中国多金属结核开辟区间隙水中铜、锰、镍的分布规律

通过对东北太平洋海域中国多金属结核开辟区沉积物间隙水中铜、锰、镍等微量元素的详细研究表明,锰主要受沉积环境的影响,其含量的变化范围在0.16～8.61μg/dm3之间;铜和镍则主要与表层海水的初级生产力有关,研究区内间隙水中铜和镍含量的变化范围分别为0.16～20.8和0.80～3.12μg/dm3,且这些元素在沉积物—水界面处均存在最大浓度梯度.利用“Fick扩散定律”计算表明,锰在研究区主要是从上覆海水向沉积物扩散,是沉积物中锰的主要来源之一;而铜和镍则是从沉积物向上覆海水扩散,是底层海水中铜和镍的主要来源。与表层海水中铜和镍向底层海水的输送通量计算结果相比,底层海水中铜和镍的含量主要受沉积物的控制.     

痕量金属标准海水的研制

本文介绍了以海水为基体的痕量金属(Cu、Pb、Cd、Cr、Zn)标准物质的制备、均匀性和稳定性,经试验,在一年零三个月时间内各元素的浓度值为Cu5.0±0.4、Pb10.0±0.6、Cd1.00±0.06、Cr5.0±0.4、Zn70±3μg/kg。     

太平洋麦哲伦海山区Roskomnedra平顶山地质构造特征与含矿性

1981年，法、美科学家用“太阳号”科考船在太平洋中部开展的工作，开始带动对海底山和平顶山富钴铁锰结壳的调查研究热潮。D．J．Frank等人关于多金属结壳适宜作为钴矿开采的观点，以及钴矿价格急剧增长引起的一系列政治问题就发生在这之前。     

天然水体中的胶体粒子

介绍了天然水特别是海水中胶体粒子的基本特性和最新研究成果，如胶体粒子的大小组成、粒径分布情况、逗留时间、对痕量金属的吸附、一些相关的分析分离方法以及在生态环境中的可能作用等，并对今后的有关研究方向作出预测。     

中国多金属结核开辟区东、西两小区小型底栖动物的空间分布

利用 1 998年“大洋一号”调查船 DY95 - 8航次在中国多金属结核开辟区东、西两小区用多管取样器采集的沉积物样品 ,对小型底栖动物的组成、分布及其与环境因子的关系进行了研究。结果表明 :(1 )东、西两小区共有 1 6个类群的小型底栖动物 ,其中线虫类占居显著优势 ,在东、西两小区各占总栖息密度的 71 %和 6 4 %,其次为猛水蚤类和蜱螨类。 (2 )东、西两小区小型底栖动物类群平均栖息密度分别为 3 2 .47ind/1 0 cm2 和 1 8.0 5 ind/1 0 cm2 ,东小区高于西小区。小区各站位间的栖息密度平面分布差异显著。 (3 )东、西两小区小型底栖动物类群栖息密度的垂直分布趋势明显 ,由表层向底层 ,栖息密度逐渐降低。 (4)东、西两小区小型底栖动物空间分布与底质沉积物、结核覆盖率和底层流等环境因子密切相关 ,底质较硬、结核覆盖率较高以及底层流较强都不利于小型底栖动物的栖息。     

Mineralogical characteristics of polymetallic sulfides from the Deyin-1 hydrothermal field near 15°S,southern Mid-Atlantic Ridge

A seafloor hydrothermal field, named Deyin-1 later, near 15°S southern Mid-Atlantic Ridge(SMAR) was newly found during the 22 nd cruise carried out by the China Ocean Mineral Resources Research Development Association(COMRA). Sulfide samples were collected at three stations from the hydrothermal field during the26 th cruise in 2012. In this paper, mineralogical characteristics of the sulfides were analyzed with optical microscope, X-ray diffractometer, scanning electron microscope and electron microprobe to study the crystallization sequence of minerals and the process of hydrothermal mineralization. According to the difference of the ore-forming metal elements, the sulfide samples can be divided into three types:(1) the Ferich sulfide, which contains mainly pyrite and chalcopyrite;(2) the Fe-Cu-rich sulfide consisting predominantly of pyrite, chalcopyrite and isocubanite, with lesser amount of sphalerite, marmatite and pyrrhotine; and(3) the Fe-Zn-rich sulfide dominated by pyrite, sphalerite and marmatite, with variable amounts of chalcopyrite, isocubanite, pyrrhotine, marcasite, galena and gratonite. Mineral precipitations in these sulfides are in the sequence of chalcopyrite(isocubanite and possible coarse pyrite), fine pyrite,sphalerite(marmatite), galena, gratonite and then the minerals out of the dissolution. Two morphologically distinct generations(Py-I and Py-II) of pyrite are identified in each of the samples; inclusions of marmatite tend to exist in the coarse pyrite crystals(Py-I). Sphalerite in the Fe-Zn-rich sulfide is characterized by a"chalcopyrite disease" phenomenon. Mineral paragenetic relationships and a wide range of chemical compositions suggest that the environment of hydrothermal mineralization was largely changing. By comparison, the Fe-rich sulfide was formed in a relatively stable environment with a high temperature, but the conditions for the formation of the Fe-Cu-rich sulfide were variable. The Fe-Zn-rich sulfide was precipitated during the hydrothermal venting at relatively low temperature.     

