Coal mine water exploration drill simulation method based on Monte Carlo method

Abstract

The invention provides a coal mine water exploration drill simulation method based on a Monte Carlo method. The heterogeneity and anisotropy characteristics of the underground coal seam of the coal mine can be simulated more truly, the accuracy and reliability of the simulation result of the water exploration drill are remarkably improved, and the risk of water inrush accidents caused by geological condition prediction deviation is reduced.

Description

Technical Field

[0001] This invention relates to the field of coal mine water exploration drilling simulation, and in particular to a coal mine water exploration drilling simulation method based on the Monte Carlo method. Background Technology

[0002] Coal mine water exploration drills are key equipment in safe coal mining and are widely used in the field of underground water hazard detection and prevention.

[0003] As coal mining in my country progresses towards deeper and more complex geological conditions, the role of water exploration drilling technology in ensuring safe mine production is becoming increasingly prominent. Related technologies typically employ a collaborative approach involving 3D modeling, material property definition, and finite element simulation to construct a simulation system for the interaction between the water exploration drill and the coal seam. Specifically, this technology encompasses the entire process from geological modeling and drilling parameter setting to mechanical response analysis, including key aspects such as drill rod stress, coal and rock fracturing, and water pressure permeability. However, existing simulation methods for coal mine water exploration drills often define coal seam material properties using homogeneous materials or homogeneous layered superposition models, failing to fully reflect the random distribution characteristics of heterogeneous structures such as interbedded rock layers and pores within the coal seam. Consequently, traditional methods exhibit significant deviations in simulating the mechanical behavior and seepage characteristics of coal seams, especially in coal seams with a high proportion of interbedded rock layers, where the difference between simulation results and actual drilling data can exceed 25%. This affects the accuracy of water hazard risk assessment and increases the uncertainty and safety risks of downhole experiments. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the first objective of this invention is to propose a simulation method for coal mine water exploration drilling based on the Monte Carlo method.

[0006] The second objective of this invention is to propose a simulation device for coal mine water exploration drilling based on the Monte Carlo method.

[0007] To achieve the above objectives, a first aspect of the present invention proposes a simulation method for water exploration drilling in coal mines based on the Monte Carlo method, comprising: S1, Based on the geological conditions of underground coal mines, set the generation parameters of heterogeneous features in coal seams, including feature type, size range, distribution ratio and orientation angle; S2, using three independent random functions to control the position, size and orientation of the heterogeneous feature body respectively, generating the irregular structure of intercalation layer and pores, and using a spatial interference judgment algorithm to detect the interference between the newly generated structure and the existing structure. If interference occurs, the structure is regenerated. S3, embedding the generated heterogeneous feature body model into the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model conforming to actual geological conditions; S4, importing the heterogeneous coal seam simulation model into finite element simulation software, realizing automatic mapping of model parameters through a script interface, and completing finite element simulation analysis of the cutting process of the water exploration drill.

[0008] In an embodiment of the present application, the setting of the generation parameters of the heterogeneous feature body in the coal seam based on the underground geological conditions of the coal mine further comprises: S11, determining the feature body type to be one or more combinations of a dirt band, a gas hole or a water pocket according to logging data and a geological exploration report; S12, setting the feature body size range to be 0.5 cm to 50 cm, and dynamically adjusting the range according to the depth of the coal seam and the lithological change.

[0009] In an embodiment of the present application, the generation of the heterogeneous feature body using three independent random functions to respectively control the position, size and orientation of the heterogeneous feature body further comprises: S21, randomly generating feature body center point coordinates through a function f(r1, r2) to simulate the spatial distribution of the feature body in the coal seam; S22, generating a curve connecting two center points through a function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular shape of the dirt band or the gas hole.

[0010] In an embodiment of the present application, the embedding of the generated heterogeneous feature body model into the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model conforming to actual geological conditions further comprises: S31, using Boolean operation to fuse the heterogeneous feature body with the basic model of the coal seam to ensure geometric continuity of the model; S32, automatically assigning corresponding material properties and mechanical parameters according to the feature body type to improve the physical authenticity of the simulation model.

[0011] In an embodiment of the present application, the importing of the heterogeneous coal seam simulation model into finite element simulation software, realizing automatic mapping of model parameters through a script interface, and completing finite element simulation analysis of the cutting process of the water exploration drill further comprises: S41, automatically identifying and mapping the contact boundary between the heterogeneous feature body and the basic model of the coal seam through a script; S42, dynamically adjusting the finite element grid density according to the feature body distribution to improve calculation accuracy and efficiency.

[0012] In an embodiment of the present application, it further comprises: S5, generating drilling path optimization suggestions according to preset geological conditions and simulation results, including adjustment strategies of drilling pressure, rotating speed and feeding speed; S6, feeding the optimized drilling parameters to the finite element simulation software for multiple rounds of iterative simulation to verify the safety and feasibility of the drilling scheme.

[0013] To achieve the above purpose, the second aspect of the present application provides a coal mine water exploration drill simulation device based on the Monte Carlo method, comprising: A parameter setting module is configured to set generation parameters of a heterogeneous feature body in a coal seam based on underground geological conditions of a coal mine, the parameters including feature body type, size range, distribution ratio and azimuth angle; A structure generation module is configured to generate a special-shaped structure of a dirt band and a gas hole by using three independent random functions to control the position, size and orientation of the heterogeneous feature body, and detect the interference between the newly generated structure and the existing structure by a spatial interference judgment algorithm, and regenerate if interference occurs; A model embedding module is configured to embed the generated heterogeneous feature body model into a three-dimensional basic model of a coal seam to form a heterogeneous coal seam simulation model that conforms to actual geological conditions; A simulation analysis module is configured to import the heterogeneous coal seam simulation model into a finite element simulation software, realize automatic mapping of model parameters through a script interface, and complete finite element simulation analysis of the water exploration drill cutting process.

[0014] The method and device of the embodiments of the present application can realistically simulate the heterogeneity and anisotropy characteristics of the coal seam in a coal mine, significantly improve the accuracy and reliability of the simulation results of the water exploration drill, and reduce the prediction deviation.

[0015] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter in the description of the application. BRIEF DESCRIPTION OF DRAWINGS

[0016] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description, taken in conjunction with the accompanying drawings, in which: Figure 1 is a flowchart of a coal mine water exploration drill simulation method based on the Monte Carlo method according to an embodiment of the present application; Figure 2 is a flowchart of a coal mine water exploration drill simulation method based on the Monte Carlo method according to an embodiment of the present application; Figure 3 is a schematic diagram of the Monte Carlo method according to an embodiment of the present application; Figure 4 is a schematic diagram of the Monte Carlo method according to an embodiment of the present application; Figure 5 is a Monte Carlo generated pore schematic diagram according to an embodiment of the present application; Figure 6 is a Monte Carlo coal seam schematic diagram according to an embodiment of the present application; Figure 7 is a structure diagram of a Monte Carlo method based coal mine water exploration drill simulation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0018] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0019] The Monte Carlo method based coal mine water exploration drill simulation method and device according to the embodiments of the present application will be described below with reference to the accompanying drawings.

