A coal seam mining working face full life cycle water inflow prediction method and system

Abstract

The present application provides a coal seam mining working face full life cycle water inrush amount prediction method and system, belonging to the field of coal mining and hydrogeology. The method comprises: determining the basic physical and mechanical parameters of each rock stratum, the unit damage variable and the rock stratum coring range; CT scanning test and seepage test are carried out on the cored rock sample to obtain the porosity, fissure rate and connectivity of the rock sample; the first damage variable, the second damage variable and the third damage variable are established, and the functional relationship between the comprehensive damage variable and the first, second and third damage variables is constructed; based on the seepage test data, the functional analytical expression between the permeability coefficient in and after the coal seam mining and the comprehensive damage variable is fitted; through the fusion algorithm, the permeability coefficient function of each rock stratum is given in stages, and the dynamic prediction of the water inrush amount in and after the coal seam working face mining is realized. The present application solves the problems of lack of dynamic nature in current coal mining working face water inrush amount prediction and incomplete consideration in water inrush amount prediction process.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of coal mining and hydrogeology, and particularly relates to a coal seam mining working face full life cycle water inflow prediction method and system. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute prior art.

[0003] For coal mine areas in arid and semiarid regions, the ecological environment is fragile, and surface water resources are scarce. Coal mining leads to the development of water-conducting fissures, which may communicate with loose-pore aquifers or bedrock aquifers, causing roof water inflow or even water inrush and sand collapse accidents, exacerbating regional water resource shortage and ecological degradation. Therefore, the prediction of water inflow at the working face is of great scientific research significance and application value for optimizing mining layout (such as controlling mining height and avoiding strong aquifers), achieving "peak shaving and valley filling" drainage control, ensuring mine safety, and reducing water resource leakage.

[0004] The prediction of water inflow at the coal mining working face is influenced by factors such as working face mining height, inclined length, mining-induced fissures, geological structure, and aquifer (barrier) structure. It has the characteristics of complex prediction conditions, significant coupling effects, and engineering dynamics, making it difficult to predict water inflow at the coal mining working face. Often, the predicted water inflow is quite different from the actual situation, resulting in significant economic losses and resource waste during working face mining. Current research on water inflow prediction at the coal mining working face mainly uses methods such as sensor borehole in-situ monitoring, classical hydrogeological mathematical models, similar physical experiments, numerical simulation, and neural networks to reveal the correlation between overburden pore fissure structure and permeability spatial heterogeneity, and to establish a dynamic model of permeability based on fissure fractal dimension and stress-strain state, thereby predicting water inrush at the coal mining working face. Although the above research has achieved rich research results and to some extent predicts water inrush at the coal mining working face, it still has the following shortcomings:

[0005] (1) Current water inflow prediction at the coal mining working face is mostly based on static mining conditions, making it difficult to depict the time evolution characteristics of overburden permeability with mining stage during the working face advancing process, resulting in delayed water inrush risk warning;

[0006] (2) Current water inflow prediction at the coal mining working face mostly only considers the water inrush from aquifers within the influence range of water-conducting fissure zones, but in fact, the internal structure of aquifers (barriers) outside the influence range of water-conducting fissure zones also changes significantly, causing a sudden change in permeability, which makes the water in the aquifer also flow into the working face;

[0007] (3) Current research focuses on the prediction of water inflow during the mining process of the working face, and often ignores the research on water accumulation in the goaf caused by water inflow after the working face is mined out, that is, there is a lack of research on the prediction of water inflow throughout the entire life cycle of the working face. Summary of the Invention

[0008] To overcome the shortcomings of the existing technology, this invention provides a method and system for predicting the water inflow of a coal seam mining face throughout its entire life cycle. By using damage mechanics theory, CT scan experiments, numerical simulation and other technologies, the method dynamically predicts the water inflow during and after mining. This overcomes the shortcomings of current methods for predicting water inflow in coal mining faces, such as lack of dynamism, only considering the sudden inflow of water from aquifers within the influence range of water-conducting fracture zones while ignoring the water inflow of aquifers outside the influence range of water-conducting fracture zones, and lack of research on predicting water inflow throughout the entire life cycle of the working face.

[0009] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0010] The first aspect of this invention provides a method for predicting the water inflow of a coal seam mining face throughout its entire life cycle;

[0011] A method for predicting water inflow throughout the entire life cycle of a coal seam mining face includes:

[0012] Based on borehole data above the working face of the mining area, the basic physical and mechanical parameters and unit damage variables of each rock stratum were determined;

[0013] Based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, the degree of development of the conductive height and the degree of change in the permeability of the rock stratum above the water-conducting fracture zone during the mining process of the working face are simulated to determine the core sampling range of the rock stratum.

