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关闭矿井采空区破碎岩体再断裂机制及空隙结构演化特性

孟凡非, 浦海, 倪宏阳, 卞正富

孟凡非,浦 海,倪宏阳,等. 关闭矿井采空区破碎岩体再断裂机制及空隙结构演化特性[J]. 煤炭科学技术,2024,52(2):104−114. DOI: 10.12438/cst.2023-1802
引用本文: 孟凡非,浦 海,倪宏阳,等. 关闭矿井采空区破碎岩体再断裂机制及空隙结构演化特性[J]. 煤炭科学技术,2024,52(2):104−114. DOI: 10.12438/cst.2023-1802
MENG Fanfei,PU Hai,NI Hongyang,et al. Research on re-fracturing mechanism and cavity structure evolution characteristics of broken rock mass in goaf of closed mine[J]. Coal Science and Technology,2024,52(2):104−114. DOI: 10.12438/cst.2023-1802
Citation: MENG Fanfei,PU Hai,NI Hongyang,et al. Research on re-fracturing mechanism and cavity structure evolution characteristics of broken rock mass in goaf of closed mine[J]. Coal Science and Technology,2024,52(2):104−114. DOI: 10.12438/cst.2023-1802

关闭矿井采空区破碎岩体再断裂机制及空隙结构演化特性

基金项目: 

国家重点研发计划资助项目(2023YFC3804200);国家自然科学基金面上资助项目(52374147);中央高校基本科研业务专项资金资助项目(JB220006)

详细信息
    作者简介:

    孟凡非: (1993—),女,山东济宁人,助理研究员,博士。E-mail:mff@cumt.edu.cn

    通讯作者:

    浦海: (1978—),男,江苏盐城人,教授,博士生导师,博士。E-mail:haipu@cumt.edu.cn

  • 中图分类号: TD325

Research on re-fracturing mechanism and cavity structure evolution characteristics of broken rock mass in goaf of closed mine

Funds: 

National Key Research and Development Program of China (2023YFC3804200); General Program of National Natural Science Foundation of China (52374147); Fundamental Research Funds for the Central Universities (JB220006)

  • 摘要:

    受“双碳”政策影响,关闭矿井地热开采技术逐渐受到关注。关闭矿井采空区内储热流体提取效率与其渗流特性密切相关,而破碎岩体空隙结构是决定采空区渗流特性的关键因素。因此,需要研究地热开采复杂环境下储热空间破碎岩体空隙结构变形演化特性。笔者基于颗粒离散元数值方法,建立浸水及侧向约束压缩条件下不同级配的破碎岩体数值模型,分析破碎岩体变形行为及二次断裂演化特性,追踪颗粒从岩体骨架结构剥离及空隙内运移规律。得到如下结论:破碎岩体压实过程应力随应变增长可分为3个阶段:初始阶段(0<ε≤0.175),缓慢增长阶段(0.175<ε≤0.275)以及快速增长阶段(ε>0.275)。快速增长阶段应力−应变曲线出现明显波动,破碎岩体二次断裂及应力重分布现象在该阶段最明显。破碎岩体热储环境下空隙率的变化值与初始空隙率成正比,最大达到0.2。当破碎岩体内岩块粒径悬殊大时,接触键应变能最大,断裂能增长缓慢。岩块与颗粒密集区接触部分断裂分布多,与空隙接触部分断裂分布极少。颗粒未剥离岩块时,随岩块运动,整体运动路径复杂速度较小;颗粒剥离瞬间速度突然增大,与岩块碰撞导致速度改变。当颗粒速度减小到与周围岩块相近时,将造成空隙空间的堵塞。研究结果可为关闭矿井储热空间换热效率评估提供理论依据。

    Abstract:

