Mining area level three-dimensional rock mass quality evaluation method, device, equipment and medium

Abstract

The invention relates to the technical field of mine engineering, and discloses a mining area level three-dimensional rock mass quality evaluation method, device and equipment and a medium. The method comprises the following steps: obtaining a plurality of drill holes and rock cores thereof through geological drilling, and counting rock mass quality data of the rock core of each return in each drill hole; obtaining structural surface data of a plurality of groups of structural surfaces in the depth direction of the drill holes, and constructing a drill hole database according to the positioning data of each drill hole, the rock mass quality data and the structural surface data; building a block model covering all drill holes based on the drill hole database, and creating an ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group; and determining a three-dimensional space block valuation algorithm according to the vector ellipsoid model group, and calculating a three-dimensional rock mass quality distribution diagram of the block model by using the three-dimensional space block valuation algorithm. According to the method, mining area-level three-dimensional rock mass quality estimation with strong anisotropic characteristics can be realized, and the problem of refined evaluation of rock mass quality is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a three-dimensional rock mass quality evaluation method, device, equipment and medium at the mining area level. Background Art

[0002] The various lithological characteristics of the rock mass distribution at the mining area level are inconsistent, and different rock mass structural plane characteristics are developed in different regions. In particular, the attitude characteristics and development density of the rock mass structural planes significantly control and make the rock mass exhibit strong anisotropic characteristics.

[0003] In the past, the three-dimensional valuation evaluation of geological grades mainly performed attribute valuation on the whole-region ore body through a single search ellipsoid. However, when applying it to the three-dimensional valuation of rock mass quality, the single search ellipsoid is difficult to characterize the strong anisotropic characteristics of the whole-region rock mass and cannot accurately reflect the influence degree of the attitude of the rock mass structural plane. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and provide a three-dimensional rock mass quality evaluation method, device, equipment and medium at the mining area level.

[0005] The present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present disclosure provides a three-dimensional rock mass quality evaluation method at the mining area level, and the method includes:

[0007] Obtaining multiple drill holes and their cores through geological drilling, and counting the rock mass quality data of the cores of each run in each drill hole;

[0008] Obtaining structural plane data of multiple groups of structural planes measured along the depth direction of the drill holes, and constructing a drill hole database according to the positioning data, rock mass quality data and structural plane data of each drill hole;

[0009] Establishing a block model covering all the drill holes based on the drill hole database, and creating an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group;

[0010] Determining a three-dimensional space block valuation algorithm according to the vector ellipsoid model group, and calculating a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block valuation algorithm.

[0011] Further, the counting of the rock mass quality of the cores of each run in each drill hole includes:

[0012] Collecting the rock mass mechanical property data of each run in each drill hole;

[0013] Using the rock mass quality evaluation method and calculating the rock mass quality of each core run according to the rock mass mechanical property data, wherein the rock mass quality evaluation method includes the MRMR method, the Q-system method, and the Q' / GSI method.

[0014] Further, establishing a block model covering all the boreholes based on the borehole database, and creating an independent ellipsoid model for each block in the block model according to the structural plane data, including:

[0015] Establishing a three-dimensional geometric model covering all the boreholes based on the borehole database, setting constraint conditions and block size according to actual needs, and establishing a block model under the constraint conditions;

[0016] According to the structural plane data, calculating the mean vector and covariance matrix of each group of structural planes, establishing an ellipsoid model corresponding to each group of structural planes, and adjusting the range of the ellipsoid model using the confidence interval;

[0017] Based on the radial basis method, anisotropically estimating the parameters of the ellipsoid model to each block in the block model, and creating an independent ellipsoid model for each block in the block model.

[0018] Further, calculating the mean vector and covariance matrix of each group of structural planes according to the structural plane data, and establishing an ellipsoid model corresponding to each group of structural planes, including:

[0019] According to the structural plane data, calculating the mean vector and covariance matrix of each group of structural planes, and constructing the probability density function of the ellipsoid model according to the mean vector and covariance matrix of each group of structural planes;

[0020] Using the probability density function of the ellipsoid model, calculating the probability density of any given structural plane parameter value, constructing the ellipsoid model of each group of structural planes, and determining the dominant plane of each ellipsoid model according to the covariance matrix.