[0014] CT scanning and seepage tests were conducted on core samples under mining disturbance stress to obtain the porosity, fracture rate, and connectivity of the samples. First, second, and third damage variables, defined by porosity, fracture rate, and connectivity, were established, and a functional relationship was constructed between the porosity-fracture-connectivity comprehensive damage variable and the first, second, and third damage variables. Based on the seepage test data, an analytical function was fitted between the permeability coefficient during and after coal seam mining and the comprehensive damage variable.

[0015] Based on the fitted function expression, the permeability coefficient and permeability are converted, and the permeability coefficient function is assigned to each rock layer in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

[0016] As a further technical solution, the unit damage variable is defined by damage mechanics theory, specifically:

[0017] When the stress state of the overlying strata of the coal seam satisfies the maximum tensile stress criterion and the Mohr-Coulomb criterion, tensile damage and shear damage occur respectively, i.e.:

[0018]

[0019]

[0020] In the formula, , These are functions representing stress states, and their values ​​being greater than zero indicate that the medium has undergone tensile and shear damage, respectively. This refers to the uniaxial tensile strength of the element. Uniaxial compressive strength of the unit; , These are the first principal stress and the third principal stress, respectively.

[0021] Based on the limit state in the above formula, the element damage variable is:

[0022]

[0023] In the formula, For unit damage variables; The element damage evolution coefficient; , These represent the maximum tensile principal strain and the maximum compressive principal strain, respectively, which correspond to the tensile damage and shear damage that occur in the element.

[0024] As a further technical solution, the process of simulating the degree of permeability change in the rock strata above the water-conducting fracture zone includes:

[0025] Analysis of the stress path of coal seam disturbance caused by overburden rock during and after mining;

[0026] Based on the actual thickness and physical and mechanical parameters of each rock stratum, and combined with the stress path of coal mining disturbance, an evolution test of the permeability coefficient of the rock stratum above the water-conducting fracture zone was carried out. The change rate of permeability coefficient was used to determine whether the change was significant. When the change was significant, the rock stratum was included in the field core sampling range.

[0027] As a further technical solution, CT scanning and seepage tests are conducted on the cored rock samples under the stress of coal mining disturbance to obtain the porosity, fracture rate, and connectivity of the samples, including:

[0028] Based on the core samples and the stress path of coal mining disturbance, CT scanning experiments were conducted on rock samples from each rock layer to obtain slice data of the rock samples along the X, Y, and Z directions.

[0029] The porosity, fracture rate, and connectivity of rock samples from each rock layer were obtained based on CT scan experimental data and AVIZO software.

[0030] As a further technical solution, a first damage variable, a second damage variable, and a third damage variable, defined by porosity, fracture rate, and connectivity, are established respectively. A functional relationship is constructed between the porosity-fracture-connectivity integrated damage variable and the first, second, and third damage variables, including:

[0031] The first damage variable, the second damage variable, and the third damage variable, defined by porosity, fracture rate, and connectivity, are as follows:

[0032]

[0033]

[0034]

[0035] In the formula, , , These are the first damage variable, the second damage variable, and the third damage variable, respectively. This represents the maximum porosity during the coal mining disturbance stress process. This represents the minimum porosity during the coal mining disturbance stress process; Porosity represents the porosity at a certain stage during the coal mining disturbance stress process; This represents the maximum fracture rate during the coal mining disturbance stress process; This represents the minimum fracture ratio during the coal mining disturbance stress process; This represents the fracture rate at a certain stage during the coal mining disturbance stress process; This represents the maximum connectivity during the coal mining disturbance stress process; This represents the minimum connectivity during the coal mining disturbance stress process; This indicates the connectivity at a certain stage during the coal mining disturbance stress process;

[0036] The functional relationship between the comprehensive damage variable (porosity-fracture-connectivity) and the first, second, and third damage variables is constructed as follows:

[0037]

[0038] In the formula, This represents the comprehensive damage variable of pores, fractures, and connectivity under coal mining disturbance stress; , , These represent the first damage variable, the second damage variable, and the third damage variable, defined by porosity, cracks, and connectivity, respectively. , , Representing damage variables respectively , , Porosity of rock samples at a certain stage during coal mining disturbance stress Crack rate Connectivity The correlation coefficient between them.

