Estimation method, system and electronic device for permeability coefficient of rock mass of underground water-sealed cave

Abstract

The application discloses a kind of underground water seal cave rock mass permeability coefficient estimation method, system and electronic equipment, the method includes according to target underground water seal cave geological index value and underground water seal cave rock mass permeability coefficient estimation model, estimates the rock mass permeability coefficient of target underground water seal cave;Wherein, the construction process of underground water seal cave rock mass permeability coefficient estimation model is: rock quality index and rock mass integrity index are divided into lithology parameter index, and fracture width index, fracture spacing index and filling material state index are divided into fracture parameter index;Then according to lithology parameter index and fracture parameter index, underground water seal cave rock mass permeability coefficient estimation model is constructed.The rock mass permeability coefficient of the application can be estimated quickly.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering technology, and in particular to a method, system and electronic equipment for estimating the permeability coefficient of rock mass in underground water-sealed caverns. Background Technology

[0002] Water-sealed underground caverns are currently the most widely used large-scale underground oil storage method in the world. These caverns are excavated in areas of intact hard rock, employing a principle of minimal or no support. They utilize the self-stability of the hard rock and groundwater pressure to create a sealed space. The oil is sealed by the pressure difference between the groundwater and the rock fissure water supplied by an artificial water curtain system and the oil. The biggest difference between water-sealed underground caverns and other underground engineering projects is that they must possess effective water-sealing properties. The rock permeability coefficient is a key parameter ensuring the water-sealing performance of the underground cavern.

[0003] Currently, in underground engineering, rock mass permeability coefficient analysis mainly employs field testing, fracture network methods, numerical back analysis, and empirical estimation methods. Among these, empirical estimation methods are relatively more convenient and widely used. Based on the different influencing factors of rock mass permeability coefficient, it is further divided into single-factor estimation methods and multi-factor estimation methods. KENJIAOKI estimated the permeability coefficient of jointed rock masses using spatial permeability tests and verified it using borehole television and inter-hole seismic tomography. Louis, Wei, Carlsson, Chen, and snow et al. provided the relationship between permeability coefficient and stratum depth. Jiang Xiaowei et al., utilizing the variation of both RQD (Rock Quality Designation) and permeability coefficient with depth, provided a method for estimating the average permeability coefficient of rock mass using RQD values. Huang Jun et al., through extensive acoustic wave testing and water pressure tests in boreholes, fitted the power law function and negative exponential function relationships between the average longitudinal wave velocity and the average permeability coefficient of rock masses at different depths.

[0004] The aforementioned existing technologies analyze the relationship between individual influencing factors and permeability coefficients. However, the formation of permeability characteristics in rock masses is complex, with a variety of influencing factors. The influencing factors for permeability characteristics differ under different geological conditions; therefore, single-factor estimation methods cannot reflect the permeability characteristics of other regions. Song Kun, Hsu, Chen Jun, Wang Wei, and others considered various geological indicators, including Rock Quality Designation (RQD), Rock Mass Integrity Index (RID), Fracture Width Index (AD), Rock Permeability Index (LPD), Clay Content Index (GCD), Permeability Coefficient (LPI), Formation Depth (h), and Fault State Index (FSD), and proposed multi-factor rock mass permeability coefficient estimation models based on previous research. These models have certain application value and promotional significance in other engineering fields; however, for underground water-sealed caverns, there is no regular relationship between permeability coefficients and formation depth, making these models unsuitable. Furthermore, Song Kun and Hsu constructed the rock mass permeability coefficient by multiplying all geological indicators without classifying them, resulting in an unsatisfactory fitting result. Wang Wei classified all parameters into positive and negative correlation indicators and used natural logarithms for fitting, requiring at least one of the positive and negative correlation indicators to be tested. However, influencing factors such as the clay content index GCD and the infill state index FSD are themselves negative correlation indicators. When at least one positive correlation indicator exists, it is not appropriate to convert it into a positive correlation indicator using 1-GCD and 1-FSD before multiplying. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and electronic equipment for estimating the permeability coefficient of rock mass in underground water-sealed caverns, which can quickly estimate the permeability coefficient of rock mass.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] In a first aspect, the present invention provides a method for estimating the permeability coefficient of rock mass in underground water-sealed caverns, comprising:

