Modeling and analysis of gas capture from sealed sections of abandoned coal mines
Modeling and analysis of gas capture from sealed sections of abandoned coal mines
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DOI：
10.1016/j.coal.2014.12.010
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发表时间：
2015-01-15
影响因子：
5.6
通讯作者：
Karacan, C. Oezgen
中科院分区：
文献类型：
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作者：
Karacan, C. Oezgen
所有煤矿最终都将结束其经济寿命，停止生产，彻底被废弃。这些矿井的通风井和通道巷道通常用混凝土封堵，将矿井环境与外界大气（地表）隔离，同时也防止未经授权的人进入旧的工作场所。虽然进入矿井的大片区域可以隔离，但留下的空隙空间永远无法与周围的煤和其他地层隔离。这些空洞就像一个巨大的水槽，随着时间的推移，开始积聚气体，也许还有地下水，形成一个甲烷储层。了解周围地层向老采空区排放的甲烷，以及矿井就地密封的泄漏特征，分析这些区域的产气潜力，可以改善类似环境下矿井的通风设计，也可以使废弃矿井甲烷（AMM）作为能源成为可能。为了实现这些目标，从不同来源获取的数据，并将其用于流动建模和油藏模拟，以及AMM井的生产，是非常宝贵的工具。然而，对废弃矿井的瓦斯排放和捕获进行建模可能不是一件容易的事。估计周围煤炭和矿山环境的各种属性的空间变异性的困难，矿山边界及其细节的复杂几何形状，以及放弃时和分析开始时的初始条件都增加了挑战。本文演示了一项储层建模研究，该研究旨在描述印第安纳州斯普林菲尔德（Springfield）一个废弃的房柱式煤矿的甲烷提取特征。通过历史匹配，首先对两个密封段的两口AMM井进行了周围煤与废弃矿井环境相互作用的分析。然后将分析扩展到评估不同的井位，以了解煤中气体排放的潜在变化，以及密封泄漏。建立详细的储层环境所需的数据来自矿山图，使用复合模型分析井产量，并通过逐点数据的地质统计建模来创建属性图。结果表明，在矿山较大的密封段和远离以前的工作面钻孔效果较好。此外，井在密封段的位置很重要，因为靠近周围煤炭的位置可以更好地促进更多的瓦斯从煤层流入，而靠近密封的位置可以利用通过密封的泄漏，并且可以从矿井其他部分贡献的更高的瓦斯率中受益。由于煤的气体排放和通过密封的泄漏随压差而变化，AMM的模拟也可以用于在类似环境下运行的矿井的通风设计中，因此也可以通过对泄漏的量化理解来帮助提高矿井的安全性。Elsevier B.V.出版
All coal mines eventually complete their economic life, stop production, and are abandoned completely. Ventilation shafts and access drifts of these mines are usually sealed by plugging with concrete to isolate the mine environment from the outside atmosphere (surface) and also to prevent unauthorized access to old workings. Although large areas of access to the mine can be isolated, the void space left behind can never be isolated from surrounding coal and other formations. The void spaces act as a huge sink and start accumulating gas, perhaps groundwater as well, over time to form a methane reservoir. Understanding methane emission into old workings from surrounding strata, and the leakage characteristics of in-place mine seals, and analyzing gas production potential from such areas can improve ventilation designs in mines operating in similar settings, and can also enable the possibility of using abandoned mine methane (AMM) as an energy source. To meet these objectives, data acquired from different sources and utilized in the context of flow modeling and reservoir simulation, along with productions of AMM wells, can be invaluable tools. However, modeling of abandoned mines for gas emission and capture may not be an easy task. The difficulties in estimating spatial variability in various properties of the surrounding coal and mine environment, the complex geometry of the mine boundary and its details, and the initial conditions at the time of abandonment and when analysis begins all add to the challenge.In this paper, a reservoir modeling study that aims to characterize methane extraction from an abandoned room-and-pillar mine in the Springfield coal, Indiana, is demonstrated. The analyses related to interactions of surrounding coal with the abandoned mine environment were performed though history matching, initially, of two AMM wells drilled into two sealed sections. Analyses were then extended to evaluate different well locations to understand potential changes in gas emission from the coal, as well as leakage from the seals. Data required for establishing a detailed reservoir environment were obtained from mine maps, analysis of well productions by using a composite model, and by geostatistical modeling of point-wise data to create property maps.Results showed that wells drilled in larger sealed sections of the mine and away from previous workings performed better. Furthermore, the location of the well in the sealed section can be important as locations close to surrounding coal can have a better chance of promoting more gas in-flow from the coal seam, whereas locations close to the seal can take advantage of leakage through the seal and can benefit from higher rates of the gas contributed from other parts of the mine. Since gas emissions from coal and leakage through seals vary with the pressure differential, simulations of AMM can also be used in ventilation design of mines operating in similar settings as estimates and thus can also help improving safety of mines with quantified understanding of leakage. Published by Elsevier B.V.