    Due to the “Dual Carbon” policy impact, geothermal extraction technology in closed mines has garnered increasing attention. The efficiency of extracting thermal fluid within the closed mine goaf is related to the permeability characteristics, with the broken rock mass porosity structure playing a key role in determining the permeability characteristics of the goaf. Therefore, it is of great significance to investigate the deformation and evolution characteristics of the porosity structure of broken rock mass in the complex environment of geothermal extraction. Numerical models of broken rock mass with different size grading indexes were established using the particle discrete element numerical method under conditions of immersion and lateral-constrained compression. The deformation behavior and evolution characteristics of the broken rock mass were analyzed, and the movement rules of particles within the rock voids were tracked. The following conclusions were obtained: the stress-strain curve during the compaction process of the broken rock mass can be divided into three stages, namely the initial stage (0<ε≤0.175), the slow growth stage (0.175<ε≤0.275), and the rapid growth stage (ε>0.275). In the rapid growth stage, the stress-strain curve shows significant fluctuations, and the phenomena of secondary fracturing and stress redistribution in the broken rock mass are most pronounced. The variation value of porosity in the broken rock mass under the thermal storage environment is directly proportional to the initial porosity, with a maximum value of 0.2. When there is a large size difference between rock blocks in the broken rock mass, the contact bond strain energy is the largest, and the growth of bond breakage energy is slow. Fractures are more common in the contact part between rock blocks and particles, while fractures in the contact part between rock blocks and voids are very rare. When the particles are not separated from the rock fragments, they move with the rock fragments, resulting in a complex overall trajectory. In the instant when the particles are detached, their velocity suddenly increases and the collision with the rock fragments causes a change in velocity. When the particle's velocity decreases to a level similar to the surrounding rock fragments, it will lead to the blocking of the void space. The research results can provide a theoretical basis for evaluating the thermal storage efficiency in the goaf of closed mines.

  • 煤层瓦斯含量测定是开展矿井瓦斯防治的一项极为重要的基础工作,我国煤矿瓦斯含量的测定主要采用煤层瓦斯含量井下直接测定方法[1-2]。井下直接法测定的瓦斯含量主要包括煤样井下自然解吸量、实验室测定残存量以及利用解吸规律推算取样过程的损失量3部分[3-4]。井下解吸量和实验室残存量可以实测,但取样开始到煤样解吸试验前的瓦斯损失不可避免,通常是依据采样结束后,煤样在前几分钟的解吸量与时间的关系拟合推算得到[5-6]。因此,尽可能地减少取样过程的瓦斯损失,以及建立可靠的损失量推算模型是实现煤层瓦斯含量精准测定的关键[7-8]

    井下现场较多采用钻屑法取样,但此法易混样,无法保证煤样的纯净,导致瓦斯含量测定的可靠性难以保证[9]。常规煤心管取样过程中,钻头切削热和管壁与钻孔壁间的摩擦热会使煤心温度升高,并且取心时间较长,导致推算的瓦斯损失量往往低于取样中实际值[10-11]。为了减少瓦斯逸散,孙四清等[12]提出了“三筒单动、球阀关闭、取心筒与解吸罐一体化”的煤层气密闭取心器;李泉新等[13]将密闭取心技术运用到煤层井下长距离定点取样;谢和平团队[14-15]研发了的保压保瓦斯工艺可实现低扰动取心,保压能力强;王西贵等[16]设计了保温保压保形的煤层气取心工具。这些方法一定程度上提高了取样深度和精度,但设备工艺较繁琐,仍无法消除取心器具局部生热对瓦斯解吸的影响。

    瓦斯损失量推算一般通过构建瓦斯扩散模型来进行计算补偿,前人总结了诸多颗粒煤中瓦斯流动规律公式[17-18]。李志强等[19]提出了煤粒多尺度多级孔隙模型,能适应均质与非均质煤体的扩散。程远平等[20]进一步研究了煤的孔径类型对气体扩散系数的影响。秦跃平等[21]提出了密度梯度驱动的扩散模型;王亮等[22]优化了颗粒煤基质尺度计算参数,使其在粉化程度高的煤样中同样具有较好适用性。王兆丰等[23-24]系统研究了−30~30 ℃条件下的颗粒煤瓦斯吸附/解吸特性,发现低温能有效抑制瓦斯解吸,并提出了低温取心技术。马树俊等[25]通过程序升/降温闭合性变温试验发现吸附和解吸两者基本可逆。此外,陈江龙等[26]认为损失瓦斯量的补偿计算值随取样时间延长而减小,与实测值误差逐渐增大。

    以往学者们对煤样在恒温、高温环境下的瓦斯吸附/解吸规律研究较多,随着低温下瓦斯吸附/解吸特性的工程意义逐渐被重视,引起了越来越多的关注。低温取心过程不同于恒温边界条件,煤中瓦斯解吸受到取心管外壁摩擦热和内部制冷剂的双重影响。基于此,笔者依托含瓦斯煤低温取心吸附解吸模拟平台,开展了不同管壁外热、平衡压力条件下低温取心瓦斯解吸模拟试验;并采用图解法,对3种不同扩散模型的解吸拟合效果进行评价,以期揭示低温取心过程中的煤心瓦斯解吸规律,构建低温取心瓦斯损失量推算方法。