[0008] Obtain the geological index values ​​of the target underground water-sealed cavern;

[0009] Based on the geological index values ​​of the target underground water-sealed cavern and the rock mass permeability coefficient estimation model of the underground water-sealed cavern, the rock mass permeability coefficient of the target underground water-sealed cavern is estimated.

[0010] The construction process of the permeability coefficient estimation model for the underground water-sealed cavern rock mass is as follows:

[0011] Based on the engineering geological characteristics of underground water-sealed caverns, geological indicators were selected for constructing a rock mass permeability coefficient estimation model for underground water-sealed caverns. These geological indicators include rock quality indicators, rock mass integrity indicators, fracture width indicators, fracture spacing indicators, and filling material state indicators.

[0012] The rock quality index and the rock mass integrity index are classified as lithological parameter indexes, and the fracture width index, the fracture spacing index and the filling material state index are classified as fracture parameter indexes.

[0013] Based on the lithological parameters and fracture parameters, an expression for estimating the permeability coefficient of the rock mass in an underground water-sealed cavern is constructed.

[0014] Based on borehole data and field hydrogeological test data of the underground water-sealed cavern, the empirical coefficients of the expression for estimating the permeability coefficient of the rock mass of the underground water-sealed cavern are fitted to obtain the final required estimation model for the permeability coefficient of the rock mass of the underground water-sealed cavern.

[0015] Optionally, the calculation process for the lithological parameters is as follows:

[0016] Based on the rock quality index and the rock mass integrity index, calculate the lithological parameter index.

[0017] Optionally, the formula for calculating the rock quality index RQD is:

[0018]

[0019] In the formula, h L h represents the total length of intact rock cores greater than 10 cm, expressed in meters (m). T This represents the total length of the rock core, in meters (m).

[0020] Optionally, the formula for calculating the rock mass integrity index (RID) is:

[0021]

[0022] In the formula, V m V represents the longitudinal wave velocity of the rock mass, in m / s. r This indicates the longitudinal wave velocity of the rock block, expressed in m / s.

[0023] Optionally, the calculation process for the fracture parameter index is as follows:

[0024] The fracture parameter index is calculated based on the fracture width index, the fracture spacing index, and the filling material state index.

[0025] Optionally, the formula for calculating the crack width index AD is:

[0026]

[0027] The formula for calculating the crack spacing index AS is as follows:

[0028]

[0029] In the formula, L Fi To calculate the width of the i-th crack within a segment, in meters; S Fi To calculate the distance between the i-th crack and the (i+1)-th crack within a segment, in meters; L T The unit for calculating the segment length is meters (m); n represents the number of cracks.

[0030] Optionally, the formula for calculating the filler state index FSD is:

[0031]

[0032] In the formula, F Fi The width of the i-th filled crack within the segment is calculated, in meters.

[0033] Optionally, the permeability coefficient estimation model for the underground water-sealed cavern rock mass is as follows:

[0034]

[0035] K = 10 LFP ;

[0036] In the formula, LFP is an intermediate variable; K is the rock mass permeability coefficient; K R For lithological parameters; K F α1, β1, γ1, λ1, α2, β2, γ2, and λ2 are empirical coefficients related to lithology and the degree of fracture development, respectively.

[0037] Secondly, the present invention provides a system for estimating the permeability coefficient of rock mass in underground water-sealed caverns, comprising:

[0038] The data acquisition module is used to acquire the geological index values ​​of the target underground water-sealed cavern.

[0039] The rock mass permeability coefficient estimation module is used to estimate the rock mass permeability coefficient of the target underground water-sealed cavern based on the geological index values ​​of the target underground water-sealed cavern and the rock mass permeability coefficient estimation model of the underground water-sealed cavern.