[0021] Further, anisotropically estimating the parameters of the ellipsoid model to each block in the block model based on the radial basis method, including:

[0022] Based on the radial basis function, taking the ellipsoid model of any group of structural planes as the starting point, and calculating the gradient or sub-gradient of the objective function at the starting point;

[0023] Based on the radial basis function and according to the gradient or sub-gradient of the objective function, update the starting point using a preset step size rule, and repeatedly calculate the gradient or sub-gradient of the objective function at the updated starting point and repeatedly update the starting point until the preset step size stop rule is satisfied, and estimate the parameters of the ellipsoid model into each block in the block model, wherein the radial basis function includes Gaussian function, multiquadric function, inverse multiquadric function, and thin plate spline function.

[0024] Further, the calculating the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block estimation algorithm includes:

[0025] Select the rock mass quality data of the known blocks from the borehole database according to the direction of the dominant plane;

[0026] Use the three-dimensional space block estimation algorithm to estimate the rock mass quality data of the known blocks onto each block in the block model, predict the rock mass quality of each unknown block, and obtain the three-dimensional rock mass quality distribution map of the block model, wherein the three-dimensional space block estimation algorithm includes the distance power inverse method and the Kriging method.

[0027] Further, after calculating the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block estimation algorithm, it further includes:

[0028] Select any block in the estimated block model, and review the anisotropic characteristics of any block to obtain a review result;

[0029] According to the review result, adjust and optimize the parameters of the three-dimensional space block estimation algorithm and the ellipsoid model.

[0030] In a second aspect, an apparatus for evaluating three-dimensional rock mass quality at the mining area level is provided in an embodiment of the present disclosure. The apparatus includes:

[0031] A statistics module, configured to obtain multiple boreholes and their cores through geological drilling, and count the rock mass quality data of the cores of each round in each borehole;

[0032] A construction module, configured to obtain the structural plane data of multiple groups of structural planes measured along the depth direction of the borehole, and construct a borehole database according to the positioning data, rock mass quality data, and structural plane data of each borehole;

[0033] A creation module, configured to establish a block model covering all the boreholes based on the borehole database, and create an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group;

[0034] A calculation module, configured to determine a three-dimensional spatial block valuation algorithm according to the vector ellipsoid model group, and calculate a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block valuation algorithm.

[0035] In a third aspect, an embodiment of the present disclosure provides a computer device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the mine-level three-dimensional rock mass quality evaluation method described in the first aspect are implemented.

[0036] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the mine-level three-dimensional rock mass quality evaluation method described in the first aspect are implemented.

[0037] Advantages of the present application:

[0038] The mine-level three-dimensional rock mass quality evaluation method provided by the embodiments of the present application includes: obtaining multiple drill holes and their cores through geological drilling, and counting the rock mass quality data of the cores of each round trip in each drill hole; obtaining structural plane data of multiple groups of structural planes tested along the depth direction of the drill holes, and constructing a drill hole database according to the positioning data, rock mass quality data, and structural plane data of each drill hole; establishing a block model covering all the drill holes based on the drill hole database, and creating an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group; determining a three-dimensional spatial block valuation algorithm according to the vector ellipsoid model group, and calculating a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block valuation algorithm. The present application can realize the mine-level three-dimensional rock mass quality valuation with strong anisotropic characteristics under complex geological body conditions, and effectively solve the problem of fine evaluation of the rock mass quality in a large area at the mine level.

[0039] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given below in conjunction with the accompanying drawings for detailed description. Description of the Drawings

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained according to these drawings without creative efforts. In each drawing, similar components are numbered similarly.

[0041] Figure 1Shows the flowchart of a three-dimensional rock mass quality evaluation method provided by an embodiment of the present application;

[0042] Figure 2 Shows the flowchart of another three-dimensional rock mass quality evaluation method provided by an embodiment of the present application;

[0043] Figure 3 Shows the structural schematic diagram of a three-dimensional rock mass quality evaluation device provided by an embodiment of the present application;

[0044] Figure 4 Shows the structural schematic diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0045] The embodiments of the present invention are described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0046] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be a middle element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be a middle element at the same time. On the contrary, when an element is referred to as being "directly on" another element, there is no middle element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration.

