

Description

Technical Field

[0001] The 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 value. There is no systematic literature discussing the underground reservoir storage capacity at home and abroad, 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] The study of the storage capacity of karst caves relative to pore and fissure-type underground reservoirs, especially the underground storage capacity curve, is of great significance to the effective implementation of reservoir area planning and dispatching schemes. Because the water storage medium is extremely uneven, the analysis is relatively difficult. The following methods are usually used to calculate the storage capacity of underground 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 seasonally increased runoff in the dry season (January to May) as the karst underground storage capacity.

[0006] 2. Plotnikov method for groundwater runoff

[0007] Plotnikov classified groundwater reserves into:

[0008]

[0009] The dynamic reserve is the volume of groundwater flowing through a certain water-passing section of the aquifer under natural conditions per unit time; the regulating reserve is the volume of water stored in the aquifer between the highest and lowest water levels under natural conditions; the static reserve is the part of the water storage volume that needs to be extracted by wells; the underground storage capacity is the regulating reserve of the volume of water stored in the aquifer between the highest and lowest water levels under natural conditions, which is the underground storage capacity.

[0010] (III) Other methods

[0011] There are also the following methods for calculating the storage capacity of underground reservoirs in the rare domestic and foreign literature:

[0012] 1. Water supply degree method: For porous and fractured underground storage capacity, water supply degree obeys different probability distributions (normal distribution) in space. Based on the determined water supply degree distribution, the spatial overlay function of ArcGIS software is used to overlay and analyze the water supply degree zoning map of the study area's phreatic aquifer with the average phreatic water level and surface elevation of a certain year, and the drainage storage capacity of the phreatic aquifer of that year is calculated. Then, the whole area is divided into rectangles, and the buried depth value of each cell is calculated in combination with the surface elevation and the average phreatic water level of that year. According to the needs of actual analysis, the Monte Carlo method is used for multiple random simulations (fuzzy method), and each simulation generates a number of water supply degree values ​​that meet a certain distribution, and obtains the corresponding multiple drainage storage capacity values.

[0013] 2. Water content method: The water content of the karst body is affected by the porosity and water absorption of the rock mass and 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.

[0014] 3. Mathematical model method of tracer detection: For the complex karst seepage field of solution crevice type, it can be generalized into two karst hydrogeological models: pipeline-solution crevice dual parallel flow field and single pipeline series pool flow field. The calculation is based on the average groundwater flow and the total mass of the tracer, the average concentration or peak concentration, and the time required for the recovery to reach half or all.

[0015] 4. Water storage space geometric morphology generalization method:

[0016] The volume of karst caves is calculated based on actual measurements.

[0017] 5. Water tank model simulation method (inversion method): that is, 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) from 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.

[0018] In summary, the existing research data on karst underground storage capacity are reviewed, and it is mainly demonstrated from a macroscopic perspective that no matter which method is used, there are certain errors and precisions, and only a total underground storage capacity result can be obtained. It is difficult to obtain its water supply degree, karst rate, and water content, and it is even more difficult to measure a large number of karst fissures. The tracer detection method has tracer adsorption reduction and it is difficult to estimate the non-water-filled cavity. The water tank simulation method is carried out after the reservoir is filled with water, and has no guiding role in the preliminary survey and design. It is even worse for the guidance of underground reservoir water storage, scheduling and flood control, and it is difficult to understand the underground storage capacity characteristics at different elevations. 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 under 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 reservoir capacity, but also to understand the reservoir 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 reservoir capacity curve based on hydrogeological parameters, characterized in that it comprises the following steps:

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

[0023] S2. Determine the scope of the underground reservoir: According to the hydrogeological conditions of the underground reservoir basin of the target underground reservoir, as well as the groundwater overflow elevation at the karst watershed, groundwater springs and hydrogeological drilling data, the groundwater level in the dry season is obtained and the isowater level map is drawn accordingly to determine the boundary and bottom limit conditions of the underground reservoir capacity;

[0024] 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;

[0025] 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;

[0026] S5. Analysis of underground reservoir capacity curve: 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;

[0027] 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;

[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 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 ;

[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 as follows: the present invention uses the unit water permeability and the encounter rate of karst caves in the boreholes, which are very easily obtained through the borehole pressure (injection) water test, combined with a small amount of water pumping test, to obtain a correlation function relationship through regression analysis between the water supply degree and karst rate that are difficult to obtain and the unit water permeability or permeability coefficient, and calculates the underground storage capacity at the corresponding elevation according to the water supply degree or karst rate and obtains the underground storage capacity curve, which can improve accuracy and reduce errors, and can play a guiding role in the water storage, scheduling and flood control of underground reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is the annual distribution diagram of the underground river P=75% of the designed annual runoff in the method of the present invention.