[0039] As a further technical solution, based on seepage test data, the functional expression between the permeability coefficient and the comprehensive damage variable during and after coal seam mining is fitted as follows:

[0040]

[0041] In the formula, Permeability coefficient; The initial permeability coefficient before coal mining disturbance; The coefficient representing the effect of damage on permeability; The initial porosity of the rock sample before coal mining disturbance.

[0042] As a further technical solution, the permeability coefficient and permeability are converted based on the fitted function expression, and the permeability coefficient function is assigned to each rock stratum in stages to achieve dynamic prediction of water inflow during and after mining in the coal seam working face, including:

[0043] The conversion between permeability coefficient and permeability is performed based on the fitted function expression, as shown in the following formula:

[0044]

[0045] in, For penetration rate, For fluid density; It is the acceleration due to gravity; For fluid dynamic viscosity;

[0046] The analytical function relating permeability coefficient and damage variable in coal seam mining is assigned to each corresponding rock stratum in stages.

[0047] Numerical simulations were conducted during coal seam mining to generate numerical results of water inflow at the working face at corresponding stages of the coal seam mining process.

[0048] After the coal seam mining is completed, the functional expression between the permeability coefficient and the damage variable is assigned to each corresponding rock stratum, and then the water inflow of the working face after coal seam mining is predicted.

[0049] By summing the water inflow at the working face before and after coal seam mining, the total water inflow of the coal seam mining working face throughout its entire life cycle is obtained.

[0050] The second aspect of the present invention provides a system for predicting the water inflow of a coal seam mining face throughout its entire life cycle.

[0051] A system for predicting water inflow throughout the entire life cycle of a coal seam mining face includes:

[0052] The data acquisition module is configured to determine the basic physical and mechanical parameters and unit damage variables of each rock stratum based on borehole data above the working face of the mining area.

[0053] The numerical simulation module is configured to: simulate the degree of development of the conductive height and the degree of permeability change of the rock strata above the water-conducting fracture zone during the mining process of the working face based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, and determine the core sampling range of the rock strata.

[0054] The damage analysis module is configured to: conduct CT scanning and seepage tests on core samples under mining disturbance stress to obtain the porosity, fracture rate, and connectivity of the samples; establish a first damage variable, a second damage variable, and a third damage variable defined by porosity, fracture rate, and connectivity, respectively; construct a functional relationship between the porosity-fracture-connectivity comprehensive damage variable and the first, second, and third damage variables; and, based on the seepage test data, fit the analytical function between the permeability coefficient during and after coal seam mining and the comprehensive damage variable.

[0055] The water inflow prediction module is configured to convert the permeability coefficient to the permeability rate based on the fitted function expression, and assign the permeability coefficient function to each rock stratum in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

[0056] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the steps of a method for predicting the total life-cycle water inflow of a coal seam mining face as described in the first aspect of the present invention.

[0057] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the method for predicting the total life cycle water inflow of a coal seam mining face as described in the first aspect of the present invention.

[0058] The above one or more technical solutions have the following beneficial effects:

[0059] (1) This invention enables dynamic prediction throughout the entire life cycle, improving the timeliness of water inflow warning. By establishing a dynamic relationship between permeability coefficient and damage variables in stages (during and after mining), it overcomes the limitations of traditional static prediction methods and can reflect the evolution of overburden permeability in real time during mining. By combining numerical simulation and experimental data, the prediction model is dynamically updated, significantly reducing the lag in water inflow prediction and providing timely and accurate data support for water control decision-making.

[0060] (2) This invention simulates the permeability changes of the rock strata above the water-conducting fracture zone and sets a threshold to screen areas with significant influence, thus avoiding the one-sidedness of traditional methods that only focus on the range of the water-conducting fracture zone. By introducing a multi-parameter damage model of porosity, fracture rate and connectivity, the impact of rock strata damage on permeability is more comprehensively characterized, making the prediction results closer to the actual engineering situation.

[0061] (3) By combining measured data such as CT scans and seepage tests with COMSOL numerical simulations, the model parameters are dynamically corrected using MATLAB algorithms to reduce human experience errors. The degree of rock strata damage is quantified using damage mechanics theory, and a mathematical relationship between permeability coefficient and damage variables is established, making the prediction process more theoretically grounded.

[0062] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0063] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0064] Figure 1 This is a flowchart of the method in the first embodiment.

