Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences
School of Geoscience & Surveying Engineering, China University of Mining and Technology (Beijing)

位于西藏羊八井−谷露裂谷中的地热水锂含量高于西藏温泉平均水平，但其水化学成因仍有争议，主要原因之一为该区域地热水中锂的空间分布规律不明。常见的空间规律分析方法为普通克里金法(Ordinary Kriging)和协同克里金法(CO-Kriging)，但前者精度不高，后者难以获得合适的辅助变量。为此，提出2种确定辅助变量的方法：一是采用与锂相关性最强的物理化学指标Cl−浓度作为辅助变量；二是采用主成分分析综合指标F作为辅助变量。将2种辅助变量分别耦合进CO-Kriging中，形成Cl−-CO-Kriging和F-CO-Kriging方法，用以分析西藏羊八井−谷露裂谷中的地热水锂分布规律。结果表明，相比于Ordinary Kriging，F-CO-Kriging和Cl−-CO-Kriging预测精度有明显提高；其中F-CO-Kriging的EMA和ERMS平均提高30.3%，Cl−-CO-Kriging的EMA和ERMS平均提高28.5%，而且显示地热水中的锂与断裂在空间分布上具有一致性，在谷露地热区锂有明显的富集现象。进一步采用系统聚类和因子分析方法，探究影响地热水中锂空间分布的水化学成因发现，高温、高TDS、低Ca2+浓度、低Mg2+浓度、高硼浓度的碱性环境中锂浓度更高。研究成果为探讨青藏高原地热水中的高锂乃至其他稀有金属的成因和资源评价奠定基础。

In the Yangbajing-Gulu rift, located in Xizang, the lithium concentration in geothermal water exceeds the average level of thermal springs in Xizang. However, the hydrochemical genesis of lithium in geothermal water in this rift remains controversial, and one primary reason for this is the unclear spatial distribution pattern of lithium. Common methods for analyzing spatial distribution patterns include Ordinary Kriging and CO-Kriging. Nevertheless, the former suffers low precision. For the latter, it is difficult to obtain suitable auxiliary variables. Given this, this study determined two auxiliary variables: (1) the Cl− concentration, a physicochemical parameter exhibiting the strongest correlation with lithium, and (2) comprehensive index F, as determined using principal component analysis. Integrating these two auxiliary variables separately into the CO-Kriging method formed the Cl−-CO-Kriging and F-CO-Kriging methods, which were employed to analyze the spatial distribution patterns of lithium in geothermal water in the Yangbajing-Gulu rift. The results indicate that, compared to Ordinary Kriging, both F-CO-Kriging and Cl−-CO-Kriging demonstrated significantly elevated prediction accuracy, with the former increasing EMA and ERMS by 30.3% and the latter by 28.5% on average. Furthermore, both methods revealed that lithium in geothermal water exhibits a spatial distribution consistent with faults and notable enrichment in the Yangbajing-Gulu geothermal area. This study further explored the hydrochemical genesis of the spatial distribution of lithium in geothermal water using hierarchical clustering and factor analysis. The results show that an alkaline environment characterized by high temperatures, high total dissolved solids (TDS), low Ca2+ and Mg2+ concentrations, and elevated born concentrations presents high lithium concentrations. The findings of this study will lay the groundwork for exploring the origin of high-concentration lithium and other rare metals in geothermal water on the Qinghai-Xizang Plateau and conducting relevant resource evaluation.

第二次青藏高原综合科学考察项目(2022QZKK0202)

陈娅奎，孔彦龙，段佳斌，等. 羊八井−谷露裂谷地热水锂空间分布规律及其成因的统计分析[J]. 煤田地质与勘探，2024，52(1)：177−188.

CHEN Yakui，KONG Yanlong，DUAN Jiabin，et al. Statistical analysis of the spatial distribution and genesis of lithium in geothermal water in the Yangbajing-Gulu rift, Xizang[J]. Coal Geology & Exploration，2024，52(1)：177−188.