Method for determining development height of water flowing fractured zone based on internal stratum subsidence prediction

Abstract

The present application belongs to the technical field of mining subsidence, and discloses a method for obtaining the development height of a water flowing fractured zone based on internal stratum subsidence prediction, comprising the following steps: step one, using an optimization algorithm to inverse the moving deformation prediction parameters and extract the stratum fracture horizontal deformation critical value; step two, predicting the internal stratum subsidence layer by layer from the goaf upwards; step three, calculating the maximum value of the stratum surface horizontal deformation; step four, comparing the maximum value of the horizontal deformation with the critical value: if the maximum value exceeds the critical value, returning to step two and adding one to the layer number, otherwise, entering step five; step five, accumulating the fractured stratum thickness to determine the development height of the water flowing fractured zone. The present application builds a fitness function for predicting the moving deformation prediction parameters in the mining process, uses an optimization algorithm to solve it, and combines the stratum fracture judgment method, which will help to more accurately predict the development of the water flowing fractured zone in the mining process, and provide strong support for the safety production and environmental protection of the mine.

Description

Technical Field

[0001] This invention belongs to the field of mining subsidence technology, specifically relating to a method for determining the development height of water-conducting fracture zones based on the predicted subsidence within rock strata. Background Technology

[0002] During mining operations, as ore is continuously extracted, the upper rock strata of the goaf gradually lose support, disrupting the original stress balance and causing fractures, displacements, or collapses, forming water-conducting fracture zones. When these fracture zones develop upwards to the aquifer, they can lead to water inrush accidents. Such sudden, large-scale water inrushes not only severely disrupt normal mining operations and threaten the lives of workers, but can also cause secondary disasters such as environmental pollution, resulting in long-term negative impacts on the ecological environment of the mine and surrounding areas. Therefore, it is necessary to adopt effective methods to accurately predict the development height of water-conducting fracture zones to prevent roof water hazards in mining. Currently, my country mainly uses empirical formulas recommended in the "Specifications for the Retention of Coal Pillars and Coal Mining under Pressure in Buildings, Water Bodies, Railways, and Main Shafts" for predicting the development height of water-conducting fracture zones. These empirical formulas are derived from a large amount of measured data, which covers different geological conditions, mining methods, and rock strata characteristics, thus meeting the needs for predicting the development height of water-conducting fracture zones to a certain extent.

[0003] In existing technologies, the predicted parameters for displacement deformation generally require accurate data after mining to be calculated. However, when predicting displacement deformation caused by mining, the predicted parameters can only be estimated values, which can lead to significant errors. Furthermore, using empirical formulas to predict the height of the water-conducting fracture zone is only relatively close to the actual value in mining areas where the single-layer mining thickness is 1–3 m and the cumulative mining thickness does not exceed 15 m. Considering the differences in ore layer thickness in different regions, when facing mining areas exceeding this specific mining thickness range, predictions based solely on empirical formulas often result in significant deviations between the predicted and actual values ​​of the water-conducting fracture zone height. This deviation may not only affect the safety planning of mining operations but also pose a potential threat to groundwater resource protection and surface environmental stability. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method for determining the development height of water-conducting fracture zones based on the predicted subsidence within rock strata, thus solving the problem of inaccurate prediction in existing technologies.

[0005] The objective of this invention can be achieved through the following technical solution: a method for determining the development height of water-conducting fracture zones based on the expected subsidence within rock strata, comprising the following steps; Step 1: Collect drilling data, geological and mining condition data, and surface measured data of the area to be tested. Then, use an optimized algorithm to derive the predicted parameters of movement and deformation, and extract the critical value of horizontal deformation of the rock strata fracture. Step 2: Based on the predicted parameters obtained in Step 1, predict the internal settlement of the rock strata layer by layer from the goaf upwards. Step 3: Based on the settlement prediction results, calculate the maximum horizontal deformation of the upper and lower surfaces of the rock strata on the strike main cross section. Step 4: Compare the maximum horizontal deformation obtained in Step 3 with the critical value of horizontal deformation of the rock strata fracture. If the maximum horizontal deformation exceeds the critical value, proceed to Step 2 and increment the layer number by one. If it does not exceed the critical value, proceed to Step 5. Step 5: Accumulate the thickness of the fractured rock strata to determine the development height of the water-conducting fracture zone. The drilling data in Step 1 includes cumulative depth, rock layer thickness, and lithological description. The geological and mining condition data in Step 1 includes mining depth, mining thickness, coal seam dip angle, strike length, and dip length. The surface measured data in Step 1 includes point number, coordinates, and subsidence value.

