Quantitative prediction process and evaluation method for seafloor polymetallic sulfide resources
文献类型：期刊论文
| 作者 | Ren, Mengyi1; Chen, Jianping1; Shao, Ke1; Yu, Miao1; Fang, Jie1 |
| 刊名 | GEOSCIENCE FRONTIERS
 |
| 出版日期 | 2016 |
| 卷号 | 7期号:2页码:245-252 |
| 通讯作者 | Chen, JP (reprint author), China Univ Geosci, Sch Earth Sci & Resources, Beijing 100083, Peoples R China. ; Chen, JP (reprint author), China Univ Geosci, Inst Land Resources & High Tech, Beijing 100083, Peoples R China. ; Chen, JP (reprint author), China Univ Geosci, Beijing Key Lab Dev & Res Land Resources Informat, Beijing 100083, Peoples R China. |
| 英文摘要 | Seafloor polymetallic sulfide resources exhibit significant development potential. In 2011, China received the exploration rights for 10,000 km(2) of a polymetallic sulfides area in the Southwest Indian Ocean; China will be permitted to retain only 25% of the area in 2021. However, an exploration of seafloor hydrothermal sulfide deposits in China remains in the initial stage. According to the quantitative prediction theory and the exploration status of seafloor sulfides, this paper systematically proposes a quantitative prediction evaluation process of oceanic polymetallic sulfide resources and divides it into three stages: prediction in a large area, prediction in the prospecting region, and the verification and evaluation of targets. The first two stages of the prediction process have been employed in seafloor sulfides prospecting of the Chinese contract area. The results of stage one suggest that the Chinese contract area is located in the high posterior probability area, which indicates good prospecting potential area in the Indian Ocean. In stage two, the Chinese contract area of 48 degrees-52 degrees E has the highest posterior probability value, which can be selected as the reserved region for additional exploration. In stage three, the method of numerical simulation is employed to reproduce the ore-forming process of sulfides to verify the accuracy of the reserved targets obtained from the three-stage prediction. By narrowing the exploration area and gradually improving the exploration accuracy, the prediction will provide a basis for the exploration and exploitation of seafloor polymetallic sulfide resources. (C) 2015, China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. |
| 学科主题 | Geology |
| 类目[WOS] | Geosciences, Multidisciplinary |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000370603300009 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39538]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.China Univ Geosci, Sch Earth Sci & Resources, Beijing 100083, Peoples R China 2.China Univ Geosci, Inst Land Resources & High Tech, Beijing 100083, Peoples R China 3.China Univ Geosci, Beijing Key Lab Dev & Res Land Resources Informat, Beijing 100083, Peoples R China 4.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 5.China Geol Survey, Nanjing Ctr, Nanjing 210016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ren, Mengyi,Chen, Jianping,Shao, Ke,et al. Quantitative prediction process and evaluation method for seafloor polymetallic sulfide resources[J]. GEOSCIENCE FRONTIERS,2016,7(2):245-252. |
| APA | Ren, Mengyi,Chen, Jianping,Shao, Ke,Yu, Miao,&Fang, Jie.(2016).Quantitative prediction process and evaluation method for seafloor polymetallic sulfide resources.GEOSCIENCE FRONTIERS,7(2),245-252. |
| MLA | Ren, Mengyi,et al."Quantitative prediction process and evaluation method for seafloor polymetallic sulfide resources".GEOSCIENCE FRONTIERS 7.2(2016):245-252. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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