CN115034652A - Mining overburden rock mud-carrying sand separation layer water inrush risk evaluation method - Google Patents

Mining overburden rock mud-carrying sand separation layer water inrush risk evaluation method Download PDF

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CN115034652A
CN115034652A CN202210735623.8A CN202210735623A CN115034652A CN 115034652 A CN115034652 A CN 115034652A CN 202210735623 A CN202210735623 A CN 202210735623A CN 115034652 A CN115034652 A CN 115034652A
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乔伟
刘梦楠
王启庆
李连刚
程香港
张磊
孟祥胜
韩昌民
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Abstract

The invention discloses a mining overburden carrying sand separation layer water inrush risk evaluation method, which comprises the steps of selecting indexes related to sand inrush accidents of roof water inrush; determining an index constant weight value based on hierarchical analysis and entropy weight synthesis; constructing a variable weight function, and determining variable weight values of all indexes; obtaining a mine sand collapse water source danger zoning map through a constant weight-variable weight model; obtaining a sand bursting source danger partition map based on the deposition micro-phase; and (4) integrating the mine sand bursting water source danger zone map and the sand bursting object source danger zone map, and finally defining a high-risk area of sand bursting. According to the method, after the weight value is determined based on the combination of experience, data statistics and variable weight, the deposition microfacies are combined, and the danger zoning method of the interaction of the sand-bursting water source and the sand source is considered, so that the mine sand-bursting danger area is predicted more accurately and conveniently finally.

Description

Mining overburden rock mud-carrying sand separation layer water inrush risk evaluation method
Technical Field
The invention relates to the field of water inrush and sand inrush prevention and control in coal mining, in particular to a method for evaluating the danger of water inrush of a mining overburden rock carrying silt separation layer.
Background
In recent years, the center of coal mining in China is transferred to the Jurassic coal field in the Erdos basin in the northwest, and due to complex engineering geological conditions, geological disasters frequently occur in the coal mining process. Particularly, the working face separation water inrush caused by a chalky aquifer has the characteristics of paroxysmal property, high water inflow and the like, and in addition, the Jurassic formation belongs to a continental phase sedimentary weakly consolidated sand-mud rock stratum, the weakly consolidated rock stratum of the lower roof in high-strength mining is seriously crushed, a large number of mud-sand particles flow into the working face under the washing of strong water flow, the water drainage facility is paralyzed and the working face is silted, so that the working progress is influenced and the life safety of miners is threatened. The water flow rate from the stratospheric space and the cementation degree of the direct roof dwarfism rock stratum of the working face are two main factors for predicting the formation of the sand burst and evaluating the scale of the sand burst.
For the prediction of sand collapse, both a water source and a sand source (material source) need to be considered, and sand collapse of a certain scale can only occur if the water source and the material source are simultaneously satisfied. On one hand, the existing mining area risk evaluation method focuses on influence factors related to mine water inrush, generally determines the weight of the influence factors based on experience, such as an analytic hierarchy process, and then adds risk coefficients of the factors to obtain a mining area (working face) water inrush risk zoning map. However, unlike conventional water burst, the direct water source (water logging in the overburden) and the water conducting channel (fracture) of the mining overburden water burst are initiated by mining, and the water source scale and channel are the result of coupling of in-situ overburden and engineering mining conditions, and cannot be predicted by the prior geophysical prospecting drilling. On the other hand, the deterioration of the formation under the action of the water flow is closely related to various factors such as lithology, structure, integrity and the like of the formation. The deposition environment of the Jurassic strata of the Ordosus basin is complex, the occurrence characteristics of the strata are changeable, the research on the water-encountering degradation of rock mass is mainly carried out in the form of indoor experiments at present, and no evaluation method is provided for linking the macroscopic characteristics of the regional strata with the water-encountering degradation degree.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a mining overburden rock carrying mud sand separation layer water inrush risk evaluation method, which is a danger zoning method for considering interaction of a sand inrush water source and a sand inrush source by combining deposition microfacies after determining a weight value based on experience, data statistics and variable weight, so that a mine sand inrush risk area is predicted more accurately and conveniently finally.