[0047] In the present invention, unless otherwise clearly defined and limited, the terms "installed", "connected", "connected", "fixed" and other terms should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0048] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise clearly specifically defined.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used in the description of the template herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0050] Embodiment 1

[0051] As Figure 1 shown, it is a flowchart of a three-dimensional rock mass quality evaluation method at the mining area level in the embodiments of the present application. The three-dimensional rock mass quality evaluation method provided by the embodiments of the present application includes the following steps:

[0052] Step S110: Obtain multiple drill holes and their cores through geological drilling, and count the rock mass quality data of the cores in each round of each of the drill holes.

[0053] In this embodiment, through a large number of geological prospecting drill holes and their cores, and limited supplementary exploration drill holes and their cores, the rock mass mechanical property data in each round of each drill hole are collected. The rock mass mechanical property data may include rock strength, deformation modulus, shear strength, etc.

[0054] Adopt a rock mass quality evaluation method to calculate the rock mass quality of the core in each round according to the collected rock mass mechanical property data. These methods comprehensively consider the physical and mechanical properties of the rock and the geological structure conditions, and can more accurately reflect the actual quality of the rock mass. In this embodiment, the rock mass quality evaluation methods include but are not limited to the MRMR method, the Q-system method, and the Q' / GSI method, and the embodiments of the present application do not limit this.

[0055] The above method for obtaining drill holes and their cores can directly obtain the physical and mechanical property data of the rock mass, which are the basis for subsequent rock mass quality evaluation. Counting the rock mass quality data of the cores in each round of each drill hole can ensure the comprehensiveness and accuracy of the data, and provide reliable data support for subsequent three-dimensional modeling and valuation.

[0056] Step S120: Obtain the structural plane data of multiple groups of structural planes obtained by testing along the depth direction of the drill hole, and construct a drill hole database according to the positioning data, rock mass quality data, and structural plane data of each drill hole.

[0057] Specifically, through limited supplementary exploration drill holes, count and obtain the occurrence of the structural planes obtained by testing along the depth direction of the drill hole. The structural plane is a discontinuous surface such as a fracture or a crack in the rock mass, which has an important impact on the mechanical properties and stability of the rock mass.

[0058] Statistically analyze the occurrence distribution of each set of structural planes within a fixed distance at regular intervals, including the dip direction, dip angle, and quantity of the most dominant structural plane within each set, as well as the quantities of structural planes in the other two directions that are 90° to it in space. This helps to understand the spatial distribution law and dominant direction of structural planes in the rock mass.

[0059] Furthermore, integrate the positioning data (such as longitude, latitude, elevation, etc.), inclinometry data (such as borehole inclination angle, direction, etc.), rock mass quality data, and structural plane data of all boreholes together to form a complete borehole database, providing a basis for subsequent 3D modeling and valuation.

[0060] The above method for obtaining structural plane data through testing along the borehole depth direction helps to understand the spatial distribution law and dominant direction of structural planes in the rock mass, which is crucial for evaluating the stability and quality of the rock mass. Constructing a borehole database by integrating the positioning data, rock mass quality data, and structural plane data of the boreholes provides a complete data basis for subsequent 3D modeling and valuation.

[0061] Step S130, establish a block model covering all the boreholes based on the borehole database, and create an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group.

[0062] In an alternative implementation, as Figure 2 shown, step S130 includes:

[0063] Step S131, establish a 3D geometric model covering all the boreholes based on the borehole database, set constraint conditions and block size according to actual needs, and establish a block model under the constraint conditions.

[0064] Understandably, based on the borehole database, establish a 3D geometric model covering the range of geological exploration boreholes and supplementary exploration boreholes, which can reflect the spatial form and distribution of the rock mass. Then, set constraint conditions (such as terrain, geological structure, etc.) according to actual needs, and determine the block size to establish a block model under the constraint conditions, which helps to more accurately reflect the actual structure and properties of the rock mass.

