five

Multi-disciplinary ore deposit exploration in Sonqor, northwest Iran|矿石勘探数据集|地质分析数据集

收藏
DataCite Commons2021-05-24 更新2024-07-28 收录
矿石勘探
地质分析
下载链接:
https://tandf.figshare.com/articles/dataset/Multi-disciplinary_ore_deposit_exploration_in_Sonqor_northwest_Iran/12462617
下载链接
链接失效反馈
资源简介:
Multi-disciplinary exploration methods are used to explore for possible ore deposits in the Sonqor area, Iran, which lies within the Sanandaj-Sirjan Zone, and contains significant iron, copper and gold mineralisation. Hydrothermal alteration was mapped using field, remotely sensed, geophysical and geochemical data as well as Landsat-8 Operational Land Imager, Landsat Enhanced Thematic Mapper plus, and two Advanced Space Borne Thermal Emission and Reflection Radiometer images. Image processing techniques, viz band ratio, principal component analysis (PCA), and various spectral analysis methods were applied to map the distribution of hydrothermally altered rocks (geochemical halos) associated with porphyry (e.g. Cu–Au) mineralisation. The geochemical halos enabled vectoring to mineralised zones with mapping of advance argillic, argillic, carbonates, Fe-oxides, phyllic, propylitic and silicification using minerals such as alunite (K/Na), muscovite, kaolinite, illite, chlorite, goethite, hematite, jarosite, calcite and silica/quartz. The band ratio combination of sensors for mapping altered areas show promising results, similar to other more advanced methods. PCA exposed variations in the spatial distribution of more hydroxyl-based minerals like alunite/jarosite, whereas the geophysical magnetic survey identified the main lineaments, possible faults and magmatic intrusion boundaries. While geochemical methods show the potential occurrence of elements like Fe, Au and Fe-bearing Ti in the southeast and southern parts, and skarn-type anomalies in the northern part of Sonqor, leaking of specific geochemical elements (such as Fe, Au and Fe-bearing Ti) produce false anomalies. Copper, Pb and Zn anomalies in the central part show the possibility of sulfide-based mineralisation.KEY POINTSSpace-based satellite technologies were used to identify mineral prospects in the Sonqor area, within the iron, copper and gold-rich Sanandaj-Sirjan Zone, Iran.The Sonqor area, part of the Zagros Orogen, is within the extensive Alpine–Himalayan orogenic belt formed by collision of the Arabian continent with the Iranian microcontinent in the Late Cretaceous to Cenozoic.The western part of the Sonqor area has first rank Hg, Au, Ag, Ta and Sb anomalies with abundant detachment faults. Dacite domes with surrounding alteration have potential for Au epithermal mineralisation (Dashkasan type); the central part may yield Cu, Zn and Pb sulfide mineralisation.The Sonqor geological map suggests good potential for Au, Fe and Fe–Ti mineralisation at the contact between limestones in the eastern and southeastern parts, but greenschist and amphibolite facies metamorphism necessitates caution in interpretation of geochemical anomalies. Space-based satellite technologies were used to identify mineral prospects in the Sonqor area, within the iron, copper and gold-rich Sanandaj-Sirjan Zone, Iran. The Sonqor area, part of the Zagros Orogen, is within the extensive Alpine–Himalayan orogenic belt formed by collision of the Arabian continent with the Iranian microcontinent in the Late Cretaceous to Cenozoic. The western part of the Sonqor area has first rank Hg, Au, Ag, Ta and Sb anomalies with abundant detachment faults. Dacite domes with surrounding alteration have potential for Au epithermal mineralisation (Dashkasan type); the central part may yield Cu, Zn and Pb sulfide mineralisation. The Sonqor geological map suggests good potential for Au, Fe and Fe–Ti mineralisation at the contact between limestones in the eastern and southeastern parts, but greenschist and amphibolite facies metamorphism necessitates caution in interpretation of geochemical anomalies.
提供机构:
Taylor & Francis
创建时间:
2020-06-11
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

LIDC-IDRI

LIDC-IDRI 数据集包含来自四位经验丰富的胸部放射科医师的病变注释。 LIDC-IDRI 包含来自 1010 名肺部患者的 1018 份低剂量肺部 CT。

OpenDataLab 收录

中国交通事故深度调查(CIDAS)数据集

交通事故深度调查数据通过采用科学系统方法现场调查中国道路上实际发生交通事故相关的道路环境、道路交通行为、车辆损坏、人员损伤信息,以探究碰撞事故中车损和人伤机理。目前已积累深度调查事故10000余例,单个案例信息包含人、车 、路和环境多维信息组成的3000多个字段。该数据集可作为深入分析中国道路交通事故工况特征,探索事故预防和损伤防护措施的关键数据源,为制定汽车安全法规和标准、完善汽车测评试验规程、

北方大数据交易中心 收录

中国农村金融统计数据

该数据集包含了中国农村金融的统计信息,涵盖了农村金融机构的数量、贷款余额、存款余额、金融服务覆盖率等关键指标。数据按年度和地区分类,提供了详细的农村金融发展状况。

www.pbc.gov.cn 收录

CIFAR-10

CIFAR-10 数据集由 10 个类别的 60000 个 32x32 彩色图像组成,每个类别包含 6000 个图像。有 50000 个训练图像和 10000 个测试图像。 数据集分为五个训练批次和一个测试批次,每个批次有 10000 张图像。测试批次恰好包含来自每个类别的 1000 个随机选择的图像。训练批次包含随机顺序的剩余图像,但一些训练批次可能包含来自一个类的图像多于另一个。在它们之间,训练批次恰好包含来自每个类别的 5000 张图像。

OpenDataLab 收录

ImageNet-1K(ILSVRC2012)

ImageNet-1K(ILSVRC2012)是一个大规模的图像分类数据集,包含1000个类别的图像,用于训练和验证图像分类模型。

github 收录