# Quantitative Evaluation for the Threat Degree of a Thermal Reservoir to Deep Coal Mining

Authors: Yun Chen; Xinyi Wang; Yanqi Zhao; Haolin Shi; Xiaoman Liu; Zhigang Niu
Journal: Geofluids
 (2020)

---

## Abstract

Taking the Suiqi coalfield located in North China as the object, where the coal seam burial depth is more than 1100 m, the water abundance of the roof pore thermal storage aquifer is better than average, the ground temperature is abnormally high, and hydrogeological data are relatively lacking, this paper selects and determines eight index factors that influence the mining of the coalfield. Based on the analytic hierarchy process (AHP), the index factor weight is defined, and then, the threat degree of the roof thermal storage aquifer to the coal mining is quantitatively evaluated and divided by using the fuzzy variable set theory. The evaluation results show that the threat degree of the roof in the eastern region is generally greater than that in the western region and that the closer it is to the coal seam outcrop line, the higher the threat degree is; near the boreholes, in the areas Qs1,Qs5, Qs8, Sx1, Tk5, Zc4, and Zc7, which are close to the hidden outcrop line of the coal seam, the classification characteristic value of the threat degree is greater than 3.5, which is in the high-threat zone for disasters caused by roof thermal storage aquifers during coal seam mining. The area above the medium-threat zone accounts for 71.82% of the total study area, indicating that deep coal mining is affected by multiple factors and that roof water and heat disasters are more likely to occur.


---

## Body

## 1. Introduction

In North China coalfields and southern Ordos Basin coalfields, minable coal seams are directly or indirectly covered by thermal storage aquifers of different thicknesses and coal seam mining operations face the serious threats of double roof water inrush and geothermal disasters. For example, the normal water inflow of a coal mine in the southern margin of the Ordos Basin reaches 106,520 m3/d and the water temperature at a depth of 700 m reaches 41°C, which greatly affect the normal production of the coal mine. To ensure the safety of underground mining engineering, the threat degree of the roof thermal storage aquifer has become an urgent problem that needs to be solved in coal mine production through scientific evaluation.Many scholars have carried out a series of research works on the problem of coal seam roof disasters. The theories and methods formed mainly include the “upper three zones” theory [1–3], the “key layer” theory [4], the “three maps-double prediction method” [5], the mathematical comprehensive evaluation method [6], and the numerical simulation method [7]. Among them, the “upper three zones” theory is the most widely used, and the corresponding empirical formula calculation guides the prediction, evaluation, and prevention of a coal seam roof water inrush [8, 9]. In recent years, some scholars have used comprehensive methods to solve practical production problems. For example, Booth and Breuer and Wu et al. applied MODFLOW software to simulate the hydrological effects of shallow aquifers under the influence of long-wall mining, put forward the change rule of hydrological parameters, such as the water head with the mining time and space, and hypothesized that the cracks produced during mining caused the water head drop of the aquifer system [10, 11]. Zhou et al. established a conceptual model of mine water inrush composed of a core network, an underground monitoring network, and an operating system, and the underground excavation and water inrush disaster process can be simulated by using the raw underground data [12]. Zhang et al. obtained the height of the “upper three zones” by numerical simulation and used it to study the roof overburden failure [13]. Yang and Sun determined the height of the water flowing through the fractured zone by using a field measurement, numerical simulation, and empirical formulas in the “upper three zones” theory to reasonably determine the size of a waterproof safety coal pillar [14]. Yao et al. used numerical simulation software to simulate the distribution characteristics of the water flowing fracture zone and the seepage characteristics of the roof water during the mining of the workface; additionally, the water inrush risk of the roof aquifer was analyzed [15]. Based on the gray correlation analytic hierarchy process, Zhang and Yang proposed a prediction model for the roof water inrush when mining a shallow coal seam, and the model was verified with engineering examples [16]. Wu et al. and Zeng et al. studied the height of the water flowing fracture zone of the coal seam roof and the richness of the water-rich aquifer and then evaluated the water inrush risk of the aquifer according to the water-rich partition map [17, 18]. Ren and Wu revised the “three figure double prediction method” and evaluated the risk of water inrush in the area where the height of the caving zone formed by coal mining is lower than the elevation of the roof aquifer [19]. Rezaei and Guo et al. used a neural network intelligent prediction model to determine the height of the water flowing fracture zone and evaluate the performance of the model by using a variety of performance indicators (correlation coefficients, variances, etc.) [20, 21]. Ruan et al. proposed a prediction model for the water inrush based on the AHP and the Dempster-Shafer evidence theory, and the feasibility and applicability of the model were also verified [22].Obviously, the above research results are mainly focused on the prediction and prevention of roof water disasters, while there are few studies on the evaluation of the threat degree of water hazard under the superimposed effect of high ground temperature. In addition, the existing methods needing to be improved generally predict the possibility of roof water inrush based on stratum lithology and mining influence, which fails to fully reflect the combined effects of multiple factors such as geology, hydrogeology, geothermal field, and mining failure. Therefore, it is of great significance to carry out research on the threat degree of water-heat coupling disaster under deep coal mining conditions.In this paper, taking the Suiqi coalfield located in the North China coalfield area as the object, based on the collected and measured geothermal well and exploration borehole data, the key evaluation indicators among factors such as the geology, hydrogeology, geothermal field, and mining failure were selected. Then, based on fractal theory, AHP, and fuzzy variable set theory, a mathematical model is constructed, by which the impact degree of the thermal storage aquifer on deep coal mining was quantitatively evaluated. The results can provide technical support for the layout of mining engineering and safety production under the cover of a thermal storage aquifer and can also provide a reference for the identification of roof water and heat disasters in other mining areas in the North China coalfield.


## 2. Geological and Hydrogeological Characteristics

The Suiqi coalfield (Figure1), which encompasses an area of approximately 4900 km2, is located at the junction of Kaifeng City, Shangqiu City, and Zhoukou City in the central part of the North China coalfield area. At a burial depth of 1100~2000 m is the no. 21 coal seam, whose average thickness and coal reserves are 5.3 m and 23 billion tons, respectively. With the gradual depletion of coal resources in other areas, to meet the needs of economic and social development, the mining of coal resources in this coalfield will be imperative.Figure 1
Schematic diagram of the location and geological structure of the Suiqi coalfield.


### 2.1. Geological Characteristics

According to the drilling data, the strata overlying the no. 21 coal seam in the coalfield area include the Shanxi Formation (P1sh) and the Lower Shihezi Formation (P1x) of the Permian System, the Neogene System (N), and the Quaternary System (Q). The combined geological column of the stratum can be seen in Figure 2.Figure 2
Combined geological column of the stratum.The geological structure in this area is relatively developed (Figure1), with Changsi anticline in the north and Taikang syncline in the south. The faults mainly include the Liaocheng-Lankao fault, Suixian fault, Minquan-Yucheng fault, Cuiqiao fault, and other high-angle normal faults. The faults have large drops and extensions, and the occurrence factors are shown in Table 1. These geological structures have destroyed the occurrence of coal seams at different degrees, leading to a lack of coal-bearing strata and changes in the coal thickness.Table 1
The main geological structures in the study area.
Structure
Occurrence factors
Changsi anticline
The axial direction is NW, with a length of approximately 7 km; the two wings are basically symmetrical, and the inclination angles of the two wings are approximately 5°, which is a wide and gentle anticline
Taikang syncline
The axial direction is NW, with a length of approximately 14 km, and the inclination angles of both wings are more than 20°. It is cut by a series of NE trending faults with incomplete morphologies
Liaocheng-Lankao fault
Strike NE, dip NW, dip angle 40~70°, drop greater than 900~4000m
Suixian fault
Strike NE, dip NW, dip angle 60~70°, drop greater than 1000 m, extension length greater than 30 km
Minquan-Yucheng fault
Strike NW, dip NE, dip angle 50~70°, drop greater than 1500 m
Cuiqiao fault
Strike NW, dip SW, dip angle 60~70°, drop 0-800 m, extension length 35 km


### 2.2. Hydrogeological Characteristics

The roof aquifers affect the excavation of the no. 21 coal seam of the sandstone fracture aquifer group of the Shanxi Formation and Lower Shihezi Formation and the pore aquifer group of the Neogene period. The water richness of the sandstone fissure aquifer group in the Shanxi Formation and the Xiashihezi Formation is relatively weak, and it has little effect on the mining of the no. 21 coal seam in the case of no supply source.The Neogene aquifer group is mainly composed of a fine sand medium that has good water richness with an average unit water inflow of 0.73 L/(s·m). The aquifer group directly affects the mining of the no. 21 coal seam in the hidden outcrop area of the coal seam and indirectly threatens the mining of the no. 21 coal seam in other areas through the underlying aquifer group.The geothermal gradient in this area is between 3.35 and 3.81°C/100 m, with an average value of 3.58°C/100 m. The average temperature of the surrounding rock and groundwater at a depth of 1100 m can reach 54.56°C. The coal mining operations will be affected by abnormally high geothermal disasters.


