Prediction of Water-Blocking Capability of Water-Seepage-Resistance Strata Based on AHP-Fuzzy Comprehensive Evaluation Method—A Case Study
Abstract
:1. Introduction
2. Research Background
2.1. Location and Climate
2.2. Geological Background
2.3. Characteristics of Underground Aquifer
3. Scientific Connotations of WSRS and NWSRZ
3.1. Definition and Classification of WSRS
3.2. Scientific Connotations of NWSRZ
4. Indicators and Membership Functions of WBCWSRS
4.1. WSRS System
4.1.1. Classification of WSRS (T)
- Type I WSRS: a single low-permeability, thick and soft strata. The permeability coefficient is usually less than 10−7 cm/s, and the Protodyakonov coefficient is generally less than 2. In contrast, it features good softening and swelling rate when soaked in water and good fissure self-healing properties. The lateral expansion rate is generally greater than 40%. This type of WSRS mainly uses its lithology to resist water seepage and thus realize WPCM.
- Type II WSRS is usually a thick and hard stratum with high original permeability. Its initial permeability coefficient is generally greater than 10−4 cm/s, and there is no low-permeability soft rock formation, such as clay, loess, mudstone, etc., in this type of WSRS. It usually has poor lithological WBC, while it has high mechanical strength. The WSRS can still maintain its structural integrity under mining disturbances and has good WBC.
- Type III WSRS is a composite stratum composed of soft and hard strata. The Protodyakonov coefficient of the hard rock layer is generally greater than 8. Although the permeability coefficient of hard strata is larger than that of soft rock layers, it can ameliorate the migration and breakage of the overlying strata and ensure that the WSRS maintains structural stability. This type of WSRS has the best WBC.
- Type IV WSRS neither has soft rock formation nor hard rock with extremely high hardness. However, this type of stratum structure still has WBC to some extent.
4.1.2. Vertical Level of WSRS (Hs)
4.1.3. Equivalent Permeability of NWSRS (ke)
4.1.4. Integrity of the WSRS (Si)
4.2. Underground Aquifer System
4.2.1. Water Yield Property (Aw)
4.2.2. Water Table Lowering (Lc)
4.2.3. Recharge of Underground Aquifer (α)
4.3. Coal Extraction System
4.3.1. Coal Mining Method (Mm)
4.3.2. Mining Parameters (P)
5. Mathematical Modeling and Weight Determination of WBCWSRS
5.1. Establishment of Mathematical Evaluation Model for WBCWSRS
5.2. Weight Distribution of Indicators of WBCWSRS
- Calculate the product Mi of each row indicator of the judgment matrix:
- 2.
- Calculate the n-th power root of Mi and obtain Vi:
- 3.
- Normalize Vi:
- 4.
- The obtained Wi is the eigenvector of the judgment matrix:
- 5.
- Calculate the maximum eigenvalue λmax of the matrix :
6. Generalization and Application of the Evaluation Model
6.1. Membership Degree Determination of the Indictors
6.1.1. Thematic Maps of Indicators of WSRS System
Types of WSRS
Vertical Level of WSRS
Equivalent Permeability Coefficient of the NWSRZ
6.1.2. Thematic Maps of Indicators of Underground Aquifer System
6.1.3. Thematic Maps of Indicators of Coal Extraction System
6.2. Comprehensive Evaluation of the WBCWSRS for Yu-Shen Coal Area
6.3. Countermeasures for Maintaining the WBCWSRS
7. Influence of Mining Methods on Underground Aquifer and WSRS
7.1. Construction of Fluid–Solid Coupling Numerical Model
7.2. Water Table Lowering under Various Mining Methods
7.3. Constraints of Ecological Vegetation on Mining Methods and Mining Parameters
8. Discussion
- (1)
- In previous studies, relevant scholars used the AHP method to identify the influencing indicators of the WBC of the water-resisting layer, and ranked the importance of the factors according to the weight distribution [68,69,70]. In addition, there are also some scholars who employed AHPF to evaluate the WBC of an aquiclude in a mining area, but all of them take an average value to represent the whole mining area to determine the membership degree of the influencing factors [71,72,73]. Their prediction results are obviously unreasonable, inaccurate and irrational, because the hydrogeological conditions at different locations in the same mining area are obviously varied [74]. Furthermore, different from the traditional evaluation of the WBC of an aquifuge, from the perspective of the mining-induced permeability deterioration rate of the overburden, the concept of “three seepage zones” is firstly put forward in this paper, and the scientific connotations of the nominal WSRZ (after coal extraction), which is important for WPCM, are systematically defined. Additionally, the concept of WSRS (before mining) is proposed, and it is classified into five various types on the basis of the initial permeability, thickness, strength, porosity and the stratigraphic structure of the WSRS [75]. The influence mechanism of the type of WSRS on the vertical level and thickness of the nominal WSRZ is revealed. Subsequently, a comprehensive evaluation mathematical model for predicting the WBCWSRS based on AHPF is established. The innovation of this paper is that the membership degree of the factors of the WSRS for various boreholes is accurately determined based on the hydrogeological conditions of each borehole, and the comprehensive evaluation value of the WBCWSRS of each borehole is obtained precisely. The zoning map of the grade of WBCWSRS for the whole mining area that has been plotted is undoubtedly more accurate than that of the previous research, so as to better guide the implementation of WPCM [76].