[0065] Step S132, according to the structural plane data, calculate the mean vector and covariance matrix of each set of structural planes, establish an ellipsoid model corresponding to each set of structural planes, and adjust the range of the ellipsoid model using the confidence interval.

[0066] Understandably, according to the structural plane data, calculate the mean vector and covariance matrix of each set of structural planes. Among them, the calculation formula for the mean vector is:

[0067]

[0068] Wherein, μ represents the mean vector, the sample set X = {x1, x2, …, x N}, each x i represents the parameter vector of a structural plane, and N is the number of structural planes.

[0069] The calculation formula of the covariance matrix is:

[0070]

[0071] Wherein, ∑ represents the covariance matrix.

[0072] Next, construct the probability density function of the ellipsoid model according to the mean vector and covariance matrix of each group of structural planes:

[0073]

[0074] Wherein, f(x; μ, ∑) represents the probability density function of the ellipsoid model, and |∑| represents the determinant of the covariance matrix.

[0075] Adjust the range of the ellipsoid model using the confidence interval to ensure the accuracy of the model at a certain confidence level. The calculation formula of the confidence interval is:

[0076]

[0077] Wherein, represents the sample mean, and S represents

[0078] Furthermore, use the probability density function of the ellipsoid model to calculate the probability density of any given structural plane parameter value, thereby constructing the ellipsoid model of each group of structural planes. And determine the dominant plane of each ellipsoid model according to the covariance matrix. Understandably, the eigenvector of the covariance matrix corresponds to the main change direction of the data in each direction, where the largest eigenvalue corresponds to the long axis direction, the smallest eigenvalue corresponds to the short axis direction, and the short axis and the long axis form the dominant plane.

[0079] Step S133, anisotropically estimate the parameters of the ellipsoid model to each block in the block model based on the radial basis method, and create an independent ellipsoid model for each block in the block model.

[0080] Understandably, the starting point is the beginning of the iterative process. Usually, the ellipsoid model of any set of structural planes is selected as the starting point. Each ellipsoid model represents the main distribution characteristics of the structural planes, including the mean vector and covariance matrix. Based on the radial basis function, the gradient or sub-gradient of the objective function is calculated at the starting point. The objective function may be a function representing the matching degree between the ellipsoid model and the actual structural planes in the block model. The gradient or sub-gradient is used to determine the direction of the next iteration, that is, how to adjust the parameters of the ellipsoid model to better match the actual data.

[0081] Next, based on the basis function of the radial basis and according to the gradient or sub-gradient of the objective function, the starting point is updated using a preset step size rule (such as a fixed step size, an adaptive step size, etc.). The step size rule determines the distance moved in the gradient direction to ensure that the iterative process can converge to the optimal solution. The updated starting point represents the new parameters of the ellipsoid model. Repeat the steps of calculating the gradient or sub-gradient of the objective function at the updated starting point and updating the starting point until the preset step size stop rule is satisfied. The stop rule may be that the number of iterations reaches a preset upper limit, or the value of the objective function converges to a certain threshold or below. In each iteration, the ellipsoid model gradually adjusts its parameters to better reflect the actual structural plane distribution in the block model.

[0082] In this embodiment, the basis functions of the radial basis include but are not limited to Gaussian functions, multiquadric functions, inverse multiquadric functions, and cardinal spline functions, which can be specifically determined according to the actual situation, and the embodiments of the present application do not limit this.

[0083] Furthermore, after the iterative process ends, the final estimated values of the ellipsoid model parameters are anisotropically applied to each block in the block model to obtain a group of vector ellipsoid models. This means that each block will have a set of ellipsoid model parameters corresponding to its position, and these parameter sets reflect the distribution characteristics of the structural planes at the position of the block.

[0084] The above method establishes a block model based on the borehole database, which can reflect the spatial form and distribution of the rock mass. Creating an independent ellipsoid model for each block can more accurately describe the spatial distribution and characteristics of the structural planes, providing a more accurate mathematical model for the subsequent calculation of the three-dimensional rock mass quality distribution map.

[0085] Step S140, determine a three-dimensional space block evaluation algorithm according to the group of vector ellipsoid models, and use the three-dimensional space block evaluation algorithm to calculate the three-dimensional rock mass quality distribution map of the block model.