In order to achieve the purpose, the invention adopts the following technical scheme:
a mining overburden carrying sand separation layer water inrush risk evaluation method comprises the following steps:
selecting indexes related to sand bursting accidents of water inrush of the top plate;
determining an index constant weight value based on hierarchical analysis and entropy weight synthesis;
constructing a variable weight function, and determining variable weight values of all indexes;
obtaining a mine sand collapse water source danger zoning map through a constant weight-variable weight model;
obtaining a sand bursting source danger partition map based on the deposition micro-phase;
and (4) integrating the mine sand bursting water source danger subarea diagram and the sand bursting object source danger subarea diagram, and finally, defining a high-risk area of sand bursting.
It should be noted that the invention utilizes the method of comprehensively determining the index constant weight value based on the analytic hierarchy process and the entropy weight method. Further, in the present invention, the analytic hierarchy process actually represents subjective judgment, and the entropy weight process represents objective statistics.
Specifically, the method comprises the following steps:
the Analytic Hierarchy Process (AHP) first regards a complex decision problem with a plurality of targets as a system, then decomposes the targets into a plurality of sub-targets according to the actual situation, then further decomposes the problem into a plurality of layers with a plurality of indexes, uses the fuzzy quantization method of qualitative indexes to calculate the single-layer sequence (weight) and the total sequence, and further achieves the purpose of optimizing the decision of the targets (multi-index) and multi-scheme
In order to make the decision result more acceptable, Saaty et al propose a consistent matrix method, i.e. for a certain criterion, each factor under it is compared pairwise and ranked according to its importance. a is ij Is the result of the importance of element i compared to element j. Table 1 lists the 9 importance ratings proposed by saath and their corresponding values. And a matrix formed by the importance results obtained by pairwise comparison is called a judgment matrix. The decision matrix has the following properties:
Figure BDA0003715240140000031
table 1 decision matrix element a ij Method of scaling
Figure BDA0003715240140000032
Judging the maximum characteristic root lambda of the matrix max The feature vector of (c) is normalized (the sum of the elements in the vector is equal to 1) and then denoted as W. Whether the hierarchical single ordering of the matrix can be confirmed or not needs to be checked for consistency, namely, the inconsistent allowable range is determined for A. Wherein the only nonzero characteristic root of the n-order coherent array is n; a is a uniform matrix if and only if λ ═ n.
Due to the continuous dependence of lambda on a ij If λ is larger than n, the inconsistency of a is more serious, the consistency index is calculated by CI, and if CI is smaller, the consistency is higher. The feature vector corresponding to the maximum feature value is used as a weight vector for influencing a certain factor at an upper layer by a certain compared factor, and the judgment error is larger when the inconsistency degree is larger. Thus can beTo quantify the degree of inconsistency of a by the size of a-n. Defining the consistency index as:
Figure BDA0003715240140000041
CI is 0, with complete identity; CI is close to 0, and the consistency is satisfactory; the larger the CI, the more severe the inconsistency. To measure the magnitude of CI, a random consistency index RI is introduced:
Figure BDA0003715240140000042
the random consistency index RI is related to the order of the judgment matrix, and in general, the larger the order of the matrix is, the higher the probability of consistency random deviation is, and the corresponding relationship is as shown in table 2:
TABLE 2 relationship of consistency index to matrix order
Order of matrix 1 2 3 4 5 6 7 8 9 10
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49
Considering that random reasons may cause deviation of consistency, when checking and judging whether the matrix has satisfactory consistency, CI and RI need to be compared to obtain a check coefficient CR, where the formula is as follows:
Figure BDA0003715240140000043
generally, if CR < 0.1, the constructed decision matrix is considered to pass the consistency check, otherwise, the constructed decision matrix does not have satisfactory consistency.
Based on this, the weight of the i-th index is
Figure BDA0003715240140000051
And (3) combining engineering experience and literature data to construct a judgment matrix A, calculating by means of matlab software to obtain a consistency index of the judgment matrix A, and further calculating according to a formula to obtain a consistency ratio CR of the judgment matrix, namely whether the consistency ratio CR meets the consistency check standard or not. And when the consistency is tested, calculating the weight value of each influence factor by using matlab.
