Research on the potential of gas resource development in abandoned mines using matter element extension theory
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摘要:
“双碳”目标下，为了精准研判废弃矿井采动稳定区瓦斯资源开发潜力和找出其影响开发潜力的关键因素，构建了“精选−内联−互补−优化”四位一体为理念的废弃矿井瓦斯资源开发潜力评价方法，最后与工程试验对比，验证评估模型的可行性。“精选”指：首先初步选取大量的评价指标，然后通过德尔菲法和敏感性分析筛选初始指标，去除不符合要求的指标因素；“内联”指：对筛选出的指标，采用DEMATEL-ISM进行内部关联性分析，判定关键指标；“互补”指：首先采用FAHP和熵值法分别对指标进行定性和定量的赋权，然后采用博弈论对指标进行综合权重确定；“优化”指：结合综合权重，采用物元可拓理论计算其关联度，判定废弃矿井瓦斯资源开发潜力等级。结果表明：煤层埋深、煤矿面积是判定废弃矿井瓦斯资源开发潜力的关键指标因素与DEMATEL-ISM模型评价一致；根据物元可拓模型计算的关联度为K3=
0.0575 ，可以判定其开发潜力为“良好”，根据工程试验统计评估可知，13个可采煤层的瓦斯资源量为61.81×108 m3，潘一矿瓦斯资源规模较大，属于中型煤层气田，其开发潜力较大与物元可拓模型评价结论一致，符合实际情况，该模型为研究废弃矿井瓦斯资源开发潜力等级提供方向。-
关键词:
- 废弃矿井 /
- DEMATEL-ISM /
- 模糊层次分析法(FAHP) /
- 熵值法 /
- 博弈论 /
- 物元可拓模型
Abstract:Based on the background of national carbon peak and carbon neutrality, in order to accurately judge the development potential of gas resources in the mining stability area of abandoned mines and find out the key factors affecting the development potential, the author constructs the “selection-inline-complementary-optimization”. “Selecting” refers to: firstly, a large number of evaluation indexes are preliminarily selected, and then the initial indexes are screened by Delphi method and sensitivity analysis to remove the index factors that do not meet the requirements. “Inline” refers to: for the selected indicators, DEMATEL-ISM is used for internal correlation analysis to determine the key indicators. “Complementarity” refers to: firstly, FAHP and entropy method are used to determine the qualitative and quantitative weights of the indicators, and then the game theory is used to determine the comprehensive weights of the indicators. “Optimization” refers to a four-in-one evaluation method for the development potential of abandoned mine gas resources based on the concept of comprehensive weight, using matter-element extension theory to calculate its correlation degree, and determining the development potential level of abandoned mine gas resources. Finally, the feasibility of the evaluation model is verified by comparison with engineering tests. The results show that the buried depth of coal seam and the area of coal mine are the key index factors to determine the development potential of gas resources in abandoned mines, which are consistent with the evaluation of DEMATEL-ISM model. According to the correlation degree calculated by the matter-element extension model, K3 =
