基于Kd的某酸法地浸铀矿山地下水铀运移模拟

doi:10.13745/j.esf.sf.2023.2.69

摘要/Abstract

摘要：

地浸铀矿山地下水U污染问题是国际社会广泛关注的环境地质问题,准确预测地浸铀矿山采区外围地下水中U的运移范围对辐射风险评估至关重要。本文以我国某酸法地浸铀矿山为研究对象,利用数值模拟方法定量模拟和预测了不同生产时间地下水中U的运移范围。数值模拟结果表明,地浸生产会明显改变采区流场形态,形成指向采区内部的水力梯度,生产井的抽注是改变流场形态的主控因素。在流场模拟的基础上,建立了不考虑吸附作用的地下水U运移模型与基于K_d值的U阻滞运移模型。根据采区内生产井及采区外围不同距离处监测井地下水pH情况,对阻滞运移模型中的K_d进行了分区赋值。对比两个模型的模拟结果可以发现,当考虑含水介质对地下水中U的吸附阻滞作用后,模拟结果能够跟现场监测数据更好拟合,表明地浸采区外围地下水中U的运移范围受含水介质的吸附阻滞作用明显;这种情况下,U在地下水中的运移距离缩短了53%,运移范围缩小了41%;阻滞运移模型预测的投产5年后采区外围地下水中U迁移距离为50 m。该结果与现场监测结果基本一致,证明数值模拟手段可以为地浸铀矿山地下水U分布范围预测提供科学依据。

关键词: 地浸铀矿山, 地下水环境, 数值模拟, 溶质运移

Abstract:

Uranium (U) contamination of groundwater at in-situ leaching uranium mines is a global environmental geological problem. Accurately predicting the transport range of U in the groundwater outside the in-situ leaching mining areas is crucial to radiation risk assessment. In this study, the migration range of groundwater U at different production times was quantitatively simulated and predicted by numerical simulation method from an acid in-situ leaching uranium mine. The numerical simulation results showed that the mining activities of in-situ leaching uranium significantly changed the groundwater flow field in the mining area, and depression cones were induced by the high ratio of pumping to injection inside the mining area. On the basis of flow modeling, the transport model of groundwater U without considering adsorption and the retardation transport model based on K_d value were established. According to the groundwater pH of production well and monitoring wells at different distances outside the mining area, different K_d value was assigned by regions. By comparing the simulation results of the two models, it could be found that when considering the adsorption-retardation effect of aqueous medium on groundwater U, the simulation results could be better fitted with the field monitoring data, indicating that the migration of U in groundwater was significantly retarded by the aqueous medium. The U reactive transport model showed that the migration distance and range were reduced by 53% and 41%, respectively. Besides, the model predicted that the migration distance of groundwater U in the mining area was 50 m after 5 years of mining, which was consistent with the monitoring results. It was proven that the numerical simulation method, as an effective tool, could be successfully used to predict the impact of in-situ mining on groundwater environment at the uranium mining site.

Key words: in-situ leaching uranium mine, groundwater environment, numerical simulation, reactive transport

中图分类号:

X523

杨冰, 孟童, 郭华明, 连国玺, 陈帅瑶, 杨曦. 基于K_d的某酸法地浸铀矿山地下水铀运移模拟[J]. 地学前缘, 2024, 31(3): 381-391.

YANG Bing, MENG Tong, GUO Huaming, LIAN Guoxi, CHEN Shuaiyao, YANG Xi. K_d-based transport modeling of uranium in groundwater at an acid leaching uranium mine[J]. Earth Science Frontiers, 2024, 31(3): 381-391.