- (2)
- The prediction model has wide applicability and can be applied to most mining areas in China. However, in the process of generalizing and applying the model, it should be noted that it cannot be employed in mining areas where the hydrogeological conditions vary greatly from those of the Yu-Shen mining area. For instance, the model cannot be applied to some of the mining areas in Xinjiang province, since the coal seams are generally extremely thick and their mining process is completely different from that of other common mining areas such as the Yu-Shen mining area [77]. Therefore, to accurately predict the impermeability of the WSRS in the process of coal mining in these mining areas, experts and scholars working on WPCM in these coal fields should be invited to analyze the weight distribution of the influencing factors and the membership function again, and then determine the impermeability of the WSRS according to the drilling data at different positions in the mining area.
- (3)
- When using the fluid–solid coupling module of FLAC3D, our predecessors generally only studied the variation in the pore water pressure of the aquifer. They argue that the amplitude of pressure fluctuation can indirectly reflect the impact of coal extraction on the aquifer [78,79,80]. The authors hold the view that the water level fluctuation induced by coal extraction is responsible for the pore water pressure variation of the Quaternary Salawusu formation aquifer. Hence, a simple formula is utilized to convert the variation in pore water pressure into that of the water level of the aquifer. The water table fluctuation reflects the degree of mining disturbance and the permeability deterioration of the WSRS indirectly; thus, it can verify the rationality and accuracy of the prediction model of the WBCWSRS. Moreover, with due consideration of the water table lowering corresponding to four different coal mining methods and the ideal ecological water level of surface vegetation, this paper proposes a mining control method, i.e., macro-adjustment of mining methods and minor adjustment of mining parameters, to achieve ecological preservation and conservation in coal mining.
9. Conclusions
- (1)
- With due consideration of the initial permeability, strength, thickness, rock combination and swelling when soaked in water of the overlying strata, the concept of WSRS is first proposed. The classification system of WSRS is constructed and the WSRS is divided into four types. Based on the mining-induced damage and permeability deterioration of the overlying strata, the overburden is divided into the “pipe flow zone”, “water seepage zone” and “NWSRZ” from bottom to top. The partition standard of the new “three zones” from the perspective of mining-induced permeability deterioration is given, i.e., pipe flow zone (k/k0 > 1000), water seepage zone (20 < k/k0 < 1000) and NWSRZ (1 < k/k0 < 20).
- (2)
- The AHPF is employed to construct a prediction model of the WBCWSRS. In the AHP model, three indicators, i.e., WSRS system, underground aquifer system and coal extracting system, are selected as sub-factors, and nine factors, such as the vertical level of WSRS, are selected as third-tier indicators. The weight distribution of influencing factors at all levels is determined. Among the secondary indicators, the WSRS system is the most important one. The equivalent permeability coefficient of NWSRZ is the most significant factor among the third-level indicators, followed by the vertical level of WSRS and the mining method.
- (3)
- The thematic maps of factors affecting the WBCWSRS in the Yu-Shen mining area are drawn. According to the established membership functions of the third-tier factors, the membership degrees of the indicators at the third level are determined. Combined with the weight distribution, the comprehensive evaluation values of the WBCWSRS for 400 boreholes in the whole mining area are calculated under backfill mining, narrow strip mining, slice mining and longwall cave mining. The Kriging interpolation method is employed to draw the contour map of Φ. According to the zoning map of Φ in the entire coal area, the WBCWSRS in the mining area is classified into five categories, namely extremely high (0.9 < Φ < 1), high (0.8 < Φ < 0.9), medium (0.7 < Φ < 0.8), low (0.6 < Φ < 0.7) and extremely low (Φ < 0.6).