    采用取心管在硬煤层取样时,由于受到钻机推进挤压作用,所取煤样多呈圆柱状,其尺寸较大,扩散路径较之颗粒煤大大增加。由于原煤结构较松散,难以打孔布置温度传感器。故选用焦作矿区赵固二矿二1煤层的无烟煤,将其研磨筛分后装入型煤模具中压制成型煤样品;并利用微型台钻在型煤样品中心位置钻进一个直径约为2.5 mm的小孔,布置温度传感器监测试验过程中煤心温度变化,如图1所示。

    图  1  柱状型煤试样
    Figure  1.  Cylindrical moulded coal

    含瓦斯煤低温取心吸附解吸模拟平台主要由真空脱气系统、注气吸附系统、程序温控系统、解吸自动计量系统、体积标定系统和样品罐自动旋转升降系统组成,可真实模拟常规/低温取心过程煤样瓦斯的扩散过程,如图2所示。

    图  2  含瓦斯煤低温取心吸附解吸模拟平台
    Figure  2.  Testing platform for gas adsorption/desorption on gas bearing coal during the freezing coring

    井下低温取心时,取心管内腔制冷剂既要抵抗取心钻头切削热和管壁与孔壁间的摩擦热,又要使所取煤心迅速降温。煤心瓦斯即处于低温变温环境中解吸。为营造冷冻取心过程“外热内冷”的温度环境,试验温控单元采用相互独立的双层夹套反应器(两夹套紧贴但不连通)。其中低温冷却液反应浴槽容积10 L,额定功率3.8 kW,空载调温范围−80 ℃~室温,制冷量3 679 W,循环泵流量20 L/min;程序升温油浴用于模拟取心钻进过程摩擦生热,加热过程中使用苯基硅油作为导热介质。双层夹套反应器具有相互独立的内/外循环泵系统,可将低温反应浴内的冷却液(95%工业酒精)和高温导热油分别引进到反应器的内外浴槽内。根据焦作矿区二1煤层实测的取样过程取心管壁温度数据[23,27],将加热油浴温度分别设定为60、70、80和90 ℃,模拟不同取心深度时的取心管壁外热温度。采用干冰接触制冷时,煤心最终达到的低温为−36.8 ℃[28],因此将制冷反应浴的温度统一设定为−40 ℃。

    首先对型煤样品进行真空脱气,至10 Pa以下。将样品罐置于30 ℃恒温水浴中,向其反复充入甲烷气体,直至罐内压力达到预设压力并保持4 h不变,以模拟煤样在未暴露时的吸附平衡状态。冷冻取心瓦斯解吸模拟时,首先将低温反应浴温度设定为−40 ℃并打开制冷循环;当内层夹套浴槽的温度达到并保持与低温反应浴相同时,启动加热油浴,根据现场实测的取心全过程温度曲线设置升温程序,以此创造冷冻取心过程的真实温度环境。在钻进升温程序开始时,立即将样品罐放入夹套反应器内,并迅速打开排气阀,释放排出样品罐内的游离气体;当样品罐内压力降至大气压时,关闭排气阀;打开样品罐与气体流量计量装置连接的所有阀门,实时采集解吸数据,直至样品罐内的瓦斯不再解吸。随后,依次重复以上试验步骤,模拟不同管壁外热和不同吸附压力条件下低温取心过程煤心瓦斯扩散过程。

    在不同管壁外热条件下(60、70、80、90 ℃),首先开展了常规取心升温瓦斯解吸试验,并与恒温30 ℃时的解吸量进行对比,如图3所示。煤样瓦斯吸附平衡压力为2 MPa,对应的吸附量为15.93 cm3/g。

    图  3  高温取心环境与常温下瓦斯解吸量对比
    Figure  3.  Comparisons of gas desorption amount at between high and normal temperatures

    常规取心时,同一时间内瓦斯累计解吸量随着取心管外壁温度的上升逐渐增大,高温取心环境中的解吸曲线始终位于恒温30 ℃解吸曲线的上方。瓦斯累计解吸量曲线可分为2个阶段:① 初期快速增长阶段,前15 min内的瓦斯解吸速率较快,因此解吸量增长迅速;② 后期稳定增长阶段,随着解吸速率大幅衰减,管壁的热量逐渐传递至煤心内部,解吸量稳定增长。管壁温度分别为60、70、80、90 ℃时,10 min时煤心累计解吸量分别为4.601、4.827、4.877和5.113 cm3/g,较之30 ℃解吸量4.362 cm3/g的增幅分别为5.48%、10.66%、11.81%和17.22%;30 min时的累计解吸量分别为6.587、7.082、7.460和7.981 cm3/g,较之30 ℃解吸量5.793 cm3/g的增幅分别为13.71%、22.25%、28.78%和37.77%。可见取心管采样过程中产生的摩擦热会大大增加煤心瓦斯损失量,若以恒温30 ℃时解吸规律推算真实取样时的瓦斯损失量,会直接影响瓦斯含量测定的准确性。