[0065] Figure 2 This is a system structure diagram of the second embodiment. Detailed Implementation

[0066] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0067] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0068] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0069] Example 1

[0070] This embodiment discloses a method for predicting water inflow throughout the entire life cycle of a coal seam mining face;

[0071] like Figure 1 As shown, a method for predicting the total water inflow of a coal seam mining face throughout its entire life cycle includes:

[0072] Step S1: Determine the basic physical and mechanical parameters and unit damage variables of each rock stratum based on borehole data above the working face of the mining area;

[0073] Step S2: Based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, simulate the degree of development of the conductive height and the degree of change in the permeability of the rock stratum above the water-conducting fracture zone during the mining process of the working face, and determine the core sampling range of the rock stratum.

[0074] Step S3: Conduct CT scanning and seepage tests on the cored rock samples under mining disturbance stress to obtain the porosity, fracture rate, and connectivity of the samples; establish a first damage variable, a second damage variable, and a third damage variable, characterized by porosity, fracture rate, and connectivity, respectively, and construct a functional relationship between the porosity-fracture-connectivity comprehensive damage variable and the first, second, and third damage variables; based on the seepage test data, fit the analytical function expression between the permeability coefficient during and after coal seam mining and the comprehensive damage variable.

[0075] Step S4: Based on the fitted function expression, the permeability coefficient and permeability are converted, and the permeability coefficient function is assigned to each rock layer in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

[0076] Furthermore, the above steps also specifically include the following:

[0077] In step S1, the basic physical and mechanical parameters and unit damage variables of each rock stratum are determined based on borehole data above the working face of the mining area. The basic physical and mechanical parameters of each rock stratum include: density, Young's modulus, Poisson's ratio, initial porosity, initial permeability, dynamic viscosity, tensile strength, and compressive strength. These obtained basic physical and mechanical parameters are used for model establishment in subsequent numerical simulations.

[0078] When obtaining the element damage variable, the element damage variable is defined by damage mechanics theory. When the stress state of the overlying strata of the coal seam satisfies the maximum tensile stress criterion and the Mohr-Coulomb criterion, tensile damage and shear damage occur respectively, that is:

[0079]

[0080]

[0081] In the formula, , These are functions representing stress states, and their values ​​being greater than zero indicate that the medium has undergone tensile and shear damage, respectively. This refers to the uniaxial tensile strength of the element. Uniaxial compressive strength of the unit; , These are the first principal stress and the third principal stress, respectively.

[0082] Based on the limit state in the above formula, the element damage variable is obtained as follows:

[0083]

[0084] In the formula, For unit damage variables; The element damage evolution coefficient; , These represent the maximum tensile principal strain and the maximum compressive principal strain, respectively, which correspond to the tensile damage and shear damage that occur in the element.

[0085] In step S2, based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, the degree of development of the conductive height and the degree of permeability change of the rock stratum above the water-conducting fracture zone during the mining process of the working face are simulated to determine the core sampling range of the rock stratum.

[0086] Specifically, in determining the core sampling range of rock strata based on the development degree of guide height during the simulated mining process, a COMSOL numerical model was established based on the actual rock strata conditions of a certain working face in the mining area, and the defined unit damage variables were used. Each rock stratum was assigned a custom variable; COMSOL software was used to simulate the mining face, and the damage variable was incorporated into the numerical simulation results. To obtain the degree of conductive height development and to perform core sampling of rock strata within the influence range of the conductive height.

[0087] Since the internal structure of the overlying rock outside the influence range of the water-conducting fracture zone is also easily affected by the disturbance of coal mining, this embodiment also simulates the change in permeability of the rock strata above the water-conducting fracture zone and judges whether the change is significant.

[0088] First, the stress path of coal seam overburden disturbance is analyzed. Specifically, during mining, the overburden is loaded to the original stress state, and then the axial pressure is increased until the overburden reaches the uniaxial ultimate axial pressure value. While maintaining a constant axial displacement, the confining pressure is gradually unloaded until the ultimate failure state. After mining, the axial pressure is first reduced to the original stress state value, and a sample is designed to reach the original stress state while maintaining a constant axial displacement. Then, the surrounding rock is added in stages until the confining pressure creeps back to the original stress state.

[0089] Secondly, based on the actual thickness and physical and mechanical parameters of each rock stratum, and combined with the stress path of coal mining disturbance, an evolution test of the permeability coefficient of the rock stratum above the water-conducting fracture zone was conducted. The significance of the change was judged based on the ratio m of the rate of change of permeability coefficient to the initial permeability coefficient, as shown in the following formula:

[0090]

[0091] In the formula, This is the ratio of the rate of change of the permeability coefficient to the initial permeability coefficient; This represents the maximum rate of change of the permeability coefficient of the upper strata in the coal mining disturbance stress path; This represents the permeability coefficient of the rock strata above the coal seam before mining.