[0040] The construction process of the permeability coefficient estimation model for the underground water-sealed cavern rock mass is as follows:

[0041] Based on the engineering geological characteristics of underground water-sealed caverns, geological indicators were selected for constructing a rock mass permeability coefficient estimation model for underground water-sealed caverns. These geological indicators include rock quality indicators, rock mass integrity indicators, fracture width indicators, fracture spacing indicators, and filling material state indicators.

[0042] The rock quality index and the rock mass integrity index are classified as lithological parameter indexes, and the fracture width index, the fracture spacing index and the filling material state index are classified as fracture parameter indexes.

[0043] Based on the lithological parameters and fracture parameters, an expression for estimating the permeability coefficient of the rock mass in an underground water-sealed cavern is constructed.

[0044] Based on borehole data and field hydrogeological test data of the underground water-sealed cavern, the empirical coefficients of the expression for estimating the permeability coefficient of the rock mass of the underground water-sealed cavern are fitted to obtain the final required estimation model for the permeability coefficient of the rock mass of the underground water-sealed cavern.

[0045] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the method for estimating the permeability coefficient of rock mass in underground water-sealed caverns according to the first aspect.

[0046] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0047] This invention fully considers the highly nonlinear relationship between geological indicators that affect the permeability coefficient of underground water-sealed caverns and the rock mass permeability coefficient, such as rock quality indicators, rock mass integrity indicators, fracture width indicators, fracture spacing indicators, and fracture filling material indicators. It can effectively analyze the influence of lithological parameters and fracture parameters on the rock mass permeability coefficient and quickly estimate the rock mass permeability coefficient. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 A flowchart illustrating the method for estimating the permeability coefficient of rock mass in underground water-sealed caverns provided in this embodiment of the invention;

[0050] Figure 2 A flowchart illustrating the method for estimating the permeability coefficient of rock mass in underground water-sealed caverns based on geological indicators, provided in an embodiment of the present invention.

[0051] Figure 3 This is a comparison chart of estimated and measured values ​​after fitting the borehole data of ZK12 and ZK23 using the LFP model, provided in an embodiment of the present invention. Figure 3 (a) is a comparison chart of the estimated values ​​and measured values ​​after fitting the ZK12 borehole data using the LFP model according to an embodiment of the present invention. Figure 3 (b) is a comparison chart of the estimated values ​​and measured values ​​after fitting the ZK23 borehole data using the LFP model according to an embodiment of the present invention.

[0052] Figure 4 A schematic diagram of the structure of the underground water-sealed cavern rock mass permeability coefficient estimation system provided in an embodiment of the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] Example 1

[0056] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for estimating the permeability coefficient of rock mass in an underground water-sealed cavern, which includes the following steps.

[0057] Step 100: Obtain the geological index values ​​of the target underground water-sealed cavern.

[0058] Step 200: Estimate the rock mass permeability coefficient of the target underground water-sealed cavern based on the geological index values ​​of the target underground water-sealed cavern and the rock mass permeability coefficient estimation model of the underground water-sealed cavern.

[0059] The construction process of the permeability coefficient estimation model for underground water-sealed caverns is as follows:

[0060] (1) Based on the engineering geological characteristics of underground water-sealed caverns, geological indicators are selected when constructing the rock mass permeability coefficient estimation model for underground water-sealed caverns; the geological indicators include rock quality indicators, rock mass integrity indicators, fracture width indicators, fracture spacing indicators and filling material state indicators.

[0061] (2) Rock quality index and rock mass integrity index are classified as lithological parameter index, and fracture width index, fracture spacing index and filling material state index are classified as fracture parameter index.

[0062] (3) Construct an expression for estimating the permeability coefficient of the rock mass in the underground water-sealed cavern based on the lithological parameters and the fracture parameters.