## 2.1. Geological Characteristics

According to the drilling data, the strata overlying the no. 21 coal seam in the coalfield area include the Shanxi Formation (P1sh) and the Lower Shihezi Formation (P1x) of the Permian System, the Neogene System (N), and the Quaternary System (Q). The combined geological column of the stratum can be seen in Figure 2.Figure 2
Combined geological column of the stratum.The geological structure in this area is relatively developed (Figure1), with Changsi anticline in the north and Taikang syncline in the south. The faults mainly include the Liaocheng-Lankao fault, Suixian fault, Minquan-Yucheng fault, Cuiqiao fault, and other high-angle normal faults. The faults have large drops and extensions, and the occurrence factors are shown in Table 1. These geological structures have destroyed the occurrence of coal seams at different degrees, leading to a lack of coal-bearing strata and changes in the coal thickness.Table 1
The main geological structures in the study area.
Structure
Occurrence factors
Changsi anticline
The axial direction is NW, with a length of approximately 7 km; the two wings are basically symmetrical, and the inclination angles of the two wings are approximately 5°, which is a wide and gentle anticline
Taikang syncline
The axial direction is NW, with a length of approximately 14 km, and the inclination angles of both wings are more than 20°. It is cut by a series of NE trending faults with incomplete morphologies
Liaocheng-Lankao fault
Strike NE, dip NW, dip angle 40~70°, drop greater than 900~4000m
Suixian fault
Strike NE, dip NW, dip angle 60~70°, drop greater than 1000 m, extension length greater than 30 km
Minquan-Yucheng fault
Strike NW, dip NE, dip angle 50~70°, drop greater than 1500 m
Cuiqiao fault
Strike NW, dip SW, dip angle 60~70°, drop 0-800 m, extension length 35 km


## 2.2. Hydrogeological Characteristics

The roof aquifers affect the excavation of the no. 21 coal seam of the sandstone fracture aquifer group of the Shanxi Formation and Lower Shihezi Formation and the pore aquifer group of the Neogene period. The water richness of the sandstone fissure aquifer group in the Shanxi Formation and the Xiashihezi Formation is relatively weak, and it has little effect on the mining of the no. 21 coal seam in the case of no supply source.The Neogene aquifer group is mainly composed of a fine sand medium that has good water richness with an average unit water inflow of 0.73 L/(s·m). The aquifer group directly affects the mining of the no. 21 coal seam in the hidden outcrop area of the coal seam and indirectly threatens the mining of the no. 21 coal seam in other areas through the underlying aquifer group.The geothermal gradient in this area is between 3.35 and 3.81°C/100 m, with an average value of 3.58°C/100 m. The average temperature of the surrounding rock and groundwater at a depth of 1100 m can reach 54.56°C. The coal mining operations will be affected by abnormally high geothermal disasters.


## 3. Index Factor Selection and Weight Determination

### 3.1. Index Factor Selection

The threat degree of the roof thermal storage aquifer during mining in the Suiqi coalfield is mainly controlled by the geological, hydrogeological, and geothermal fields; mining failure; and other factors (as shown in Figure3).Figure 3
Evaluation index factors of the threat degree during deep coal mining.The geological factors include the overburden structure of the coal seam, the rock thickness, the burial depth of the coal seam roof, and the fault characteristics. The roof of the no. 21 coal seam in the coalfield area is an interlayer of brittle sandstone and plastic mudstone. The greater the number of sandstone layers and the greater the thickness of a single layer, the more easily the roof will be damaged under the influence of mining. Therefore, the thickness ratio of the brittle and plastic rock (the ratio of brittle rock thickness to plastic rock thickness) exposed by drilling can be used to characterize the structure and thickness of the coal seam overburden. The deeper the burial depth of the coal seam roof and the thicker the overlying rock layer, the greater the pressure on the roof will be during mining. The more complex the faults of the coal seam roof are, the higher the roof failure height is and the greater the water inrush is. Therefore, the thickness ratio of the brittle and plastic rock, the burial depth of the coal seam roof, and the fault complexity are chosen to reflect the influence of the geological factors in this paper.The hydrogeological factors include the thickness of the aquifer and the water richness within the height of the “upper three zones” of a roof failure. The greater the thickness and the stronger the water richness, the more water that is provided during the inrush it has and the more harmful it is. The thickness of the aquifer and water richness can be obtained from the drilling and field pumping (injection) water test data. Because the Suiqi coalfield is in the exploration stage, no pumping (injection) water test has been carried out at present. In addition, the number of geothermal wells constructed in the area is limited, and it is difficult to obtain the unit water inflow, which characterizes the water richness of the aquifer. In the absence of the unit water inflow, the drill flushing fluid consumption and core recovery rate can be used as a substitute measure [23, 24]. The greater the consumption of flushing fluid during drilling construction, the more developed the pores and cracks in the rock layer are and the stronger the water richness of the aquifer is.The ground temperature of the Suiqi coalfield is abnormally high. To directly show the threat of the ground temperature field to deep coal seam mining, the surrounding rock temperature at the depth of the coal seam roof is used to indicate its influence. In the Suiqi coalfield, the bedrock composed of sandstone and mudstone is separated between the Neogene thermal reservoir aquifer group and the no. 21 coal seam to be mined. The larger the difference between roof failure height and the whole thickness of the bedrock during coal mining, the higher the influence of the Neogene thermal storage aquifer is on the coal seam mining. Therefore, the difference between height of the “upper three zones” and the bedrock thickness is chosen to characterize the impact of a mining failure.In short, it is reasonable and practical to select the following eight elements as index factors to evaluate the threat degree of the overlying thermal aquifer during coal mining operations: the thickness ratio of brittle and plastic rock, the coal seam roof depth, the fault complexity, the aquifer thickness, the borehole flushing fluid consumption, the core recovery rate, the surrounding rock temperature, and the difference between the height of the “upper three zones” and the bedrock thickness.According to the water and heat disaster characteristics of a coal seam roof [1], the difference between the height of the “upper three zones” and the bedrock thickness and the complexity of the fault should be the most important levels among the eight index factors; the aquifer thickness, borehole flushing fluid consumption, core recovery rate, and surrounding rock temperature should be at the second most important influence level, while the coal seam roof depth and thickness ratio of brittle and plastic rock have been reflected in other indexes to some extent, and they should be at the third influence level.


### 3.2. Index Factor Weight

Referring to the existing results [25], the weights of the eight index factors can be determined by AHP. The judgment matrix of the evaluation system composed of the eight index factors is shown in Tables 2–5.Table 2
Judgment matrixA−Bii=1,2,3.
A
B
1
B
2
B
3
w
A
/
B
i
B
1
1
8/9
7/9
0.2925
B
2
9/8
1
9/7
0.3164
B
3
9/7
9/7
1
0.3911
Note: maximum characteristic valueλmax=3.0016, CI=0.0008<0.1, and CR=0.0014<0.1.Table 3
Judgment matrixB1−Cii=1,2,3.
B
1
C
1
C
2
C
3
w
B
1
/
C
i
C
1
1
4/3
1/6
0.1443
C
2
3/4
1
1/5
0.1265
C
3
6
5
1
0.7285
Note: maximum characteristic valueλmax=3.0247, CI=0.0124<0.1, and CR=0.0213<0.1.Table 4
Judgment matrixB2−Cii=1,2,3.
B
2
C
4
C
5
C
6
w
B
2
/
C
i
C
4
1
6/5
3/2
0.4000
C
5
5/6
1
5/4
0.3333
C
6
2/3
4/5
1
0.2667
Note: maximum characteristic 5valueλmax=3, CI=0<0.1, and CR=0<0.1.Table 5
Judgment matrixB3−Cii=1,2.
B
3
C
7
C
8
w
B
3
/
C
i
C
7
1
1/3
0.2500
C
8
3
1
0.7500
Note: maximum characteristic valueλmax=2, CI=0<0.1, and CR=0<0.1.When the AHP model is used to determine the index factor weights, only when it is established that the consistency indexCI<0.1 and the consistency ratio CR<0.1 can the judgment matrix and the single order of the factors be logically consistent and can the calculation results be credible. Obviously, the results of all the levels in this paper have passed the consistency test, and the determined index factor weights are credible. The results are shown in Table 6.Table 6
Weights of the evaluation index factors.
Index factor
C
1
C
2 (m)
C
3
C
4 (m)
C
5 (m3/h)
C
6
C
7 (°C)
C
8
Weight
0.0422
0.0370
0.2131
0.1267
0.1055
0.0844
0.0978
0.2933