[0092] when If the value is less than 100%, it indicates that the change is not significant, meaning that the permeability of the rock stratum is not greatly affected by the stress of coal mining disturbance; if it is greater than or equal to 100%, it indicates that the change is significant, and the rock stratum should be included in the field core sampling scope.

[0093] Step S3 also includes the following:

[0094] Step S31: Conduct CT scanning and seepage tests on the cored rock samples under the stress of coal mining disturbance to obtain the porosity, fracture rate and connectivity of the rock samples.

[0095] Based on the obtained core samples and the stress path of coal mining disturbance, CT scan experiments were conducted on rock samples from each stratum to obtain slice data of the rock samples along the X, Y, and Z directions. Based on the CT scan data and AVIZO software, the porosity of the rock samples from each stratum was obtained. Crack rate and connectivity Specifically, this involves using the Interactive Top-Hat module of AVIZO software to distinguish between pores and fractures and the matrix, and selecting the Aix Connectivity module to extract connectivity. The analysis involves: defining custom analysis attributes using the Label Analysis module; using the Analysis Filter module to select Shape_VA3d to differentiate between pores and fractures; and using the VolumeFraction module to obtain porosity. and fracture rate .

[0096] Step S32: Establish a first damage variable, a second damage variable, and a third damage variable, defined by porosity, crack rate, and connectivity, respectively, and construct a functional relationship between the porosity-crack rate-connectivity integrated damage variable and the first damage variable, the second damage variable, and the third damage variable.

[0097] Among them, damage variables defined by pore characterization are established. With porosity The first damage variable defined by characterization Model:

[0098]

[0099] in: This represents the maximum porosity during the coal mining disturbance stress process. This represents the minimum porosity during the coal mining disturbance stress process; It represents the porosity at a certain stage during the coal mining disturbance stress process.

[0100] Establish damage variables defined by crack characterization With crack ratio The second damage variable defined by characterization Model:

[0101]

[0102] in, This represents the maximum fracture rate during the coal mining disturbance stress process; This represents the minimum fracture ratio during the coal mining disturbance stress process; It represents the fracture rate at a certain stage during the coal mining disturbance stress process.

[0103] Considering that the distribution of pore and fracture structures within the rock also affects its permeability, a damage variable defined by connectivity is further established. With connectivity The third damage variable defined by characterization Model:

[0104]

[0105] in, This represents the maximum connectivity during the coal mining disturbance stress process; This represents the minimum connectivity during the coal mining disturbance stress process; It represents the connectivity at a certain stage in the coal mining disturbance stress process.

[0106] Furthermore, the functional relationship between the porosity-fracture-connectivity integrated damage variable and the first, second, and third damage variables is constructed as shown in the following equation:

[0107]

[0108] In the formula, This represents the comprehensive damage variable of pores, fractures, and connectivity under coal mining disturbance stress; , , These represent the first damage variable, the second damage variable, and the third damage variable, defined by porosity, cracks, and connectivity, respectively. , , Representing damage variables respectively , , Porosity of rock samples at a certain stage during coal mining disturbance stress Crack rate Connectivity The correlation coefficient between them.

[0109] Step S33: Based on the seepage test data, fit the analytical function between the permeability coefficient and the comprehensive damage variable during and after coal seam mining.

[0110] Specifically, based on the core samples and coal mining disturbance stress paths obtained above, seepage tests were conducted on rock samples from each stratum to obtain the permeability coefficient of each rock sample under different stress states. Simultaneously, CT scans can be used to obtain the porosity under these stress states. Crack rate Connectivity This is used to subsequently solve the comprehensive damage variable and permeability coefficient calculation formulas to obtain the relevant function analytical expression through comprehensive fitting.

[0111] Furthermore, the permeability coefficient during and after coal seam mining was fitted based on seepage test data. Comprehensive damage variables of pore-fracture-connectivity under coal mining disturbance stress The functional expression between them.

[0112] In coal seam mining, the porosity during the mining stage is only included in the entire process of obtaining mining disturbance stress. and fracture rate and connectivity The maximum and minimum values ​​of the permeability coefficient during coal seam mining are used to obtain the permeability coefficient, which is:

[0113]

[0114] In the formula, Permeability coefficient; The initial permeability coefficient before coal mining disturbance; The coefficient representing the effect of damage on permeability; The initial porosity of the rock sample before coal mining disturbance.