[0006] In some publications, the specific calculation steps for step two are as follows; The calculation lengths for the orientation and dip of the working face are shown in Equations (1) and (2): (1) (2) in D 3. D 1 represents the working face direction and dip length, respectively; s 1. s 2. s 3. s 4 represents the inflection point offset distance for downhill, uphill, leftward, and rightward directions, respectively.

[0007] In some publications, the rock strata are simplified as beams, and the cross-section in the middle of the rock strata is the neutral plane. The main influence radius for calculating the position of the neutral plane of the rock strata is shown in Equation (3). (3) in H Indicates the depth of mining; tan β Indicates the tangent of the main influencing angle; z Indicates the distance from the ground surface to the neutral plane of the rock strata; n This represents the main radius of influence related to lithology, and is an empirical value. r This indicates the main radius of influence of surface subsidence.

[0008] In some publicly available methods, the maximum surface subsidence is calculated as follows; Calculate the maximum surface subsidence value W 0, the calculation formula is shown in equation (4): (4) in m Indicates thickening; q Indicates the subsidence coefficient; α Indicates the dip angle of the ore layer.

[0009] In some disclosures, the predicted parameters are... q , s 1. s 2. s 3. s 4. tan β The prediction methods include collecting mining data, constructing fitness functions, and selecting optimization algorithms; Collect mining data, including settlement data from other mines in the same area, and conduct actual data measurements and collection for the predicted mining area, including geological and mining conditions and measured data. Geological and mining conditions include mining depth, mining thickness, coal seam dip angle, strike length, and dip length. Measured data includes point number, coordinates, and subsidence value.

[0010] In some disclosures, the fitness function is constructed, and the objective function can be defined as the sum of squared errors between the predicted and measured land subsidence. The smaller the sum of squared errors, the more accurate the prediction result. in, f ( i (for individuals) i fitness value, M The number of surface measurement points. This represents the predicted amount of surface subsidence. This represents the measured amount of surface subsidence.

[0011] In some publications, the selection of optimization algorithms involves choosing a suitable neural network architecture, such as a BP neural network, a convolutional neural network, or a genetic algorithm. Based on the data inversion results, the input and output layers of the neural network are determined. The input layer should include geological and mining conditions such as mining depth, mining thickness, coal seam dip angle, strike length, dip length, etc., as well as actual surface measurement data. The output layer consists of predicted parameters for movement and deformation.

[0012] In some publications, the subsidence value of the strike-oriented main cross-section of the calculated neutral plane location of the rock strata is described. The calculation formula is shown in equation (5): (5) in This indicates the subsidence value towards the main cross-section when fully exploited; This indicates the subsidence value of the main cross-section when it is fully mined; Indicates the direction towards the point on the main cross-section. coordinate; This indicates the maximum subsidence value of the main cross-section when it is fully mined.

[0013] In some publications, the specific steps of step three are as follows: The flexural section modulus of the rock strata is calculated using the formula shown in equation (6): (6) in J Represents the moment of inertia; Z Indicates the thickness of the rock strata; The bending moment is calculated using the formula shown in equation (7): (7) in E Indicates the elastic modulus; The horizontal deformation of the upper and lower surfaces of the rock strata is calculated using the formula shown in equation (8): (8) The beneficial effects of this invention are: 1. This invention constructs a fitness function for predicting the parameters of surface movement and deformation during mining and solves it using an optimization algorithm. This will help to more accurately predict the surface movement and deformation after mining and provide strong support for safe production and environmental protection in mines.

[0014] 2. This invention significantly improves prediction accuracy by forecasting subsidence within rock strata and estimating the development height of water-conducting fracture zones layer by layer. This innovative method provides a scientific and reliable basis for the design of mining schemes and effectively guides the formulation and implementation of roof water hazard prevention strategies. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention. Detailed Implementation

[0017] 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.