## 3.1. Index Factor Selection

The threat degree of the roof thermal storage aquifer during mining in the Suiqi coalfield is mainly controlled by the geological, hydrogeological, and geothermal fields; mining failure; and other factors (as shown in Figure3).Figure 3
Evaluation index factors of the threat degree during deep coal mining.The geological factors include the overburden structure of the coal seam, the rock thickness, the burial depth of the coal seam roof, and the fault characteristics. The roof of the no. 21 coal seam in the coalfield area is an interlayer of brittle sandstone and plastic mudstone. The greater the number of sandstone layers and the greater the thickness of a single layer, the more easily the roof will be damaged under the influence of mining. Therefore, the thickness ratio of the brittle and plastic rock (the ratio of brittle rock thickness to plastic rock thickness) exposed by drilling can be used to characterize the structure and thickness of the coal seam overburden. The deeper the burial depth of the coal seam roof and the thicker the overlying rock layer, the greater the pressure on the roof will be during mining. The more complex the faults of the coal seam roof are, the higher the roof failure height is and the greater the water inrush is. Therefore, the thickness ratio of the brittle and plastic rock, the burial depth of the coal seam roof, and the fault complexity are chosen to reflect the influence of the geological factors in this paper.The hydrogeological factors include the thickness of the aquifer and the water richness within the height of the “upper three zones” of a roof failure. The greater the thickness and the stronger the water richness, the more water that is provided during the inrush it has and the more harmful it is. The thickness of the aquifer and water richness can be obtained from the drilling and field pumping (injection) water test data. Because the Suiqi coalfield is in the exploration stage, no pumping (injection) water test has been carried out at present. In addition, the number of geothermal wells constructed in the area is limited, and it is difficult to obtain the unit water inflow, which characterizes the water richness of the aquifer. In the absence of the unit water inflow, the drill flushing fluid consumption and core recovery rate can be used as a substitute measure [23, 24]. The greater the consumption of flushing fluid during drilling construction, the more developed the pores and cracks in the rock layer are and the stronger the water richness of the aquifer is.The ground temperature of the Suiqi coalfield is abnormally high. To directly show the threat of the ground temperature field to deep coal seam mining, the surrounding rock temperature at the depth of the coal seam roof is used to indicate its influence. In the Suiqi coalfield, the bedrock composed of sandstone and mudstone is separated between the Neogene thermal reservoir aquifer group and the no. 21 coal seam to be mined. The larger the difference between roof failure height and the whole thickness of the bedrock during coal mining, the higher the influence of the Neogene thermal storage aquifer is on the coal seam mining. Therefore, the difference between height of the “upper three zones” and the bedrock thickness is chosen to characterize the impact of a mining failure.In short, it is reasonable and practical to select the following eight elements as index factors to evaluate the threat degree of the overlying thermal aquifer during coal mining operations: the thickness ratio of brittle and plastic rock, the coal seam roof depth, the fault complexity, the aquifer thickness, the borehole flushing fluid consumption, the core recovery rate, the surrounding rock temperature, and the difference between the height of the “upper three zones” and the bedrock thickness.According to the water and heat disaster characteristics of a coal seam roof [1], the difference between the height of the “upper three zones” and the bedrock thickness and the complexity of the fault should be the most important levels among the eight index factors; the aquifer thickness, borehole flushing fluid consumption, core recovery rate, and surrounding rock temperature should be at the second most important influence level, while the coal seam roof depth and thickness ratio of brittle and plastic rock have been reflected in other indexes to some extent, and they should be at the third influence level.


## 3.2. Index Factor Weight

Referring to the existing results [25], the weights of the eight index factors can be determined by AHP. The judgment matrix of the evaluation system composed of the eight index factors is shown in Tables 2–5.Table 2
Judgment matrixA−Bii=1,2,3.
A
B
1
B
2
B
3
w
A
/
B
i
B
1
1
8/9
7/9
0.2925
B
2
9/8
1
9/7
0.3164
B
3
9/7
9/7
1
0.3911
Note: maximum characteristic valueλmax=3.0016, CI=0.0008<0.1, and CR=0.0014<0.1.Table 3
Judgment matrixB1−Cii=1,2,3.
B
1
C
1
C
2
C
3
w
B
1
/
C
i
C
1
1
4/3
1/6
0.1443
C
2
3/4
1
1/5
0.1265
C
3
6
5
1
0.7285
Note: maximum characteristic valueλmax=3.0247, CI=0.0124<0.1, and CR=0.0213<0.1.Table 4
Judgment matrixB2−Cii=1,2,3.
B
2
C
4
C
5
C
6
w
B
2
/
C
i
C
4
1
6/5
3/2
0.4000
C
5
5/6
1
5/4
0.3333
C
6
2/3
4/5
1
0.2667
Note: maximum characteristic 5valueλmax=3, CI=0<0.1, and CR=0<0.1.Table 5
Judgment matrixB3−Cii=1,2.
B
3
C
7
C
8
w
B
3
/
C
i
C
7
1
1/3
0.2500
C
8
3
1
0.7500
Note: maximum characteristic valueλmax=2, CI=0<0.1, and CR=0<0.1.When the AHP model is used to determine the index factor weights, only when it is established that the consistency indexCI<0.1 and the consistency ratio CR<0.1 can the judgment matrix and the single order of the factors be logically consistent and can the calculation results be credible. Obviously, the results of all the levels in this paper have passed the consistency test, and the determined index factor weights are credible. The results are shown in Table 6.Table 6
Weights of the evaluation index factors.
Index factor
C
1
C
2 (m)
C
3
C
4 (m)
C
5 (m3/h)
C
6
C
7 (°C)
C
8
Weight
0.0422
0.0370
0.2131
0.1267
0.1055
0.0844
0.0978
0.2933


## 4. Quantitative Value of Index Factors Divided

### 4.1. Fault Complexity

The fractal theory can be used to distinguish the complexity of the faults in the study area [26]. According to a certain scale, the study area is into several square blocks, and the blocks containing faults are counted and numbered. For block i, first divide it according to the magnification of scale r=1/2, and count the number of block segments containing fault trajectories N1/2; further, divide it according to the scale r=1/4,1/8,1/16⋯, and count the number of blocks Nr containing fault trajectories. Then, the fitting straight line equation of lgr and lgNr can be constructed, and the slope of the line is the fault fractal dimension D of block i. In the same way, the fault fractal dimension of other blocks can be obtained. The larger the fractal dimension D, the more fault traces are contained in the block and the higher the complexity of the fault [27].The study area is divided into 49 blocks, 31 of which are fault blocks, as shown in Figure4. According to the above steps, the fractal dimension values of each block can be determined, and the results are shown in Table 7. Obviously, the fault fractal dimension range is 0.7551~1.5838, with an average value of 1.2432. The correlation coefficients of lgr and lgNr of each block are above 0.96, which indicates that the fractal characteristics of the fault distribution in the study area are good under the selected scale. Additionally, the statistical self-similarity of the fractal structure is good, and the fractal dimension value can be used to represent the complexity of the fault.Figure 4
Block number of the study area.Table 7
Fractal dimension and correlation coefficient of each block.
Block number
Fractal dimension
Correlation coefficient
Block number
Fractal dimension
Correlation coefficient
1
1.2644
0.9893
17
1.5838
0.9981
2
1.0247
0.9665
18
0.9007
0.9836
3
1.1963
0.9879
19
1.3422
0.9730
4
1.0095
0.9648
20
1.4700
0.9820
5
1.0000
1.0000
21
1.3262
0.9705
6
0.7551
0.9884
22
1.3415
0.9903
7
0.6000
0.9000
23
1.5965
0.9823
8
1.1755
0.9854
24
1.4548
0.9841
9
0.9007
0.9836
25
1.4966
0.9853
10
1.1288
0.9968
26
1.3136
0.9862
11
1.4963
0.9721
27
1.5030
0.9809
12
0.8340
0.9902
28
1.2943
0.9927
13
1.2807
0.9661
29
1.4066
0.9713
14
1.5975
0.9823
30
1.3222
0.9950
15
1.0247
0.9665
31
1.0703
0.9749
16
1.8279
0.9941The 28 geological boreholes belong to different blocks, and the fractal dimension representing the fault complexity is shown in Table8.Table 8
Fractal dimension values of the faults in the block where the borehole is located.
Borehole number
Fractal dimension
Drilling number
Fractal dimension
Drilling number
Fractal dimension
Drilling number
Fractal dimension
Qs1
0.7551
Qs8
1.1755
Sx2
1.5838
Zc1
1.4548
Qs2
0.7551
Qs9
1.4963
Sx3
1.5838
Zc2
1.4548
Qs3
1.1755
Qs10
1.4963
Tk1
1.0247
Zc3
1.4966
Qs4
1.1755
Qs11
1.4963
Tk2
1.0247
Zc4
1.4548
Qs5
0.9007
Qs12
1.4963
Tk3
1.3262
Zc5
1.4966
Qs6
0.9007
Qs13
1.4963
Tk4
1.3262
Zc6
1.4966
Qs7
0.9007
Sx1
1.5975
Tk5
1.3262
Zc7
1.4548