[0020] Embodiment 1 Figure 1 is a flowchart of a Monte Carlo method based coal mine water exploration drill simulation method according to an embodiment of the present application, as shown in Figure 1 , including: as shown in Figure 1 , the Monte Carlo method based coal mine water exploration drill simulation method includes the following steps: S1, setting generation parameters of non-homogeneous feature bodies in the coal seam based on the underground geological conditions of the coal mine, the parameters including feature body type, size range, distribution proportion and azimuth angle.

[0021] Specifically, the step of "setting generation parameters of non-homogeneous feature bodies in the coal seam based on the underground geological conditions of the coal mine" is a key link for realizing real non-homogeneous modeling of the coal seam in the present application. The technical implementation principle is based on the Monte Carlo random distribution method, combined with the needs of geostatistics and finite element simulation, and the non-homogeneous feature bodies such as coal gangue layers and pores in the coal seam are parameterized modeled. In some implementations, this step defines parameters such as feature body type (such as coal gangue, pore), size range (such as length, diameter), distribution proportion (such as volume ratio) and azimuth angle (such as deflection angle a, b) to construct a coal seam non-homogeneous structure model that conforms to the actual geological conditions.

[0022] This step first determines the type and distribution of the heterogeneous feature body in the coal seam according to geological exploration data or logging data. For example, coal gangue is usually irregular ellipsoidal or columnar, and its size range can be set to 0.1m~1.5m in length and 0.05m~0.5m in diameter; the gas hole is usually spherical or spherical, and the diameter range can be set to 0.01m~0.1m. The distribution ratio is set according to the coal seam gangue ratio or porosity, such as the volume ratio of coal gangue can be set to 5%~20%, and the gas hole ratio can be set to 1%~10%. The azimuth angles α and β represent the deflection angles of the feature body in the X-Y plane and the Y-Z plane, respectively, and their value range is usually 0°~360° to simulate the anisotropic distribution of the feature body in the coal seam.

[0023] This step needs to meet the input requirements of the finite element simulation software (such as Abaqus) for model geometry and material properties. For example, the elastic modulus, Poisson's ratio, and compressive strength of coal gangue and coal matrix need to be set according to actual coal rock mechanics test data to ensure the physical consistency of the simulation model. In addition, the generation of the feature body needs to meet the non-interference condition, that is, during the random generation process, geometric interference detection algorithms (such as bounding box detection and distance threshold judgment) are used to ensure that each feature body does not overlap or nest, thereby improving the geometric rationality and simulation stability of the model.

[0024] This step is widely applicable to simulation analysis scenarios such as coal mine water exploration drilling path planning, drilling parameter optimization, and drill bit wear prediction. For example, when simulating the water exploration drill bit passing through the coal body containing gangue layers, by setting different gangue sizes and distribution ratios, the change of drilling resistance and the stress state of the drill bit can be more realistically reflected, providing data support for drilling strategy adjustment.

[0025] This step controls the generation of heterogeneous feature bodies through parameterization, significantly improving the geological authenticity and simulation accuracy of the coal seam model, solving the problem that traditional homogeneous or layered superposition models cannot reflect the complexity of the internal structure of the coal seam, providing a more reliable geological basis for water exploration drilling simulation, and having good engineering practical value and innovation.

[0026] Further, S1 includes: S11, determining the feature body type to be one or more combinations of gangue layer, gas hole, or water bag according to logging data and geological exploration reports.

[0027] Specifically, in some implementations, determining the feature body type as one or more combinations of interbedded rock layers, pores, or water pockets based on well logging data and geological exploration reports is a key modeling step in the coal mine water exploration drilling simulation method based on the Monte Carlo method of this invention. Its technical implementation principle is based on a combination of geostatistics and stochastic modeling, aiming to improve the matching degree between the heterogeneity of the coal seam model and the actual geological features. This step first identifies anomalous response segments in the coal seam using well logging curves (such as natural gamma, resistivity, sonic transit time, etc.), and then classifies and identifies the heterogeneous structure inside the coal seam by combining parameters from the geological exploration report regarding coal-rock assemblages, interbedded rock thickness, fracture development degree, and porosity. Intercalated rock layers typically exhibit high density and high elastic modulus lithological intercalations, with a thickness generally greater than 1 cm, and show obvious abrupt changes in well logging data; vesicles are mainly identified by parameters such as porosity and permeability, and their distribution is random and locally clustered; water pockets are identified by characteristics such as low resistivity and high sonic transit time, and are usually associated with fractured areas or fault zones.

[0028] Optionally, this step introduces a variogram from geostatistics to model the spatial continuity of the interbedded rock layers, sets a distribution probability threshold for the interbedded rock layers (e.g., 0.1~0.3), and performs spatial interpolation based on coal seam thickness (generally 1~5m) and borehole spacing (typically 10~30m) to determine the distribution type and combination of feature volumes in the three-dimensional coal seam model. Furthermore, this step provides input parameters for the subsequent Monte Carlo random distribution algorithm, such as the proportion of interbedded rock layers (generally 5%~20%), pore density (0.5~2 pores / m³), and water pocket volume fraction (0.01~0.1), thereby achieving high-fidelity simulation of real geological conditions in the simulation model.

[0029] In practical applications, this step is mainly used to construct coal seam models with realistic geological characteristics, suitable for water exploration drilling path planning and risk assessment under complex hydrogeological conditions. By accurately identifying the types of feature bodies, the prediction accuracy of coal seam mechanical response and seepage characteristics in finite element simulation can be significantly improved, providing a reliable basis for drilling parameter optimization (such as drilling pressure and rotation speed), thereby reducing the risk of underground water inrush accidents and improving the level of safe production in coal mines.

[0030] S12, the size range of the feature body is set to 0.5cm to 50cm, and this range is dynamically adjusted according to the coal seam depth and lithological changes.

[0031] Specifically, in some implementations, the characteristic body size range is set to 0.5 cm to 50 cm, and this range is dynamically adjusted according to the depth and lithology of the coal seam. This is a key step in the coal mine water exploration drill simulation method based on the Monte Carlo method, aiming to improve the accuracy and adaptability of the heterogeneous structure modeling of the coal seam. This step simulates the real underground geological conditions by randomly generating heterogeneous features such as coal gangue and pores in the coal seam model, thereby improving the reliability of the finite element simulation results.

[0032] This step first builds a basic model of the coal seam in a three-dimensional modeling software, and then randomly generates characteristic bodies inside the model through a Monte Carlo script. Each characteristic body is defined by two points P and Q as control points for generating irregular coal gangue or pores. The size range of the characteristic body is controlled by random functions f(r1, r2) and f(r3, r4) respectively, ensuring that its diameter is between 0.5 cm and 50 cm. In addition, the random function f(X1, Y1, Z1, X2, Y2, Z2) is used to generate a connection curve between the two points, thereby constructing a coal gangue or pore structure with a real shape. During the generation process, the system will judge in real time whether the newly generated characteristic body interferes with the existing structure, and if there is interference, it will be regenerated to ensure the geometric rationality of the model.