- (4)
- Corresponding countermeasures are put forward for the WSRS with various WBC. For areas with no Salawusu aquifer or with extremely high WBCWSRS, longwall cave mining can be selected. The coordinated mining methods, such as slice mining, can be employed to achieve WPCM in the areas with high WBCWSRS. For areas with medium WBCWSRS, the partial mining methods, including narrow strip mining, room-and-pillar mining and height-limited mining, can be employed. Moreover, backfill mining is an ideal method to realize WPCM for areas with low WBCWSRS. In view of the areas with extremely low WBCWSRS, such as the stratigraphic structure of burnt rock, WSRS reconstruction or underground reservoir construction can be employed to achieve WPCM in the sense of blocking and dredging.
- (5)
- The fluid–solid coupling module of FLAC3D is employed to simulate the variation law of the groundwater level under backfill mining, narrow strip mining, slice mining and longwall cave mining. The water level drop of the Salawusu aquifer corresponding to the four mining methods is 0.22 m, 1.33 m, 5.98 m and 6.64 m, respectively, which indirectly suggests the various impacts of the four mining methods on the stability and integrity of the WBCWSRS. Two mining methods, such as backfill mining and narrow strip mining, which have been optimized in terms of their mining parameters, are determined to meet the water demand of ecological vegetation in the study area.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
WPCM | water-preserving coal mining |
NWSRZ | nominal water-seepage-resisting zone |
WSRS | water-seepage-resistance strata |
WBC | water-blocking capacity |
WBCWSRS | water-blocking capacity of water-seepage-resistance strata |
AHPF | AHP-fuzzy comprehensive evaluation |
WCFZ | water-conducting fracture zone |
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Lithology | Permeability Coefficient (cm/s) |
---|---|
Clay | <10−7 |
Loess | 3 × 10−4–6 × 10−3 |
Siltstone | 6 × 10−4–1 × 10−3 |
Fine sandstone | 1 × 10−3–6 × 10−3 |
Medium sandstone | 6 × 10−3–2 × 10−2 |
Coarse sandstone | 2 × 10−2–6 × 10−2 |
Circular gravel | 6 × 10−2–1 × 10−1 |
Gravel | 1 × 10−1–6 × 10−1 |
Water Richness | Thickness (m) | Unit Water Inflow (L·s−1·m−1) | Permeability Coefficient (m·d−1) |
---|---|---|---|
Very high | >30 | >10 | >50 |
High | 15–30 | 5–10 | 10–50 |
Medium | 5–15 | 0.1–5 | 1–10 |
Low | 1–5 | 0.005–0.1 | 0.01–1 |
Very low | <1 | <0.005 | <0.01 |
Grade | Type | Φ Value | Remark |
---|---|---|---|
Ⅰ | Very high | Φ > 0.90 | The underground aquifer can completely be preserved and conserved since the WSRS is fully capable of resisting water seepage. |
Ⅱ | High | 0.90 ≥ Φ > 0.80 | Mining activities exert little influence on the WBCWSRS. Micro water seepage may occur in the WSRS. However, it is too small to be emphasized, and the WPCM can still be achieved under this situation. |
Ⅲ | Moderate | 0.80 ≥ Φ > 0.70 | Mining-induced migration of overburden aggregates, and fractures with moderate aperture are generated and developed in the WSRS, contributing to the degradation of WBCWSRS. Underground water is prone to penetrating through the WSRS and then percolating into the mined-out area. However, this is controllable by taking countermeasures, such as partial mining and harmonic mining. |