图/表 19

图1 C1-C9采区外围监测井布置示意图

Fig.1 The monitoring well sites of C1-C9 mining areas

图2 模型范围

Fig.2 The range of models

表1 主要输入参数一览表

Table 1 Main input parameters

序号	参数及其单位	数值
1	渗透系数,m/d	5.76
2	垂直各向异性系数	10
3	孔隙度,%	30
4	纵向弥散度,m	2
5	横向弥散度,m	20
6	弹性释水率,m^-1	10^-5

图3 生产井抽注液量概化情况流量为正值代表注液井;负值代表抽液井。

Fig.3 The conceptualization flow rate of production and injection wells

图4 模拟区水平剖分

Fig.4 The horizontal spatial discretization

图5 模拟区垂向剖分

Fig.5 The vertical spatial discretization

表2 不同井位地下水pH

Table 2 The pH value of groundwater in different wells

井编号	井类型	位置	pH
KC9502	抽液井	采区内	1.19
6034-1	监测井	采区边界外10 m	2.15
6034-2	监测井	采区边界外30 m	7.38
6034-3	监测井	采区边界外50 m	7.45
6034-4	监测井	采区边界外100 m	7.35
6034-5	监测井	采区边界外150 m	7.27

图6 模型Kd分区图

Fig.6 The Kd Model partition diagram

表3 拟合结果

Table 3 The fitted parameters

序号	观测/拟合日期	(X_obs)_max	(X_obs)_min	n	$1 n ∑ i = 1 n R i 2$	误差/ %	备注
1	2018-11-06	940.65	938.51		0.32	15.15	模型识别
2	2019-05-10	940.84	938.77		0.33	15.95
3	2019-07-21	941.51	938.00	21	0.47	13.48
4	2019-11-17	941.37	939.15		0.46	20.60	模型验证

表3 拟合结果

Table 3 The fitted parameters

序号	观测/拟合日期	(X_obs)_max	(X_obs)_min	n	$1 n ∑ i = 1 n R i 2$	误差/ %	备注
1	2018-11-06	940.65	938.51		0.32	15.15	模型识别
2	2019-05-10	940.84	938.77		0.33	15.95
3	2019-07-21	941.51	938.00	21	0.47	13.48
4	2019-11-17	941.37	939.15		0.46	20.60	模型验证

表4 绝对平均误差拟合分布

Table 4 The fitting distribution of absolute mean errors

观测/拟合日期	平均绝对误差范围	观测井个数	各误差范围观测井个数占总数的比例/%
2018-11-06	<0.5 m	18	85.71
	0.5~1 m	3	14.29
	0 m	0	0
2019-05-10	<0.5 m	18	85.71
	0.5~1 m	3	14.29
	0 m	0	0
2019-07-21	<0.5 m	15	71.43
	0.5~1 m	6	28.57
	0 m	0	0
2019-11-17	<0.5 m	13	61.91
	0.5~1 m	7	33.33
	0 m	1	4.76

图7 2018—2019年监测井水头拟合情况 A—2018年11月;B—2019年5月;C—2019年7月;D—2019年11月。

Fig.7 The fitting of waterhead in monitoring wells in 2018-2019 (A—in November 2018; B—in May 2019; C—in July 2019; D—in November 2019)

图8 不同模拟时间采区流场图

Fig.8 The flow field diagram at different simulation time

图9 采区降落漏斗示意图

Fig.9 Diagram of falling funnel in mining area

图10 C8采区地下水U浓度分布模拟结果

Fig.10 The fitting results of U concentration distribution in groundwater from C8 mining area

图11 地下水U浓度模拟值与实测值对比

Fig.11 Comparison of simulated and measured groundwater U concentration

图12 考虑阻滞作用U迁移范围

Fig.12 The U migration range when the retardation was considered

图13 6034-1监测井U(IV)浓度拟合结果

Fig.13 The fitting results of U(IV) concentration in 6034-1 monitoring well

图14 不考虑吸附阻滞时模拟期末C8采区地下水U浓度分布

Fig.14 The distribution of U concentrations in C8 mining area groundwater at the end of the simulation period when the adsorbent retardation was not considered

图15 考虑吸附阻滞时模拟期末C8采区地下水U浓度分布

Fig.15 The distribution of U concentrations in C8 mining area groundwater at the end of the simulation period when the adsorbent retardation was considered

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