Remote sensing-based identification and potential evaluation of the mineralization elements of calcrete-hosted uranium deposits in Saudi Arabia
GUO Bangjie1(), PAN Wei2, ZHANG Chuang2, ABDULLAH I. Nabhan3, HASSAN Zowawi3
1. China Institute of Nuclear Industry Strategy, Beijing 100048, China 2. Beijing Research Institute of Uranium Geology, Beijing 100029, China 3. Saudi Geological Survey, Jeddah 21514, Saudi Arabia
This study aims at the identification and potential evaluation of the mineralization elements of calcrete-hosted uranium deposits in Saudi Arabia through the exploration of calcrete-hosted uranium deposits in the uranium exploration project of China and Saudi Arabia. Based on satellite (ASTER) remote sensing data and DEM data, the uranium metallogenic conditions of three calcrete areas were compared and analyzed using methods including visual discrimination, hydrological analysis, and principal component analysis and techniques including uranium source evaluation, source-pathway-trap system division, and ore-bearing rock identification. The results show that Area 2 has the most complete uranium metallogenic conditions in terms of uranium source and source-pathway-trap conditions, Area 1 lacks a good sedimentary basin as a drainage area, and Area 3 lacks a good uranium source. Accordingly, the following conclusions were drawn. The integrity of the source-pathway-trap system is crucial and indispensable for the metallogenesis of calcrete-hosted uranium deposits. Moreover, high-quality uranium sources and sedimentary environments are conducive to the formation of large-scale calcrete-hosted uranium deposits. The duration of uranium enrichment and accumulation directly affects the scale of calcrete-hosted uranium deposits. The favorable sedimentary environment for calcrete-hosted uranium deposits is an evaporative lake (playa) with large uranium sources in the study areas of Saudi Arabia. Therefore, this study can guide the exploration of calcrete-hosted uranium deposits in similar areas.
郭帮杰, 潘蔚, 张闯. 基于遥感技术沙特阿拉伯地区钙结岩型铀矿成矿要素识别及潜力评价[J]. 自然资源遥感, 2022, 34(4): 299-306.
GUO Bangjie, PAN Wei, ZHANG Chuang, ABDULLAH I. Nabhan, HASSAN Zowawi. Remote sensing-based identification and potential evaluation of the mineralization elements of calcrete-hosted uranium deposits in Saudi Arabia. Remote Sensing for Natural Resources, 2022, 34(4): 299-306.
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