[0032] Figure 2 It is a schematic diagram of the hydrogeology and exploration drilling arrangement of the Shilin underground reservoir in the method of the present invention.

[0033] Figure 3 It is a cross-sectional view of the water pumping hole in the method of the present invention.

[0034] Figure 4 It is a curve diagram of underground reservoir capacity in the method of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 here 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 middle and upper reaches of the Xijiang River system in the Pearl River Basin. The karst is very developed. The total underground and surface runoff area is 26.63km 2 The 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 attached Figure 1 shown.

[0038] The reservoir consists of two ground reservoir basins (Xiangshuidong karst funnel reservoir basin and Qingshikan karst basin reservoir basin) and one underground reservoir basin. The main buildings are composed of the Qingshikan karst basin reservoir basin dam, inter-reservoir connecting tunnels, water transfer culverts, water collection corridors, underground river dredging tunnels, etc. The inlet bottom plate elevation of the water transfer culvert (high culvert) is 1851.50m. The bottom width of the gate of the underground river dredging tunnel is 1.6m, and the bottom plate elevation is 1822.50m.

[0039] The hydrogeological conditions of underground reservoirs in karst areas are relatively complex. The underground reservoir basin is composed of underground rivers, caves, rock karst gaps, and fissures. To intercept and fully utilize the underground karst caves through engineering measures to form underground reservoirs and regulate water, it is necessary to study the underground reservoir capacity characteristics, focusing on the reservoir capacity characteristics at different elevations.

[0040] Combined with Figure 1-4 The working method of this embodiment includes the following steps:

[0041] S1. Brief Introduction of Hydrogeology and Exploration

[0042] The Shilin underground reservoir is located in the karst platform of eastern Yunnan. Since 1966, an underground hydrological observation station has been established, and project demonstration, feasibility study, preliminary design and construction have been carried out. The karst strata involved in the Shilin underground reservoir are the limestones of the Qixia Formation of the Carboniferous and the Lower Permian System. The dam site is located in the sandstone and mudstone intercalated with mudstone of the Daoshitou Formation of the Lower Permian System between two layers of limestone. Figure 2 As shown, underground reservoirs are formed by intercepting and blocking underground rivers, karst caves and karst fissures, raising the groundwater level, building dams in the hub area and storing water in the upstream karst depressions to form surface reservoirs to achieve gravity water supply.

[0043] According to the karst development characteristics of Shilin underground reservoir and the layout of engineering buildings, a total of 47 exploration boreholes were completed, with a drilling footage of 3,319m and 567 sections of water pressure (injection) tests; 18 boreholes in the underground reservoir basin (including 6 pumping holes and monitoring holes) were involved. In order to find out the karst conditions of the dam site and reservoir area, and the distribution of karst groundwater, the boreholes 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 20m and 50m 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 in the karst watershed (karst lake), 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 is statistically analyzed, and the karst caves between the highest water storage level and the lowest groundwater level are further surveyed, with a focus on identifying the volume and elevation distribution of the accessible karst caves. At the same time, the volume distribution of water-storage rock masses and explorable karst caves at different elevations above the lowest groundwater level is calculated.

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

[0049] In order to analyze the underground storage capacity curve, it is important to obtain the water supply degree of the relevant elevation, and the water supply degree involves many relevant hydrogeological parameters. Since a certain scale of exploration boreholes and pumping test holes are arranged in the catchment area of ​​the underground reservoir, a large number of borehole pressure (injection) water tests have been carried out, which makes it easy to obtain relevant rock unit permeability and borehole karst cave encounter rate and other hydrogeological parameters.

[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]

[0053] (2) Unit water permeability (q: lu): It is the amount of water (Q: l / min) injected under unit pressure (P: MPa) and unit test section length (L: m):

[0054]

[0055] (3) Permeability coefficient

[0056] It is mainly obtained from the two pumping test holes ZK114 and ZK111. There are many methods for calculating the permeability coefficient. According to the "Water Supply Hydrogeological Survey Code GB50027-2001" and "Hydropower and Water Conservancy Project Drilling Pumping Test Code DL / T5213-2005", there are mainly water supply specification formulas, Qiu Buyi, Babushkin, Skabaranovich 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:

[0057]

[0058] 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.

[0059] 2. Drop curve and drainage volume

[0060] (1) Pumping test and related results are shown in Table 1;

[0061] (2) Calculated according to the Kusakin influence radius formula and the Weber water supply degree formula:

[0062] According to the Kusakin influence radius formula:

[0063] In the formula: s is the influence radius of the decline 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~206m, which is somewhat different from the measured data.