    不同管壁外热常规取心过程的瓦斯解吸速率如图4所示。解吸初期瓦斯扩散速率最高,扩散速率随时间延长呈幂函数衰减,如式(1)所示。扩散速率曲线具有明显的分段特征:前15 min扩散速率急剧下降;15 min后解吸速率降至较低值。且高温环境下的解吸速率曲线始终位于恒温30 ℃速率曲线的上方,表明升温加快了瓦斯解吸。

    图  4  常规取心过程瓦斯扩散速率
    Figure  4.  Gas desorption velocities during the conventional coring
    $$ {v_t} = {v_1} {t^{ - \alpha }} $$ (1)

    式中:v1为第1 min时瓦斯扩散速率,cm3/(g·min);vtt时刻的瓦斯扩散速率,cm3/(g·min);$\alpha $为扩散速率衰减系数。

    为了控制变量,探讨低温取心过程与常规取心瓦斯解吸规律的差异,在管壁外热温度(60、70、80、90 ℃)保持不变的前提下,在低温取心试验中,将内层夹套低温反应浴的温度设为−40 ℃。开展了吸附平衡压力为2 MPa下的低温取心瓦斯解吸试验,结果如图5所示。

    图  5  低温取心环境瓦斯初始解吸量曲线
    Figure  5.  Primary curves of gas desorption amounts during the freezing coring

    不同于常温和高温环境解吸,低温条件下的瓦斯初始解吸曲线呈现出三段式变化。初期快速解吸阶段,煤心内部与外界的甲烷体积分数梯度较大,因此扩散速率较大,解吸量迅速增加。中期缓慢解吸,瓦斯扩散速率大幅衰减和煤心温度逐渐降低,解吸量增长缓慢,并出现了短暂的停滞现象。后期出现“倒吸回流”现象,20 min后当煤心温度降至一定程度,累计解吸量开始逐渐下降;并且管壁外热温度越低,低温取心时解吸曲线出现倒吸的时间就越短。

    扩散是由吸附体系内外的浓度差引起的,低温取心时甲烷分子的平均自由程随温度下降逐渐降低[29],即低温对扩散具有抑制效应。但只要吸附体系内的甲烷体积分数大于外界浓度,在绝对零度以上甲烷分子就不会停止运动,扩散现象就不会停止。由理想气体状态方程(PV=nZRT)可知,对于整个吸附系统而言,吸附质甲烷物质的量n、理想气体常数R、压缩因子Z和煤样罐吸附空间体积V均为恒定。系统处于低温环境解吸时,温度T不断下降,样品罐内压力P势必会相应地降低,当温度下降到一定程度,煤样罐内的压力低于煤样罐外大气压时,就会出现外界的空气向罐内回流的现象。

    为消除倒吸回流对瓦斯解吸定量计算的影响,在低温取心解吸试验前,在同样的环境温度下(高温浴依次设为60~90 ℃,低温设置−40 ℃),开展了不含瓦斯型煤的纯倒吸对比试验(罐内不充入甲烷),以校正低温取心过程瓦斯的真实解吸量。倒吸试验结果如图6所示。

    图  6  不含瓦斯煤低温环境下倒吸量与温度变化曲线
    Figure  6.  The back-flow rate and temperature changes in the coal sample without gas during the freezing coring

    图6可知:在低温条件下,样品罐倒吸曲线与煤心降温曲线变化趋势总体一致,具有良好的线性关系,即说明倒吸现象的实质是在低温作用下,样品罐内压力降低造成的结果。初始阶段,样品罐内部与外部温差较大,降温速率较快,故罐内的压力下降较快导致倒吸量急剧增加。随着煤心降温速率逐渐减小,样品罐内负压不再增加,倒吸量增长速率也随之减缓。当管壁外热分别为60、70、80、90 ℃时,低温取心煤心最终温度为−17.9、−22.1、−25.0、−29.8 ℃。

    得到不含瓦斯煤的绝对倒吸量后,将图5中混合瓦斯解吸和倒吸的初始解吸曲线减去各对应温度条件下的倒吸量,即可校正得到低温取心过程的真实解吸量,如图7所示。低温环境下,煤样真实解吸量随时间延长逐渐增加。相较于常规取心解吸规律,低温取心时解吸量快速增长阶段的时间更短,10 min后解吸量缓慢增长至解吸停止。管壁外热越低,低温取心的累计解吸量就越小。当外热温度分别为60、70、80、90 ℃时,前10 min内低温解吸量分别为3.207、3.391、3.623和3.780 cm3/g;30 min内解吸量分别为3.578、3.842、4.215和4.76 cm3/g。

