1. 武汉大学 土木建筑工程学院,湖北,武汉,430072
2. 中国电建集团成都勘测设计研究院有限公司,四川,成都,610072
3. 中国地质大学(武汉) 工程学院,湖北,武汉,430074
网络首发:2021-06-15,
纸质出版:2021
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邓申缘, 姜清辉, 商开卫, 等. 高温对花岗岩微结构及渗透性演化机制影响分析[J]. 岩土力学, 2021,42(6):1601-1611.
DENG Shen-yuan, JIANG Qing-hui, SHANG Kai-wei, et al. Effect of high temperature on micro-structure and permeability of granite[J]. 2021, 42(6): 1601-1611.
邓申缘, 姜清辉, 商开卫, 等. 高温对花岗岩微结构及渗透性演化机制影响分析[J]. 岩土力学, 2021,42(6):1601-1611. DOI: 10.16285/j.rsm.2020.1515.
DENG Shen-yuan, JIANG Qing-hui, SHANG Kai-wei, et al. Effect of high temperature on micro-structure and permeability of granite[J]. 2021, 42(6): 1601-1611. DOI: 10.16285/j.rsm.2020.1515.
高温会使岩石产生热破裂现象,从而影响岩石的渗透性能。为了探寻温度对岩石微结构及渗透性能的影响,对50~800 ℃高温热处理后花岗岩开展了气体渗透率试验,并结合CT扫描技术,对高温热处理后花岗岩内部的微结构进行三维重构及特征分析,深入讨论了花岗岩受热后微结构的变化规律。在此基础上,对Kozeny-Carman模型及其改进模型在高温下的适用性进行讨论与验证,最后结合孔隙分形模型提出了高温后花岗岩温度?渗透率模型。结果表明:(1)温度升高过程中,花岗岩内部微结构发生明显变化,在400 ℃之前,矿物热膨胀性不均,岩石颗粒之间产生微小孔隙,构成了孔隙结构;而随着温度继续增加,孔隙端部产生裂纹并迅速扩展、连通,形成孔隙?裂隙网络结构。(2)当热处理温度不高于600 ℃时,花岗岩内部微结构形状因子概率分布曲线基本保持一致;当温度高于600 ℃时峰值对应的形状因子左移明显,其平均形状因子降低较大。(3)在孔隙结构阶段,花岗岩的渗透率变化不大,约为10?18 m2;在孔隙?裂隙网络结构阶段,花岗岩的渗透率随着裂隙的扩展而呈指数型增长,800 ℃时的花岗岩渗透率是常温下的8×104倍。(4)在应用4种孔隙率?渗透率模型对50~800 ℃孔隙率和渗透率的拟合结果中,Bayles模型和Costa模型描述高温后花岗岩更合理,拟合结果较K-C模型和S-R模型更高。(5)在温度低于600 ℃时,花岗岩内部微结构的形状基本没有变化,可以认为K-C形状系数保持为常数,说明对于花岗岩,Bayles模型和Costa模型在温度低于600 ℃时是适用的。(6)在Costa模型的基础上,结合高温后花岗岩孔隙分形特征,得到了高温后花岗岩温度?渗透率模型。将50~600 ℃的试验数据代入新模型进行验证,结果表明拟合度较好,达到0.99以上。
High temperature can cause the thermal fracture of rock
which affects the permeability of rock. In order to investigate the effect of temperature on the microstructure and permeability of rock
the ultrasonic velocity
density and gas permeability of granite after thermal treatment at 50–800 ℃ were measured. With the aid of CT scanning technique
the microstructure of granite was extracted and reconstructed. The influence of variation of microstructure after thermal treatment on permeability was also discussed in detail. According to this
the applicability of the K-C model and its improved model at high temperatures was discussed and verified. Finally
combined with the pore fractal model
a temperature-permeability model of granite after thermal treatment was proposed. The results show that: 1) The change of the internal microstructure of granite can be observed obviously as temperature increases. Uneven thermal expansibility of minerals before 400 ℃ can contribute to generation of many small pores between rock particles
which constitutes the pore structure. As temperature increases
these pores expand rapidly and connect with each other
forming the pore-fracture network. 2) When the temperature of heat treatment is not higher than 600 ℃
the probability distribution curve of the shape factor of the internal granite microstructure is basically consistent. When the temperature is higher than 600 ℃
the peak value of the shape factor shifts to the left obviously
and the average shape factor decreases greatly. 3) In the stage of pores
the permeability of granite doesn’t change too much
which is around the value of 10?18 m2. In the stage of the pore-fracture network
the permeability of granite increases exponentially with the connection of fracture. The permeability of granite under 800 ℃ is 8×104 times of the normal atmospheric temperature condition. 4) According to the fitting results of porosity and permeability at 50–800 ℃ using four porosity-permeability models
Bayles model and Costa model are more reasonable to describe granite after thermal treatment
and the fitting results are higher than K-C model and S-R model. 5) When the temperature is lower than 600 ℃
there is basically no change in the shape of the internal microstructure of the granite
and the shape coefficient of K-C can be considered as a constant. This indicates that Bayles model and Costa model are applicable for granite when the temperature is lower than 600 ℃. 6) On the basis of Costa model
the temperature-permeability model of granite after thermal treatment is obtained by combining the pore fractal characteristic of high-temperature heated granite. The experimental data within the temperature range of 50–600 ℃ are used to verify the new model and the coefficient of determination of fitting result reaches 0.99.
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