[0086] Understandably, a search radius is determined, and a suitable three-dimensional spatial block valuation algorithm is determined according to the vector ellipsoid model group. Then, according to the direction of the dominant plane, the rock mass quality data of the known blocks are selected from the borehole database, and the rock mass quality data of the known blocks are valued onto each block in the block model by using the three-dimensional spatial block valuation algorithm, and the quality of each unknown block is predicted to obtain the three-dimensional rock mass quality distribution map of the block model.

[0087] In an alternative embodiment, the three-dimensional spatial block valuation algorithm may be the inverse distance power method. For each unknown point P, its distances from all known points are calculated; according to the distance calculation formula, the influence weights of each known point on the unknown point are calculated; according to the values and weights of the known points, the predicted value of the unknown point is calculated. For the unknown point P, its predicted value Z P can be calculated by the following formula:

[0088]

[0089] In the formula, Z P represents the value of the unknown point P, Z i represents the value of the known point i, d i represents the distance between the unknown point P and the known point i, t represents the power parameter, usually taking a real number greater than 0, and n represents the number of known points.

[0090] In another alternative embodiment, the three-dimensional spatial block valuation algorithm may be the Kriging method. For each unknown point P, its distances from all known points are calculated; based on the distance and the spatial autocorrelation between the known points, the weights of each known point are determined; according to the weights and the values of the known points, the predicted value of the unknown point is calculated. For the unknown point P, its predicted value Z P can be calculated by the following formula:

[0091]

[0092] In the formula, Z P represents the value of the unknown point P, Z i represents the value of the known point i, λ i represents the weight associated with the known point i, and n represents the number of known points.

[0093] It should be noted that in this embodiment, the three-dimensional spatial block valuation algorithm includes but is not limited to the inverse distance power method and the Kriging method, and the embodiments of the present application do not limit this.

[0094] The above method selects a suitable three-dimensional spatial block valuation algorithm, which can ensure the accuracy and reliability of the calculation results. By using a suitable algorithm to estimate the rock mass quality data of known blocks onto each block in the block model, the three-dimensional rock mass quality distribution map of the block model can be predicted, providing an intuitive visualization result for the stability and quality assessment of the rock mass.

[0095] Preferably, after calculating the three-dimensional rock mass quality distribution map of the block model, any block in the estimated block model can be selected, and the anisotropic characteristics of any block can be rechecked to obtain a recheck result; according to the recheck result, check whether the anisotropic characteristics of the rechecked and estimated block are significant and reasonable, and then adjust and optimize the parameters of the three-dimensional spatial block valuation algorithm and the ellipsoid model to ensure the reliability of the evaluation results.

[0096] The mining area-level three-dimensional rock mass quality evaluation method provided by the embodiments of the present application obtains multiple drill holes and their cores through geological drilling, and statistically analyzes the rock mass quality data of the cores of each round in each of the drill holes; obtains the structural plane data of multiple groups of structural planes measured along the depth direction of the drill holes, and constructs a drill hole database according to the positioning data, rock mass quality data, and structural plane data of each drill hole; establishes a block model covering all the drill holes based on the drill hole database, and creates an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group; determines a three-dimensional spatial block valuation algorithm according to the vector ellipsoid model group, and uses the three-dimensional spatial block valuation algorithm to calculate the three-dimensional rock mass quality distribution map of the block model. The present application can realize the mining area-level three-dimensional rock mass quality valuation with strong anisotropic characteristics under complex geological body conditions, and effectively solve the problem of fine evaluation of the rock mass quality in a large area of the mining area.

[0097] Embodiment 2

[0098] As Figure 3 shown, it is a schematic structural diagram of a mining area-level three-dimensional rock mass quality evaluation device 300 in the embodiments of the present application. The device includes:

[0099] A statistics module 310, configured to obtain multiple drill holes and their cores through geological drilling, and statistically analyze the rock mass quality data of the cores of each round in each of the drill holes;

[0100] A construction module 320, configured to obtain the structural plane data of multiple groups of structural planes measured along the depth direction of the drill holes, and construct a drill hole database according to the positioning data, rock mass quality data, and structural plane data of each drill hole;

[0101] A creation module 330 is configured to establish a block model covering all the boreholes based on the borehole database, and create an independent ellipsoid model for each block in the block model according to the structural plane data, thereby obtaining a group of vector ellipsoid models;

[0102] A calculation module 340 is configured to determine a three-dimensional spatial block evaluation algorithm according to the group of vector ellipsoid models, and calculate a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block evaluation algorithm.

