Department of Mineralogy and Geology, University of Debrecen, Debrecen, 4032, Hungary.
Geology Department, Tanta University, Tanta, 31527, Egypt.
Sci Rep. 2023 Jun 6;13(1):9173. doi: 10.1038/s41598-023-36388-7.
Since their recent first record within the Egyptian Nubian Shield, auriferous and uraniferous marbles (Au = 0.98-2.76 g/t; U = 133-640 g/t) have rarely been addressed, despite not only their probable economic importance but also the fact that it is a new genetic style of gold and uranium mineralization in the Nubian Shield rocks. This is mainly attributed to the inadequate localization of these marbles within harsh terrains, as well as the cost and time spent with conventional fieldwork for their identification compared to the main lithological components of the Nubian Shield. On the contrary, remote sensing and machine learning techniques save time and effort while introducing reliable feature identification with reasonable accuracy. Consequently, the current research is an attempt to apply the well-known machine learning algorithm (Support vector Machine-SVM) over Sentinel 2 remote sensing data (with a spatial resolution of up to 10 m) to delineate the distribution of auriferous-uraniferous marbles in the Barramiya-Daghbagh district (Eastern Desert of Egypt), as a case study from the Nubian Shield. Towards better results, marbles were accurately distinguished utilizing ALOS PRISM (2.5 m) pan-sharpened Sentinel 2 data and well-known exposures during fieldwork. With an overall accuracy of more than 90%, a thematic map for auriferous-uraniferous marbles and the major rock units in the Barramiya-Daghbagh district was produced. Marbles are spatially related to ophiolitic serpentinite rocks, as consistent with their genesis within the Neoproterozoic oceanic lithosphere. Field and petrographic investigations have confirmed the newly detected Au and U-bearing zones (impure calcitic to impure dolomitic marbles in Wadi Al Barramiya and Wadi Daghbagh areas and impure calcitic marble in Gebel El-Rukham area). Additionally, X-ray diffraction (XRD), back-scattered electron images (BSEIs), and Energy Dispersive X-ray spectroscopy (EDX) results were integrated to verify our remote sensing results and petrographic investigations. Different times of mineralization are indicated, ranging from syn-metamorphism (gold in Wadi Al Barramiya and Gebel El-Rukham) to post-metamorphism (gold in Wadi Daghbagh and uranium in all locations). Based on the application of geological, mineralogical, machine learning and remote sensing results for the construction of a preliminary exploration model of the auriferous-uraniferous marble in the Egyptian Nubian Shield, we recommend a detailed exploration of Au and U-bearing zones in Barramiya-Dghbagh district and applying the adopted approach to other districts of similar geological environments.
自在埃及努比亚盾中首次发现含金和含铀的大理石（金=0.98-2.76 g/t；铀=133-640 g/t）以来，尽管这些大理石不仅具有潜在的经济重要性，而且代表了努比亚盾岩石中一种新的金和铀矿化遗传类型，但它们很少受到关注。这主要归因于这些大理石在恶劣地形中的位置不够精确，以及与努比亚盾的主要岩性成分相比，用于识别它们的常规野外工作的成本和时间。相比之下，遥感和机器学习技术节省了时间和精力，同时以合理的精度引入了可靠的特征识别。因此，当前的研究旨在尝试将著名的机器学习算法（支持向量机-SVM）应用于 Sentinel 2 遥感数据（空间分辨率高达 10 m），以划定 Barramiya-Daghbagh 地区（埃及东部沙漠）含金-含铀大理石的分布情况，作为努比亚盾的一个案例研究。为了获得更好的结果，利用 ALOS PRISM（2.5 m）全色锐化的 Sentinel 2 数据和野外工作中的知名露头，准确区分了大理石。总体准确率超过 90%，生成了 Barramiya-Daghbagh 地区含金-含铀大理石和主要岩石单元的专题地图。大理石与蛇纹石化橄榄岩有关，与其在新元古代海洋岩石圈中的成因一致。野外和岩相调查证实了新发现的含金和含铀带（Wadi Al Barramiya 和 Wadi Daghbagh 地区不纯方解石到不纯白云石质大理石和 Gebel El-Rukham 地区不纯方解石质大理石）。此外，还整合了 X 射线衍射（XRD）、背散射电子像（BSEIs）和能量色散 X 射线能谱（EDX）的结果，以验证我们的遥感结果和岩相调查。指示了不同时期的矿化作用，从变质同期（Wadi Al Barramiya 和 Gebel El-Rukham 中的金）到变质后（Wadi Daghbagh 的金和所有地点的铀）。基于地质、矿物学、机器学习和遥感结果在构建埃及努比亚盾含金-含铀大理石初步勘查模型中的应用，我们建议对 Barramiya-Daghbagh 地区的含金和含铀带进行详细勘查，并将采用的方法应用于类似地质环境的其他地区。