东太平洋海隆13°N表层含金属沉积物物质组成与元素赋存状态

为了解不同类型含金属沉积物在物质组成和元素赋存状态的差异,对东太平洋海隆13°N洋中脊两侧表层含金属沉积物(站号:E271和E53)进行了矿物学、地球化学分析,顺序提取实验,并与前人对轴部表层沉积物(站号:17A-EPR-TVG1)的研究结果作了对比分析。研究结果表明, E271和E53是远端含金属沉积物,由非浮力热液羽状流中颗粒物沉降所形成的;17A-EPR-TVG1沉积物是近喷口含金属沉积物,由黑烟囱或者热液硫化物丘状体崩塌、堆积,或者由热液羽状流中Fe-Mn氧化物和硫化物快速沉淀而形成的,近喷口沉积物比远端沉积物更富集Fe、Cu和Zn等元素。元素在两种含金属沉积物中的赋存状态基本相同,除了Fe,Cu,Zn,Mo和稀土元素(REE)等元素在远端沉积物中主要存在于Fe-Mn氧化物相,在近喷口沉积物中主要在残留相中。远端沉积物中REE页岩标准化配分模式与海水相似,表明REE主要来自海水,而近喷口沉积物中REE配分模式与热液流体相似,说明REE以高温热液流体来源为主。相关研究结果加深了对热液沉积作用研究的认识。     

Low-temperature alteration of oceanic island basalts and their contribution to transition metal circulation of the ocean

The major elements, rare earth elements （REE） and trace elements of four basalt samples from central and western Pacific ferro- manganese crust provinces have been analyzed using chemical methods and ICP - MS, respectively. The results indicate that the samples have been extensively altered and that the contents of their major elements have changed significantly. However, the similarity of REE partition patterns and trace element contents of basalt samples to those of fresh oceanic island basalts （OIB） indicate that the basalt samples originated as OIB. Because of low-temperature alteration, the contents of A1203 , Fe203 , MnO, K20 and P205 increased, while MgO and FeO decreased. Active components, such as magnesium and iron, were leached from OIB resulting in the relative enrichment of SiO2. The leaching of active components can cause the relative enrichment of REE, while the precipitation of LREE-rich ferromanganese oxides in vesicles and fissures not only causes an increase of REE contents, but also induces ＂fractionation＂ of LREE and HREE. Based on the enrichment mechanism of REE contents, the theoretical quantities of precipitated ferromanganese oxides and the depleted quantities of active components are calculated ： the depleted quantities of active components for the unit mass of fresh basalts vary in the range of 0.15 ～ 0. 657, and the precipitated quantities of ferromanganese oxides for the unit mass of fresh basahs vary in the range of 0. 006 ～ 0. 042. Of the major elements, the two most depleted are iron, and magnesium, with 18.28% ～ 70.95% of iron and 44.50% ～ 93.94% of magnesium in the fresh basalts was leached out. Theoretical calculation and geochemistry results both indicate that low-temperature alteration of basalts can supply abundant amount of metals to seawater, and may play an important role in ocean metal circulation.     

“海洋四号”船再赴太平洋勘查

地矿部广州海洋地质调查局“海洋四号”科学调查船已于5月8日从广州启航再赴东太平洋海域，开始了“八五”大洋多金属结核资源研究开发计划的第三个航次--DY85-3航次的航行。     

基于深度学习的钨钼找矿靶区预测方法研究

随着矿产勘查工作由浅部矿向深部隐伏矿、由易识别矿向难识别矿发展,找矿难度日益增大,地质专家越来越重视新理论、新方法、新技术的应用。深度学习作为人工智能的前沿领域/技术,对于实现矿产资源预测“智能化预测评价”具有得天独厚的优势。本文以陕西省镇安县西部钨钼矿集区单元素化探异常原始数据为基础,提出了基于深度学习的钨钼矿产评价方法。该方法以归一化地球化学数据作为模型训练数据,通过深度学习中深度自编码网络方法实现异常值提取进而识别重点成矿有利地段,实现矿产资源找矿远景区定性预测。研究结果表明,在对957条单元素化探异常原始数据分类且做好模型标签后,整个过程在计算机的“黑盒子”中自动完成学习和预测,相较于传统预测研究方法,本文方法具有自动化程度高和客观性强的特征。此外,本文利用已知矿点构建训练数据集,采用随机森林方法对预测区进行矿产资源找矿靶区预测圈定,为进一步缩小找矿靶区范围提供科学依据。