[0103] The mine-level three-dimensional rock mass quality evaluation device provided by the embodiments of the present application can realize the mine-level three-dimensional rock mass quality evaluation with strong anisotropic characteristics under complex geological body conditions, and effectively solve the problem of fine evaluation of the rock mass quality in a large area at the mine level.

[0104] Embodiment 3

[0105] The embodiments of the present application further provide a computer device. Specifically, please refer to Figure 4 , Figure 4 which is the basic structural block diagram of the computer device in this embodiment.

[0106] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are communicatively connected to each other through a system bus. It should be noted that only the computer device 4 with the memory 41, the processor 42, and the network interface 43 is shown in the figure. However, it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented. Among them, those skilled in the art of the present technology can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0107] The computer device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can perform human-computer interaction with the user through means such as a keyboard, a mouse, a remote controller, a touchpad, or a voice control device.

[0108] The memory 41 includes at least one type of readable storage medium, which includes flash memory, hard disk, multimedia card, card-type memory (such as SD or D-slot compatibility test memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disc, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Of course, the memory 41 may also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the slot compatibility test method. In addition, the memory 41 may also be used to temporarily store various types of data that have been output or will be output.

[0109] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other mine-level three-dimensional rock mass quality evaluation chips. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions of the slot compatibility test method.

[0110] The network interface 43 may include a wireless network interface or a wired network interface, and this network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0111] The computer device provided in this embodiment can execute the above-mentioned mine-level three-dimensional rock mass quality evaluation method. Here, the mine-level three-dimensional rock mass quality evaluation method may be the mine-level three-dimensional rock mass quality evaluation method of each of the above embodiments.

[0112] Embodiment 4

[0113] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the mine-level three-dimensional rock mass quality evaluation method in the embodiment are implemented.

[0114] In this embodiment, the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the computer-readable storage medium may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. equipped on the computer device. Of course, the computer-readable storage medium may also include both the internal storage unit and the external storage device of the computer device. In this embodiment, the computer-readable storage medium is generally used to store the operating system and various application software installed on the computer device. In addition, the computer-readable storage medium can also be used to temporarily store various data that have been output or will be output.

[0115] In several embodiments provided by the present application, it should be understood that the disclosed device and method can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and structure diagrams in the drawings show the possible architectures, functions, and operations of the device, method, and computer program product according to multiple embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in an alternative implementation, the functions marked in the block may occur in a different order than marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the structure diagram and / or flowchart, and the combination of blocks in the structure diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0116] In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0117] When the above-mentioned functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium can be a non-volatile storage medium or a volatile storage medium. For example, the storage medium can be: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc., which can store program codes.

[0118] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention.

Claims

1. A three-dimensional rock mass quality evaluation method at the mining area level, characterized in that, The method includes: Obtaining multiple boreholes and their cores through geological drilling, and statistically analyzing the rock mass quality data of the cores for each round trip in each borehole; Obtaining the structural plane data of multiple groups of structural planes measured along the depth direction of the boreholes, and constructing a borehole database based on the positioning data, rock mass quality data, and structural plane data of each borehole; Establishing a block model covering all the boreholes based on the borehole database, and creating an independent ellipsoid model for each block in the block model according to the structural plane data to obtain a vector ellipsoid model group; Determining a three-dimensional spatial block evaluation algorithm according to the vector ellipsoid model group, and calculating the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block evaluation algorithm.

2. The three-dimensional rock mass quality evaluation method at the mining area level according to claim 1, wherein The statistically analyzing the rock mass quality of the cores for each round trip in each borehole includes: Collecting the rock mass mechanical property data for each round trip in each borehole; Calculating the rock mass quality of the cores for each round trip by using a rock mass quality evaluation method and according to the rock mass mechanical property data, wherein the rock mass quality evaluation method includes the MRMR method, the Q system method, and the Q' / GSI method.