    图  7  不同管壁外热条件低温与常规取心瓦斯解吸量对比
    Figure  7.  Comparisons of gas desorption amounts during freezing and conventional coring under different tube temperatures

    为量化相同管壁外热条件低温取心对瓦斯解吸的抑制效果,将低温与常规取心各时段的解吸量进行比较,见表1。解吸抑制率定义为低温与常规取心瓦斯解吸量差值与常规解吸量的比值,即

    表  1  低温与常规取心瓦斯解吸参数
    Table  1.  Parameters of gas desorption during between the freezing and conventional coring
    时间/
    min
    管壁60 ℃解吸量/
    (cm3·g−1)
    抑制
    率/%
    管壁70 ℃解吸量/
    (cm3·g−1)
    抑制
    率/%
    管壁80 ℃解吸量/
    (cm3·g−1)
    抑制
    率/%
    管壁90 ℃解吸量/
    (cm3·g−1)
    抑制
    率/%
    冷冻 常规 冷冻 常规 冷冻 常规 冷冻 常规
    10 3.207 4.601 30.30 3.391 4.827 29.75 3.623 4.877 25.71 3.780 5.113 26.07
    20 3.510 5.770 39.17 3.704 6.071 38.99 3.996 6.279 36.36 4.469 6.698 33.28
    30 3.578 6.587 45.68 3.842 7.082 45.75 4.215 7.46 43.50 4.76 7.981 40.36
    40 3.599 7.31 50.77 3.898 7.901 50.66 4.330 8.291 47.77 4.880 8.809 44.60
    60 3.602 8.190 56.02 3.914 8.752 55.28 4.387 9.253 52.59 4.91 10.080 51.29
    下载: 导出CSV 
    | 显示表格
    $$ \eta=\frac{|Q_{{\mathrm{f}}}-Q_{{\mathrm{c}}}|}{Q_{\mathrm{c}}} \times 100 \% $$ (2)

    式中:η为低温取心瓦斯解吸抑制率,%;Qf为低温取心解吸量,cm3/g;Qc为常规取心时解吸量,cm3/g。

    表1,低温取心较之常规取心法的解吸抑制率随时间延长逐渐增大,基本呈线性增长。前10 min内低温取心解吸抑制率在25%~30%;30 min内的解吸抑制率在40%~46%;60 min内的抑制率在51%~56%,验证了低温取心确实可有效降低采样过程中的瓦斯损失量。

    为了分析低温取心时瓦斯吸附平衡压力对“低温抑解”效应的影响,开展了不同平衡压力(1、2、3、4 MPa)条件下低温取心解吸模拟试验。这里管壁外热均设为70 ℃,制冷浴为−40 ℃。校正后的不同平衡压力条件下的真实解吸量、解吸速率结果如图8图9所示。

    图  8  不同平衡压力下低温取心瓦斯解吸量
    Figure  8.  Gas desorption amounts at different adsorption pressures during the freezing coring
    图  9  不同平衡压力低温解吸速率
    Figure  9.  Curves of gas diffusion velocity at different adsorption pressures during freezing coring

    图8表明:在相同的低温取心环境下,瓦斯解吸曲线仍可分为初期快速增长、后期缓慢增长2个阶段。高压条件下,解吸量初期增幅较大且解吸持续时间更长,整个过程的累计解吸总量更大。当平衡压力从1~4 MPa等压递增时,各对应的解吸量曲线间距变得逐渐紧密,表明解吸量随压力的增长幅度逐渐减小。这是由于吸附压力高的煤心解吸时吸收的热量更多,煤心降温更快,增强了低温对瓦斯抑解效果。平衡压力分别为1、2、3、4 MPa时,10 min内的解吸量分别为2.391、3.391、3.850和4.20 cm3/g,解吸率分别为20.05%、21.29%、21.64%和22.27%;30 min内累计解吸量分别为2.708、3.842、4.361和4.758 cm3/g,解吸率分别达到22.71%、24.11%、24.51%和25.23%。

    图9可知,不同平衡压力下,前10 min为解吸速率迅速下降阶段,10 min后进入平缓下降阶段;且瓦斯解吸速率随平衡压力上升而逐渐增大。平衡压力分别为1、2、3、4 MPa时,第10 min时的平均解吸速率分别为0.239、0.339、0.385和0.42 cm3/(g·min),分别降低至第1 min解吸速率v1的21.24%、21.81%、21.78%和21.69%;第30 min时的平均解吸速率分别为0.091、0.128、0.147和0.157 cm3/(g·min),分别降至v1的8.09%、8.24%、8.31%和8.11%。可见前10 min内的瓦斯解吸速率衰减率最大,故解吸过程具有明显的分段特征。