0.0575 , it can be judged that its development potential is “good”. According to the statistical evaluation of engineering tests, the gas resources of 13 coal seams are 61.81 × 108 m3. The gas resources of Panyi Mine are large and belong to medium-sized coalbed methane fields. Its development potential is consistent with the evaluation conclusion of the matter-element extension model, which is in line with the actual situation. The model provides a direction for studying the development potential level of gas resources in abandoned mines. -
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图 3 废弃矿井采动稳定区瓦斯资源开发潜力评价指标体系
Figure 3. Evaluation index system for the potential development of gas resources in the stable mining area of abandoned mines
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图 6 煤层瓦斯含量与煤层埋深的关系
Figure 6. Relationship between coal seam gas content and coal seam burial depth
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图 7 潘一煤矿区段划分及位置关系
Figure 7. Division and Position Relationship of Panyi Coal Mine Sections
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图 8 煤层瓦斯含量与煤层面积关系
Figure 8. Relationship between coal seam gas content and coal seam area
表 1 废弃矿井采动稳定区瓦斯资源开发潜力评价初始指标体系及选取依据
Table 1 Initial index system and selection basis of gas resource development potential evaluation in abandoned mine mining stability area
目标层 准则层 指标层 选取依据 参数阈值（范围） 废弃矿井采动稳定区瓦斯资源开发潜力评价指标体系 瓦斯资源量因素 采空区遗煤瓦斯资源量 遗煤越多，瓦斯量越大 潘一矿可采煤层的瓦斯总量为61.81×
108 m3，属于中型煤层气田采空区未动用煤瓦斯资源量 未动用煤越多，瓦斯量越大 邻近层煤瓦斯资源量 邻近层煤越多，瓦斯量越大 煤矿面积 越大，遗煤越多，瓦斯含量越大 54.6717 km2煤炭采出率 越多，遗煤越少 — 煤厚 越厚，瓦斯含量越高 矿井含可采煤层13层，可采煤层平均总厚 30.38 m 资源丰度 越大，价值越大 — 稳定性因素 采空区封闭条件 越好，瓦斯越难逸散 良好 巷道支护完好程度 越好，瓦斯储存空间越大 良好 煤层埋深 越深，地应力越大，瓦斯保存条件越好 −500～−800 m 围岩性质 越硬，岩层透气性越差，瓦斯保存条件越好 砾岩、细砂岩、粗砂岩、粉砂岩 矿井涌水量 越大，抽采成本越多 144.1～177.7 m3/h 瓦斯抽采条件因素 废弃时间 越长，解吸瓦斯越多 6 a 煤层孔裂隙发育程度 越好，孔隙率越高，越有利于抽采 各可采煤层孔隙率为 0.7%～8.3% 煤体破坏程度 越高，渗透率越差，抽采时易堵孔 破坏程度较高 地面钻孔甲烷浓度 越大，瓦斯可利用率越高 — 环境风险 井下积水、遗煤自燃，瓦斯逸散严重，不利于开发利用 有自燃倾向性、自燃等级 Ⅱ 级 社会影响 瓦斯抽采，有利于减少瓦斯在井下聚集的浓度，减少瓦斯灾害 — 可持续性 瓦斯资源量越多、稳定性越好等，瓦斯抽采的可持续性越长 — 经济条件因素 矿井现有设备条件 越好，投入成本越低 良好 矿井巷道开拓状态 越好，抽采提升速度越快 — 瓦斯价格 越高，成本回升越快 2.5元/m3（受市场影响较大） 抽采工艺 越好，抽采效率越好 “L”型钻井抽采 管网阻力 越大，抽采率越低 — 
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表 2 DEMATEL-ISM模型结果
Table 2 DEMATEL-ISM Model Results
指标 影响度 被影响度 中心度 原因度 指标 影响度 被影响度 中心度 原因度 C1 0.3675 1.2837 1.6512 − 0.9162 C10 0.9944 0.4926 1.4870 0.5018 C2 0.3675 1.0597 1.4272 − 0.6922 C11 0.3852 0.2318 0.6170 0.1534 C3 0.3675 1.0597 1.4272 − 0.6922 C12 0 2.1601 2.1601 − 2.1601 C4 0.7888 0 0.7888 0.7888 C13 0.8835 0.5572 1.4407 0.3263 C5 1.3839 0.3672 1.7511 1.0167 C14 0.0483 0.5820 0.6303 − 0.5337 C6 0.4641 0.5251 0.9892 −0.0610 C15 0.3015 0.1420 0.4435 0.1595 C7 1.4192 0 1.4192 1.4192 C16 0.0639 0.3590 0.4229 − 0.2951 C8 0.4070 0.4926 0.8996 − 0.0856 C17 0.3423 0.3998 0.7421 − 0.0575 C9 1.0085 0.0622 1.0707 0.9463 C18 0.4645 0.2829 0.7474 0.1816