[0033] The setting of the characteristic body size range is based on coal mine geological exploration data and lithology analysis results. For example, in shallow coal seams (<200 m), the size of coal gangue is usually small, and the range is set to 0.5 cm~10 cm; while in deep coal seams (>500 m), due to the large tectonic stress, the size of coal gangue may increase to 20 cm~50 cm. In addition, the generation proportion of the characteristic body needs to meet the statistical distribution characteristics of the coal seam with interburden and fracture development, usually controlled between 5%~30%, the specific value is adjusted according to the type of coal seam (such as sandy coal, argillaceous coal) and the complexity of geological structure.

[0034] This step is widely applicable to the finite element simulation modeling of coal mine water exploration drilling, especially in simulating the drilling process under complex geological conditions such as fault fracture zone, goaf, and water-bearing fracture development area. By dynamically adjusting the size range of the characteristic body, the mechanical response and seepage characteristics of the coal seam at different depths can be more realistically reflected, providing data support for drilling parameter optimization.

[0035] This step effectively overcomes the defect that traditional homogeneous or layered superposition models cannot reflect the heterogeneity of the coal seam by introducing a dynamic size adjustment mechanism. Its innovation lies in combining geological statistics with Monte Carlo random generation algorithm to achieve high-precision modeling of the coal seam structure, thereby significantly improving the engineering applicability and prediction accuracy of the water exploration drill simulation results.

[0036] S2, generate the heterogeneous structure of the dirt band and the air hole by using three independent random functions to control the position, size and orientation of the heterogeneous features respectively, and detect the interference between the newly generated structure and the existing structure by a spatial interference judgment algorithm, and if interference occurs, regenerate.

[0037] Specifically, in some implementations, step S330 generates the heterogeneous structure of the coal seam by introducing three independent random functions to control the position, size and orientation of the heterogeneous features (such as the dirt band and the air hole) respectively. This step is based on the random sampling principle of the Monte Carlo method and combines a spatial interference judgment algorithm to ensure that the generated structure does not overlap or interfere with the existing structure in three-dimensional space, thereby improving the geometric authenticity and physical simulation accuracy of the coal seam model.

[0038] First, define two base points P and Q as the starting point and the ending point of the generation of the dirt band or the air hole. Control the distance r between the two points by a random function f(r1, r2) to define the size of the structure; a random function f(X1, Y1, Z1, X2, Y2, Z2) is used to generate the coordinates of the two points in three-dimensional space to control the position distribution of the structure; and a random function f(a, b) is used to control the azimuth a and the deflection angle b of the structure to realize the random rotation of the structure in space. Further, the size and position of the air hole are generated by f(r3, r4) and f(X3, Y3, Z3, X4, Y4, Z4) respectively to make it present a non-uniform and irregular distribution in the coal seam.

[0039] The input parameters of the random function need to satisfy certain statistical distribution characteristics. For example, the size r1, r2 of the dirt band can follow a normal distribution N(μ=5cm, σ=2cm), the position coordinates (X1, Y1, Z1) and (X2, Y2, Z2) are uniformly randomly sampled in the coal seam modeling space (such as 10m x 10m x 3m), and the azimuth a and b are randomly generated in the range of [0°, 360°]. The interference judgment algorithm uses the AABB (Axis-Aligned Bounding Box) or OBB (Oriented Bounding Box) collision detection mechanism with a minimum detection accuracy of 0.1m to ensure that the newly generated structure does not overlap with the existing structure in space.

[0040] This step is suitable for finite element simulation modeling of coal mine water exploration drilling, especially when simulating the heterogeneous distribution of dirt bands and air holes in the coal seam, it can effectively improve the restoration degree of the model to the actual geological conditions. For example, when simulating fault fracture zones or old goaf water areas, this method can generate heterogeneous bodies with complex geometric characteristics, providing more reliable input for drilling path planning and water pressure distribution prediction.

[0041] The technical effect of this step is that by introducing a multi-dimensional random function and an interference detection mechanism, a high-precision, non-repetitive, irregular distribution of the gangue layer and the air hole is realized, the heterogeneous expression capability of the coal seam model is significantly improved, and the accuracy and engineering applicability of the water exploration drill simulation result are enhanced.

[0042] Further, S2 includes: S21, randomly generating the feature body center point coordinates by the function f(r1, r2) to simulate the spatial distribution thereof in the coal seam.

[0043] Specifically, in step S330, the center point coordinates of the feature body (such as coal gangue or air hole) are randomly generated by the function f(r1, r2), which is one of the core links for realizing the heterogeneous modeling of the coal seam. This step is based on the Monte Carlo random simulation method and aims to generate an irregular structure in the three-dimensional coal seam model that conforms to the actual geological distribution characteristics, thereby improving the authenticity and reliability in the water exploration drill simulation process.

[0044] In some implementations, the function f(r1, r2) adopts a random number generation algorithm with uniform distribution or normal distribution, where r1 and r2 are independent random variables in the interval [0, 1], which are respectively used to control the transverse coordinates of the feature body in the X-Y plane. By mapping the random variables to the three-dimensional space range of the coal seam model, the random distribution of the feature body center point in the coal seam can be realized. Further, to enhance the heterogeneity of the geological features, a spatial distribution weight function can be introduced in the function, such as a variogram or Kriging interpolation based on geological statistics, to simulate the aggregation or dispersion distribution characteristics of the coal gangue in the coal seam.

[0045] At the parameter index level, the input parameters of this function usually include the boundary coordinates of the coal seam model (such as Xmin, Xmax, Ymin, Ymax, Zmin, Zmax), the minimum and maximum distances of the feature body (such as ≥0.5m), the generation density of the feature body (such as 0.1~0.5 per cubic meter), and the coal gangue and air hole proportion set by the geological conditions (such as coal gangue proportion 10%~30%, air hole proportion 5%~15%). The output result is a set of center point coordinates of the feature body, which is used for subsequent geometric modeling and finite element meshing.

[0046] This step is usually embedded in the Python script of the Abaqus simulation platform, and communicates with the Abaqus API interface to realize the automatic random generation and model integration of the feature body. When simulating complex geological structures such as fault fracture zones, gangue layers, or gas-containing coal seams, this method can effectively reproduce the spatial distribution characteristics of the coal gangue and air hole in the coal seam, thereby improving the mechanical response and seepage simulation accuracy in the drilling process.

[0047] This step achieves non-uniform distribution of feature body center points by introducing a random function f(r1, r2), overcoming the problem of insufficient description of coal seam heterogeneity in traditional homogeneous or layered superposition models, and significantly improving the geological authenticity and prediction ability of the water exploration drill simulation model.

[0048] S22, a curve connecting the two center points is generated by a function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular morphology of the parting layer or the air hole.

[0049] Specifically, in step S330, a curve connecting two center points P(X1, Y1, Z1) and Q(X2, Y2, Z2) is generated by a function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular morphology of the parting layer or the air hole, which is one of the core technical links of the coal seam heterogeneity modeling based on the Monte Carlo method. The function is essentially a parametric curve generator, which is technically implemented based on the method of random sampling combined with geometric interpolation to ensure that the generated coal gangue or air hole has natural and irregular distribution characteristics in three-dimensional space.