    扩散系数是衡量气体在多孔介质中扩散难易程度的重要参量。为研究温度对取样时煤中瓦斯扩散系数的影响,采用聂百胜法[30]对常规取样及低温取样时30 min内的平均扩散系数进行计算,结果见表2。在第3类边界条件下,用毕欧准数和傅里叶准数来反映煤样瓦斯扩散与时间的动态变化特征,扩散率Qt/Q一般表达式为

    表  2  不同外热冷冻/常规取心扩散系数拟合关系
    Table  2.  Fitting parameters of gas diffusion coefficient during the freezing and conventional coring
    解吸温度/ ℃ 拟合方程 R2 扩散系数D/(cm2·s−1)
    30 ln(1−Qt/Q)=−0.010 7t−0.178 3 0.872 1.086×10−7
    管壁60 ln(1−Qt/Q)=−0.013t−0.178 8 0.924 1.32×10−7
    管壁70 ln(1−Qt/Q)=−0.014 5t−0.184 4 0.950 1.466×10−7
    管壁80 ln(1−Qt/Q)=−0.016 2t−0.172 9 0.965 1.644×10−7
    管壁90 ln(1−Qt/Q)=−0.018 4t−0.172 4 0.966 1.866×10−7
    −40制冷+管壁60 ln(1−Qt/Q)=−0.003 5t−0.172 4 0.832 3.536×10−8
    −40制冷+管壁70 ln(1−Qt/Q)=−0.004t−0.179 4 0.847 4.022×10−8
    −40制冷+管壁80 ln(1−Qt/Q)=−0.005t−0.183 8 0.875 5.005×10−8
    −40制冷+管壁90 ln(1−Qt/Q)=−0.006 9t−0.181 1 0.872 6.961×10−8
    下载: 导出CSV 
    | 显示表格
    $$ \mathrm{ln}\left(1-\frac{{Q}_{t}}{{Q}_{\infty }}\right)=-\lambda t+\mathrm{ln\;}A\text{,}\lambda =\frac{{\pi }^{2}D}{{r}_{0}^{2}} $$ (3)

    其中,r0为煤样颗粒半径,这里取平均值0.1 mm;A为拟合系数;Qtt时刻的解吸量,cm3/g;Qt时的极限解吸量,通常为煤样处于吸附平衡后在常压0.1 MPa下t→∞时的扩散量,即

    $$ {Q_\infty } = \left(\frac{{abP}}{{1 + bP}} - \frac{{ab{P_0}}}{{1 + b{P_0}}}\right) \frac{{100 - {A_{{\mathrm{ad}}}} - {M_{{\mathrm{ad}}}}}}{{100}} \frac{1}{{1 + 0.31{M_{{\mathrm{ad}}}}}} $$ (4)

    其中,a为吸附常数,当P→∞时的极限吸附量,cm3/g;b为吸附常数,MPa−1Aad为煤样灰分,%;Mad为煤样中的水分,%;P0为常压0.1 MPa。常规/低温取样时扩散率的拟合结果如图10图11所示。

    图  10  常规取样瓦斯扩散率与时间关系
    Figure  10.  Relations between the gas desorption ratio and time during the conventional coring

    表2可知:相同管壁外热条件下,低温取心时瓦斯扩散系数较之常规取心扩散系数减少得多;并且扩散系数随着环境温度的下降而呈现线性降低。管壁外热分别为60、70、80、90 ℃时,常规取心环境下的扩散系数分别为1.32×10−7、1.466×10−7、1.644×10−7、1.866×10−7 cm2/s;而低温取心时扩散系数分别为3.536×10−8、4.022×10−8、5.005×10−8和6.961×10−8 cm2/s,仅占到同外热常规取心的0.3~0.4间。在低温环境下(<0 ℃),瓦斯分子的平均自由程和活性能减小,分子热运动受限,多数吸附态气体分子无法获得足够的动能摆脱吸附势阱的束缚从煤孔隙表面扩散出来,在煤孔隙表面的停留时间也被延长。同时瓦斯解吸是吸热过程,煤心降温也抑制了解吸进程。宏观表现为低温环境的扩散系数比高温环境扩散系数小得多。

    图  11  低温取样瓦斯扩散率与时间关系
    Figure  11.  Relations between the gas desorption ratio and time during the conventional coring