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表 3 判断矩阵标度含义
Table 3 3Meaning of Judgment Matrix Scale
标度 含义 0.9 ri元素极端重要于rj元素 0.8 ri元素强烈重要于rj元素 0.7 ri元素明显重要于rj元素 0.6 ri元素稍微重要于rj元素 0.5 ri元素与rj元素同样重要 互补数 若ri比rj相比较判断为rij，那么rj比ai相比较判断为1−rij
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表 4 判断矩阵B-G及特征向量
Table 4 Judgment matrix B-G and eigenvectors
B-G B1 B2 B3 B4 $ {G_i} $ B1 0.5000 0.5304 0.5469 0.5834 0.2917 B2 0.4696 0.5000 0.5166 0.5536 0.2583 B3 0.4531 0.4834 0.5000 0.5371 0.2417 B4 0.4166 0.4464 0.4629 0.5000 0.2083
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表 5 基于FAHP的指标层对目标层的各指标权重值
Table 5 Weight values of each indicator in target layer based on FAHP indicator layer
C-G B1( 0.2917 )B2( 0.2583 )B3( 0.2417 )B4( 0.2083 )$ {G_i} $ C1 0.2500 — — — 0.0729 C2 0.2417 — — — 0.0705 C3 0.2250 — — — 0.0656 C4 0.2833 — — — 0.0826 C5 — 0.2833 — — 0.0732 C6 — 0.2500 — — 0.0646 C7 — 0.2417 — — 0.0624 C8 — 0.2250 — — 0.0581 C9 — — 0.2000 — 0.0483 C10 — — 0.1533 — 0.0371 C11 — — 0.1500 — 0.0363 C12 — — 0.1600 — 0.0387 C13 — — 0.1600 — 0.0387 C14 — — 0.1767 — 0.0427 C15 — — — 0.2833 0.0590 C16 — — — 0.2333 0.0486 C17 — — — 0.2583 0.0538 C18 — — — 0.2250 0.0469
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表 6 基于Entropy的指标层对目标层的各指标权重值
Table 6 Weight values of each indicator in target layer based on Entropy’s indicator layer
C-G B1( 0.2917 )B2( 0.2583 )B3( 0.2417 )B4( 0.2083 )C1 0.8138 — — — C2 0.7918 — — — C3 0.7934 — — — C4 0.8222 — — — C5 — 0.8280 — — C6 — 0.0025 — — C7 — 0.6070 — — C8 — 0.8263 — — C9 — — 0.8615 — C10 — — 0.8210 — C11 — — 0.8147 — C12 — — 0.8201 — C13 — — 0.0025 — C14 — — 0.0025 — C15 — — — 0.3967 C16 — — — 0.8401 C17 — — — 0.6830 C18 — — — 0.8264
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表 7 基于博弈论的指标层对目标层的各指标权重值
Table 7 Weight values of each indicator combination in target layer based on game theory for indicator layer
指标 FAHP权重 熵值法权重 组合权重 C1 0.0729 0.8138 0.3414 C2 0.0705 0.7918 0.3319 C3 0.0656 0.7934 0.3293 C4 0.0826 0.8222 0.3506 C5 0.0732 0.8280 0.3467 C6 0.0646 0.0025 0.0421 C7 0.0624 0.6070 0.2598 C8 0.0581 0.8263 0.3365 C9 0.0483 0.8615 0.3430 C10 0.0371 0.8210 0.3212 C11 0.0363 0.8147 0.3184 C12 0.0387 0.8201 0.3219 C13 0.0387 0.0025 0.0256 C14 0.0427 0.0025 0.0281 C15 0.0590 0.3967 0.1814 C16 0.0486 0.8401 0.3354 C17 0.0538 0.6830 0.2818 C18 0.0469 0.8264 0.3294