[0018] Example 1: Please refer to Figure 1 The present invention provides a specific calculation method as follows: (1) Collect drilling data, geological and mining conditions data, and surface measured data of the area to be tested. Then, use the optimization algorithm to inversely derive the predicted parameters of movement and deformation, and extract the critical value of horizontal deformation of rock strata fracture. In this embodiment, the strike length is 667 meters, the dip length is 126 meters, the coal seam depth is 511 meters, the average mining thickness is 2.1 meters, and it is a near-horizontal coal seam. The predicted displacement and deformation parameters were obtained using a genetic algorithm. q =0.85, tan β =2.0, s 1= s 2= s 3= s 4=0. n We take 1.05 as an empirical value. The critical value for horizontal deformation of rock strata is taken as 1.0 mm / m, which is the critical horizontal tensile deformation value for relatively soft rock strata such as mudstone.

[0019] (2) Based on the predicted parameters obtained in step (1), the settlement of the rock strata is predicted layer by layer from the goaf upwards, where the rock strata are simplified as beams and the cross-section in the middle of the rock strata is a neutral surface. Furthermore, the specific steps of step (2) are as follows: The calculation lengths for the orientation and dip of the working face are shown in Equations (1) and (2): (1) (2) in D 3. D 1 represents the working face direction and dip length, respectively; s 1. s 2. s 3. s 4 represents the inflection point offset distance for downhill, uphill, leftward, and rightward directions, respectively; The main influence radius of the location of the neutral plane in the rock strata is calculated using the formula shown in equation (3): (3) in H Indicates the depth of mining; tan β Indicates the tangent of the main influencing angle; z Indicates the distance from the ground surface to the neutral plane of the rock strata; n This represents the main radius of influence related to lithology, and is an empirical value. r Indicates the main radius of influence of surface subsidence; Calculate the maximum surface subsidence value W 0, the calculation formula is shown in equation (4): (4) in m Indicates thickening; q Indicates the subsidence coefficient; α Indicates the dip angle of the coal seam; The expected parameters q , s 1. s 2. s 3. s 4. tan β The prediction methods include collecting mining data, constructing fitness functions, and selecting optimization algorithms; Collect mining data, including settlement data from other mines in the same area, and conduct actual data measurements and collection for the predicted mining area, including geological and mining conditions and measured data. Geological and mining conditions include mining depth, mining thickness, coal seam dip angle, strike length, and dip length. Measured data includes point number, coordinates, and subsidence value.

[0020] In some disclosures, the fitness function is constructed, and the objective function can be defined as the sum of squared errors between the predicted and measured land subsidence. The smaller the sum of squared errors, the more accurate the prediction result. in, f ( i (for individuals) i fitness value, M The number of surface measurement points. This represents the predicted amount of surface subsidence. This represents the measured amount of surface subsidence.

[0021] Genetic algorithms are selected for inversion. Based on the data inversion results, the input and output layers of the neural network are determined. The input layer should include geological and mining conditions such as mining depth, mining thickness, coal seam dip angle, strike length, dip length, etc., as well as actual surface measurement data. The output layer is the predicted parameters of movement and deformation.

[0022] Calculate the subsidence value of the main cross section with the strike of the neutral plane of the rock strata. The calculation formula is shown in equation (5): (5) in This indicates the subsidence value towards the main cross-section when fully exploited; This indicates the subsidence value of the main cross-section when it is fully mined; Indicates the direction towards the point on the main cross-section. coordinate; This indicates the maximum subsidence value of the main cross-section when it is fully mined.

[0023] Based on the settlement prediction results, the maximum horizontal deformation of the upper and lower surfaces of the rock strata on the strike main section is calculated; Furthermore, the specific steps of step (3) are as follows: (31) Calculate the bending section modulus of the rock strata. The calculation formula is shown in equation (6): (6) in J Represents the moment of inertia; Z Indicates the thickness of the rock strata; The bending moment is calculated using the formula shown in equation (7): (7) in E Indicates the elastic modulus; The horizontal deformation of the upper and lower surfaces of the rock strata is calculated using the formula shown in equation (8): (8) Based on the above formula, the calculation results of the maximum horizontal deformation of the rock strata above the goaf are shown in Table 1: Table 1 Maximum horizontal deformation of the upper and lower surfaces of the rock strata (4) Compare the maximum horizontal deformation obtained in step (3) with the critical value of horizontal deformation of rock strata fracture. If the maximum horizontal deformation obtained exceeds the critical value, proceed to step (2) and increment the layer number by one. If it does not exceed the critical value, proceed to step (5). (5) Accumulate the thickness of the fractured rock layers to determine the development height of the water-conducting fracture zone.

[0024] In this embodiment, the predicted height of the water-conducting fracture zone according to Table 1 is 50.97 meters.