The entropy weight method is a method for objectively assigning an index weight according to the amount of information included in each index. Generally, the larger the change width of the index is, the larger the amount of information included in the index is, and therefore the weight of the index is also larger. Calculating index weight by using an entropy weight method, and comprising the following steps:
1) normalizing raw data matrices
Assuming that there are m evaluation indexes and n evaluation objects, there is an original data matrix:
Figure BDA0003715240140000052
the matrix is normalized by:
Figure BDA0003715240140000053
in the formula, r ij Calculating a standard value of the jth evaluation object on the ith evaluation index according to formula
Figure BDA0003715240140000054
2) Definition entropy
For the evaluation indexes with m numbers and the evaluation objects with n numbers, the entropy of the ith index is defined as
Figure BDA0003715240140000061
Figure BDA0003715240140000062
When f is ij When equal to 0, another f ij ln f ij ＝0。 (10)
3) Defining entropy weights
Based on the defined entropy, the entropy weight of the ith index can be defined, namely:
Figure BDA0003715240140000063
wherein u is more than or equal to 0 i ≤1，
Figure BDA0003715240140000064
Subjective weighting w determined by AHP i And EM determined objective weight u i As an integrated weight of risk influencing factors, i.e.
W i ＝(w i +u i )/2 (12)
Note that the weight is set to a negative value for those factors that are negatively correlated with the risk of roof flooding.
It should be noted that the constructing variable weight function includes:
definition 1: hypothesis vector
Figure BDA0003715240140000065
Is an n-dimensional constant weight vector, full
Figure BDA0003715240140000066
Definition 2: let W have a mapping [0,1 ]] m →(0,1] m ,W(x)＝(w 1 (x),w 2 (x),…w m (x) Is m-dimensional variable weight vector, which satisfies the following conditions:
(1)w j (x) Is epsilon (0,1) and
Figure BDA0003715240140000067
(2) when j ∈ {1,2, …, m }, there is α j ,β j ∈[0,1]And alpha is j ≤β j ；w j (x 1 ,…,x m ) In the interval [0, alpha ] j ]With x j Monotonically decreasing in the interval [ 2 ]β j ,1]Monotonically increasing.
Definition 3: assume that there is a mapping S: [0,1 ]] m →(0,+∞) m (x) converting S to (S) 1 (x),S 2 (x),…,S m (x) Is defined as an m-dimensional variable weight vector, for
Figure BDA0003715240140000071
β j ∈[0,1]And alpha is j ≤β j . It satisfies the following conditions:
(1)
Figure BDA0003715240140000072
in the interval [0, alpha ] j ]With x j Monotonically decreasing, in the interval [ beta ] j ,1]Monotonically increasing.
(2) When x is more than or equal to 0 i ≤x k ≤α i ∧α k When there is S i (x)≥S k (x) (ii) a When beta is i ∨β k ≤x i ≤x k Less than or equal to 1, with S i (x)≤S k (x)。
S (x) is a random m-dimensional state variable weight vector;
Figure BDA0003715240140000073
and if the vector is a random m-dimensional constant weight vector, the modified weight vector is:
Figure BDA0003715240140000074
the above formula is a sand bursting water source risk evaluation model.
It should be further noted that because drilling is costly, and the mine geological conditions are complex, and the regional area is wide, rely on-the-spot rock core to sample and carry out the indoor experiment and carry out the subregion to the cementation degree of the roof rock stratum of full mining area, the expense is big and the accuracy is low. Therefore, the invention uses the method of depositing the microphase to obtain the danger zone map of the sand crushing source.
Specifically, the sedimentary facies is the sum of the environment and conditions of formation of sediments and their characteristics, and is a stratigraphic unit reflecting certain natural environmental characteristics and having certain lithology and ancient biomarkers. The environment and the action process during the deposition can be judged from characteristics of lithology, color, structure, archaea and the like of the sedimentary rock. The sedimentary environment of the rock stratum has a close relation with the cementation degree after the sedimentary environment of the rock stratum is consolidated into rock, so that the danger identification of a top plate sand collapsing source in a mine area is carried out by a method of sedimentary facies identification on a large area and sedimentary microfacies subdivision, and the method comprises the following specific steps:
(1) and identifying large-area sedimentary facies. Through data research and well core observation, the sedimentary facies and the main characteristics of the Jurassic system-lower chalky system Luo river group in the south of Ordos basin are summarized by combining a logging curve, and a foundation is laid for sedimentary microfacies division and research in a research area.