[0063] (4) Based on the borehole data and field hydrogeological test data of the underground water-sealed cavern, the empirical coefficients of the estimation expression of the rock mass permeability coefficient of the underground water-sealed cavern are fitted to obtain the final required estimation model of the rock mass permeability coefficient of the underground water-sealed cavern.

[0064] Among them, the lithological parameter index K R The calculation process is as follows:

[0065] Based on the rock quality index and the rock mass integrity index, lithological parameters are calculated. The rock quality index RQD and the rock mass integrity index RID are positively correlated, and their calculation formula is: K R =RQD×RID.

[0066] Rock Quality Degree (RQD) is an important indicator for evaluating the degree of rock mass damage. It reflects the frequency of structural plane development. The formula for calculating RQD is:

[0067]

[0068] Where: h L h represents the total length of intact rock cores greater than 10 cm, expressed in meters (m). T This represents the total length of the rock core, in meters (m).

[0069] The Rock Integrity Index (RID) reflects the integrity of a rock sample by measuring the P-wave velocity of the rock mass and rock blocks. The maximum value is 1. A higher RID indicates better rock mass integrity and therefore lower permeability. The formula for calculating the RID is:

[0070]

[0071] In the formula: V m V represents the longitudinal wave velocity of the rock mass, in m / s. r This indicates the longitudinal wave velocity of the rock block, expressed in m / s.

[0072] Crack parameter index K F The calculation process is as follows:

[0073] The fracture parameter indices are calculated based on the fracture width index, the fracture spacing index, and the filling material state index. Among these, the fracture width index (AD), the fracture spacing index (AS), and the filling material state index (FSD) are negatively correlated indices, and their calculation formulas are as follows:

[0074] Studies have shown that structural features such as fracture width and fracture spacing have a significant impact on the permeability coefficient of fractured rock masses. The permeability coefficient increases with increasing fracture width and decreases with increasing fracture spacing. Since fracture width and fracture spacing in deep rock masses can be determined through borehole television image identification and measurement, both the fracture width index (AD) and the fracture spacing index (AS) are considered in the permeability coefficient estimation model.

[0075] The crack width index AD is determined by the ratio of the sum of all crack widths in the calculation segment to the length of the calculation segment, and the crack spacing index AS is determined by the ratio of the average spacing of all cracks in the calculation segment to the length of the calculation segment, as shown in formulas (3) and (4):

[0076]

[0077]

[0078] In the formula: L Fi To calculate the width of the i-th crack within a segment, in meters, if L Fi =0, take 1.0mm; S Fi To calculate the distance between the i-th crack and the (i+1)-th crack within a segment, in meters; L T The unit for calculating the segment length is meters (m); n represents the number of cracks.

[0079] The content of infill material in fractures affects their connectivity; the permeability coefficient decreases with increasing infill material content. The infill material state index (FSD) represents the infill material state of rock mass fractures, with a maximum value of 1. A larger FSD indicates a greater amount of infill in the fracture, thus lower permeability. Therefore, the formula for calculating the infill material state index (FSD) is:

[0080]

[0081] In the formula: F Fi The width of the i-th filled crack within the segment is calculated, in meters.

[0082] (2) Establish a model for estimating the permeability coefficient of rock mass in underground water-sealed caverns.

[0083] After completing the lithological parameter index K R and fracture parameter index K FAfter classification, a rock mass permeability coefficient estimation LFP model based on lithological parameters and fracture parameters is proposed:

[0084]

[0085] K = 10 LFP (7);

[0086] In the formula: LFP is an intermediate variable; K is the rock mass permeability coefficient; K R For lithological parameters; K F α1, β1, γ1, λ1, α2, β2, γ2, and λ2 are empirical coefficients related to lithology and the degree of fracture development. Where L represents the lithology parameter index; F represents the fracture parameter index; and P represents the permeability coefficient.

[0087] Example 2

[0088] like Figure 2 As shown in the figure, an embodiment of the present invention provides a method for estimating the permeability coefficient of rock mass in underground water-sealed caverns based on geological indicators, which includes the following steps.