[0050] In some implementations, the function can use spline interpolation (such as cubic B-spline or NURBS curve) or random perturbation linear interpolation to generate a curve path with random offset based on the coordinates of P and Q. Specifically, the function first calculates the straight line vector between the two points, and introduces a random perturbation term based on the vector, and the amplitude of the perturbation term is controlled by a random function f(r1, r2), where r1 and r2 are random numbers uniformly distributed in the interval [0, 1], used to adjust the curvature and local morphology of the curve. In addition, the deflection direction of the curve is controlled by angles a and β, a is the rotation angle of the curve in the XOY plane, and β is the inclination angle of the curve in the YOZ plane, both of which are generated by a random function in a predetermined range (such as a∈[0°, 360°], β∈[0°, 90°]), so as to realize the random orientation of the coal gangue or air hole in three-dimensional space.

[0051] Further, after generating the curve, it is used as the boundary profile of the parting layer or the air hole, and two end points generated by f(r3, r4) are combined to construct a three-dimensional solid model by Boolean operation or mesh fusion. This process needs to satisfy the geometric interference judgment (step S340), that is, to ensure that the newly generated coal gangue or air hole does not overlap or penetrate the existing structure, so as to meet the spatial arrangement rules of the real geological structure.

[0052] This step has important value in coal mine water exploration drilling simulation. By introducing irregular curve structure, the heterogeneity and anisotropy characteristics of the coal seam model are significantly improved, thereby improving the accuracy of drilling path, stress distribution and seepage simulation in finite element simulation. The method is applicable to mainstream finite element simulation platforms such as Abaqus and COMSOL, and has good universality and scalability.

[0053] S3, the generated heterogeneous feature model is embedded in the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model conforming to the actual geological conditions.

[0054] Specifically, the generated heterogeneous feature model is embedded in the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model conforming to the actual geological conditions, which is a key step in the present application to realize high-precision coal mine water exploration drilling simulation. This step introduces the common heterogeneous geological bodies (such as coal gangue, air holes, fissures, etc.) in the coal seam into the finite element model of the coal seam in a random distribution manner, thereby improving the restoration degree and prediction ability of the simulation model to the real geological environment.

[0055] In terms of technical implementation, this step is based on the Monte Carlo random distribution method and interacts with finite element simulation platforms such as Abaqus by writing a custom script. First, a basic geometric model of the coal seam is constructed in a three-dimensional modeling software, usually represented as a block or layered structure, and its size is set according to the actual underground roadway layout and coal seam thickness. Then, coal gangue and air holes and other heterogeneous bodies are randomly generated in the coal seam model by the Monte Carlo method. Specifically, define two random points P and Q as control points of the heterogeneous body, control its size parameters through random functions f(r1, r2) and f(r3, r4), control its deflection direction through azimuth angles α and β, and finally generate a connecting curve through the function f(X1, Y1, Z1, X2, Y2, Z2) to construct the three-dimensional geometric features of the irregular coal gangue or air hole. During the generation process, the system will judge in real time whether the newly generated heterogeneous body interferes with the existing structure, and if there is interference, it will be regenerated to ensure the geometric reasonableness of the model.

[0056] The generation of coal gangue and air holes needs to set key parameters according to actual geological survey data, such as coal gangue proportion (usually 5%~20%), air hole density (10~50 / m³), size range (diameter 1~10cm), distribution direction (α, β angle range 0°~360°), shape complexity (ellipsoid, irregular polyhedron, etc.). These parameters can be set according to the requirements of GB / T 25217.1-2010 "Technical Code for Water Exploration in Coal Mines" for coal seam structure and hydrogeological conditions to ensure that the model conforms to the actual engineering.

[0057] This step is widely used in the finite element simulation analysis of coal mine water exploration drilling, especially in simulating the interaction between the drill bit and the coal seam heterogeneous body, the stability evaluation of the drilling path, and the water pressure mutation warning during drilling. By constructing a heterogeneous coal seam model, the drilling resistance, coal and rock breaking behavior, and seepage characteristics can be more realistically reflected, providing data support for drilling parameter optimization (such as rotation speed and drilling pressure).

[0058] The technical effect of this step is to significantly improve the heterogeneous expression ability of the simulation model, overcoming the limitations of traditional homogeneous or layered superposition models in mechanical response and seepage simulation. By introducing randomly distributed coal gangue and pores, the model can more accurately predict the mechanical failure behavior and water hazard risk during drilling, thereby improving the reliability and engineering guidance value of coal mine water exploration drilling simulation analysis. Further, this method has good scalability and can be adapted to different geological conditions and simulation platforms, with high practicality and innovation.

[0059] Further, S3 includes: S31, adopting Boolean operation to fuse the heterogeneous feature body with the coal seam basic model, ensuring the geometric continuity of the model.

[0060] Specifically, in the step of the present application, the Boolean operation is adopted to fuse the heterogeneous feature body (such as coal gangue, pores, etc.) with the coal seam basic model, which is the key link to realize high-precision coal mine water exploration drilling finite element simulation. The core of this step is to topologically connect the randomly generated heterogeneous body with the main model of the coal seam through geometric modeling technology, ensuring the continuity of the model in geometric structure and the integrity of physical properties.

[0061] In some implementations, the fusion process is based on the ABAQUS software platform, which calls its geometric modeling interface (Part Module) through Python scripts to realize the Boolean operation of the coal seam basic model and the heterogeneous feature body. Specifically, the heterogeneous feature body is randomly generated by the Monte Carlo method, its shape is defined by two control points P, Q, and its size, position, and deflection angles α and β are controlled by random functions f(r1, r2), f(X1,Y1,Z1,X2,Y2,Z2), etc., so as to generate irregular coal gangue or pores with real geological characteristics. During the generation process, the system will detect the interference between the newly generated body and the existing model in real time, and if interference occurs, a re-generation mechanism will be triggered to ensure the reasonableness of the model geometry.

[0062] The key parameters involved in this step include: the volume ratio of coal gangue and air holes (usually set to 5%-20%, adjusted according to actual geological conditions), the minimum and maximum size of the feature body (such as diameter range of 1cm-10cm), the value range of deflection angles a and b (generally 0°-360°), the distribution density of random function (such as Poisson distribution or uniform distribution), etc. The setting of these parameters needs to meet the modeling requirements of coal seam heterogeneity in the "Coal Mine Geological Modeling Technical Specification" (MT / T 1049-2007) to improve the engineering applicability of the model.

[0063] This step is mainly used to build a coal seam model with a real geological structure, providing a reliable geometric and material basis for subsequent stress-strain analysis, fracture propagation simulation, and water pressure response prediction during water exploration drilling. The model fused by Boolean operation can maintain continuous mesh division boundaries, avoiding finite element solution failure or result distortion caused by geometric discontinuity.

[0064] This step significantly improves the heterogeneity expression capability of the coal seam model, making the simulation results more close to the actual underground coal seam structure, thereby enhancing the scientificity and accuracy of water exploration drilling path planning and parameter optimization, and providing strong digital twin support for coal mine water disaster prevention.

[0065] S32, automatically assigning corresponding material properties and mechanical parameters according to the feature body type to improve the physical reality of the simulation model.