(2) And (4) carrying out deposition microphase division on the mining area. Sedimentary facies interpretation of well logs is a well-established technical approach. Resistivity logging, conductivity logging and natural potential logging all belong to electrode logging, and different stratum, lithology and electrical characteristics are different. The most common parameters for interpreting sedimentary facies using well logs are natural potential and natural gamma.
The natural potential curve is composed of three potentials, mainly controlled by granularity, sorting property and argillaceous content, and depends on hydrodynamic energy and source supply conditions during deposition, so that the change of the natural potential curve can reflect the deposition environment. The hydrodynamic force is strong, and when the deposition environment is more turbulent, the natural potential numerical value shows as a negative number with a large absolute value, and shows as a strong deviation to the left side on a logging curve graph. Sandstone particles are large and are often formed in environments with strong hydrodynamic force, such as rivers, delta plains, intertidal zones and the like, and parallel bedding and staggered bedding formed by strong hydrodynamic force conditions are often developed. When the hydrodynamic force is weak and the deposition environment is calmer, the natural potential value is represented as a positive number near 0 or a positive number with a larger absolute value, and is represented as a strong deviation to the right side on a logging curve chart. Mudstone particles are small and tend to form in less hydrodynamic environments such as the anterior delta, lakes, deep sea, semi-deep sea, etc.
The natural gamma-ray logging is a logging method for detecting the intensity of radioactive gamma-rays of natural radioactive minerals of a stratum so as to judge stratum parameters, and is mainly used for distinguishing sand from a mud rock stratum in a sand-mud rock profile. The natural gamma rays can be used for dividing sand-mud rock layers, can also be used for distinguishing sandstone with high mud content or sandstone with low mud content, can be used for distinguishing marl with high mud content, higher dolomite and lower limestone, can also be used for indirectly indicating the existence of a fracture development zone, and is also used for the comparison of carbonate profiles.
(3) And determining the danger relationship between the sedimentary micro-phase and the sand crushing source. Analyzing the mapping relation between the sedimentary microfacies and lithology, particle size and cementation degree according to the sedimentary environments corresponding to different sedimentary microfacies; and sequencing the rock stratums with different sedimentary microfacies according to the difficulty of particle migration under the action of water flow, and further obtaining a danger level zoning map of the ore crushing source in the right mining area.
The invention has the beneficial effects that:
1. on a sand bursting water source danger subarea, firstly, a normal weight value is determined by combining an analytic hierarchy process and an entropy weight method, and then a variable weight function is constructed to adjust index weight. The method combines subjective evaluation and objective statistics, namely, on-site experience of experts in actual work is used for reference, and the influence of a parameter interval on the weight is considered in combination with a statistical result of on-site investigation, so that the defect that the experience, the statistics and the variable weight cannot be considered simultaneously in the aspect of weight determination in the past is overcome.
2. On the danger subarea of the sand bursting source, the traditional drilling sampling is broken through, the conventional method for obtaining the physical and mechanical indexes of the rock sample through an indoor experiment is taken into consideration, the macroscopic geological condition is considered, and the danger grade of the sand bursting source is identified by a sedimentary microfacies method.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
FIG. 2 is a diagram of a risk partition of a sand bursting water source, which is provided by an embodiment of the present invention and takes into account the comprehensive influence of experience, statistics, and weight change;
FIG. 3 illustrates an example borehole log provided by an embodiment of the present invention;
FIG. 4 is a microphase partition diagram of Jurassic direct group deposition in a mining area;
FIG. 5 is a microphase partition diagram of Jurassic group deposition in a mining area.
Detailed Description
The present invention will be further described below, and it should be noted that the following examples are provided to give detailed embodiments and specific operation procedures on the premise of the technical solution, but the protection scope of the present invention is not limited to the examples.