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表 8 指标评估等级划分
Table 8 Classification of Index Evaluation Levels
评估指标 差Ⅰ 一般Ⅱ 良好Ⅲ 优秀Ⅳ 采空区遗煤瓦斯资源量C1 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 采空区未动用煤瓦斯资源量C2 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 邻近层煤瓦斯资源量C3 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 煤矿面积C4 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 采空区封闭条件C5 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 巷道支护完好程度C6 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 煤层埋深C7 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 围岩性质C8 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 废弃时间C9 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 煤层孔裂隙发育程度C10 较差[0，60） 一般[60，70） 较高[70，80） 高[80，100] 煤体破坏程度C11 高[0，60） 较高[60，70） 一般[70，80） 低[80，100] 地面钻孔甲烷浓度C12 少[0，60） 一般[60，70） 较多[70，80） 多[80，100] 环境风险C13 高[0，60） 较高[60，70） 一般[70，80） 低[80，100] 社会影响C14 少[0，60） 一般[60，70） 较多[70，80） 多[80，100] 矿井现有设备条件C15 少[0，60） 一般[60，70） 较多[70，80） 多[80，100] 矿井巷道开拓状态C16 较差[0，60） 一般[60，70） 较好[70，80） 好[80，100] 瓦斯价格C17 低[0，60） 一般[60，70） 较高[70，80） 高[80，100] 抽采工艺C18 较差[0，60） 一般[60，70） 较好[70，80） 好[80，100]
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表 9 二级评估等级关联度
Table 9 Level 2 evaluation level correlation
因素层B1−4 指标层 权重 评估指标关联度Kj 所属等级 j=1 j=2 j=3 j=4 B1 C1 0.3414 −0.425 −0.233 0.3 −0.115 Ⅲ C2 0.3319 −0.4 −0.2 0.4 −0.143 Ⅲ C3 0.3293 −0.079 0.3 −0.167 −0.327 Ⅱ C4 0.3506 −0.525 −0.367 −0.05 0.05 Ⅳ B2 C5 0.3467 −0.350 −0.133 0.400 −0.188 Ⅲ C6 0.0421 −0.375 −0.167 0.500 −0.167 Ⅲ C7 0.2598 −0.500 −0.667 0 0 Ⅲ C8 0.3365 0.083 −0.100 −0.250 −0.357 Ⅰ B3 C9 0.3430 −0.300 −0.067 0.200 −0.222 Ⅲ C10 0.3212 −0.500 −0.667 0 0 Ⅲ C11 0.3184 −0.150 0.400 −0.105 −0.292 Ⅱ C12 0.3219 −0.125 0.500 −0.125 −0.300 Ⅱ C13 0.0256 −0.500 −0.333 0 0 Ⅲ C14 0.0281 −0.05 0.2 −0.174 −0.391 Ⅱ B4 C15 0.1814 −0.300 −0.067 0.200 −0.222 Ⅲ C16 0.3354 −0.250 0 0 −0.250 Ⅲ C17 0.2818 0.067 −0.241 −0.833 −0.353 Ⅰ C18 0.3294 −0.375 −0.167 0.500 −0.167 Ⅲ
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表 10 一级评估等级关联度
Table 10 Level 1 evaluation level correlation
目标层 指标层 权重 评估指标关联度Kj 所属等级 j=1 j=2 j=3 j=4 G B1 0.2917 − 0.4879 − 0.1758 0.1627 − 0.1769 Ⅲ B2 0.2583 − 0.2391 − 0.2601 0.0756 − 0.1923 Ⅲ B3 0.2417 − 0.3657 0.0482 − 0.0100 − 0.2767 Ⅱ B4 0.2083 − 0.2429 − 0.1351 − 0.0338 − 0.2786 Ⅲ — — − 0.3431 − 0.1350 0.0575 − 0.2262 Ⅲ
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