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摘要:
康古尔塔格韧性剪切带是金矿重要控矿带，产有康古尔、马头滩、石英滩等重要矿床。野马泉西金矿即位于该韧性剪切带的东延苦水-雅满苏韧性剪切带上，属韧性剪切带控矿型金矿。本文在野外地质调查基础上采集了野马泉西金矿探矿工程坐标、工程内样品的分析测试成果等数据，采用地质块段法对野马泉西金矿资源量进行了估算，形成了数据集。数据集测试样品均委托有国家甲级资质的测试中心进行，内外检合格率90%以上，数据质量可靠，对周边同类型矿床的资源量估算具参考意义。
Abstract:The Kangguertage ductile shear zone in western China is an important gold ore-controlling belt, where important deposits such as Kangguer, Matoutan and Shiyingtan are found. The West Yemaquan gold ore deposit, typical of the ductile shear zone ore-controlling type, is situated along the eastern shear zone extension-the Kushui-Yamansu ductile shear zone. A new dataset created from estimation of resources in the West Yemaquan gold ore deposit uses the geological ore block method, utilizing data on coordinates of mineral prospecting sites and results obtained from the analytic testing of samples collected during field geological survey in sites within the West Yemaquan Goldfield. All samples for the dataset were tested by national testing centers owning Level-A certificate. The qualified rates from both internal and external inspection are over 90%, indicating that the data are credible and provide important referential implications for the estimation of surrounding deposits of the same kind.
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Key words:
- West Yemaquan gold ore deposit /
- Resource /
- Dateset /
- Ductile shear zone /
- Kumul Xinjiang
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1. 引言
东天山觉罗塔格铜镍铁锰钒钛金银钨钼稀有金属矿带是新疆最重要的成矿带之一，主要矿产地有上百处。康古尔塔格韧性剪切带即位于该矿带内，赋存有康古尔、马头滩、石英滩等重要矿床（董连慧等，2010）。区域地层出露太古宇至新生界，其中以石炭系分布最广。大型构造非常发育，自北向南分布有康古尔塔格−黄山断裂、秋格明塔什−黄山韧性剪切带、苦水−雅满苏断裂带、尾亚韧性剪切带和阿其克库都克−沙泉子大断裂等。岩浆活动频繁，形成的岩浆岩以晚古生代侵入岩最为发育❶。
野马泉西金矿区位于康古尔塔格韧性剪切带的东延苦水−雅满苏韧性剪切带上（图 1）。矿区出露地层较简单，除第四系外，主要见下石炭统雅满苏组，岩性以砾岩、砂岩、硅质粉砂岩为主，夹灰岩和凝灰岩等（图 2）。区内构造发育，规模最大的主断裂为苦水−雅满苏断裂，向东横贯野马泉西整个矿区，呈NE向展布，为北倾逆断层，走向60°~70°，倾角70°~85°。断裂南侧发育一套北强南弱具推覆逆冲性质的走滑型韧性剪切带，由F1、F2控制。韧性剪切带内次级断裂主要有三组，一组与主构造方向大致一致，与剪切带边界成10°~15°夹角；一组与剪切带呈高角度相交，夹角约70°，以NNE向剪性裂隙为主；一组以SN向为主，为压性断裂。目前金矿体多分布于第一组断裂中，后两组断裂中未发现金矿（化）体。矿区岩浆岩发育，以海西中、晚期中酸性侵入岩为主。北侧为花岗闪长岩，南侧为闪长岩。此外中酸性岩脉发育，以花岗斑岩、石英闪长岩、闪长岩脉、石英脉占主体❷。