[0066] Specifically, this step "automatically assigning corresponding material properties and mechanical parameters according to the feature body type" is a key link in the coal mine water exploration drilling simulation method based on the Monte Carlo method, aiming to improve the physical reality of the finite element simulation model for the heterogeneous structure of the coal seam. In some implementations, this step identifies the randomly generated feature bodies (such as coal gangue, air holes, etc.) in the coal seam model and automatically assigns corresponding material properties and mechanical parameters according to their types, thereby constructing a simulation environment closer to the actual geological conditions.

[0067] This step relies on the heterogeneous feature body model generated by the Monte Carlo method. In step S300, three independent random functions are used to control the position, size, and orientation of the feature body. For example, the random function f(r1, r2) is used to generate the initial radius range of the feature body (such as r1=0.5cm, r2=3cm), the function f(X1, Y1, Z1, X2, Y2, Z2) is used to determine the coordinate distribution of the feature body in three-dimensional space, and angles a and b are used to control its deflection direction (such as a∈[0°, 360°], b∈[0°, 90°]). After the generation of the feature body, the system uses interference judgment algorithm (such as Euclidean distance detection) to ensure that it does not overlap or penetrate in the coal seam, thereby ensuring the geometric reasonableness of the model.

[0068] This step involves the setting of various material properties, including but not limited to Young's modulus (E), Poisson's ratio (v), compressive strength (σ_c), tensile strength (σ_t), and permeability coefficient (k). For example, the Young's modulus of coal gangue is usually between 10-30 GPa, while that of coal body is in the range of 2-8 GPa, and the air pores impart zero or low stiffness properties. These parameters can be dynamically adjusted according to different geological conditions (such as water-bearing sandstone, fault fracture zone) to meet the coal seam parameter proportion requirements set in S400 (such as coal gangue proportion of 10%-30%, air pore proportion of 5%-15%).

[0069] This step is widely used in the finite element simulation of coal mine water exploration drilling, especially in the simulation of the mechanical response analysis of heterogeneous coal seams during drilling. By automatically assigning material properties, the cutting resistance of the drill bit at different coal-rock interfaces, the crack propagation path, and the water pressure penetration behavior can be effectively simulated, thereby optimizing drilling parameters (such as rotation speed, drilling pressure) and reducing the risk of water inrush accidents.

[0070] The technical effect of this step is to significantly improve the physical authenticity and prediction accuracy of the simulation model. By introducing an automatic matching mechanism between feature body types and material properties, errors caused by traditional homogenization modeling are avoided, making the simulation results more close to the actual underground working conditions, providing reliable data support for the design and safety evaluation of coal mine water exploration drilling.

[0071] S4, importing the heterogeneous coal seam simulation model into the finite element simulation software, realizing automatic mapping of model parameters through a script interface, and completing the finite element simulation analysis of the cutting process of the water exploration drill.

[0072] Specifically, in some implementations, the step "importing the heterogeneous coal seam simulation model into the finite element simulation software, realizing automatic mapping of model parameters through a script interface, and completing the finite element simulation analysis of the cutting process of the water exploration drill" is the key link in the present technical solution for realizing high-precision and high-efficiency simulation analysis of coal mine water exploration drilling. This step imports the three-dimensional model of the heterogeneous coal seam generated based on the Monte Carlo method into the finite element simulation platform (such as Abaqus), and uses a script interface (Scripting Interface) to realize automatic mapping of the material properties, geometric parameters, and finite element unit properties of the heterogeneous bodies such as coal gangue and air pores in the model, thereby constructing a simulation environment that conforms to the actual geological conditions.

[0073] This step first interacts with Abaqus through a Python script, calling the API interface of its CAE module to mesh the coal seam geometry model exported from a three-dimensional modeling software such as SolidWorks (usually in STEP or IGES format). Subsequently, the script identifies non-homogeneous regions in the model one by one based on the coal gangue and pore distribution data generated by the Monte Carlo method, and maps them as different material domains or material property groups (Material Assignment) in Abaqus. During the mapping process, the script matches the randomly generated coal gangue and pore positions with the finite element mesh nodes through coordinate matching algorithms such as K-D trees or nearest neighbor search, ensuring that the spatial distribution of non-homogeneous bodies is consistent with the actual geological characteristics.

[0074] This step involves multiple key parameters, including the volume percentage of coal gangue and pores (usually set to 5%~30%), size distribution range (diameter range 1cm~10cm), shape parameters (ellipticity, aspect ratio), spatial distribution density (number of non-homogeneous bodies per unit volume), etc. In addition, material property parameters such as Young's modulus, Poisson's ratio, compressive strength, and tensile strength need to be set to distinguish the mechanical behavior of coal bodies and non-homogeneous bodies such as gangue and pores. In Abaqus, the Cohesive Zone Model (CZM) or Drucker-Prager plasticity model is usually used to simulate the failure process of coal and rock.

[0075] This step is widely used in coal mine underground water exploration drilling path planning, drill bit wear prediction, drilling parameter optimization, etc. By introducing a heterogeneous coal seam model in simulation, the stress state and cutting behavior of the drill bit in different lithology regions (such as coal seam, gangue layer, and fracture zone) can be more realistically reflected, thereby improving the engineering guidance value of the simulation results.

[0076] This step effectively solves the simulation deviation problem caused by ignoring non-homogeneity in traditional homogeneous models in coal seam simulation. Through automatic mapping by script, not only the modeling efficiency is improved, but also the repeatability and scalability of the model are enhanced, providing reliable technical support for mechanical response analysis, drilling resistance prediction, and water hazard risk assessment in the water exploration drilling process.

[0077] Further, S4 includes: S41, automatically identifying and mapping the contact boundary between the non-homogeneous feature body and the coal seam base model through a script.

[0078] In the present invention, this step aims to achieve high-precision identification and mapping of the contact boundary between randomly generated heterogeneous features (such as coal gangue, pores, etc.) and the coal seam main body in the coal seam basic model through automation scripting technology, thereby providing accurate geometric and mechanical boundary conditions for subsequent water exploration drilling simulation. In some implementations, the script is developed based on the Python API interface of Abaqus, which realizes the automatic extraction and topological mapping of the contact surface between the heterogeneous body and the coal base in the coal seam model by calling the geometric modeling and finite element analysis modules.

[0079] This step first reads the three-dimensional geometric data of coal gangue and pores generated by the Monte Carlo method, including its position coordinates, size parameters (such as radii r1, r2, r3, r4), deflection angles α and β, etc. Subsequently, the script identifies the contact area between the heterogeneous body and the coal seam main body through Boolean operations and geometric interference detection algorithms (such as the GJK-EPA algorithm). In the contact boundary identification process, grid node adjacency relationship analysis and surface fitting techniques are used to ensure the continuity and geometric accuracy of the contact surface. Further, the script maps the identified contact boundary to the contact pair (Contact Pair) in Abaqus and sets the corresponding contact properties (such as friction coefficient μ, contact stiffness K, penalty function parameters, etc.) to meet the mechanical response requirements during water exploration drilling.