Ⅳ | Low | 0.70 ≥ Φ ≥ 0.60 | The WSRS has been slightly broken and interconnected fractures with wide aperture from the bottom to the top of WSRS have been formed. It is necessary to use backfill mining to maintain the integrity of WSRS. Otherwise, water inrush may happen without any countermeasures being taken. |
Ⅴ | Extremely low | 0.60 > Φ | The WSRS is totally broken and water and sand inrush will occur; the mining activities should be strictly prohibited. |
Matrix | Sort Vector | λmax | C.I. | R.I. | C.R. |
---|---|---|---|---|---|
A~B | (0.5502, 0.2395, 0.2103) | 3.0722 | 0.0361 | 0.52 | 0.0690 |
B1~C | (0.1413, 0.2830, 0.4240, 0.1517) | 4.0817 | 0.0272 | 0.89 | 0.0310 |
B2~C | (0.5453, 0.2726, 0.1821) | 3.0017 | 0.0009 | 0.52 | 0.0016 |
B3~C | (0.7500, 0.2500) | 2 | 0 | 0 | 0 |
Weights of Layer B | Weights of Layer C |
---|---|
WSRS system B1 0.5502 | The classification of the WSRS C1 0.0777 |
The vertical level of WSRS C2 0.1557 | |
The equivalent permeability of NWSRZ C3 0.2333 | |
The integrity of WSRS C4 0.0835 | |
Underground aquifer system B2 0.2395 | Water yield property C5 0.1306 |
Water table lowering C6 0.0653 | |
Recharge C7 0.0436 | |
Coal extraction system B3 0.2103 | Mining methods C8 0.1577 |
Mining parameters C9 0.0526 | |
Total of layer B 1.0000 | Total of layer C 1.0000 |
Strata | Bulk Density (kN/m3) | Bulk Modulus (GPa) | Shear Modulus (GPa) | Friction Angle (°) | Cohesion (MPa) | Tensile Strength (MPa) |
---|---|---|---|---|---|---|
Fine sandstone | 26 | 30.8 | 20.3 | 35 | 5.6 | 4.0 |
Sandstone | 25 | 2.5 | 2.3 | 36 | 2.2 | 1.3 |
Clay | 19 | 0.28 | 0.093 | 25 | 0.85 | 0.35 |
Siltstone | 24 | 16.1 | 11.6 | 21 | 2.0 | 1.2 |
Gritstone | 25 | 20.8 | 11.9 | 23 | 3.0 | 1.4 |
Mudstone | 22 | 8.3 | 4.3 | 25 | 2.1 | 1.0 |
Medium sandstone | 25 | 23.1 | 14.5 | 2.8 | 4.4 | 2.0 |
Coal/filling body | 18/17 | 2.2/0.13 | 0.76/0.11 | 20/36 | 1/0.19 | 18.8/18.0 |
Vegetation Type | Water Level and the Growth of Vegetation | |||
---|---|---|---|---|
Salix mongolica | <1.5 m (Flourishing) | 1.5–3.0 m (Decent) | 3.0–5.0 m (Regular) | >5.0 m (Terrible) |
Artemisia annua | <1.5 m (Flourishing) | 1.5–3.0 m (Decent) | 3.0–5.0 m (Regular) | >5.0 m (Terrible) |
Populus diversifolia | <1.5 m (Flourishing) | 1.5–3.0 m (Decent) | 3.0–5.0 m (Regular) | >5.0 m (Terrible) |
Dryland willow | <3.0 m (Flourishing) | 3.0–7.0 m (Decent) | 7.0–12.0 m (Regular) | >12.0 m (Terrible) |
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Ma, L.; Xu, Y.; Ngo, I.; Wang, Y.; Zhai, J.; Hou, L. Prediction of Water-Blocking Capability of Water-Seepage-Resistance Strata Based on AHP-Fuzzy Comprehensive Evaluation Method—A Case Study. Water 2022, 14, 2517. https://doi.org/10.3390/w14162517
Ma L, Xu Y, Ngo I, Wang Y, Zhai J, Hou L. Prediction of Water-Blocking Capability of Water-Seepage-Resistance Strata Based on AHP-Fuzzy Comprehensive Evaluation Method—A Case Study. Water. 2022; 14(16):2517. https://doi.org/10.3390/w14162517
Chicago/Turabian StyleMa, Liqiang, Yujun Xu, Ichhuy Ngo, Yangyang Wang, Jiangtao Zhai, and Lixiao Hou. 2022. "Prediction of Water-Blocking Capability of Water-Seepage-Resistance Strata Based on AHP-Fuzzy Comprehensive Evaluation Method—A Case Study" Water 14, no. 16: 2517. https://doi.org/10.3390/w14162517
APA StyleMa, L., Xu, Y., Ngo, I., Wang, Y., Zhai, J., & Hou, L. (2022). Prediction of Water-Blocking Capability of Water-Seepage-Resistance Strata Based on AHP-Fuzzy Comprehensive Evaluation Method—A Case Study. Water, 14(16), 2517. https://doi.org/10.3390/w14162517