### 4.2. Difference between the Height of the “Upper Three Zones” and the Bedrock Thickness

After the coal seam is excavated, the roof overburden rock failure is divided into the collapse zone, crack zone, and bending zone (referred to as the “upper three zones”). According to the code for coal pillar reservation and mining under the pressure of buildings, water bodies, railways, and main shafts [28] (referred to as the “three lower code”) and the code for hydrogeological engineering geological exploration in a mining area [29] (referred to as the “mining area code”), the height of the “upper three zones” can be calculated by using the empirical formula (Table 9). The maximum value is selected as the basic data for the evaluation in this paper [30] (see Table 10). The bedrock thickness of the coal seam roof can be determined by the drilling exploration results, and the difference between the height of the “upper three zones” and the bedrock thickness is shown in Table 10.Table 9
Height calculation formula for the “upper three zones”.
Code category
Overburden lithology
Formula 1
Formula 2
Three lower code
Hard lithology
H
1
=
100
∑
M
/
1.2
∑
M
+
2.0
+
18.9
H
l
=
30
∑
M
+
20
Medium hard lithology
H
l
=
100
∑
M
/
1.6
∑
M
+
3.6
+
15.6
H
l
=
20
∑
M
+
20
Mining area code
Hard lithology
H
l
=
100
∑
M
/
2.4
n
+
2.1
+
21.2
—
Medium hard lithology
H
l
=
100
∑
M
/
3.3
n
+
3.8
+
15.1
—
Note:Hl is the height of the upper three zones (m), M is the cumulative mining thickness (m) (when M<6, n takes 1; when M>6, n takes 2), and the bending zone height is taken as 10 m and is directly included in the formula.Table 10
Difference between the height of the “upper three zones” and the bedrock thickness.
Borehole number
Height of the “upper three zones”
Difference between the height of the “upper three zones” and the bedrock thickness
Borehole number
Height of the “upper three zones”
Difference between the height of the “upper three zones” and the bedrock thickness
Qs1
93.27
-39.73
Sx2
122.79
-143.21
Qs2
84.25
-235.14
Sx3
93.47
-156.05
Qs3
139.20
-87.75
Tk1
103.27
-187.55
Qs4
76.06
-263.67
Tk2
49.46
-70.98
Qs5
77.64
15.20
Tk3
97.70
-204.17
Qs6
93.87
-32.37
Tk4
165.11
103.46
Qs7
121.20
-193.92
Tk5
160.77
77.64
Qs8
118.30
21.58
Zc1
91.45
-37.45
Qs9
96.93
-69.22
Zc2
90.87
-175.14
Qs10
48.07
-62.10
Zc3
40.30
-94.38
Qs11
81.42
-73.09
Zc4
111.87
-35.52
Qs12
76.83
-146.91
Zc5
131.20
81.17
Qs13
73.85
-212.14
Zc6
120.76
-33.32
Sx1
97.92
3.81
Zc7
93.18
23.15


### 4.3. Index Factor Set

The indexes, such as the thickness ratio of brittle and plastic rock, the aquifer thickness, the borehole flushing fluid consumption, the core recovery rate, the coal seam roof depth, and the surrounding rock temperature within the height of the “upper three zones” of roof failure, can be statistically obtained according to the actual information disclosed by the exploration drilling. For the convenience of evaluation, the reciprocal value of the core recovery rate is taken.According to the 28 geological boreholes in the Suiqi coalfield, the quantitative values of the 8 index factors used to evaluate the threat degree of the thermal reservoir aquifer are listed in Table11.Table 11
Evaluation index value of the threat degree of the thermal storage aquifer.
Borehole number
Index factor
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
Qs1
0.8224
1470.12
0.7551
42.09
1.9383
1.3966
56.18
-39.73
Qs2
1.0064
1561.16
0.7551
42.26
0.0416
1.2005
58.68
-235.14
Qs3
0.9559
1468.39
1.1755
62.57
0.2300
1.2092
56.13
-87.75
Qs4
1.0053
1691.00
1.1755
38.65
0.0399
1.1338
62.25
-263.67
Qs5
1.5949
1334.97
0.9007
47.72
3.1990
1.7212
52.46
15.20
Qs6
1.8727
1325.76
0.9007
32.11
0.0506
1.1038
52.21
-32.37
Qs7
0.8099
1526.42
0.9007
48.42
0.0890
1.1792
57.73
-193.92
Qs8
1.7077
1264.02
1.1755
59.43
2.9629
1.5949
50.51
21.58
Qs9
0.7841
1352.94
1.4963
42.60
1.8820
1.2690
52.96
-69.22
Qs10
1.5810
1204.30
1.4963
27.51
0.7990
1.3986
48.87
-62.10
Qs11
1.7095
1364.02
1.4963
51.37
0.2496
1.0834
53.26
-73.09
Qs12
0.1789
1521.00
1.4963
11.66
0.9416
1.1601
57.58
-146.91
Qs13
0.3719
1493.27
1.4963
20.14
0.1394
1.1403
56.81
-212.14
Sx1
0.2864
1261.70
1.5975
17.85
2.1440
1.4327
47.59
3.81
Sx2
0.9584
1393.03
1.5838
39.16
1.6810
1.4085
50.90
-143.21
Sx3
0.6118
1450.83
1.5838
30.39
0.0402
1.3850
52.36
-156.05
Tk1
0.4415
1570.14
1.0247
29.82
0.1799
1.1173
64.51
-187.55
Tk2
0.4131
1376.04
1.0247
14.46
0.0402
1.1390
58.47
-70.98
Tk3
0.5381
1565.08
1.3262
24.13
0.0460
1.0905
64.35
-204.17
Tk4
1.1794
1357.85
1.3262
29.80
2.9678
1.7301
57.91
103.46
Tk5
0.8309
1388.23
1.3262
45.42
2.8799
1.5748
58.85
77.64
Zc1
0.4629
1277.50
1.4548
28.88
2.3816
1.8315
47.99
-37.45
Zc2
0.9228
1460.61
1.4548
38.60
2.2623
1.6000
52.60
-175.14
Zc3
0.2077
1221.04
1.4966
4.31
0.3990
1.1274
46.57
-94.38
Zc4
1.5399
1339.83
1.4548
40.25
2.0805
1.9157
49.56
-35.52
Zc5
1.4500
1202.78
1.4966
37.84
0.1294
1.1806
46.11
81.17
Zc6
2.2950
1318.17
1.4966
50.32
0.1218
1.2579
49.01
-33.32
Zc7
0.4280
1270.66
1.4548
39.88
2.6783
1.6026
47.82
23.15
Mean valueρ
0.9631
1393.9593
1.2972
35.6300
1.1641
1.3566
53.94
-79.56
Standard deviationσ
0.5547
123.3001
0.2623
13.7339
1.1509
0.2446
5.17
98.33


## 4.1. Fault Complexity

The fractal theory can be used to distinguish the complexity of the faults in the study area [26]. According to a certain scale, the study area is into several square blocks, and the blocks containing faults are counted and numbered. For block i, first divide it according to the magnification of scale r=1/2, and count the number of block segments containing fault trajectories N1/2; further, divide it according to the scale r=1/4,1/8,1/16⋯, and count the number of blocks Nr containing fault trajectories. Then, the fitting straight line equation of lgr and lgNr can be constructed, and the slope of the line is the fault fractal dimension D of block i. In the same way, the fault fractal dimension of other blocks can be obtained. The larger the fractal dimension D, the more fault traces are contained in the block and the higher the complexity of the fault [27].The study area is divided into 49 blocks, 31 of which are fault blocks, as shown in Figure4. According to the above steps, the fractal dimension values of each block can be determined, and the results are shown in Table 7. Obviously, the fault fractal dimension range is 0.7551~1.5838, with an average value of 1.2432. The correlation coefficients of lgr and lgNr of each block are above 0.96, which indicates that the fractal characteristics of the fault distribution in the study area are good under the selected scale. Additionally, the statistical self-similarity of the fractal structure is good, and the fractal dimension value can be used to represent the complexity of the fault.Figure 4
Block number of the study area.Table 7
Fractal dimension and correlation coefficient of each block.
Block number
Fractal dimension
Correlation coefficient
Block number
Fractal dimension
Correlation coefficient
1
1.2644
0.9893
17
1.5838
0.9981
2
1.0247
0.9665
18
0.9007
0.9836
3
1.1963
0.9879
19
1.3422
0.9730
4
1.0095
0.9648
20
1.4700
0.9820
5
1.0000
1.0000
21
1.3262
0.9705
6
0.7551
0.9884
22
1.3415
0.9903
7
0.6000
0.9000
23
1.5965
0.9823
8
1.1755
0.9854
24
1.4548
0.9841
9
0.9007
0.9836
25
1.4966
0.9853
10
1.1288
0.9968
26
1.3136
0.9862
11
1.4963
0.9721
27
1.5030
0.9809
12
0.8340
0.9902
28
1.2943
0.9927
13
1.2807
0.9661
29
1.4066
0.9713
14
1.5975
0.9823
30
1.3222
0.9950
15
1.0247
0.9665
31
1.0703
0.9749
16
1.8279
0.9941The 28 geological boreholes belong to different blocks, and the fractal dimension representing the fault complexity is shown in Table8.Table 8
Fractal dimension values of the faults in the block where the borehole is located.
Borehole number
Fractal dimension
Drilling number
Fractal dimension
Drilling number
Fractal dimension
Drilling number
Fractal dimension
Qs1
0.7551
Qs8
1.1755
Sx2
1.5838
Zc1
1.4548
Qs2
0.7551
Qs9
1.4963
Sx3
1.5838
Zc2
1.4548
Qs3
1.1755
Qs10
1.4963
Tk1
1.0247
Zc3
1.4966
Qs4
1.1755
Qs11
1.4963
Tk2
1.0247
Zc4
1.4548
Qs5
0.9007
Qs12
1.4963
Tk3
1.3262
Zc5
1.4966
Qs6
0.9007
Qs13
1.4963
Tk4
1.3262
Zc6
1.4966
Qs7
0.9007
Sx1
1.5975
Tk5
1.3262
Zc7
1.4548


