【摘要】 粤北长江矿集区是我国花岗岩型铀矿的重要产区，分布有我国现存唯一的特大型硬岩铀矿床——棉花坑铀矿床。为评价该区北部深部铀矿找矿潜力，选取与棉花坑铀矿床成矿条件相似的犁壁岭地段，开展了RaA氡气、分量化探联袂测量，从而进一步扩大SN向断裂带的找矿成果。方法组合的可行性研究及犁壁岭地段找矿实践表明，RaA氡气、分量化探联袂测量方法能够有效预测深部隐伏铀矿，隐伏铀矿化体常定位于U-Rn-Be-Mo等找矿指示元素的复合异常区。针对区内找矿指示元素在局部铀成矿有利位置存在弱异常的现象，提出采用多找矿指示元素组合构建铀成矿有利地段综合预测指数（H），用于弥补依靠U、Rn复合异常定位隐伏矿体会遗漏部分铀成矿有利位置的缺点，达到强化弱异常及指示隐伏矿体有效信息的目的。据此，在犁壁岭地段预测了4处综合异常（编号为ZH-1～ZH-4），从中优选异常面积最大、浓集程度最高的ZH-3号异常进行钻探揭露验证。结果显示，14号和19号带揭露到累计视厚度为8.80 m、平均品位为0.085%的工业铀矿段，证实犁壁岭地段深部具备良好的铀矿找矿潜力，扩大了长江矿集区北部的找矿空间。更多还原

【Abstract】 The Changjiang mineral concentration area in northern Guangdong is a significant production region for granite-hosted uranium deposits in China, notably housing the Mianhuakeng deposit, the nation’s sole super large-scale hard-rock uranium deposit. Uranium mineralization in this area is primarily influenced by near northsouth trending fault zones, which are characterized by considerable thickness, high grade, and strong continuity. In order to assess the deep prospecting potential in the northern extension faults of the Changjiang mineral concentration area, the Libiling segment was selected due to its analogous uranium metallogenic conditions to the Mianhuakeng deposit. This segment was subjected to integrated surveys utilizing RaA radon gas measurement and partial extraction geochemical prospecting methods. The aim of this study was to further enhance prospecting outcomes associated with the north-south trending fault zones. The feasibility study of this methodological combination and subsequent exploration practice in the Libiling segment demonstrated the efficacy of integrating RaA radon gas measurement with partial extraction geochemical prospecting methods for predicting deeply concealed uranium deposits. This integrated approach leverages the convenience and immediacy of RaA radon gas measurements alongside the reliability of partial extraction geochemical prospecting in detecting anomalies associated with mineralization. Research indicates that concealed uranium ore bodies are typically situated within composite anomalies of key pathfinder elements, such as uranium(U), radon(Rn), beryllium(Be), and molybdenum(Mo). This pattern is governed by the metallogenic characteristics of hydrothermal uranium deposits, specifically the “synergistic migration and enrichment of multiple elements”,which inevitably results in a composite altered geochemical field exhibiting significant spatial correlation with uranium. In response to the presence of weak anomalies of pathfinder elements in some uranium-prospective locations within the area, a comprehensive prediction index(H) for favorable uranium mineralization areas is proposed by the use of a multi-element combination. This index is designed to address potential oversights in identifying favorable mineralization sites that may occur when relying exclusively on uranium(U) and radon(Rn) composite anomalies for targeting concealed ore bodies. The objective is to “enhance weak anomalies and extract effective information indicative of concealed mineralization”, thereby reducing the likelihood of missing concealed ore bodies in the Libiling segment. Based on the analysis conducted, and with a threshold value of H≥28.1 for the composite predictive index, four composite anomalies(designated as No. ZH-1 to No. ZH-4) were identified, taking into account the geological context of the study area. Among these, the No. ZH-3 anomaly, which exhibits the largest area and highest concentration, was selected for drilling verification. The results revealed an industrial-grade uranium orebody with a cumulative apparent thickness of 8.80 meters and an average grade of 0.085%. This orebody is closely associated with silicification, hematitization, and purplishblack fluoritization within fault belts No.14 and No.19. These findings not only confirm that the deep part of the Libiling segment possesses considerable uranium prospecting potential but also expand the prospecting space in the northern part of the Changjiang mineral concentration area. Furthermore, it provides a scientific reference for deep uranium prospecting prediction in adjacent regions.更多还原