[0025] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0026] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the present invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for determining the development height of water-conducting fracture zones based on the prediction of subsidence within rock strata, characterized in that, Includes the following steps; Step 1: Collect drilling data, geological and mining conditions data, and surface measured data of the area to be tested. Then, use an optimized algorithm to inversely derive the predicted parameters of movement and deformation, and extract the critical value of horizontal deformation of rock strata fracture. Step 2: Based on the predicted parameters obtained in Step 1, predict the internal subsidence of the rock strata layer by layer from the goaf upwards; Step 3: Based on the settlement prediction results, calculate the maximum horizontal deformation of the upper and lower surfaces of the rock strata on the strike main cross section; Step 4: Compare the maximum horizontal deformation obtained in Step 3 with the critical value of horizontal deformation of the rock strata fracture. If the maximum horizontal deformation exceeds the critical value, proceed to Step 2 and increment the layer number by one. If it does not exceed the critical value, proceed to Step 5. Step 5: Accumulate the thickness of the fractured rock layers to determine the development height of the water-conducting fracture zone; The drilling data in step one includes cumulative depth, rock layer thickness, and lithological description; the geological and mining condition data in step one includes mining depth, mining thickness, coal seam dip angle, strike length, and dip length; and the surface measured data in step one includes point number, coordinates, and subsidence value. The specific calculation steps for step two are as follows: The calculation lengths for the orientation and dip of the working face are shown in Equations (1) and (2): (1) (2) in, D 3. D 1 represents the working face direction and dip length, respectively; s 1. s 2. s 3. s 4 represents the offset distance of the turning point in the downhill direction, uphill direction, leftward direction, and rightward direction, respectively; The rock strata are simplified as beams, and the cross-section in the middle of the rock strata is the neutral plane. The main influence radius of the position of the neutral plane of the rock strata is calculated. The calculation formula is shown in Equation (3). (3) in, H Indicates the depth of mining; tan β Indicates the tangent of the main influencing angle; z Indicates the distance from the ground surface to the neutral plane of the rock strata; n This represents the main radius of influence related to lithology, and is an empirical value. r Indicates the main radius of influence of surface subsidence; Calculate the maximum surface subsidence value W 0, the calculation formula is shown in equation (4): (4) in, m Indicates thickening; q Indicates the subsidence coefficient; α Indicates the dip angle of the ore layer; Calculate the subsidence value of the main cross section with the strike of the neutral plane of the rock strata. The calculation formula is shown in equation (5): (5) in, This indicates the subsidence value towards the main cross-section when fully exploited; This indicates the subsidence value of the main cross-section when it is fully mined; Indicates the direction towards the point on the main cross-section. coordinate; This indicates the maximum subsidence value of the main cross-section when the mining is fully initiated. The specific steps of step three are as follows: The flexural section modulus of the rock strata is calculated using the formula shown in equation (6): (6) in, J Z represents the moment of inertia; Z represents the thickness of the rock strata. The bending moment is calculated using the formula shown in equation (7): (7) Where E represents the elastic modulus; The horizontal deformation of the upper and lower surfaces of the rock strata is calculated using the formula shown in equation (8): (8)。 2. The method for determining the development height of water-conducting fracture zones based on the predicted subsidence within rock strata according to claim 1, characterized in that, The expected parameters q , s 1. s 2. s 3. s 4. tan β The prediction methods include collecting mining data, constructing fitness functions, and selecting optimization algorithms; Collect mining data, collect settlement data from other mines in the same area, and conduct actual data measurements and collect data on the areas to be mined, including geological mining conditions and measured data.

3. The method for determining the development height of water-conducting fracture zones based on the predicted subsidence within rock strata according to claim 2, characterized in that, The fitness function is constructed by defining the objective function as the sum of squared errors between the predicted and measured land subsidence. The smaller the sum of squared errors, the more accurate the prediction result. in, f ( i (for individuals) i fitness value, M The number of surface measurement points. This represents the predicted amount of surface subsidence. This represents the measured amount of surface subsidence.

4. The method for determining the development height of water-conducting fracture zones based on the predicted subsidence within rock strata according to claim 2, characterized in that, The selection optimization algorithm selects a suitable neural network architecture and determines the input and output layers of the neural network based on the data inversion results. The input layer includes geological and mining conditions and actual surface measurement data; the output layer is the predicted parameters of movement and deformation.

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