## 4.2. Difference between the Height of the “Upper Three Zones” and the Bedrock Thickness

After the coal seam is excavated, the roof overburden rock failure is divided into the collapse zone, crack zone, and bending zone (referred to as the “upper three zones”). According to the code for coal pillar reservation and mining under the pressure of buildings, water bodies, railways, and main shafts [28] (referred to as the “three lower code”) and the code for hydrogeological engineering geological exploration in a mining area [29] (referred to as the “mining area code”), the height of the “upper three zones” can be calculated by using the empirical formula (Table 9). The maximum value is selected as the basic data for the evaluation in this paper [30] (see Table 10). The bedrock thickness of the coal seam roof can be determined by the drilling exploration results, and the difference between the height of the “upper three zones” and the bedrock thickness is shown in Table 10.Table 9
Height calculation formula for the “upper three zones”.
Code category
Overburden lithology
Formula 1
Formula 2
Three lower code
Hard lithology
H
1
=
100
∑
M
/
1.2
∑
M
+
2.0
+
18.9
H
l
=
30
∑
M
+
20
Medium hard lithology
H
l
=
100
∑
M
/
1.6
∑
M
+
3.6
+
15.6
H
l
=
20
∑
M
+
20
Mining area code
Hard lithology
H
l
=
100
∑
M
/
2.4
n
+
2.1
+
21.2
—
Medium hard lithology
H
l
=
100
∑
M
/
3.3
n
+
3.8
+
15.1
—
Note:Hl is the height of the upper three zones (m), M is the cumulative mining thickness (m) (when M<6, n takes 1; when M>6, n takes 2), and the bending zone height is taken as 10 m and is directly included in the formula.Table 10
Difference between the height of the “upper three zones” and the bedrock thickness.
Borehole number
Height of the “upper three zones”
Difference between the height of the “upper three zones” and the bedrock thickness
Borehole number
Height of the “upper three zones”
Difference between the height of the “upper three zones” and the bedrock thickness
Qs1
93.27
-39.73
Sx2
122.79
-143.21
Qs2
84.25
-235.14
Sx3
93.47
-156.05
Qs3
139.20
-87.75
Tk1
103.27
-187.55
Qs4
76.06
-263.67
Tk2
49.46
-70.98
Qs5
77.64
15.20
Tk3
97.70
-204.17
Qs6
93.87
-32.37
Tk4
165.11
103.46
Qs7
121.20
-193.92
Tk5
160.77
77.64
Qs8
118.30
21.58
Zc1
91.45
-37.45
Qs9
96.93
-69.22
Zc2
90.87
-175.14
Qs10
48.07
-62.10
Zc3
40.30
-94.38
Qs11
81.42
-73.09
Zc4
111.87
-35.52
Qs12
76.83
-146.91
Zc5
131.20
81.17
Qs13
73.85
-212.14
Zc6
120.76
-33.32
Sx1
97.92
3.81
Zc7
93.18
23.15


## 4.3. Index Factor Set

The indexes, such as the thickness ratio of brittle and plastic rock, the aquifer thickness, the borehole flushing fluid consumption, the core recovery rate, the coal seam roof depth, and the surrounding rock temperature within the height of the “upper three zones” of roof failure, can be statistically obtained according to the actual information disclosed by the exploration drilling. For the convenience of evaluation, the reciprocal value of the core recovery rate is taken.According to the 28 geological boreholes in the Suiqi coalfield, the quantitative values of the 8 index factors used to evaluate the threat degree of the thermal reservoir aquifer are listed in Table11.Table 11
Evaluation index value of the threat degree of the thermal storage aquifer.
Borehole number
Index factor
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
Qs1
0.8224
1470.12
0.7551
42.09
1.9383
1.3966
56.18
-39.73
Qs2
1.0064
1561.16
0.7551
42.26
0.0416
1.2005
58.68
-235.14
Qs3
0.9559
1468.39
1.1755
62.57
0.2300
1.2092
56.13
-87.75
Qs4
1.0053
1691.00
1.1755
38.65
0.0399
1.1338
62.25
-263.67
Qs5
1.5949
1334.97
0.9007
47.72
3.1990
1.7212
52.46
15.20
Qs6
1.8727
1325.76
0.9007
32.11
0.0506
1.1038
52.21
-32.37
Qs7
0.8099
1526.42
0.9007
48.42
0.0890
1.1792
57.73
-193.92
Qs8
1.7077
1264.02
1.1755
59.43
2.9629
1.5949
50.51
21.58
Qs9
0.7841
1352.94
1.4963
42.60
1.8820
1.2690
52.96
-69.22
Qs10
1.5810
1204.30
1.4963
27.51
0.7990
1.3986
48.87
-62.10
Qs11
1.7095
1364.02
1.4963
51.37
0.2496
1.0834
53.26
-73.09
Qs12
0.1789
1521.00
1.4963
11.66
0.9416
1.1601
57.58
-146.91
Qs13
0.3719
1493.27
1.4963
20.14
0.1394
1.1403
56.81
-212.14
Sx1
0.2864
1261.70
1.5975
17.85
2.1440
1.4327
47.59
3.81
Sx2
0.9584
1393.03
1.5838
39.16
1.6810
1.4085
50.90
-143.21
Sx3
0.6118
1450.83
1.5838
30.39
0.0402
1.3850
52.36
-156.05
Tk1
0.4415
1570.14
1.0247
29.82
0.1799
1.1173
64.51
-187.55
Tk2
0.4131
1376.04
1.0247
14.46
0.0402
1.1390
58.47
-70.98
Tk3
0.5381
1565.08
1.3262
24.13
0.0460
1.0905
64.35
-204.17
Tk4
1.1794
1357.85
1.3262
29.80
2.9678
1.7301
57.91
103.46
Tk5
0.8309
1388.23
1.3262
45.42
2.8799
1.5748
58.85
77.64
Zc1
0.4629
1277.50
1.4548
28.88
2.3816
1.8315
47.99
-37.45
Zc2
0.9228
1460.61
1.4548
38.60
2.2623
1.6000
52.60
-175.14
Zc3
0.2077
1221.04
1.4966
4.31
0.3990
1.1274
46.57
-94.38
Zc4
1.5399
1339.83
1.4548
40.25
2.0805
1.9157
49.56
-35.52
Zc5
1.4500
1202.78
1.4966
37.84
0.1294
1.1806
46.11
81.17
Zc6
2.2950
1318.17
1.4966
50.32
0.1218
1.2579
49.01
-33.32
Zc7
0.4280
1270.66
1.4548
39.88
2.6783
1.6026
47.82
23.15
Mean valueρ
0.9631
1393.9593
1.2972
35.6300
1.1641
1.3566
53.94
-79.56
Standard deviationσ
0.5547
123.3001
0.2623
13.7339
1.1509
0.2446
5.17
98.33


## 5. Evaluation of the Impact Degree

### 5.1. Basic Formula

Leta, b, c, d, and k be the points on the fuzzy domain U (see Figure 5), the interval a,b belongs to the interval c,d, and the point k is located at the midpoint of the interval a,b.Figure 5
Schematic diagram of the location of the intervalsa,b and c,d.If the intervalsa,b and c,d are denoted by A and B, respectively, u is any sample on U. According to the theory of fuzzy variable sets, the relative difference degree can be calculated as follows.Whenu is within interval B and to the left of the k point, then we have the following:(1)DAu=u−ak−aβ,u∈a,k,DAu=−u−ac−aβ,u∈c,a.Whenu is within interval B and to the right of the k point, then we have the following:(2)DAu=u−bk−bβ,u∈k,b,DAu=−u−bd−bβ,u∈b,d.Whenu does not belong to interval B, then we have the following:(3)DAu=−1,where β is an index greater than 0, and usually β=1.After using formulas (1)–(3) to obtain the relative difference degree DAu, the following formula can be used to calculate the relative membership degree μAu:(4)μAu=1+DAu2.If there aren interval levels on the domain U and the sample u is composed of m index factors, the comprehensive relative membership degree of the sample u belonging to level h can be calculated as follows:(5)φhu=1+∑i=1mwi1−μhμip∑i=1mwiμhμipα/p−1,where μhui is the relative membership of the index factor; wi is the weight of the index factor; i=1,2,⋯,m; h=1,2,⋯,n; α is the optimization criterion parameter (α=1 or α=2); and p is the distance parameter (p=1 is the Hamming distance and p=2 is the Euclidean distance).The calculation formula of the level characteristic value of sampleu is as follows:(6)Hu=∑h=1nφhu∑h=1nφhuh.According to the level characteristic valueHu, the level of the sample u can be judged.