    建立可靠的损失量推算模型是测定采样过程中瓦斯损失量的关键。经典的$\sqrt t $模型、负指数模型、幂函数模型、动扩散系数模型[31]等是基于颗粒煤瓦斯扩散试验建立的经验或半经验公式。严格来讲,这些球状扩散模型并不能准确描述瓦斯在型煤孔隙中的扩散特征。李志强等[32]建立的柱状煤单孔隙扩散模型存在无穷级数项,也不便应用于现场取样推算损失量。

    根据低温取心模拟试验得到的瓦斯解吸量曲线特征,笔者发现低温变温环境下,解吸量与解吸时间呈现Logistic函数增长的趋势。Logistic增长曲线模型特点是初始阶段样本的数量随时间大致呈几何级数增长;而后受环境条件制约开始变得缓和,直至停止增长[33]。低温取心采样时,煤心刚暴露被切削下来进入取心管时,瓦斯大量放散;随后退钻过程中受制冷剂作用,煤心温度持续降低,低温很好地抑制了瓦斯解吸,因此后期的瓦斯累计解吸量曲线逐渐平缓,这与Logistic模型(式(5))的增长趋势相似。

    $$ {Q_t} = b_1 + \frac{{a_1 - b_1}}{{[1 + {{(t/{t_0})}^c}]}} $$ (5)

    式中:a1为低温取心过程瓦斯损失量,cm3/g;b1为取样结束后,煤样在测定时间内的井下解吸量,cm3/g;t0为解吸总量中值所对应的时间,min;c为解吸曲线增长因子。

    基于图解法,分别采用$ \sqrt{t} $模型、指数式模型和Logistic增长模型对不同管壁外热、平衡压力条件下的低温取心解吸Q-t曲线拟合分析,评价这3种损失量推算模型的优劣。为统一比较,整个取心过程和装入样品罐的总时长设为15 min,则前15 min的解吸量即为取样过程的损失量;15 min后开始计时,记录煤样罐中瓦斯解吸量。不同条件下,低温取心过程的解吸量拟合结果如图12图13所示。

    图  12  不同外热低温取心过程损失量拟合曲线
    Figure  12.  Fitting curves of the gas loss at different tube temperatures during the freezing coring
    图  13  不同平衡压力下低温取心过程损失量拟合曲线
    Figure  13.  Fitting curves of the gas loss at different sorption pressures during the freezing coring

    图12图13可见,采用Logistic增长模型对不同低温取心条件下的瓦斯解吸拟合曲线基本与试验数据重合,拟合精度均在0.99以上,效果明显优于$ \sqrt{t} $模型和指数模型。低温取心过程中煤心迅速降温,且柱状煤心由于尺寸较大,瓦斯扩散路程及在孔隙中迂曲程度较大,取样结束被装入煤样罐后,解吸量曲线开始出现拐点,测试时间内的解吸量较小。而$ \sqrt{t} $模型和指数模型解吸拟合曲线随时间逐渐递增,在测试时间内(15 min)并没有收敛的趋势。因此,采用$ \sqrt{t} $模型和指数模型推算低温取样过程的损失量严重失真。

    表3可知,不同管壁外热、平衡压力条件下,采用Logistic增长模型推算出的瓦斯损失量与解吸试验值之间的误差均小于0.5%。指数式拟合的损失量误差在29.3%~56.3%,当瓦斯吸附压力较大或取心管外热较高时,推算误差逐渐降低;而$ \sqrt{t} $模型的推算误差更大,整体在41.6%~58.1%,推算出的瓦斯损失量远低于真实值。因此,现阶段采用Logistic增长曲线模型拟合低温取心过程瓦斯解吸曲线,能够满足推算各种低温环境下的瓦斯损失量的需要。

    表  3  3种模型低温取心过程损失量推算结果对比
    Table  3.  Comparisons of calculation results of gas loss during the freezing coring by the three models
    低温取心 损失量试验值/
    (cm3·g−1)
    指数式模型 $ \sqrt{t} $模型 Logistic模型
    推算值/
    (cm3·g−1)
    误差/% R2 推算值/
    (cm3·g−1)
    误差/% R2 推算值/
    (cm3·g−1)
    误差/% R2
    不同管壁外热 60 ℃ 3.406 1.803 56.3 0.71 1.428 58.1 0.82 3.402 0.12 0.99
    70 ℃ 3.578 2.003 44.02 0.74 1.559 56.43 0.84 3.569 0.25 0.99
    80 ℃ 3.839 2.401 37.46 0.77 1.879 51.05 0.88 3.833 0.16 0.99
    90 ℃ 4.202 2.97 29.32 0.92 2.454 41.60 0.95 4.195 0.17 0.99
    不同吸附压力 1 MPa 2.523 1.255 50.26 0.69 1.099 56.44 0.83 2.514 0.36 0.99
    2 MPa 3.578 2.003 44.02 0.74 1.559 56.43 0.84 3.569 0.25 0.99
    3 MPa 4.062 2.391 41.14 0.77 1.770 54.54 0.86 4.053 0.22 0.99
    4 MPa 4.431 2.708 38.89 0.78 1.931 57.67 0.87 4.423 0.18 0.99
    下载: 导出CSV 
    | 显示表格