[0064] Table 1 Comprehensive results of pumping test

[0065]

[0066]

[0067] According to the Weibull formula: Transformed into

[0068] In the formula: μ is the water supply rate, t is the pumping time d. The water supply rate calculated by the influence radius using the Kusakin formula is 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; the water supply rate calculated according to the measured influence radius is 0.4-4989%, which is quite different.

[0069] (3) Drainage volume of the drop funnel

[0070] According to the observation results of groundwater drawdown curves of ZK111 and 114 holes (see attached Figure 3 As shown), fit:

[0071] 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 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;

[0072] 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 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:

[0073]

[0074] Due to the small sample size, the regression coefficient is 0.96, which is highly correlated.

[0075] The coefficient ξ in the formula is adjusted according to the corresponding drop curve shape, and its value is 0.49~1.16 (still waiting for more pumping tests to further study), s and K are fixed values, so the comprehensive coefficient is set to m=ξs 1.02 K 0.46 .

[0076] The volume of the body of rotation of this falling curve around the h(y) axis is:

[0077]

[0078] For 114 holes ξ=1.04~1.16, 111 holes ξ=0.49~0.75, the calculation results are shown in Table 2;

[0079] 3. Water supply degree correlation analysis

[0080] (1) 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;

[0081] Right now:

[0082] (2) Correlation analysis of water supply at different elevations of underground reservoir basins

[0083] In order to obtain the water supply degree at different elevations of the underground reservoir basin, firstly, the relevant hydrogeological parameters obtained from the pumping test wells are fully utilized for regression analysis. For two related parameters, a univariate linear regression can be performed, and if two or more parameters are involved, a binary or multivariate regression analysis can be used.

[0084] Table 2 Calculation results of falling funnel

[0085]

[0086] (2.1) The linear regression formula is y = a + bx (linear function) or y = 10 a x b (exponential function),

[0087] but in: is the average

[0088] Correlation coefficient:

[0089] (2.2) Multiple linear regression

[0090] set up

[0091] The regression coefficient Regression equation y = β0 + β1x1 + β2x2 + ... + β n x n (linear function), or (Exponential function), multiple correlation coefficient:

[0092] (2.3) 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:

[0093] 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;

[0094] (2.4) According to the existing data, the water supply degree μ sA univariate linear correlation analysis was performed between the average borehole karst cave encounter rate n / %, permeability coefficient K / m / d and unit permeability q / lu within the corresponding drop depth; the results are shown in Table 3.

[0095] Table 3 Correlation analysis results of water supply degree, borehole karst cave encounter rate and unit water permeability

[0096]

[0097] In the drilling pressure (injection) water test, the more developed the karst is, the greater its unit water permeability is. For unfilled karst caves, it is impossible to conduct pressure (injection) water tests when they have a certain width. During the pressure (injection) water test, it is difficult to conduct statistics on the encounter rate of borehole caves for parts with a small unit water permeability. Therefore, to investigate the karst development intensity and karst rate of a part, it is necessary to combine the encounter rate of borehole karst caves and the unit water permeability for simultaneous analysis. The filling material of the filled karst caves 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 caves is calculated as 51%. The comprehensive karst cave encounter rate should be determined by adding 51% of the filled karst cave encounter rate plus 100% of the unfilled karst cave rate.

[0098] (2.5) According to the binary regression of the karst water supply rate of ZK114 and ZK111 holes, the encounter rate of karst caves 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 univariate 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.

[0099] Table 4 Water supply calculation results

[0100]

[0101] S5. Underground storage capacity curve analysis

[0102] The karst bodies in the area involve the Qixia Formation limestone of the Carboniferous and Lower Permian. After statistical analysis, the average encounter rate of karst caves in the Carboniferous and Permian limestone boreholes and the weighted average unit permeability are shown in Table 5.

[0103] Based on the drilling data, the karst cave encounter rate (according to filled type and unfilled type) and unit water permeability of each hole were statistically analyzed according to the elevation distribution, and the weighted average was used using the relevant section length to calculate the karst cave encounter rate and unit water permeability of the comprehensive drilling holes at each elevation.

[0104] The underground storage capacity only involves the Carboniferous limestone above the lowest groundwater level, so only this part of the rock mass is considered in the statistics. Since the limestone karst caves with high permeability (q≥1000lu) are often opened to more than 3mm, these caves are easy to measure with the increase of the width of the karst caves. However, during the pressure (injection) water test, the test section above the groundwater level usually cannot raise the test water level to the top of the test section. Its unit permeability is as high as tens of thousands of lu, and even accurate results cannot be obtained. The water content obtained is mostly greater than 100%, so the data of the highly permeable section are eliminated. According to the regression relationship between the karst water supply rate and the comprehensive drilling karst cave encounter rate and the unit permeability μ=0.525n+0.088q, the calculation results of the water supply degree at each elevation involved in the underground storage capacity are shown in Table 6.