Examples
The advantages of the invention are better illustrated by the following examples.
Taking a certain coal mine in a Jurassic coal field as an example, the thickness of the coal seam is 10-25m, high overlying strata are not uniformly settled under high-intensity mining, so that a closed bed separation space is formed between a chalky hard rock aquifer and a Jurassic stable group shale water-resisting layer, underground water stored in the chalky hard rock aquifer is continuously collected to the bed separation space, and once a water diversion crack penetrates through the stable group shale water-resisting layer, strong bed separation water burst is initiated. On the other hand, because the Jurassic formation of the coal bed roof is a weakly consolidated sand and mud layer deposited on the continental facies, a large amount of particles flow into a working face under the action of high-flow-rate water flow, and a sand collapse accident is caused. Based on the analysis, 8 influence factors (coal seam thickness X1, coal seam depth X2, distance between a chalk system aquifer and the coal seam X3, thickness of a chalk system aquifer X4, unit water inflow quantity of the chalk system aquifer X5, overlying rock hard rock rate X6, thickness of a stable group X7, cumulative thickness of mudstones of Yanan group and a Taurolith group X8 and the like) are selected to evaluate the water inrush risk of the research area.
And (4) combining engineering experience and literature data to construct a judgment matrix A.
Figure BDA0003715240140000111
By means of matlab software, the consistency index CI of the judgment matrix A is calculated to be 0.13938, and the consistency ratio CR of the judgment matrix is further calculated to be 0.09885<0.01 according to a formula, namely the consistency index accords with the consistency check standard. Therefore, each impact factor weight value is calculated using matlab, as shown in table 3:
TABLE 3 AHP-based impact factor weight values
Table3 The weight of factors based on AHP
Index (I) X1 X2 X3 X4 X5 X6 X7 X8
Weight value 0.1625 0.02007 0.14652 0.05726 0.11403 0.21834 0.12921 0.15007
And selecting 30 drilling data, and combining the eight influence factors analyzed and selected in the previous step, namely 8 evaluation indexes and 30 evaluation objects exist in the evaluation problem. The measured data are listed in table 4. The measured data were normalized according to equation 8, and the results are shown in table 5.
TABLE 4 measured values of borehole data
Figure BDA0003715240140000112
Figure BDA0003715240140000121
TABLE 5 borehole data normalization results
Figure BDA0003715240140000131
Figure BDA0003715240140000141
According to equation 11, the entropy value and entropy weight of each influencing factor are calculated and shown in table 6.
TABLE 6 influence factor entropy and entropy weight calculation results
Figure BDA0003715240140000142
Since the hard rock rate and settled group thickness are negatively correlated with roof water inrush risk, the weights are set to negative values. Therefore, the results of the AHP-EWM integrated weight calculation are shown in Table 7.
TABLE 7 AHP-EWM synthetic weight results
Figure BDA0003715240140000143
Then, an exponential type variable weight vector is established as follows:
Figure BDA0003715240140000144
according to the clustering analysis, the determined interval values are shown in Table 8, and the variable weight coefficient a is obtained by calculation according to the iterative method 1 ＝0.05,a 2 ＝0.24,a 3 ＝0.13,c＝1.73。
TABLE 8 variable weight function interval values
Figure BDA0003715240140000145
Figure BDA0003715240140000151
According to the formula, the state variable weight of 30 borehole exposure indexes can be calculated, and finally, the partition values of the boreholes obtained based on the analytic hierarchy process-entropy weight process-variable weight process are shown in the table. Using Arcgis software, a plot of the risk of mine sand-bursting water source was obtained (fig. 2).