[0115] Furthermore, by combining the first damage variable, the second damage variable, the third damage variable, the comprehensive damage variable, and the permeability coefficient calculation formula, a comprehensive fitting is obtained to obtain the analytical expression of the relevant function, as shown in the following formula:

[0116]

[0117] Furthermore, in coal seam mining, the porosity during the mining disturbance stress phase is only included in the entire process of obtaining the mining disturbance stress. Crack rate and connectivity The maximum and minimum values ​​are determined by the permeability coefficient during coal seam mining. The analytical expression of the relevant function is obtained by combining the third damage variable, the comprehensive damage variable and the permeability coefficient calculation formula;

[0118] After coal seam mining, the porosity obtained during the entire process of obtaining mining disturbance stress only includes the porosity during the post-mining creep stage. Crack rate and connectivity The maximum and minimum values ​​are then used to obtain the analytical expression of the relevant function through comprehensive fitting, but at this point... The permeability coefficient of a rock sample immediately after coal seam mining. The porosity of a rock sample immediately after coal seam mining.

[0119] In step S4, the permeability coefficient and permeability are converted according to the fitted function expression, as shown below:

[0120]

[0121] in, For penetration rate, For fluid density; It is the acceleration due to gravity; This refers to the fluid dynamic viscosity.

[0122] The above formula is used to assign the functional expression between the permeability coefficient and the comprehensive damage variable in coal seam mining to each corresponding rock stratum in stages; this enables dynamic prediction of water inflow during and after coal seam mining. Specifically:

[0123] Numerical simulations of coal seam mining are carried out. Based on the existing numerical model of coal seam mining that includes physical and mechanical parameters of each rock stratum, unit damage variables and permeability coefficient functions, numerical simulation calculations of the coal seam mining stage are performed to obtain flow field distribution data at each moment during the mining process.

[0124] Based on the results analysis interface of the numerical simulation software, a two-dimensional plotting group is created for calculating water inflow. The analysis object of this plotting group is defined as the computational domain where the coal seam mining face is located. Within the aforementioned two-dimensional plotting group, an analysis carrier of type "surface" is created. This surface must completely cover the spatial range of the coal seam mining face to ensure that it can capture the fluid motion parameters of the entire working face.

[0125] The water inflow at the working face is calculated using the expression derived from Darcy's law: Water inflow at the working face = Working face model volume × Darcy velocity × Time; where the working face model volume is the spatial volume of the working face computational domain in the numerical model; Darcy velocity is the magnitude of the Darcy velocity vector of the fluid within the working face domain output by the simulation; and time is the duration of the corresponding mining stage.

[0126] Finally, the flow field data within the working face region is integrated based on the input expression to generate numerical results of the working face water inflow at the corresponding stage of coal seam mining, and the results are output in the form of data files or visualization charts.

[0127] Based on the above process, after the coal seam mining is completed, the functional expression between the permeability coefficient and the comprehensive damage variable is also assigned to each corresponding rock stratum, so as to predict the water inflow of the working face after coal seam mining.

[0128] Ultimately, the total water inflow of the coal seam mining face throughout its entire life cycle can be obtained by summing up the water inflow before and after coal seam mining.

[0129] Example 2

[0130] This embodiment discloses a system for predicting water inflow throughout the entire life cycle of a coal seam mining face;

[0131] like Figure 2 As shown, a system for predicting the total water inflow of a coal seam mining face throughout its entire life cycle includes:

[0132] The data acquisition module is configured to determine the basic physical and mechanical parameters and unit damage variables of each rock stratum based on borehole data above the working face of the mining area.

[0133] The numerical simulation module is configured to: simulate the degree of development of the conductive height and the degree of permeability change of the rock strata above the water-conducting fracture zone during the mining process of the working face based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, and determine the core sampling range of the rock strata.

[0134] The damage analysis module is configured to: conduct CT scanning and seepage tests on core samples under mining disturbance stress to obtain the porosity, fracture rate, and connectivity of the samples; establish a first damage variable, a second damage variable, and a third damage variable defined by porosity, fracture rate, and connectivity, respectively; construct a functional relationship between the porosity-fracture-connectivity comprehensive damage variable and the first, second, and third damage variables; and, based on the seepage test data, fit the analytical function between the permeability coefficient during and after coal seam mining and the comprehensive damage variable.

[0135] The water inflow prediction module is configured to convert the permeability coefficient to the permeability rate based on the fitted function expression, and assign the permeability coefficient function to each rock stratum in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

[0136] Example 3

[0137] The purpose of this embodiment is to provide a computer-readable storage medium.