[0105] Table 5 Average value of encounter rate of karst caves in boreholes and weighted average value of unit permeability length

[0106]

[0107] Table 6 Calculation results of karst water supply rate

[0108]

[0109] 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 remaining soluble rock volume 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 Table 8. Figure 4 .

[0110] Table 7 Storage capacity characteristics of Shilin underground reservoir

[0111]

[0112] S6. Results:

[0113] According to the analysis, the total storage capacity of Shilin underground reservoir is 6.4882 million m 3 (including ground storage capacity of 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 m3 , Xingli reservoir capacity 4.8718 million m 3 , flood control storage capacity 468,500 m 3 , dead water level 1853.01m (reservoir capacity 722,400m 3 ).

[0114] 1. Beneficial technical effects of the technical solution of this application

[0115] Through the trial water storage operation of Shilin underground reservoir, according to the upstream inflow (water) and outflow (water release) observation (water tank model simulation method), it is calculated:

[0116] (1) Inflow analysis

[0117] 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 increased from 1823.04m to 1857.32m, and the storage capacity was 2.1335 million m 3 , minus the surface reservoir capacity of 694,600 m 3 That is, 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% 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 storage capacity is smaller than that of the reservoir, the deviation is larger, see Table 8.

[0118] Table 8 Inflow analysis summary

[0119]

[0120]

[0121] (2) Outflow analysis

[0122] After the trial water storage, the gates were opened to release water on October 9. According to the observation of the outflow from the underground river tunnel and the high culvert gate opening, the outflow volume and the drop in elevation were observed until the outflow flow reached the natural base flow of the underground river (flow 0.11~0.09m) on November 29. 3 / s). After releasing the water, we entered the underground cave for exploration on November 7. We observed that there were still many cracks with a width of less than 3mm and karst cracks with fillings, and water was released through slow seepage. The total outflow of the tunnel and high culvert dredged from October 9 to November 29 was 2.1453 million m 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 reservoir 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 1850m. However, the outflow volume between the elevations above 1831.20m is 40% to 110% of the calculated underground storage capacity between the corresponding elevations. The results are shown in Table 9.

[0123] Table 9 Outflow analysis summary

[0124]

[0125]

[0126] (3) Conclusion

[0127] 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 1857.34m are 4.22% and 3.83%, respectively, which are 103% and 92% of the average value of 4.01% predicted in the preliminary design.

[0128] Second, compare the following methods based on the most suitable ones at present:

[0129] (1) Using the groundwater balance method, the annual distribution analysis of the designed annual runoff (P ​​= 75%) of the groundwater reservoir was carried out based on the groundwater hydrological observation results. The runoff in April, the driest period, was 203,000 m 3 As a stable runoff, the Shilin underground reservoir has a stable runoff of 2.436 million m 3 The 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 ) in total, the underground storage capacity is 2.983 million m 3 .

[0130] (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, the regulating reserve (underground storage capacity) in the aquifer between the highest and lowest water levels under natural conditions is 2.0201 million m 3 / year, the static reserves that need to be extracted by mining wells are about 30.15 million m 3 .

[0131] 3. The underground reservoir capacity obtained based on hydrogeological parameters is 2.733 million m 3 , between Plotnikov 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 .

[0132] Through the use of a variety of methods to analyze and demonstrate the underground reservoir capacity, we strive to objectively and accurately obtain relatively reliable results. The biggest highlight of this application is that the spatial distribution function of unit water permeability, permeability coefficient, karst rate and water supply degree obtained by a large number of easily available hydrogeological tests is used to obtain the corresponding reservoir capacity curve, which is summarized through water storage operation inspection, and has a good guiding significance for the water storage, scheduling and flood control of underground reservoirs. Due to the decrease in precipitation in the reservoir area in recent years, in order to ensure water storage and drought resistance, the underground reservoir capacity between the 1857.34m water storage level and the normal water storage level of 1864.58m needs to be further reviewed and analyzed according to the water release observation during the water use process during operation.

[0133] The present invention and its embodiments are described above, and such 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 ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope 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 in the dam site area, the karst conditions in the 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, count the karst fissure rate at multiple points, further survey the karst caves between the highest water storage level and the lowest groundwater level, find 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 borehole pressure / water injection tests to obtain hydrogeological parameters, including borehole void encounter rate and 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 degree, 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 Not less than 0.03 thousand m 3 Unfilled karst caves; 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 l / m seen in the borehole to the drilling footage L / m:

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: Make full use of the relevant hydrogeological parameters obtained from the pumping test wells for regression analysis; (1) For two related parameters, a univariate linear regression can be performed, 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) If two or more parameters are involved, binary or multivariate regression analysis can be used, specifically: Multiple linear regression design 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, there is 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 degree, 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.

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