TABLE 9 zone values for each borehole
Drill numbering 1 2 3 4 5 6 7 8 9 10
Partition value -0.1245 -0.0329 -0.0740 -0.0448 -0.0647 -0.0579 0.0484 0.2002 0.0383 0.1504
Drill hole numbering 11 12 13 14 15 16 17 18 19 20
Partition value 0.1429 0.1308 -0.0385 -0.0185 -0.0583 0.1298 0.1818 0.1554 0.0375 0.1764
Drill numbering 21 22 23 24 25 26 27 28 29 30
Partition value 0.1721 -0.0354 0.0052 0.0827 -0.0308 -0.1301 0.0217 0.0989 -0.0441 0.0376
For the danger identification of a sand bursting source in a mining area, firstly, the sedimentary facies of the Jurassic series Yanan group and the Canro group in the south of the Ordos basin and the main characteristics thereof are summarized by data investigation and well core observation in combination with a logging curve:
(1) and (4) carrying out Yanan group. The Yanan group is a coal-containing and oil-containing layer system, the bottom of the Yanan group is light gray siderite-containing oolitic bauxite mudstone and silty mudstone, and the Yanan group upwards comprises lenticular fine conglomerate, grave-containing coarse sandstone, medium-fine sandstone, carbonaceous mudstone and a coal layer. Under the stable slow sinking environment, the evolution of residual accumulation phase, alluvial fan, river and lake delta phase is carried out, wherein a river sedimentation system is widely developed between the alluvial fan and the lake system sedimentation area.
(2) And (4) carrying out direct loop group. The lower part of the straight set is grayish green and grey white platy staggered stratification, namely fine-grained sandstone inclusion grayish purple wavy bedding mudstone and sandy mudstone; the upper part of the sandstone is mainly grayish green, purple gray siltstone and mottled aluminum mudstone, and the sandstone is grayish green and medium grained sandstone and gravelly coarse sandstone. The deposition thickness of the direct-current group is large, the whole body shows the characteristic of a low-water-level system region, a river facies mainly develops in the range of the current residual basin, the southeast part of the basin is a part of the original deposition center, and the shallow lake facies is mainly deposited. The braided river sedimentation is mainly used in the early stage of the stramonium stage, the meandering river and interlaced river sedimentation are mainly used in the middle and late stages, and the river spreads over the lake, reflecting the process that the fluctuation of the substrate is gradually changed from steep to slow, and the basin is gradually filled with sediment. When the Zuoluo group is deposited, the water body is shallow, the climate is earlier than the delay period, the supply of the crumbles is limited, and the delta does not develop. The distribution of the sedimentary facies bands at this stage is reflected by the deposition in a structurally stable environment.
By lithology analysis and combination with a well logging curve (figure 2), determining that the Ann group and the Rou group of the research area are land facies deposits, mainly comprising lake facies, braided river facies, tortuous flow river facies and alluvial fan facies. And (3) performing single-well sedimentary microphase analysis on the single well by using a sequence stratigraphy theory according to sedimentary facies marks in the research area and combining the data of the rock core, the logging curve and the like, and finally obtaining a sedimentary microphase partition diagram of the Jurassic rock stratum in the mining area.
Based on the existing drilling data, the gyromagneous component was divided into braided river and flooded plain as shown in fig. 4. The braided river flow sedimentation is characterized by large continuous thickness of a sand layer, wide transverse distribution range of a rock stratum, and the rock types including quartz sandstone and feldspar quartz sandstone, and detritus feldspar sandstone and feldspar detritus sandstone. The lower structure of the braided river has good deposition and development, large thickness, no or small thickness of the top layer deposition, coarse granularity of stratum deposition and development of the conglomerate. The flood plain is the deposit formed in low-lying area after the natural dike is washed out by flood, the cementation is poor, and the lithology is mainly gray green mudstone and silty mudstone. Therefore, the stratum of the flooded plain is weaker in cementation and finer in particles, and the particles are easier to migrate under water flow scouring, so that the muddy sand is broken.
As shown in FIG. 5, the thickness of the sands in Yanan group in the research area tends to decrease from north to south, and the sedimentary microfacies are divided into river-free marsh, river-free lake, river-free beach and meandering riverway. It is known that in the meandering stream, sediments are mainly composed of fine sandstone and silty mudstone. The sand body is a lens body with a flat upper part and a convex lower part on the cross section, the periphery of the lens body is surrounded by the fine-grain river flood plain deposit, the sand body substrate has an obvious scouring surface, and the scouring surface has strong undulation. Flood beaches, silt and clay deposits are the main. The wave-like and flood laminae predominate, and the horizontal laminae are visible. Has asymmetric wave marks, dry cracks, rain marks and plant fragments. The river-overflowing lake mainly deposits clay, and is the finest deposit of river deposit. The bedding mainly comprises horizontal bedding, and the dry cracking is common; calcium and iron nodules are common in arid climates. The river-swamp, also called post-shore swamp, is evolved from low-lying ponding areas of river floodbeaches and river-swamps under humid climatic conditions, mainly deposits clay, and deposits peat and silt.