图 1. 新疆东天山觉洛塔格地区区域地质简图（据韩春明等，2002修改）1—中新生代沉积盖层；2—二叠纪陆相火山−沉积岩系；3—石炭纪火山−沉积岩系；4—奥陶—泥盆纪火山−沉积岩系；5—前寒武纪变质岩；6—花岗岩类；7—金矿床；8—铜矿床；9—铜镍硫化物矿床；10—铁矿床；11—铁铜矿床；12—铅锌矿床；13—银多金属矿床；14—多金属矿床；15—断层；16—剪切带；17—矿区位置
图 2. 野马泉西金矿区地质简图（据任经武等, 2017.新疆东天山野马泉西发现中型金矿床.中国地质调查成果快讯, 3(14): 5−8）1—第四系冲−洪积物；2—下石炭统雅满苏组上段砂岩；3—下石炭统雅满苏组；4—下石炭统雅满苏组下段；5—中华力西期闪长岩；6—中华力西期花岗闪长岩；7—中华力西期钾长花岗岩；8—闪长岩脉；9—石英闪长岩脉；10—花岗斑岩脉；11—石英斑岩脉；12—区域性大断裂；13—次级断裂；14—韧性剪切带；15—地层产状；16—金矿体及编号区内共圈出金矿体群3处（Ⅰ、Ⅱ、Ⅲ，见表 1），其中金矿体12条，金矿化体23条。1号矿体为矿区的主要矿体，总体走向70°。矿体形态多为似层状、透镜状、脉状。矿体长160 m，倾向延伸大于400 m，厚1.14~5.54 m。金品位0.54×10−6~109.10×10−6，矿床成因属韧性剪切带型，工业类型属于石英脉型（资料来源：同图 2）。对该矿床进行资源量的调查与评估，既可对同类型矿床的资源量评估作为参考，又可为研究野马泉西地区同类型矿床的矿体分布特征提供借鉴（刘焕贵等，2017）。
金属矿产资源量估算方法的研究工作开展较多，多侧重于传统方法与地质统计、信息技术相结合或者地质统计学方法（白瑞和等，2010；郭慧锦，2010；肖玉华等，2012；曹建洲等，2015；张鹏川等，2017）。传统资源量估算方法的实质是将自然界不规则的地质体看作近似规则的几何体，然后运用几何学的方法计算几何体的体积，并将其视为矿体的资源量。它包括断面法和地质块段法两种基本方法（张鹏川等，2017），本次资源量估算主要采用地质块段法。
新疆野马泉西金矿区的资源量数据集为3个Excel工作簿（.xls格式），它们分别被命名为“工程登记表”、“样品测试结果表”和“资源量估算表”。其中“工程登记表”工作簿由2个Excel工作表页文件构成，即槽探工程登记表和钻探工程登记表；“样品测试结果表”工作簿由3个Excel工作表页文件构成，即槽探样品测试结果表、钻探样品测试结果表和小体积质量测试结果表；“资源量估算表”工作簿由5个Excel工作表页文件构成，即槽探工程矿体水平厚度与加权平均品位计算表，钻探工程矿体水平厚度与加权平均品位计算表，矿体块段面积计算表，矿体块段厚度与加权品位计算表，以及资源量估算表。
新疆哈密市野马泉西金矿资源量数据集元数据如表 2所示。
2. 数据采集和处理方法
2.1 样品采集
本次调查工作所采集的样品主要来自探槽和钻孔岩心，共采集样品270个。采集的样品包括岩化粉砂岩、变质粉砂岩和石英闪长玢岩等。钻孔岩心采用劈半法，按样长0.8~1.5 m连续采样。地表矿体以10 cm×5 cm规格，0.8~1.5 m一个样品，连续刻槽采样。组合样采用单工程组合，一般视地质情况变化，取2~7个样品为一组合。
角岩化粉砂岩：深灰绿色，变余粉砂结构，块状构造。碎屑较细，一般粒径 < 0.03 mm，属细粉砂级，碎屑物粒度均匀。岩石中泥质物发生变质重结晶作用，产生新生矿物棕红色的黑云母，及少量绢云母。金属矿物少见，有时呈不规则细脉产出。岩石中可见少量石英呈不规则细脉状，或不规则团块状产出，系岩石热变质产物。
变质粉砂岩：灰黑色，青灰色，变余粉砂状结构，变余层理状构造。碎屑物长石粘土化比较明显，石英呈次棱角状。碎屑物粒径多小于0.1 mm，属粗粉砂−细砂级。偶见粗者粒径在0.25 mm左右，属细砂级。碎屑物存在变质结晶现象，长石与石英紧密弯曲镶嵌。泥质物变质重结晶产生新生矿物细鳞片状绢云母、黑云母雏晶等，其晶面展布与岩石的微层理方向一致。岩石受到一定的后期气液交代作用，发生次生石英岩化。石英呈他形粒状，颗粒之间紧密镶嵌，在岩石中分布不均匀，或呈团块状集合体，或断续相连成线状、细脉状，与岩石的微层理方向基本一致。偶见碳酸盐细脉穿切岩石。