[0080] The precision of contact boundary identification is affected by key parameters such as grid density (recommended minimum element size of 1-5 mm), geometric overlap threshold between heterogeneous body and coal base (usually set to 0.1-0.5 mm), and contact algorithm iteration step (default is 0.01 mm). The friction coefficient μ is usually set according to the coal rock friction experimental data, ranging from 0.2 to 0.6, to meet the simulation requirements of the "Coal Mine Safety Regulations" (GB 3836) for friction behavior during drilling.

[0081] This step is widely used in finite element simulation of coal mine water exploration drilling, especially in simulating the interaction between the drill bit and the coal seam with gangue layers, fracture zones or pores, which can significantly improve the heterogeneous expression ability of the model and the reliability of the simulation results. By automatically identifying the contact boundary, the discontinuity problem caused by human error in traditional manual modeling is avoided, improving the modeling efficiency and simulation accuracy.

[0082] By automatically processing the contact boundary between heterogeneous features and the coal seam through the script, not only the geometric authenticity of the model is improved, but also a reliable foundation is provided for subsequent stress-strain analysis, fracture expansion simulation and water pressure response prediction during drilling, thereby enhancing the prediction ability and engineering guidance value of coal mine water exploration drilling simulation.

[0083] S42, dynamically adjust the finite element grid density according to the feature body distribution to improve the calculation accuracy and efficiency.

[0084] Specifically, the step of "dynamically adjusting the finite element grid density according to the feature body distribution to improve the calculation accuracy and efficiency" in the present application is a key link for finite element simulation optimization based on the heterogeneous coal seam model constructed by the Monte Carlo method. In some implementations, this step dynamically adjusts the grid division density of the local area in the finite element model by analyzing the spatial distribution density, geometric shape and relative position of the randomly generated coal gangue, pores and other feature bodies in the coal seam and the contact area with the drill tool, thereby effectively controlling the consumption of overall computing resources while ensuring calculation accuracy.

[0085] This step first reads the coal seam feature body distribution data generated by the Monte Carlo script in the Abaqus simulation platform, including the center coordinates, length, width, height dimensions, deflection angles a and β and other parameters of the feature bodies. Subsequently, through a self-defined script or Abaqus plug-in interface, the feature body dense areas (such as coal gangue accumulation zone, pore high incidence area) in the model are subjected to grid refinement processing, while in the feature body sparse or uniform areas, relatively coarse grid division is adopted. The grid density adjustment is usually based on the feature body volume ratio, spatial distribution gradient and proximity to the drill cutting path, etc., and is realized by using adaptive meshing algorithm (Adaptive Meshing) or local mesh refinement strategy (Local Mesh Refinement).

[0086] The threshold for grid density adjustment is usually set to trigger local mesh refinement when the feature body volume ratio exceeds 15% or the feature body spacing is less than 1 / 3 of the drill bit diameter. The grid size of the encrypted area can be set to 1 / 2 to 1 / 5 of the original grid size, for example, from 10mm to 2mm, to ensure that the stress and strain field calculation accuracy in the complex geological structure area reaches within 0.5%. At the same time, to avoid excessive encryption leading to decreased calculation efficiency, the total number of nodes in the encrypted area is controlled to be below 30% of the total number of nodes in the overall model.

[0087] This step is widely applicable to dynamic simulation in the process of coal mine water exploration drilling, especially when simulating the drill bit passing through fault fracture zone, coal gangue dense area or gas hole containing coal seam, which can significantly improve the model's ability to capture local damage behavior, seepage path and stress concentration effect. By dynamically adjusting the grid density, the calculation accuracy and solving efficiency can be effectively balanced, and it is suitable for mainstream finite element simulation platforms such as Abaqus, ANSYS, etc.

[0088] By means of the responsive grid adjustment mechanism, the adaptability of the simulation model to the non-homogeneous coal seam structure is remarkably improved, thereby improving the accuracy of the water pressure distribution, rock stratum damage mode and drilling resistance prediction in the water exploration drilling process, and providing a more reliable simulation basis for the safe mining of coal mines.

[0089] The coal mine water exploration drilling simulation method based on the Monte Carlo method in the embodiment of the application can simulate the non-homogeneous coal seam structure in a coal mine underground, improve the accuracy and reliability of the simulation result of the water exploration drilling, simplify the coal seam modeling process, and enhance the applicability and flexibility of the simulation method.

[0090] Further, it also includes: S5, generating drilling path optimization suggestions according to the preset geological conditions and the simulation result, including adjustment strategies of the drilling pressure, the rotating speed and the feeding speed.

[0091] Specifically, in some implementations, generating drilling path optimization suggestions according to the preset geological conditions and the simulation result, including adjustment strategies of the drilling pressure, the rotating speed and the feeding speed, is a key decision step in the coal mine water exploration drilling simulation method based on the Monte Carlo method. This step analyzes the non-homogeneity of the coal seam, the coal and gangue distribution, the pore structure and the water pressure change and other multi-physical field coupling data in the simulation process, combines the preset geological parameters (such as the coal seam hardness, the permeability, the gangue layer thickness proportion, the fracture development degree, etc.), constructs a mapping relationship model between the drilling parameters and the geological response, and thus realizes the dynamic optimization of the drilling path.

[0092] Firstly, based on the stress-strain field, the drill bit wear condition, the drilling resistance curve and other data output by the Abaqus simulation platform, and in combination with the non-homogeneous model of the coal seam generated by the Monte Carlo method, the high-risk areas (such as the gangue layer intensive area, the pore development zone and the water pressure mutation point) in the drilling process are identified. Subsequently, through a multi-objective optimization algorithm (such as NSGA-II and particle swarm optimization PSO), the drilling pressure (usually controlled within the range of 5~20 kN), the rotating speed (usually set as 50~200 r / min) and the feeding speed (usually 0.1~0.5 m / min) are optimized in combination, with the minimum drilling resistance, drill bit wear and water inrush risk as the objective function, and the drilling efficiency and safety as the constraint conditions.

[0093] The drilling pressure adjustment strategy is usually calculated according to the coal seam compressive strength (σ_c) and the drill bit cross-sectional area (A) to obtain the theoretical maximum bearing capacity, and is dynamically corrected in combination with the real-time simulation feedback drilling resistance (F_d); the rotating speed is optimized and configured according to the coal rock crushing characteristics (such as the brittleness index BI) and the drill bit cutting tooth wear rate (W_rate); and the feeding speed is set through the balance between the drilling speed and the drilling stability, and usually uses the ratio of the drilling speed to the drilling deviation (Δx) as the evaluation index.

[0094] The optimization strategy can be applied to the early simulation planning of water exploration drilling in coal mines, and is especially suitable for complex geological environments with multiple interburden layers, developed fissures, or large water pressure gradient changes. By simulating the drilling effect under different parameter combinations in advance in the simulation, the equipment loss and water inrush accident risk in the actual drilling process can be effectively reduced.

[0095] Further, the technical effect of this step is to significantly improve the prediction accuracy and engineering guidance value of the water exploration drilling simulation results, providing a scientific basis for real-time adjustment of drilling parameters and path optimization, thereby enhancing the safety and economy of coal mine water exploration operations.