[0089] (1) Based on engineering geological characteristics, geological indicators were selected when constructing the rock mass permeability coefficient estimation model for underground water-sealed caverns.

[0090] A complete granite formation is a dense, low-permeability rock mass with a permeability coefficient of less than 6 × 10⁻⁶. -5 The permeability coefficient of fractured granite is determined by the fractures within it, which are the main channels for water conduction. Furthermore, the water exchange between the rock and the fractures is relatively weak. Therefore, the integrity of the fractured rock mass and the nature of the fractures are key factors determining the permeability and anisotropy of the seepage. Song Kun and Hsu constructed the permeability coefficient by multiplying all geological indicators without classifying them, resulting in an unsatisfactory fitting result. Wang Wei's paper categorized all parameters into positive and negative correlation indicators, using natural logarithms for fitting, and required at least one of the positive or negative correlation indicators to be tested. However, influencing factors such as the clay content index GCD and the infill state index FSD are inherently negatively correlated. When at least one positively correlated indicator exists, converting them to positively correlated indicators using 1-GCD and 1-FSD before multiplication is inappropriate. Considering the engineering geological characteristics of underground water-sealed caverns, this invention considers summarizing and classifying geological indicators, categorizing them into lithological parameter indicators K... R and fracture parameter index K F To construct a new model for estimating the permeability coefficient of rock mass in underground water-sealed caverns.

[0091] (2) Establish a model for estimating the permeability coefficient of rock mass in underground water-sealed caverns.

[0092] After completing the lithological parameter index K R and fracture parameter index K F After classification, a rock mass permeability coefficient estimation LFP model based on lithological parameters and fracture parameters is proposed:

[0093]

[0094] K = 10 LFP (7);

[0095] In the formula: K is the rock mass permeability coefficient; K R For lithological parameters; K F α represents the fracture parameter index; α, β, and λ are empirical coefficients related to lithology and fracture development degree, respectively.

[0096] (3) Based on the borehole data and field hydrogeological test data of the underground water-sealed cavern, the empirical coefficients α, β and λ of the rock mass permeability coefficient estimation model of the underground water-sealed cavern are fitted.

[0097] To verify the feasibility of the rock mass permeability coefficient LFP estimation model proposed in this embodiment of the invention, it was applied to borehole data ZK12 and ZK23 of a domestic underground water-sealed cavern, and the fitting results were compared with the fitting results of the RMP model, PNC model, HC model and ZRF model, respectively.

[0098] Table 1 shows the fitting results for the borehole data of ZK12. The results indicate that the fitting effect is good, and the correlation coefficient R is [value missing]. 2 =0.947, where a1 = 2.791 × 10 -3 a2 = 1.82 × 10 -3 a3 = -1.04 × 10 -3 a4 = -2.69 × 10 -4 a5 = -8.39 × 10 -4 a6 = 9.79 × 10 -5 a7 = 1.14 × 10 -3 a8 = 9.95 × 10 -5 .

[0099] Table 1. Fitting Results of ZK12 Borehole Data

[0100]

[0101]

[0102] Table 2 shows the fitting results for the ZK23 data. The results indicate a good fit, with a correlation coefficient R0.2 =0.887. Where a1 = -1288.34, a2 = -9925.29, a3 = -20734.98, a4 = 62.25, a5 = 673.52, a6 = 5351.88, a7 = 10756.99, a8 = -10.71.

[0103] Table 2 shows the fitting results of the ZK23 borehole data.

[0104]

[0105] Table 3 compares the fitting results of the LFP model proposed in this invention on borehole data of ZK12 and ZK23 with the fitting results of other models. Figure 3 As shown in Table 3, the LFP model fits the borehole data of the underground water-sealed cavern well, with a correlation coefficient far exceeding that of other models, proving that the model is feasible for estimating the rock mass permeability coefficient of an underground water-sealed cavern in China.

[0106] Table 3. Comparison of correlation coefficients for borehole data from a domestic underground water-sealed cavern.