石英闪长玢岩：褐黄色、褐色，变余斑状结构，基质显微鳞片微粒变晶结构，定向构造。岩石轻度变质重结晶，斑晶、基质平行定向，新生黑云母呈条痕状平行分布。斜长石含量90%，不等粒，多数呈粒径 < 0.25 mm他形微粒基质。变余斑晶占35%，粒径0.73~1.7 mm×1.2 mm半自形板粒状，斑晶斜长石泥化强，可见双晶，压扁定向密集分布。石英含量5%，粒径一般0.03~0.18 mm，他形粒状，散布于斜长石粒间。黑云母含量5%，黄褐色，显微鳞片状，呈条痕状平行分布于长石和石英颗粒间。偶见粒状磁铁矿，粒径 < 0.05 mm，星点状分布。
2.2 测试方法
金样品测试单位为新疆维吾尔自治区有色地质勘查局测试中心。体重样采用常规蜡封法，化验分析采用原子吸收测定法。
2.3 资源量估算方法
2.3.1 采用的工业指标
按照《岩金矿地质勘查规范》（DZ/T0205−2002）的要求，综合物相分析，确定的金矿物以自然金和硫化物包裹金为主的矿物学特征。其中1号金矿体品位高、规模大，埋藏浅（地表直接出露）（图 3），地形平坦、交通方便，适宜露天开采。确定的工业指标如下：
边界品位Au（10−6）：0.5；
最低工业品位Au（10−6）：1；
最小可采厚度（m）：0.8；
夹石剔除厚度（m）：4。
2.3.2 资源量估算方法的选择及其依据
根据矿体的形态、产状和规模，采用地质块段法，在矿体垂直纵投影图上进行资源量估算（国土资源部储量司，2000）。
资源量估算公式：
式中：Q−矿石量；d−矿石体；S−块段投影面积；H−块段平均水平厚度；P−金属量；c−矿石平均品位。
2.3.3 资源量估算参数的确定
（1）块段面积的测定
在资源量估算的垂直纵投影图上，根据所圈定矿体块段的形态利用MapGIS软件测量块段区面积。
（2）水平厚度的确定
单工程矿体水平厚度采用该工程内切穿矿体厚度连续样品的水平厚度之和。探槽和钻探工程均采用厚度公式计算，即
式中：Hv−矿体水平厚度（m）；L−矿体视厚度（m）；β−工程穿过矿体时坡度角（°）；α−矿体倾角（°）；γ−探槽方位与矿体走向间夹角（°），其中地层倾向与坡向相反取正号，地层倾向与坡向相同取负号。
矿体块体水平厚度为矿块内各单工程矿体水平厚度的算术平均值。
（3）平均品位的确定
单工程矿体平均品位由工程内样品的成矿元素含量与长度加权平均求得：
式中：C−单工程矿体平均品位，C1、C2…Cn−单样品成矿元素含量；L1、L2…Ln−单样品长度（m）。
矿体平均品位采用各单工程加权平均品位算得。
2.3.4 资源量的分类
由于区内工程控制程度低，控制网度较稀疏，本次仅对矿床333类推断的资源量和334类预测的资源量进行估算。矿区内矿体地质块段划分为4段，分别为1号矿体：333、334；38号矿体：333、334。
2.4 金矿测试数据统计表
3. 数据样本描述
“槽探工程登记表”（表 5）包含如下内容：序号、工程编号、施工目的、开工日期、完工日期、地质编录（开始日期、结束日期、编录人）、施工结果、设计长度（单位m）、实际长度（单位m）、设计方位（单位°）、实际方位（单位°）、起点坐标（X、Y、Z）、备注。
“钻探工程登记表”（表 6）包含如下内容：序号、工程编号、施工目的、开工日期、完工日期、地质编录（开始日期、结束日期、编录人）、施工结果、设计长度（单位m）、实际长度（单位m）、设计方位（单位°）、实际方位（单位°）、设计倾角（单位°）、实际倾角（单位°）、起点坐标（X、Y、Z）、备注。
“槽探样品测试结果表”（表 7）包含如下内容：序号、工程编号、样品编号、采用位置[自（单位m）、至（单位m）、计（单位m）]、采样线[样长（单位m）、方位（单位°）、坡度（单位°）]、矿体产状[倾向（单位°）、倾角（单位°）]、Pb品位（单位%）、Zn品位（单位%）、Cu品位（单位%）、Au品位（单位×10−6）。
“钻探样品测试结果表”与“槽探样品分析结果表”一致，同表 7。
“小体积质量测试结果表”（表 8）包含如下内容：序号、样品编号、样品取样工程位置、岩石特征、矿体编号、矿石品位（单位×10−6）（Au、Ag）、小体积质量（单位g/cm3）、备注。
“槽探工程矿体水平厚度与加权平均品位计算表”（表 9）包含如下内容：序号、工程编号、矿体编号、样品编号、采样位置[自（单位m）、至（单位m）、计（单位m）]、采样线[样长（单位m）、方位（单位°）、坡度（单位°）]、勘探线方位（单位°）、矿体产状[倾向（单位°）、倾角（单位°）]、工程方位与矿体倾向夹角（单位°）、样品真厚度（单位m）、样品水平厚度（单位m）、Au品位（单位×10−6）、Au矿体平均品位（单位×10−6）、Au矿体真厚度（单位m）、Au矿体水平厚度（单位m），备注。