### 5.2. Level Matrix Construction

In view of the fact that the overlying thermal storage aquifer in the study area has good water richness and is affected by a high ground temperature, referring to the existing research results [31], the threat degree of the overlying thermal storage aquifer of the coal seam is divided into five levels, i.e., safe, low threat, medium threat, relatively high threat, and high threat, which are expressed as I, II, III, IV, and V, respectively. The corresponding level characteristic values are shown in Table 12.Table 12
Classification of the threat degree of the thermal reservoir aquifer.
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
Level characteristic value
H
≤
2.0
2.0
<
H
≤
2.5
2.5
<
H
≤
3.0
3.0
<
H
≤
3.5
H
>
3.5For a certain evaluation index factor, the intervalsa,b and c,d corresponding to the five levels can be determined according to the mean-standard deviation method [32]. k is the average value of a and b, and the specific calculation formula is shown in Table 13.Table 13
Calculation formula for thea,b and c,d assignment.
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
a
,
b
ρ
−
1.25
σ
,
ρ
−
0.75
σ
ρ
−
0.75
σ
,
ρ
−
0.25
σ
ρ
−
0.25
σ
,
ρ
+
0.25
σ
ρ
+
0.25
σ
,
ρ
+
0.75
σ
ρ
+
0.75
σ
,
ρ
+
1.25
σ
c
,
d
ρ
−
1.5
σ
,
ρ
−
0.5
σ
ρ
−
σ
,
μ
ρ
−
0.5
σ
,
ρ
+
0.5
σ
ρ
,
ρ
+
σ
ρ
+
0.5
σ
,
ρ
+
1.5
σ
k
ρ
−
σ
ρ
−
0.5
σ
ρ
ρ
+
0.5
σ
ρ
+
σ
Note:ρ and σ are the mean and standard deviation of the index factor, respectively; when a or c is less than 0, its value is 0.According to the assignment criteria in Table13, the AB, CD, and K matrices are composed of the index factors and threat levels can be obtained, as shown in Tables 14–16.Table 14
Composition of matrixAB.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
[0.27, 0.55]
[0.55, 0.82]
[0.82, 1.10]
[1.10, 1.38]
[1.38, 1.66]
C
2
[1239.83, 1301.48]
[1301.48, 1363.13]
[1363.13, 1424.78]
[1424.78, 1486.43]
[1486.43, 1548.08]
C
3
[0.97, 1.10]
[1.10, 1.23]
[1.23, 1.36]
[1.36, 1.49]
[1.49, 1.63]
C
4
[18.46, 25.33]
[25.33, 32.20]
[32.20, 39.06]
[39.06, 45.93]
[45.93, 52.80]
C
5
[0, 0.30]
[0.3, 0.88]
[0.88, 1.45]
[1.45, 2.03]
[2.03, 2.60]
C
6
[1.05, 1.17]
[1.17, 1.30]
[1.30, 1.42]
[1.42, 1.54]
[1.54, 1.66]
C
7
[47.48, 50.06]
[50.06, 52.65]
[52.65, 55.23]
[55.23, 57.82]
[57.82, 60.40]
C
8
[-202.48, -153.31]
[-153.31, -104.15]
[-104.15, -54.98]
[-54.98, -5.81]
[-5.81, 43.35]Table 15
Composition of matrixCD.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
[0.13, 0.69]
[0.41, 0.96]
[0.69, 1.24]
[0.96, 1.52]
[1.24, 1.80]
C
2
[1209.01, 1332.31]
[1270.66, 1393.96]
[1332.31, 1455.61]
[1393.96, 1517.26]
[1455.61, 1578.91]
C
3
[0.90, 1.17]
[1.03, 1.30]
[1.17, 1.43]
[1.30, 1.56]
[1.43, 1.69]
C
4
[15.03, 28.76]
[21.90, 35.63]
[28.76, 42.50]
[35.63, 49.36]
[42.50, 56.23]
C
5
[0, 0.59]
[0.01, 1.16]
[0.59, 1.74]
[1.16, 2.32]
[1.74, 2.89]
C
6
[0.99, 1.23]
[1.11, 1.36]
[1.23, 1.48]
[1.36, 1.60]
[1.48, 1.72]
C
7
[46.19, 51.36]
[48.77, 53.94]
[51.36, 56.52]
[53.94, 59.11]
[56.52, 61.69]
C
8
[-227.07, -128.73]
[-177.90, -79.56]
[-128.73, -30.4]
[-79.56, 18.77]
[-30.4, 67.94]Table 16
Composition of matrixK.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
0.4084
0.6858
0.9631
1.2405
1.5178
C
2
1270.66
1332.31
1393.96
1455.61
1517.26
C
3
1.0349
1.1661
1.2972
1.4284
1.5595
C
4
21.8961
28.7631
35.6300
42.4970
49.3639
C
5
0.0132
0.5887
1.1641
1.7396
2.3150
C
6
1.1120
1.2343
1.3566
1.4789
1.6012
C
7
48.7721
51.3561
53.9400
56.5240
59.1079
C
8
-177.8983
-128.7312
-79.5640
-30.3969
18.7703


### 5.3. Evaluation Results

For the borehole Qs1, the relative difference degree and relative membership degree (as shown in Tables17 and 18) can be obtained by using formulas (1)–(6); then, the comprehensive membership degree and level characteristic values (as shown in Tables 19 and 20) under different parameters α and p can be further calculated. The calculation results show that the average level characteristic value of borehole Qs1 is 3.8603, which belongs to a high-threat area according to the classification standard in Table 12. According to the calculation steps of borehole Qs1, the level characteristic values of 28 boreholes can be given in turn, as shown in Table 21.Table 17
Relative difference matrix of borehole Qs1.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
-1
-0.0171
0.0171
-1
-1
C
2
-1
-1
-1
0.5291
-0.5292
C
3
-1
-1
-1
-1
-1
C
4
-1
-1
-0.8808
0.8821
-1
C
5
-1
-1
-1
0.3162
-0.3162
C
6
-1
-1
0.39
-0.39
-1
C
7
-1
-1
-0.6218
0.6242
-1
C
8
-1
-0.5081
-0.6204
0.6203
-1Table 18
Relative membership matrix of borehole Qs1.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
0
0.4914
0.5086
0
0
C
2
0
0
0
0.7646
0.2354
C
3
0
0
0
0
0
C
4
0
0
0.0596
0.9410
0
C
5
0
0
0
0.6581
0.3419
C
6
0
0
0.6950
0.3050
0
C
7
0
0
0.1891
0.8121
0
C
8
0
0
0.1899
0.8101
0Table 19
Comprehensive membership matrix of borehole Qs1.
Parameter assignment
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
α
=
1, p=1
0
0.0207
0.1618
0.5597
0.0448
α
=
1, p=2
0
0.0470
0.1892
0.5505
0.0822
α
=
2, p=1
0
0.0004
0.0359
0.6177
0.0022
α
=
2, p=2
0
0.0024
0.0516
0.6000
0.0080Table 20
Level characteristic values of borehole Qs1.
Parameter assignment
Threat level
Sum
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
α
=
1, p=1
0
0.0527
0.6169
2.8446
0.2845
3.7987
α
=
1, p=2
0
0.1081
0.6531
2.5344
0.4731
3.7685
α
=
2, p=1
0
0.0014
0.1643
3.7649
0.0167
3.9472
α
=
2, p=2
0
0.0073
0.2339
3.6254
0.0601
3.9267
Mean value
0
0.0424
0.4170
3.1933
0.2074
3.8603Table 21
Borehole level characteristic value and threat degree level.
Borehole number
Level characteristic value
Threat degree level
α
=
1, p=1
α
=
1, p=2
α
=
2, p=1
α
=
2, p=2
Mean value
Qs1
3.7987
3.7685
3.9472
3.9267
3.8603
V
Qs2
3.1859
3.1691
3.4444
3.4207
3.3050
IV
Qs3
2.5265
2.5628
2.4522
2.5588
2.5250
III
Qs4
2.2011
2.2613
2.0194
2.0668
2.1372
II
Qs5
4.2872
4.1676
4.8764
4.8075
4.5347
V
Qs6
1.8210
1.8441
1.6587
1.6617
1.7464
I
Qs7
2.5865
2.6138
1.8951
1.8889
2.2461
II
Qs8
3.5078
3.4391
4.0806
3.9407
3.7421
V
Qs9
3.4943
3.4589
3.5209
3.5204
3.4986
IV
Qs10
3.1276
3.1309
3.2121
3.2368
3.1768
IV
Qs11
3.2272
3.2326
3.3266
3.3260
3.2781
IV
Qs12
2.9278
2.8802
2.7781
2.6720
2.8145
III
Qs13
2.5854
2.9463
1.7968
2.5684
2.4742
II
Sx1
3.8993
3.9521
4.5876
4.6299
4.2672
V
Sx2
3.0592
3.0541
2.9384
3.0072
3.0147
IV
Sx3
2.5640
2.7300
2.1946
2.5243
2.5032
III
Tk1
1.2672
1.3886
1.0412
1.0935
1.1976
I
Tk2
2.7366
2.9585
2.6189
2.9054
2.8048
III
Tk3
1.8434
2.1897
1.2607
1.7741
1.7670
I
Tk4
3.1855
3.1930
3.0486
2.9762
3.1008
IV
Tk5
3.9012
3.7841
3.9331
3.7070
3.8313
V
Zc1
3.3253
3.3231
3.6613
3.6741
3.4959
IV
Zc2
2.9098
2.7651
2.6888
2.2687
2.6581
III
Zc3
2.7722
3.1029
2.5133
3.2040
2.8981
III
Zc4
3.7228
3.5441
3.9969
3.9215
3.7963
V
Zc5
3.1836
3.1898
3.3773
3.4149
3.2914
IV
Zc6
3.3586
3.4039
3.3745
3.8063
3.4858
IV
Zc7
3.8714
3.8507
4.4635
4.4201
4.1514
VIt can be seen from Table21 that the proportion of the 28 boreholes that are in the high threat and relatively high threat levels is 57.14%, 32.14% of the boreholes are in the medium threat and low threat levels, and 10.71% of the boreholes are in the safe level.Contour maps can be drawn based on the average level characteristic values of the 28 boreholes, and the threat degree division of the overlying thermal storage aquifer under the condition of coal mining can be delineated according to the criteria in Table13, as shown in Figure 6.Figure 6
Threat degree division of the coal seam roof.The overall threat degree of the roof thermal storage aquifer is as follows: the threat degree in the western portion of the study area is less than that in the eastern portion, and the threat degree increases as the hidden outcrop line of the coal seam is approached. Due to the influences of multiple factors, the average level characteristic valueH of the areas near the boreholes Qs1,Qs5, Qs8, Sx1, Tk5, Zc4, and Zc7, which are close to the hidden outcrop line of the coal seam, is greater than 3.5, which are the high-threat areas caused by the roof thermal storage aquifer.According to the statistical results in Figure6, it can be seen that the high-threat zone of the roof thermal storage aquifer accounts for 10.21% of the study area, the relatively high-threat zone accounts for 33.85%, the medium-threat zone accounts for 27.76%, the low-threat zone accounts for 19.76%, and the safe zone accounts for 8.42%. Obviously, the proportion of the area above the medium-threat zone is 71.82%, and the possibility of a roof water and heat disaster accident occurring under coal mining conditions is greater.