[0096] S6, feeding back the optimized drilling parameters to the finite element simulation software for multiple rounds of iterative simulation to verify the safety and feasibility of the drilling scheme.

[0097] Specifically, feeding back the optimized drilling parameters to the finite element simulation software and performing multiple rounds of iterative simulation to verify the safety and feasibility of the drilling scheme is the core step of realizing the closed-loop optimization of coal mine water exploration drilling simulation in this application. This step inputs the key parameters involved in the drilling process (such as drilling pressure, rotation speed, feed speed, drill bit geometry parameters, etc.) into the finite element simulation platform (such as ABAQUS), generates a heterogeneous coal seam model using the Monte Carlo method, and performs multiple rounds of simulation iteration to evaluate key mechanical and seepage response indicators such as stress distribution, crack propagation, drill bit wear, and water pressure changes during drilling.

[0098] In some implementations, this step first automatically imports the optimized parameters into the ABAQUS model through a script interface as boundary conditions or load inputs. The parameter feedback mechanism is usually based on failure indicators in the previous round of simulation results (such as maximum equivalent stress exceeding coal and rock yield strength, drill bit torque fluctuation exceeding a set threshold, abnormal crack propagation rate, etc.), and adjusts the parameters by setting convergence criteria (such as maximum number of iterations, error tolerance Δ≤5%). For example, if the drill bit torque peak value reaches 1200 N·m in a simulation, and the safety threshold is 1000 N·m, the system will automatically reduce the drilling pressure or rotation speed and perform simulation calculations again.

[0099] Further, the finite element simulation used in this step needs to meet the following technical indicators: the model mesh size is controlled between 0.5~2.0 mm to ensure high-precision capture of the drill bit and coal rock contact area; the time step is set to 0.001~0.01 s to adapt to the dynamic response of high-speed rotary drilling; the material model uses a modified Mohr-Coulomb constitutive model or Drucker-Prager model, combined with the coal and gangue and pore distribution generated by Monte Carlo, to simulate the heterogeneity and anisotropy characteristics of the coal seam.

[0100] This step is widely used in the pre-design and optimization of coal mine water exploration drilling scheme, especially in the mine area with complex geological conditions, fault fracture zone or high pressure aquifer. Through multiple rounds of iterative simulation, potential drilling risk points can be effectively identified, drilling path and parameter setting can be optimized, drilling efficiency can be improved, equipment damage rate and water inrush accident probability can be reduced, and significant engineering practical value can be achieved.

[0101] The coal mine water exploration drilling simulation method based on the Monte Carlo method in the embodiment of the application generates drilling path optimization suggestions according to the preset geological conditions and simulation results, and feeds back the optimized parameters to the finite element simulation software for multiple rounds of iterative verification, thereby further improving the safety and feasibility of the water exploration drilling operation scheme, realizing closed-loop control from structural simulation to process optimization, and significantly enhancing the intelligent level of coal mine water exploration drilling design and construction.

[0102] Embodiment 2 The application distributes random numbers to coal gangue by Monte Carlo, and simulates the distribution of underground coal gangue according to the previous research. This method is simple to operate, has a high simulation degree for coal seams, and the simulation results are relatively accurate.

[0103] As shown in Figure 2 The application comprises the following steps: step S100 of three-dimensional modeling, step S200 of model conversion, step S300 of script writing, step S400 of parameter filling, and step S500 of joint simulation.

[0104] Step S100 is the basis of coal mine water exploration drilling simulation. The establishment of the water exploration drilling model and the basic model of the coal seam are realized by using a three-dimensional modeling software. Subsequently, the simulation of the coal mine water exploration drilling is realized by feeding and rotating the cutting coal seam.

[0105] Step S200 is to export the model drawn by the solidwrks software into a format that can be used by abaqus, so as to facilitate subsequent abaqus water exploration drilling simulation.

[0106] Step S300 mainly realizes the real simulation of the geological conditions in the underground coal mine by randomly distributing different numbers and sizes of air holes and coal gangue in the coal seam.

[0107] Step S400 mainly fills in different coal seam parameters according to different geological conditions of the coal seam, so as to ensure the reliability and authenticity of the finite element simulation.

[0108] Step S500 introduces the Monte Carlo script into the abaqus simulation, and realizes the purpose of cutting the coal seam by the water exploration drilling by changing the finite element boundary of the coal seam in step S200.

[0109] The implementation principle of the Monte Carlo method is shown in Figure 3 The Monte Carlo generated coal gangue is shown inFigure 4 As shown, the Monte Carlo generated air holes are as Figure 5 As shown, the Monte Carlo coal seam is as Figure 6 As shown; Monte Carlo random generation principle: Step S330 mainly uses the Monte Carlo method to randomly arrange the coal seam, and the Monte Carlo method generates the air hole and the coal gangue from step S310, S320 size definition, S330 random function distribution, S340 interference judgment, S350 coal gangue air hole generation, S360 judge whether the generation ratio meets the condition, S370 end.

[0110] Step S310 communicates with abaqus, and the abaqus control script starts execution.

[0111] Step S320 defines two points P and Q in the coal gangue or air hole, and generates special-shaped coal gangue or air hole based on P and Q.

[0112] Step S330 introduces a random function, and randomly arranges the connecting line of the coal gangue or air hole generated by the above P point and Q point, changes the deflection direction by changing the angles α and β, randomly generates a circle with the coal gangue P and Q as the origin through f(r1, r2), randomly generates a connecting curve between the two circles through f(X1, Y1, Z1, X2, Y2, Z2), and constructs a randomly distributed coal gangue through the above three random functions. Change the deflection direction by changing the angles α and β, randomly generate a circle with the coal gangue P and Q as the origin through f(r3, r4), randomly generate a connecting curve between the two circles through f(X3, Y3, Z3, X4, Y4, Z4), and construct a randomly distributed air hole through the above three random functions.

[0113] Step S340 judges whether the coal gangue or air hole generated by the current random function distribution has interference with the previously generated one, and if there is interference, it is regenerated, and if there is no interference, the next step is executed.

[0114] Step S350 introduces the coal gangue and air hole model into each layer.

[0115] Step S360 analyzes the current coal gangue and air hole ratio and compares it with the geological conditions in S400, and if the ratio is less than the preset condition in S400, new coal gangue and air hole is generated.

[0116] Step S370 calls the designed coal seam model to abaqus to end the Monte Carlo method script.

[0117] Example 3 In order to realize the above embodiment, as Figure 7 As shown, the Monte Carlo method based coal mine water drilling simulation device 10 is also provided in the embodiment, which comprises: The parameter setting module 100 is configured to set the generation parameters of the heterogeneous feature bodies in the coal seam based on the geological conditions of the underground coal mine, the parameters including the feature body type, size range, distribution proportion, and azimuth angle. The structure generation module 200 is configured to generate the irregular structure of the dirt band and the air hole by using three independent random functions to respectively control the position, size, and azimuth of the heterogeneous feature bodies, and detect the interference between the newly generated structure and the existing structure by a spatial interference judgment algorithm, and regenerate if interference occurs. The model embedding module 300 is configured to embed the generated heterogeneous feature body model into the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model conforming to the actual geological conditions. The simulation analysis module 400 is configured to import the heterogeneous coal seam simulation model into a finite element simulation software, realize automatic mapping of model parameters through a script interface, and complete the finite element simulation analysis of the water exploration drill cutting process.