[0107]

[0108] Example 2

[0109] In order to implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, a system for estimating the permeability coefficient of rock mass in underground water-sealed caverns is provided below.

[0110] like Figure 4 As shown in the figure, an embodiment of the present invention provides a system for estimating the permeability coefficient of rock mass in underground water-sealed caverns, comprising:

[0111] Data acquisition module 1 is used to acquire the geological index values ​​of the target underground water-sealed cavern.

[0112] The rock mass permeability coefficient estimation module 2 is used to estimate the rock mass permeability coefficient of the target underground water-sealed cavern based on the geological index values ​​of the target underground water-sealed cavern and the rock mass permeability coefficient estimation model of the underground water-sealed cavern.

[0113] The construction process of the permeability coefficient estimation model for the underground water-sealed cavern rock mass is as follows:

[0114] Based on the engineering geological characteristics of underground water-sealed caverns, geological indicators were selected for constructing a rock mass permeability coefficient estimation model for underground water-sealed caverns. These geological indicators include rock quality indicators, rock mass integrity indicators, fracture width indicators, fracture spacing indicators, and filling material state indicators.

[0115] The rock quality index and the rock mass integrity index are classified as lithological parameter indexes, and the fracture width index, the fracture spacing index, and the filling material state index are classified as fracture parameter indexes.

[0116] Based on the lithological parameters and fracture parameters, an expression for estimating the permeability coefficient of the rock mass in underground water-sealed caverns is constructed.

[0117] Based on borehole data and field hydrogeological test data of the underground water-sealed cavern, the empirical coefficients of the expression for estimating the permeability coefficient of the rock mass of the underground water-sealed cavern are fitted to obtain the final required estimation model for the permeability coefficient of the rock mass of the underground water-sealed cavern.

[0118] Example 3

[0119] This invention provides an electronic device including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to execute a method for estimating the permeability coefficient of underground water-sealed cavern rock mass based on geological indicators, as described in Embodiment 1.

[0120] Alternatively, the aforementioned electronic device may be a server.

[0121] In addition, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for estimating the permeability coefficient of rock mass in an underground water-sealed cavern based on geological indicators, as described in Embodiment 1.

[0122] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0123] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for estimating the permeability coefficient of a rock mass of a water-sealed underground repository, characterized in that, The method comprises the following steps: obtaining geological index values of a target underground water-sealed cavern; estimating the rock mass permeability coefficient of the target underground water-sealed cavern according to the geological index values of the target underground water-sealed cavern and an underground water-sealed cavern rock mass permeability coefficient estimation model; wherein the construction process of the underground water-sealed cavern rock mass permeability coefficient estimation model is as follows: selecting geological indexes for constructing the underground water-sealed cavern rock mass permeability coefficient estimation model based on the engineering geological characteristics of the underground water-sealed cavern; the geological indexes include rock quality indexes, rock mass integrity indexes, fracture width indexes, fracture spacing indexes, and filling state indexes; The rock mass quality index and the rock mass integrity index are divided into lithology parameter indexes, and the fracture width index, the fracture spacing index and the filling state index are divided into fracture parameter indexes; the lithology parameter indexes are calculated according to the rock mass quality index and the rock mass integrity index; the rock mass quality index RQD and the rock mass integrity index RID are positive correlation indexes, and the calculation formula is: ; calculating a fracture parameter index according to the fracture width index, the fracture spacing index and the filling state index; the fracture width index AD , the fracture spacing index AS , the filling state index FSD is a negative correlation index, and the calculation formula is: ; constructing an underground water-sealed cavern rock mass permeability coefficient estimation expression according to the rock quality indexes and the fracture indexes; fitting empirical coefficients of the underground water-sealed cavern rock mass permeability coefficient estimation expression according to drilling data and in-situ hydrogeological test data of the underground water-sealed cavern to obtain a final required underground water-sealed cavern rock mass permeability coefficient estimation model; the underground water-sealed cavern rock mass permeability coefficient estimation model is as follows: ； ； In the formula, LFP is an intermediate variable; K is a rock permeability coefficient; is a lithology parameter index; is a fracture parameter index; , , , , , , , are empirical coefficients related to the degree of lithology and fracture development, respectively.