[0138] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in a method for predicting the total life-cycle water inflow of a coal seam mining face as described in Example 1.

[0139] Example 4

[0140] The purpose of this embodiment is to provide an electronic device.

[0141] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for predicting the total life-cycle water inflow of a coal seam mining face as described in Example 1.

[0142] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0143] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0144] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for predicting water inflow throughout the entire life cycle of a coal seam mining face, characterized in that, include: Based on borehole data above the working face of the mining area, the basic physical and mechanical parameters and unit damage variables of each rock stratum were determined; Based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, the degree of development of the conductive height and the degree of change in the permeability of the rock stratum above the water-conducting fracture zone during the mining process of the working face are simulated to determine the core sampling range of the rock stratum. CT scanning and seepage tests were conducted on the cored rock samples under the stress of coal mining disturbance to obtain the porosity, fracture rate and connectivity of the samples. First, second, and third damage variables, defined by porosity, fracture rate, and connectivity, are established respectively. The functional relationship between the porosity-fracture-connectivity integrated damage variable and the first, second, and third damage variables is constructed, including: the first, second, and third damage variables, defined by porosity, fracture rate, and connectivity, are as follows: In the formula, , , These are the first damage variable, the second damage variable, and the third damage variable, respectively. This represents the maximum porosity during the coal mining disturbance stress process. This represents the minimum porosity during the coal mining disturbance stress process; Porosity represents the porosity at a certain stage during the coal mining disturbance stress process; This represents the maximum fracture rate during the coal mining disturbance stress process; This represents the minimum fracture ratio during the coal mining disturbance stress process; This represents the fracture rate at a certain stage during the coal mining disturbance stress process; This represents the maximum connectivity during the coal mining disturbance stress process; This represents the minimum connectivity during the coal mining disturbance stress process; This indicates the connectivity at a certain stage during the coal mining disturbance stress process; The functional relationship between the comprehensive damage variable (porosity-fracture-connectivity) and the first, second, and third damage variables is constructed as follows: In the formula, This represents the comprehensive damage variable of pores, fractures, and connectivity under coal mining disturbance stress; , , These represent the first damage variable, the second damage variable, and the third damage variable, defined by porosity, cracks, and connectivity, respectively. , , Representing damage variables respectively , , Porosity of rock samples at a certain stage during coal mining disturbance stress Crack rate Connectivity The correlation coefficient between them; Based on seepage test data, a functional expression is fitted between the permeability coefficient and the comprehensive damage variable during and after coal seam mining. The functional expression is: In the formula, Permeability coefficient; The initial permeability coefficient before coal mining disturbance; The coefficient representing the effect of damage on permeability; The initial porosity of the rock sample before coal mining disturbance; Based on the fitted function expression, the permeability coefficient and permeability are converted, and the permeability coefficient function is assigned to each rock layer in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

2. The method for predicting the total water inflow of a coal seam mining face throughout its entire life cycle as described in claim 1, characterized in that, The unit damage variable is defined by damage mechanics theory, specifically: When the stress state of the overlying strata of the coal seam satisfies the maximum tensile stress criterion and the Mohr-Coulomb criterion, tensile damage and shear damage occur respectively, i.e.: In the formula, , These are functions representing stress states, and their values ​​being greater than zero indicate that the medium has undergone tensile and shear damage, respectively. This refers to the uniaxial tensile strength of the element. Uniaxial compressive strength of the unit; , These are the first principal stress and the third principal stress, respectively. Based on the limit state in the above formula, the element damage variable is: In the formula, For unit damage variables; The element damage evolution coefficient; , These represent the maximum tensile principal strain and the maximum compressive principal strain, respectively, which correspond to the tensile damage and shear damage that occur in the element.

3. The method for predicting the total water inflow of a coal seam mining face throughout its entire life cycle as described in claim 1, characterized in that, The process of simulating the degree of permeability change in the rock strata above the water-conducting fracture zone includes: Analysis of the stress path of coal seam disturbance caused by overburden rock during and after mining; Based on the actual thickness and physical and mechanical parameters of each rock stratum, and combined with the stress path of coal mining disturbance, an evolution test of the permeability coefficient of the rock stratum above the water-conducting fracture zone was carried out. The change rate of permeability coefficient was used to determine whether the change was significant. When the change was significant, the rock stratum was included in the field core sampling range.