3. The three-dimensional rock mass quality evaluation method at the mining area level according to claim 1, characterized in that The establishing a block model covering all the boreholes based on the borehole database, and creating an independent ellipsoid model for each block in the block model according to the structural plane data includes: Establishing a three-dimensional geometric model covering all the boreholes based on the borehole database, setting constraint conditions and block size according to actual needs, and establishing a block model under the constraint conditions; Calculating the mean vector and covariance matrix of each group of structural planes according to the structural plane data, establishing an ellipsoid model corresponding to each group of structural planes, and adjusting the range of the ellipsoid model by using a confidence interval; Anisotropically estimating the parameters of the ellipsoid model to each block in the block model based on the radial basis method, and creating an independent ellipsoid model for each block in the block model.

4. The three-dimensional rock mass quality evaluation method at the mining area level according to claim 3, characterized in that, The calculating the mean vector and covariance matrix of each group of structural planes according to the structural plane data, and establishing an ellipsoid model corresponding to each group of structural planes includes: Calculating the mean vector and covariance matrix of each group of structural planes according to the structural plane data, and constructing a probability density function of the ellipsoid model according to the mean vector and covariance matrix of each group of structural planes; Using the probability density function of the ellipsoid model to calculate the probability density of any given structural plane parameter value, constructing an ellipsoid model for each group of structural planes, and determining the dominant plane of each ellipsoid model according to the covariance matrix.

5. The method for evaluating the three-dimensional rock mass quality at the mining area level according to claim 3, wherein The anisotropically estimating the parameters of the ellipsoid model to each block in the block model based on the radial basis method includes: Taking the ellipsoid model of any group of structural planes as a starting point based on the radial basis function, and calculating the gradient or sub-gradient of the objective function at the starting point; Based on the radial basis function and according to the gradient or sub-gradient of the objective function, update the starting point using a preset step size rule, and repeatedly calculate the gradient or sub-gradient of the objective function at the updated starting point and repeatedly update the starting point until the preset step size stopping rule is satisfied. Estimate the parameters of the ellipsoid model into each block in the block model, where the radial basis function includes Gaussian function, multi-quadratic function, inverse multi-quadratic function, and cubic spline function.

6. The three-dimensional rock mass quality evaluation method at the mining area level according to claim 4, characterized in that The calculating the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block valuation algorithm includes: Select the rock mass quality data of the known blocks from the borehole database according to the direction of the dominant plane; Use the three-dimensional spatial block valuation algorithm to estimate the rock mass quality data of the known blocks onto each block in the block model, predict the rock mass quality of each unknown block, and obtain the three-dimensional rock mass quality distribution map of the block model, where the three-dimensional spatial block valuation algorithm includes the distance power inverse method and the Kriging method.

7. The method for evaluating the three-dimensional rock mass quality at the mining area level according to claim 3, wherein After calculating the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block valuation algorithm, it further includes: Select any block in the estimated block model, and review the anisotropic characteristics of the any block to obtain a review result; According to the review result, adjust and optimize the parameters of the three-dimensional spatial block valuation algorithm and the ellipsoid model.

8. A three-dimensional rock mass quality evaluation device at the mining area level, characterized in that, The device includes: A statistics module, configured to obtain multiple boreholes and their cores through geological drilling, and statistics the rock mass quality data of the cores of each run in each borehole; A construction module, configured to obtain the structural plane data of multiple groups of structural planes measured along the depth direction of the borehole, and construct a borehole database according to the positioning data, rock mass quality data, and structural plane data of each borehole; A creation module, configured to establish a block model covering all the boreholes based on the borehole database, and create an independent ellipsoid model for each block in the block model according to the structural plane data, to obtain a vector ellipsoid model group; A calculation module, configured to determine a three-dimensional spatial block valuation algorithm according to the vector ellipsoid model group, and calculate the three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block valuation algorithm.

9. A computer device, characterized in that, It includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the mine-level three-dimensional rock mass quality evaluation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the mine-level three-dimensional rock mass quality evaluation method according to any one of claims 1-7.

Images