    1)常规取心时,瓦斯解吸量随取心管壁温度上升逐渐增大;解吸曲线分为初期快速增长、后期稳定增长两阶段。管壁外热分别为60、70、80、90 ℃时,30 min内解吸量分别为6.587、7.082、7.460和7.981 cm3/g,较之恒温30 ℃解吸量5.793 cm3/g的增幅分别为13.71%、22.25%、28.78%和37.77%。可见取心管采样过程中产生的摩擦热会大大增加煤心瓦斯损失量。

    2)低温取心过程中,煤心解吸量曲线出现倒吸回流现象,这是降温导致煤样罐内压力小于大气压造成的。通过不含瓦斯煤倒吸对比试验校正,得到低温取心真实解吸量,相较于常规取心,低温取心解吸量快速增长的时间更短;且随着管壁外热降低,解吸量逐渐减小。管壁外热分别为60、70、80、90 ℃时,30 min内低温取心解吸量分别为3.578、3.842、4.215和4.76 cm3/g,较之常规取心的解吸抑制率在40%~46%间。

    3)低温环境下,瓦斯解吸量随平衡压力升高逐渐增大,但增长幅度逐渐减小;前10 min内的解吸速率衰减率最大。低温取心扩散系数较之常规取心减少得多;且扩散系数随着降温呈现线性降低。

  • 图  1   储水采热法地热开采系统空间分布示意[2]

    Figure  1.   Spatial distribution diagram of geothermal exploitation system with water storage and heat production system[2]

    图  2   破碎岩体室内实验与数值模拟应力应变曲线对比

    Figure  2.   Stress-strain curve of broken rock mass numerical simulation and indoor experiment

    图  3   破碎岩体颗粒离散元数值模型建立过程

    Figure  3.   Broken rock mass specimen generation by particle discrete elements

    图  4   破碎岩体试样颗粒级配分布

    Figure  4.   Particle size gradings of broken rock mass specimens

    图  5   不同级配破碎岩体应力−应变曲线

    Figure  5.   Stress-strain curve of broken rock mass with different particle size grade

    图  6   空隙率监测位置示意

    Figure  6.   Schematic diagram of voidage monitoring position

    图  7   不同级配破碎岩体空隙率变化曲线

    Figure  7.   Changing law of porosity of broken rock mass with different particle size grading

    图  8   不同颗粒级配破碎岩体能量–应变曲线

    Figure  8.   Energy and strain changing curve of broken rock mass with different size gradings

    图  9   不同级配破碎岩体断裂能曲线

    Figure  9.   Bond energy density changing curve of different size grading scheme

    图  10   破碎岩体数值模型切割面位置

    Figure  10.   Relative position of cutting plane and numerical sample

    图  11   力链和裂隙分布

    Figure  11.   Force chain and fracture field

    图  12   G1试样切面的力链和颗粒分布

    Figure  12.   Cutting plane of force chain and particles for G1 specimen

    图  13   某岩块断裂切面示意

    1—断裂轨迹;2—颗粒密集区域;3—颗粒非密集区

    Figure  13.   Description of processing

    图  14   裂隙与岩块分布切面(ε=0.3)

    Figure  14.   Cutting plane of fracture field and fragments distribution (ε=0.3)

    图  15   某岩块内颗粒追踪轨迹

    Figure  15.   Track line of particles in fragment

    图  16   ε=0.33时的颗粒轨迹细节

    Figure  16.   Detailed diagram of particle tracks when ε=0.33

    ρp(颗粒密度)/(kg·m−3)2700
    deform_emod (线性接触模量)/GPa5.3
    pb_deform_emod (平行黏结模量)/GPa49.7
    pb_ten (抗剪强度)/MPa43
    pb_coh (法向强度)/MPa52
    kratio (刚度比)1.2
    下载: 导出CSV
  • [1] 袁 亮. 废弃矿井资源综合开发利用助力实现“碳达峰、碳中和”目标[J]. 科技导报,2021,39(13):1.

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出版历程
  • 收稿日期:  2023-11-12
  • 网络出版日期:  2024-01-29
  • 刊出日期:  2024-02-22

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