4. The method for predicting the total water inflow of a coal seam mining face throughout its entire life cycle as described in claim 1, characterized in that, CT scanning and seepage tests were conducted on cored rock samples under mining disturbance stress to obtain the porosity, fracture rate, and connectivity of the samples, including: Based on the core samples and the stress path of coal mining disturbance, CT scanning experiments were conducted on rock samples from each rock layer to obtain slice data of the rock samples along the X, Y, and Z directions. The porosity, fracture rate, and connectivity of rock samples from each rock layer were obtained based on CT scan experimental data and AVIZO software.

5. The method for predicting the total water inflow of a coal seam mining face throughout its entire life cycle as described in claim 1, characterized in that, Based on the fitted function's analytical expression, the permeability coefficient and permeability are converted, and the permeability coefficient function is assigned to each rock stratum in stages to achieve dynamic prediction of water inflow during and after coal seam mining, including: The conversion between permeability coefficient and permeability is performed based on the fitted function expression, as shown in the following formula: in, For penetration rate, For fluid density; It is the acceleration due to gravity; For fluid dynamic viscosity; The analytical function relating permeability coefficient and damage variable in coal seam mining is assigned to each corresponding rock stratum in stages. Numerical simulations were conducted during coal seam mining to generate numerical results of water inflow at the working face at corresponding stages of the coal seam mining process. After the coal seam mining is completed, the functional expression between the permeability coefficient and the damage variable is assigned to each corresponding rock stratum, and then the water inflow of the working face after coal seam mining is predicted. By summing the water inflow at the working face before and after coal seam mining, the total water inflow of the coal seam mining working face throughout its entire life cycle is obtained.

6. A system for predicting water inflow throughout the entire life cycle of a coal seam mining face, characterized in that, include: The data acquisition module is configured to determine the basic physical and mechanical parameters and unit damage variables of each rock stratum based on borehole data above the working face of the mining area. The numerical simulation module is configured to: simulate the degree of development of the conductive height and the degree of permeability change of the rock strata above the water-conducting fracture zone during the mining process of the working face based on the determined basic physical and mechanical parameters and unit damage variables of each rock stratum, and determine the core sampling range of the rock strata. The damage analysis module is configured to perform CT scanning and seepage tests on core samples under coal mining disturbance stress to obtain the porosity, fracture rate and connectivity of the core samples. First, second, and third damage variables, defined by porosity, fracture rate, and connectivity, are established respectively. The functional relationship between the porosity-fracture-connectivity integrated damage variable and the first, second, and third damage variables is constructed, including: the first, second, and third damage variables, defined by porosity, fracture rate, and connectivity, are as follows: In the formula, , , These are the first damage variable, the second damage variable, and the third damage variable, respectively. This represents the maximum porosity during the coal mining disturbance stress process. This represents the minimum porosity during the coal mining disturbance stress process; Porosity represents the porosity at a certain stage during the coal mining disturbance stress process; This represents the maximum fracture rate during the coal mining disturbance stress process; This represents the minimum fracture ratio during the coal mining disturbance stress process; This represents the fracture rate at a certain stage during the coal mining disturbance stress process; This represents the maximum connectivity during the coal mining disturbance stress process; This represents the minimum connectivity during the coal mining disturbance stress process; This indicates the connectivity at a certain stage during the coal mining disturbance stress process; The functional relationship between the comprehensive damage variable (porosity-fracture-connectivity) and the first, second, and third damage variables is constructed as follows: In the formula, This represents the comprehensive damage variable of pores, fractures, and connectivity under coal mining disturbance stress; , , These represent the first damage variable, the second damage variable, and the third damage variable, defined by porosity, cracks, and connectivity, respectively. , , Representing damage variables respectively , , Porosity of rock samples at a certain stage during coal mining disturbance stress Crack rate Connectivity The correlation coefficient between them; Based on seepage test data, a functional expression is fitted between the permeability coefficient and the comprehensive damage variable during and after coal seam mining. The functional expression is: In the formula, Permeability coefficient; The initial permeability coefficient before coal mining disturbance; The coefficient representing the effect of damage on permeability; The initial porosity of the rock sample before coal mining disturbance; The water inflow prediction module is configured to convert the permeability coefficient to the permeability rate based on the fitted function expression, and assign the permeability coefficient function to each rock stratum in stages to realize the dynamic prediction of water inflow during and after mining in the coal seam working face.

7. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the method for predicting the total life cycle water inflow of a coal seam mining face as described in any one of claims 1-5.

8. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the method for predicting the total life cycle water inflow of a coal seam mining face as described in any one of claims 1-5.

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