Because the particle migration under the action of rock stratum water flow is mainly determined by particle size components and cementation degree, particularly, a weakly cemented block body with large particles and tiny clay is easier to cause clay loss under the action of water flow, and further causes the disintegration of a rock mass structure. And synthesizing the rock stratum characteristics corresponding to each deposition environment to obtain a meandering river channel which is most prone to generate the sand bursting and mainly comprises fine sandstone and silty mudstone, a river is arranged on the lower side of the river, then a river-swamp is arranged, and finally a river-swamp lake is arranged.
Based on the analyzed deposition microphase of the easy-to-break sand, and by combining with a mine water source danger partition map, the dangerous areas with the easy-to-break water and the easy-to-break sand can be defined to comprise the working faces 21301, 21302, 21303, 21304, 21305, 21306, 22304 and 22306, and in the actual production process, the working faces are determined to have serious water-break sand-break events, which indicates that the method has certain guiding significance for the prediction of the water-break sand-break.
Various corresponding changes and modifications can be made by those skilled in the art based on the above technical solutions and concepts, and all such changes and modifications should be included in the protection scope of the present invention.

Claims (2)

1. A mining overburden sand carrying bed water inrush risk evaluation method is characterized by comprising the following steps:
selecting indexes related to sand bursting accidents of water inrush of the top plate;
determining an index constant weight value based on hierarchical analysis and entropy weight synthesis;
constructing a variable weight function, and determining variable weight values of all indexes;
obtaining a mine sand collapse water source danger zoning map through a constant weight-variable weight model;
obtaining a sand bursting source danger partition map based on the deposition micro-phase;
and (4) integrating the mine sand bursting water source danger subarea diagram and the sand bursting object source danger subarea diagram, and finally, defining a high-risk area of sand bursting.
2. The mining overburden carrying sand-bedding water inrush risk assessment method of claim 1, wherein the construction variable weight function comprises:
definition 1: hypothesis vector
Figure FDA0003715240130000011
Is an n-dimensional constant weight vector satisfying
Figure FDA0003715240130000012
Definition 2: let W have a mapping [0,1 ]] m →(0,1] m ,W(x)＝(w 1 (x),w 2 (x),…w m (x) Ism dimensional variable weight vector, which satisfies the following condition:
(1)w j (x) Is epsilon (0,1) and
Figure FDA0003715240130000013
(2) when j ∈ {1,2, …, m }, there is α j ,β j ∈[0,1]And alpha is j ≤β j ；w j (x 1 ,…,x m ) In the interval [0, alpha ] j ]With x j Monotonically decreasing, in the interval [ beta ] j ,1]Monotonically increasing.
Definition 3: assume that there is a mapping S: [0,1 ]] m →(0,+∞) m (x) converting S to (S) 1 (x),S 2 (x),…,S m (x) Is defined as an m-dimensional variable weight vector, for
Figure FDA0003715240130000014
And alpha is j ≤β j . It satisfies the following conditions:
(1)
Figure FDA0003715240130000015
in the interval [0, alpha ] j ]With x j Monotonically decreasing, in the interval [ beta ] j ,1]Monotonically increasing.
(2) When x is more than or equal to 0 i ≤x k ≤α i ∧α k When there is S i (x)≥S k (x) (ii) a When beta is i ∨β k ≤x i ≤x k Less than or equal to 1, with S i (x)≤S k (x)。
S (x) is a random m-dimensional state variable weight vector;
Figure FDA0003715240130000021
is a random m-dimensional constant weight vector,the modified weight vector is then:
Figure FDA0003715240130000022
the above formula is a sand bursting water source risk evaluation model.
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