[0118] Further, the parameter setting module is further configured to: determine the feature body type to be one or more combinations of the dirt band, the air hole, or the water pocket according to the logging data and the geological exploration report; set the feature body size range to 0.5 cm to 50 cm, and dynamically adjust the range according to the depth of the coal seam and the lithology change.

[0119] Further, the structure generation module is further configured to: randomly generate the feature body center point coordinates through the function f(r1, r2) to simulate the spatial distribution of the feature bodies in the coal seam; generate the curve connecting the two center points through the function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular shape of the dirt band or the air hole.

[0120] Further, the model embedding module is further configured to: fuse the heterogeneous feature bodies and the coal seam basic model by using Boolean operation to ensure the geometric continuity of the model; automatically assign the corresponding material properties and mechanical parameters according to the feature body type to improve the physical authenticity of the simulation model.

[0121] Further, the simulation analysis module is further configured to: automatically identify and map the contact boundary between the heterogeneous feature bodies and the coal seam basic model through a script; dynamically adjust the finite element grid density according to the feature body distribution to improve the calculation accuracy and efficiency.

[0122] Further, it further comprises: A path optimization module is configured to generate drilling path optimization suggestions, including adjustment strategies of drilling pressure, rotating speed and feeding speed, according to preset geological conditions and simulation results. A feedback iteration module is configured to feed back the optimized drilling parameters to the finite element simulation software for multiple rounds of iteration simulation to verify the safety and feasibility of the drilling scheme.

[0123] The coal mine water exploration drilling simulation device based on the Monte Carlo method according to the present embodiment generates drilling path optimization suggestions according to preset geological conditions and simulation results, and feeds back the optimized parameters to the finite element simulation software for multiple rounds of iteration verification, further improving the safety and feasibility of the water exploration drilling operation scheme, realizing closed-loop control from structural simulation to process optimization, and significantly enhancing the intelligent level of coal mine water exploration drilling design and construction.

[0124] In the description of the present specification, the description referring to the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0125] In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "multiple" is at least two, for example, two, three, etc., unless otherwise specifically limited.

Claims

1. A coal mine water exploration drill simulation method based on a Monte Carlo method, characterized in that, The method comprises the following steps: S1, setting the generation parameters of the heterogeneous feature bodies in the coal seam based on the geological conditions underground, the parameters including the feature body type, size range, distribution proportion and azimuth angle; S2, using three independent random functions to control the position, size and orientation of the heterogeneous feature bodies respectively, generating the irregular structure of the dirt band and air hole, and detecting the interference between the newly generated structure and the existing structure through a spatial interference judgment algorithm, and if interference occurs, re-generate; S3, embedding the generated heterogeneous feature body model into the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model that conforms to the actual geological conditions; S4, importing the heterogeneous coal seam simulation model into the finite element simulation software, realizing the automatic mapping of model parameters through a script interface, and completing the finite element simulation analysis of the drilling process.

2. The method of claim 1, wherein, The setting of the generation parameters of the heterogeneous feature bodies in the coal seam based on the geological conditions underground further comprises: S11, determining the feature body type as one or a combination of dirt band, air hole or water pocket according to the logging data and geological exploration report; S12, setting the feature body size range to 0.5cm to 50cm, and dynamically adjusting the range according to the depth of the coal seam and the change of lithology.

3. The method of claim 1, wherein, The generation of the irregular structure of the dirt band and air hole using three independent random functions to control the position, size and orientation of the heterogeneous feature bodies further comprises: S21, randomly generating the feature body center point coordinates through the function f(r1, r2) to simulate the spatial distribution in the coal seam; S22, generating the curve connecting the two center points through the function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular shape of the dirt band or air hole.

4. The method of claim 1, wherein, The embedding of the generated heterogeneous feature body model into the three-dimensional basic model of the coal seam to form a heterogeneous coal seam simulation model that conforms to the actual geological conditions further comprises: S31, using Boolean operation to fuse the heterogeneous feature body with the coal seam basic model to ensure the geometric continuity of the model; S32, automatically assigning corresponding material properties and mechanical parameters according to the feature body type to improve the physical authenticity of the simulation model.

5. The method of claim 1, wherein, The importing of the heterogeneous coal seam simulation model into the finite element simulation software, the realization of the automatic mapping of model parameters through a script interface, and the completion of the finite element simulation analysis of the drilling process further comprise: S41, automatically identifying and mapping the contact boundary between the heterogeneous feature body and the coal seam basic model through a script; S42, dynamically adjusting the finite element grid density according to the feature body distribution to improve the calculation accuracy and efficiency.

6. The method of claim 1, wherein, Further comprising: S5, generating drilling path optimization suggestions according to the preset geological conditions and simulation results, including adjustment strategies for drilling pressure, rotation speed and feed speed; S6, feeding the optimized drilling parameters back to the finite element simulation software for multiple rounds of iterative simulation to verify the safety and feasibility of the drilling scheme.

7. A coal mine water detection drill simulation device based on a Monte Carlo method, characterized in that, The method comprises the following steps: A parameter setting module is configured to set the generation parameters of the heterogeneous feature bodies in the coal seam based on the geological conditions underground, the parameters including the feature body type, size range, distribution proportion and azimuth angle; The structure generation module is configured to generate the irregular structure of the dirt band and the air hole by using three independent random functions to respectively control the position, size and orientation of the non-homogeneous feature body, and detect the interference between the newly generated structure and the existing structure by a spatial interference judgment algorithm, and if the interference occurs, the structure is re-generated. The model embedding module is configured to embed the generated non-homogeneous feature body model into a three-dimensional basic model of the coal seam to form a non-homogeneous coal seam simulation model conforming to actual geological conditions. The simulation analysis module is configured to import the non-homogeneous coal seam simulation model into a finite element simulation software, realize automatic mapping of model parameters through a script interface, and complete finite element simulation analysis of the water exploration drill cutting process.

8. The apparatus of claim 7, wherein, The parameter setting module is further configured to: determine the feature body type to be one or more combinations of a dirt band, an air hole or a water pocket according to logging data and a geological exploration report; set the feature body size range to be 0.5 cm to 50 cm, and dynamically adjust the range according to the depth of the coal seam and the lithological change.

9. The apparatus of claim 8, wherein, The structure generation module is further configured to: randomly generate the feature body center point coordinates through a function f(r1, r2) to simulate the spatial distribution of the feature body in the coal seam; generate a curve connecting two center points through a function f(X1, Y1, Z1, X2, Y2, Z2) to simulate the irregular shape of the dirt band or the air hole.

10. The apparatus of claim 9, wherein, The model embedding module is further configured to: fuse the non-homogeneous feature body and the coal seam basic model by using a Boolean operation to ensure the geometric continuity of the model; automatically assign corresponding material properties and mechanical parameters according to the feature body type to improve the physical authenticity of the simulation model.

Images