### 5.4. Verification of Evaluation Results

According to the “upper three zones” theory of a coal seam roof, when the calculated height of the “upper three zones” is greater than the thickness of the bedrock, the roof failure zone of the coal mining operation will reach the overlying Neogene thermal storage aquifer with strong water richness and good permeability, which will greatly increase the risk of a roof disaster. Therefore, the difference between the thickness of the coal seam roof bedrock and the height of the “upper three zones” (referred to as “difference”) is a common index and a traditional method to evaluate the roof threat level at present. The smaller the “difference” is, the greater the roof threat level is. The areas where the “difference” is negative belong to the high-threat areas of the roof.The “difference” contour of the Suiqi coalfield is shown in Figure7. Obviously, the “difference” in the west is larger than that in the east during the mining of the no. 21 coal seam, which indicates that the roof disaster threat is greater as the hidden outcrop line of the coal seam is approached. In addition, the high-threat area of the roof in Figure 7 is located in the high-threat area and relatively high-threat area in Figure 6, which shows that the evaluation results of the “difference” method and the method adopted in this paper are basically the same. However, the fuzzy variable set method adopted in this paper considers more influencing factors and can obtain more precise evaluation results.Figure 7
Difference contour diagrams between the thickness of the roof bedrock and the height of the “upper three zones.”


## 5.1. Basic Formula

Leta, b, c, d, and k be the points on the fuzzy domain U (see Figure 5), the interval a,b belongs to the interval c,d, and the point k is located at the midpoint of the interval a,b.Figure 5
Schematic diagram of the location of the intervalsa,b and c,d.If the intervalsa,b and c,d are denoted by A and B, respectively, u is any sample on U. According to the theory of fuzzy variable sets, the relative difference degree can be calculated as follows.Whenu is within interval B and to the left of the k point, then we have the following:(1)DAu=u−ak−aβ,u∈a,k,DAu=−u−ac−aβ,u∈c,a.Whenu is within interval B and to the right of the k point, then we have the following:(2)DAu=u−bk−bβ,u∈k,b,DAu=−u−bd−bβ,u∈b,d.Whenu does not belong to interval B, then we have the following:(3)DAu=−1,where β is an index greater than 0, and usually β=1.After using formulas (1)–(3) to obtain the relative difference degree DAu, the following formula can be used to calculate the relative membership degree μAu:(4)μAu=1+DAu2.If there aren interval levels on the domain U and the sample u is composed of m index factors, the comprehensive relative membership degree of the sample u belonging to level h can be calculated as follows:(5)φhu=1+∑i=1mwi1−μhμip∑i=1mwiμhμipα/p−1,where μhui is the relative membership of the index factor; wi is the weight of the index factor; i=1,2,⋯,m; h=1,2,⋯,n; α is the optimization criterion parameter (α=1 or α=2); and p is the distance parameter (p=1 is the Hamming distance and p=2 is the Euclidean distance).The calculation formula of the level characteristic value of sampleu is as follows:(6)Hu=∑h=1nφhu∑h=1nφhuh.According to the level characteristic valueHu, the level of the sample u can be judged.


## 5.2. Level Matrix Construction

In view of the fact that the overlying thermal storage aquifer in the study area has good water richness and is affected by a high ground temperature, referring to the existing research results [31], the threat degree of the overlying thermal storage aquifer of the coal seam is divided into five levels, i.e., safe, low threat, medium threat, relatively high threat, and high threat, which are expressed as I, II, III, IV, and V, respectively. The corresponding level characteristic values are shown in Table 12.Table 12
Classification of the threat degree of the thermal reservoir aquifer.
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
Level characteristic value
H
≤
2.0
2.0
<
H
≤
2.5
2.5
<
H
≤
3.0
3.0
<
H
≤
3.5
H
>
3.5For a certain evaluation index factor, the intervalsa,b and c,d corresponding to the five levels can be determined according to the mean-standard deviation method [32]. k is the average value of a and b, and the specific calculation formula is shown in Table 13.Table 13
Calculation formula for thea,b and c,d assignment.
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
a
,
b
ρ
−
1.25
σ
,
ρ
−
0.75
σ
ρ
−
0.75
σ
,
ρ
−
0.25
σ
ρ
−
0.25
σ
,
ρ
+
0.25
σ
ρ
+
0.25
σ
,
ρ
+
0.75
σ
ρ
+
0.75
σ
,
ρ
+
1.25
σ
c
,
d
ρ
−
1.5
σ
,
ρ
−
0.5
σ
ρ
−
σ
,
μ
ρ
−
0.5
σ
,
ρ
+
0.5
σ
ρ
,
ρ
+
σ
ρ
+
0.5
σ
,
ρ
+
1.5
σ
k
ρ
−
σ
ρ
−
0.5
σ
ρ
ρ
+
0.5
σ
ρ
+
σ
Note:ρ and σ are the mean and standard deviation of the index factor, respectively; when a or c is less than 0, its value is 0.According to the assignment criteria in Table13, the AB, CD, and K matrices are composed of the index factors and threat levels can be obtained, as shown in Tables 14–16.Table 14
Composition of matrixAB.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
[0.27, 0.55]
[0.55, 0.82]
[0.82, 1.10]
[1.10, 1.38]
[1.38, 1.66]
C
2
[1239.83, 1301.48]
[1301.48, 1363.13]
[1363.13, 1424.78]
[1424.78, 1486.43]
[1486.43, 1548.08]
C
3
[0.97, 1.10]
[1.10, 1.23]
[1.23, 1.36]
[1.36, 1.49]
[1.49, 1.63]
C
4
[18.46, 25.33]
[25.33, 32.20]
[32.20, 39.06]
[39.06, 45.93]
[45.93, 52.80]
C
5
[0, 0.30]
[0.3, 0.88]
[0.88, 1.45]
[1.45, 2.03]
[2.03, 2.60]
C
6
[1.05, 1.17]
[1.17, 1.30]
[1.30, 1.42]
[1.42, 1.54]
[1.54, 1.66]
C
7
[47.48, 50.06]
[50.06, 52.65]
[52.65, 55.23]
[55.23, 57.82]
[57.82, 60.40]
C
8
[-202.48, -153.31]
[-153.31, -104.15]
[-104.15, -54.98]
[-54.98, -5.81]
[-5.81, 43.35]Table 15
Composition of matrixCD.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
[0.13, 0.69]
[0.41, 0.96]
[0.69, 1.24]
[0.96, 1.52]
[1.24, 1.80]
C
2
[1209.01, 1332.31]
[1270.66, 1393.96]
[1332.31, 1455.61]
[1393.96, 1517.26]
[1455.61, 1578.91]
C
3
[0.90, 1.17]
[1.03, 1.30]
[1.17, 1.43]
[1.30, 1.56]
[1.43, 1.69]
C
4
[15.03, 28.76]
[21.90, 35.63]
[28.76, 42.50]
[35.63, 49.36]
[42.50, 56.23]
C
5
[0, 0.59]
[0.01, 1.16]
[0.59, 1.74]
[1.16, 2.32]
[1.74, 2.89]
C
6
[0.99, 1.23]
[1.11, 1.36]
[1.23, 1.48]
[1.36, 1.60]
[1.48, 1.72]
C
7
[46.19, 51.36]
[48.77, 53.94]
[51.36, 56.52]
[53.94, 59.11]
[56.52, 61.69]
C
8
[-227.07, -128.73]
[-177.90, -79.56]
[-128.73, -30.4]
[-79.56, 18.77]
[-30.4, 67.94]Table 16
Composition of matrixK.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
0.4084
0.6858
0.9631
1.2405
1.5178
C
2
1270.66
1332.31
1393.96
1455.61
1517.26
C
3
1.0349
1.1661
1.2972
1.4284
1.5595
C
4
21.8961
28.7631
35.6300
42.4970
49.3639
C
5
0.0132
0.5887
1.1641
1.7396
2.3150
C
6
1.1120
1.2343
1.3566
1.4789
1.6012
C
7
48.7721
51.3561
53.9400
56.5240
59.1079
C
8
-177.8983
-128.7312
-79.5640
-30.3969
18.7703