2. The method according to claim 1, characterized in that, The calculation process of the rock quality indexes is as follows: calculating rock quality indexes according to the rock quality indexes and the rock mass integrity indexes.

3. The method of claim 2, wherein, The rock quality designation RQD The calculation formula is: ； wherein is the sum of the lengths of the complete cores greater than 10 cm, in m; is the total length of the cores, in m.

4. The method of claim 2, wherein, The rock mass integrity index RID The calculation formula is: ； In the formula, represents the longitudinal wave velocity of the rock mass, with the unit of m / s; represents the longitudinal wave velocity of the rock mass, with the unit of m / s.

5. The method of claim 1, wherein, The calculation process of the fracture indexes is as follows: calculating fracture indexes according to the fracture width indexes, the fracture spacing indexes, and the filling state indexes.

6. The method of estimating the permeability coefficient of the rock mass of a groundwater-sealed storage cavern according to claim 5, characterized in that, The crack width index AD The calculation formula is: ； The fracture spacing indicator AS The formula for calculating the fracture spacing indicator is: ； wherein is the length of the segment, in meters; i is the width of the segment, in meters; is the distance between the first i and the first i +1 crack, in meters; is the length of the segment, in meters; n is the number of cracks.

7. The method of estimating the hydraulic conductivity of a rock mass of a groundwater- sealed storage cave according to claim 6, characterized in that, The fill state indicator FSD The calculation formula is: ； In the formula, To calculate the first segment i The width of the filled crack, in meters.

8. A system for estimating the permeability coefficient of a rock mass of a groundwater- sealed cavern, characterized by comprising: The method comprises the following steps: a data acquisition module for acquiring geological index values of a target underground water-sealed cavern; a rock mass permeability coefficient estimation module for estimating the rock mass permeability coefficient of the target underground water-sealed cavern according to the geological index values of the target underground water-sealed cavern and an underground water-sealed cavern rock mass permeability coefficient estimation model; wherein the construction process of the underground water-sealed cavern rock mass permeability coefficient estimation model is as follows: selecting geological indexes for constructing the underground water-sealed cavern rock mass permeability coefficient estimation model based on the engineering geological characteristics of the underground water-sealed cavern; the geological indexes include rock quality indexes, rock mass integrity indexes, fracture width indexes, fracture spacing indexes, and filling state indexes; The rock quality index and the rock mass integrity index are classified as lithology parameter indexes, the fracture width index, the fracture spacing index and the filling state index are classified as fracture parameter indexes; the lithology parameter indexes are calculated according to the rock quality index and the rock mass integrity index; the rock quality index RQD and the rock mass integrity index RID are positive correlation indexes, and the calculation formula is: ; the fracture parameter indexes are calculated according to the fracture width index, the fracture spacing index and the filling state index; the fracture width index AD , the fracture spacing index AS , and the filling state index FSD are negative correlation indexes, and the calculation formula is: ; constructing an underground water-sealed cavern rock mass permeability coefficient estimation expression according to the rock quality indexes and the fracture indexes; fitting empirical coefficients of the underground water-sealed cavern rock mass permeability coefficient estimation expression according to drilling data and in-situ hydrogeological test data of the underground water-sealed cavern to obtain a final required underground water-sealed cavern rock mass permeability coefficient estimation model; the underground water-sealed cavern rock mass permeability coefficient estimation model is as follows: ； ； In the formula, LFP is an intermediate variable; K is a rock permeability coefficient; is a lithology parameter index; is a fracture parameter index; , , , , , , , are empirical coefficients related to the degree of lithology and fracture development, respectively.

9. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to execute the underground water-sealed cavern rock mass permeability coefficient estimation method according to any one of claims 1 to 7.

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