## 5.3. Evaluation Results

For the borehole Qs1, the relative difference degree and relative membership degree (as shown in Tables17 and 18) can be obtained by using formulas (1)–(6); then, the comprehensive membership degree and level characteristic values (as shown in Tables 19 and 20) under different parameters α and p can be further calculated. The calculation results show that the average level characteristic value of borehole Qs1 is 3.8603, which belongs to a high-threat area according to the classification standard in Table 12. According to the calculation steps of borehole Qs1, the level characteristic values of 28 boreholes can be given in turn, as shown in Table 21.Table 17
Relative difference matrix of borehole Qs1.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
-1
-0.0171
0.0171
-1
-1
C
2
-1
-1
-1
0.5291
-0.5292
C
3
-1
-1
-1
-1
-1
C
4
-1
-1
-0.8808
0.8821
-1
C
5
-1
-1
-1
0.3162
-0.3162
C
6
-1
-1
0.39
-0.39
-1
C
7
-1
-1
-0.6218
0.6242
-1
C
8
-1
-0.5081
-0.6204
0.6203
-1Table 18
Relative membership matrix of borehole Qs1.
Index factor
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
C
1
0
0.4914
0.5086
0
0
C
2
0
0
0
0.7646
0.2354
C
3
0
0
0
0
0
C
4
0
0
0.0596
0.9410
0
C
5
0
0
0
0.6581
0.3419
C
6
0
0
0.6950
0.3050
0
C
7
0
0
0.1891
0.8121
0
C
8
0
0
0.1899
0.8101
0Table 19
Comprehensive membership matrix of borehole Qs1.
Parameter assignment
Threat level
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
α
=
1, p=1
0
0.0207
0.1618
0.5597
0.0448
α
=
1, p=2
0
0.0470
0.1892
0.5505
0.0822
α
=
2, p=1
0
0.0004
0.0359
0.6177
0.0022
α
=
2, p=2
0
0.0024
0.0516
0.6000
0.0080Table 20
Level characteristic values of borehole Qs1.
Parameter assignment
Threat level
Sum
Safe (I)
Low threat (II)
Medium threat (III)
Relatively high threat (IV)
High threat (V)
α
=
1, p=1
0
0.0527
0.6169
2.8446
0.2845
3.7987
α
=
1, p=2
0
0.1081
0.6531
2.5344
0.4731
3.7685
α
=
2, p=1
0
0.0014
0.1643
3.7649
0.0167
3.9472
α
=
2, p=2
0
0.0073
0.2339
3.6254
0.0601
3.9267
Mean value
0
0.0424
0.4170
3.1933
0.2074
3.8603Table 21
Borehole level characteristic value and threat degree level.
Borehole number
Level characteristic value
Threat degree level
α
=
1, p=1
α
=
1, p=2
α
=
2, p=1
α
=
2, p=2
Mean value
Qs1
3.7987
3.7685
3.9472
3.9267
3.8603
V
Qs2
3.1859
3.1691
3.4444
3.4207
3.3050
IV
Qs3
2.5265
2.5628
2.4522
2.5588
2.5250
III
Qs4
2.2011
2.2613
2.0194
2.0668
2.1372
II
Qs5
4.2872
4.1676
4.8764
4.8075
4.5347
V
Qs6
1.8210
1.8441
1.6587
1.6617
1.7464
I
Qs7
2.5865
2.6138
1.8951
1.8889
2.2461
II
Qs8
3.5078
3.4391
4.0806
3.9407
3.7421
V
Qs9
3.4943
3.4589
3.5209
3.5204
3.4986
IV
Qs10
3.1276
3.1309
3.2121
3.2368
3.1768
IV
Qs11
3.2272
3.2326
3.3266
3.3260
3.2781
IV
Qs12
2.9278
2.8802
2.7781
2.6720
2.8145
III
Qs13
2.5854
2.9463
1.7968
2.5684
2.4742
II
Sx1
3.8993
3.9521
4.5876
4.6299
4.2672
V
Sx2
3.0592
3.0541
2.9384
3.0072
3.0147
IV
Sx3
2.5640
2.7300
2.1946
2.5243
2.5032
III
Tk1
1.2672
1.3886
1.0412
1.0935
1.1976
I
Tk2
2.7366
2.9585
2.6189
2.9054
2.8048
III
Tk3
1.8434
2.1897
1.2607
1.7741
1.7670
I
Tk4
3.1855
3.1930
3.0486
2.9762
3.1008
IV
Tk5
3.9012
3.7841
3.9331
3.7070
3.8313
V
Zc1
3.3253
3.3231
3.6613
3.6741
3.4959
IV
Zc2
2.9098
2.7651
2.6888
2.2687
2.6581
III
Zc3
2.7722
3.1029
2.5133
3.2040
2.8981
III
Zc4
3.7228
3.5441
3.9969
3.9215
3.7963
V
Zc5
3.1836
3.1898
3.3773
3.4149
3.2914
IV
Zc6
3.3586
3.4039
3.3745
3.8063
3.4858
IV
Zc7
3.8714
3.8507
4.4635
4.4201
4.1514
VIt can be seen from Table21 that the proportion of the 28 boreholes that are in the high threat and relatively high threat levels is 57.14%, 32.14% of the boreholes are in the medium threat and low threat levels, and 10.71% of the boreholes are in the safe level.Contour maps can be drawn based on the average level characteristic values of the 28 boreholes, and the threat degree division of the overlying thermal storage aquifer under the condition of coal mining can be delineated according to the criteria in Table13, as shown in Figure 6.Figure 6
Threat degree division of the coal seam roof.The overall threat degree of the roof thermal storage aquifer is as follows: the threat degree in the western portion of the study area is less than that in the eastern portion, and the threat degree increases as the hidden outcrop line of the coal seam is approached. Due to the influences of multiple factors, the average level characteristic valueH of the areas near the boreholes Qs1,Qs5, Qs8, Sx1, Tk5, Zc4, and Zc7, which are close to the hidden outcrop line of the coal seam, is greater than 3.5, which are the high-threat areas caused by the roof thermal storage aquifer.According to the statistical results in Figure6, it can be seen that the high-threat zone of the roof thermal storage aquifer accounts for 10.21% of the study area, the relatively high-threat zone accounts for 33.85%, the medium-threat zone accounts for 27.76%, the low-threat zone accounts for 19.76%, and the safe zone accounts for 8.42%. Obviously, the proportion of the area above the medium-threat zone is 71.82%, and the possibility of a roof water and heat disaster accident occurring under coal mining conditions is greater.


## 5.4. Verification of Evaluation Results

According to the “upper three zones” theory of a coal seam roof, when the calculated height of the “upper three zones” is greater than the thickness of the bedrock, the roof failure zone of the coal mining operation will reach the overlying Neogene thermal storage aquifer with strong water richness and good permeability, which will greatly increase the risk of a roof disaster. Therefore, the difference between the thickness of the coal seam roof bedrock and the height of the “upper three zones” (referred to as “difference”) is a common index and a traditional method to evaluate the roof threat level at present. The smaller the “difference” is, the greater the roof threat level is. The areas where the “difference” is negative belong to the high-threat areas of the roof.The “difference” contour of the Suiqi coalfield is shown in Figure7. Obviously, the “difference” in the west is larger than that in the east during the mining of the no. 21 coal seam, which indicates that the roof disaster threat is greater as the hidden outcrop line of the coal seam is approached. In addition, the high-threat area of the roof in Figure 7 is located in the high-threat area and relatively high-threat area in Figure 6, which shows that the evaluation results of the “difference” method and the method adopted in this paper are basically the same. However, the fuzzy variable set method adopted in this paper considers more influencing factors and can obtain more precise evaluation results.Figure 7
Difference contour diagrams between the thickness of the roof bedrock and the height of the “upper three zones.”


## 6. Conclusions

(1)
Based on the analysis of multiple factors affecting coal mining, eight factors are selected as the index factors for threat assessment, including the thickness ratio of brittle and plastic rock, the coal seam roof depth, the fault complexity, the aquifer thickness, the borehole flushing fluid consumption, the core recovery rate, the surrounding rock temperature, and the difference between the height of the “upper three zones” and the bedrock thickness, which provide a guarantee for the comprehensive and accurate identification of water and heat disasters of coal seam roofs
(2)
The mathematical model of the threat degree evaluation is established by coupling the AHP and the fuzzy variable set theory. Based on the weights and quantitative values of the eight index factors, the threat degree of the thermal storage aquifer to the deep coal mining operation was identified and the threat degree was divided, which lays the foundation for the prevention and control of water and heat disasters of the overlying strata and safe mining
(3)
The quantitative evaluation of the threat degree of the thermal storage aquifer shows that the risk in the western region is less than that in the eastern region, and the closer it is to the outcrop line of the coal seam, the greater the risk; in the areas near the boreholes Qs1,Qs5, Qs8, Sx1, Tk5, Zc4, and Zc7, which are close to the hidden outcrop line of the coal seam, the classification characteristic values of the threat degree are greater than 3.5, which belong to high-threat areas caused by the roof thermal storage aquifer. In these areas, roof water and heat disasters are prone to occur during coal mining
(4)
According to the threat degree of the thermal storage aquifer of the coal seam roof, comparing the evaluation results of the traditional “upper three zones” theory (taking the difference between the thickness of the bedrock and the height of the “upper three zones” as parameters) with modern mathematical methods (coupling AHP and variable fuzzy set theory), it can be obtained that the evaluation results of the two methods are basically the same, but the evaluation results of the latter are more precise
(5)
For the entire study area, the high-threat zone accounts for 10.21%, the relatively high-threat zone accounts for 33.85%, the medium-threat zone accounts for 27.76%, the low-threat zone accounts for 19.76%, and the safe zone accounts for 8.42%. The area above the medium-threat zone accounts for 71.82%, which includes a greater possibility of the roof water and a heat disaster occurring during mining of the no. 21 coal seam



---

*Source: 8885633-2020-11-09.xml*