“钻探工程矿体水平厚度与加权平均品位计算表”与“槽探工程矿体水平厚度与加权平均品位计算表”一致，见表 9。
“矿体块段面积计算表”（表 10）包含如下内容：矿区、序号、矿体编号、资源量类别、块段面积（单位m2）、备注。
“矿体块段厚度与加权品位计算表”（表 11）包含如下内容：矿区、序号、矿体编号、工程编号、资源量类别、单工程矿体水平厚度（单位m）、单工程矿体平均品位（Au、Ag）、矿体块段水平厚度（单位m）、矿体块段品位（Au、Ag）。
“资源量估算表”（表 12）包含如下内容：矿区、矿体编号、资源量类别、块段水平厚度（单位m）、块段品位（Au、Ag）、块段面积（单位m2）、平均体积质量（单位t/m3）、矿石量（单位kt）（Au、Ag）、金属量（单位kg）（Au、Ag）、备注。
4. 数据质量控制和评估
对矿区主要工程点（钻孔、探槽），在已有已知控制点的基础上，使用拓普康RTK卫星定测与全站仪测量相结合的方法进行测量，精度可以满足预普查资源量估算要求。
外检样品30个，委托国土资源部乌鲁木齐矿产资源监督检测中心和有色金属桂林矿产地质测试中心进行外检分析对比。内检样品39个，由新疆维吾尔自治区有色地质勘查局测试中心进行自检。根据基本分析结果和内外检结果对比，测试结果基本准确可靠，外检合格率93%，内检合格率92%，基本满足资源量估算要求。
5. 结论
新疆野马泉西金矿区的资源量数据集包含3个Excel工作簿，内含10个Excel工作表页文件，是采用地质块段法对野外采集的数据进行计算和整理形成的。各类表格参数齐全，数据真实可靠。数据集内地表槽探样品3 537个，深部钻探样品1 471个，样品总含矿率为12.4%，含矿岩性以粉砂岩、石英脉、石英闪长岩脉为主，富矿率（高品位样品）0.22%，富矿体主要集中于石英脉中，具开采利用价值。该数据集对矿区下一步勘查开发和周边同类型矿床的资源量估算具参考意义。
注释：
❶赵恒乐, 郭利, 刘巍国, 李嵩龄. 2009.新疆哈密市旱草湖一带1:5万区域地质调查成果报告[R].新疆维吾尔自治区地质调查院。
❷任经武, 叶雷, 漆树基等. 2016.新疆哈密市野马泉西地区矿产地质调查成果报告[R].有色金属矿产地质调查中心。
1. Introduction
The Jueluotage Cu−Ni−Fe−Mn−V−Ti−Au−Ag−W−Mo rare metal ore belt in East Tianshan is one of the most important metallogenic belts in Xinjiang, with hundreds of main deposits. The Kangguertage ductile shear zone is also situated within this belt, where important deposits such as Kangguer, Matoutan and Shiyingtan are found (Dong LH et al., 2010). The strata range in age from Archaean to Cenozoic outcrops in this region and strata of the Carboniferous system is widely distributed. There are well-developed large structures, including from north to south, Kangguertage–Huangshan fault, Qiugemingtashi–Huangshan ductile shear zone, Kushui−Yamansu fault zone, Weiya ductile shear zone, and Aqqikkuduk–Shaquanzi major fault. The area experiences frequent magmatic activities and among the generated igneous rocks, Late Paleozoic intrusive rocks are most developed❶.
The West Yemaquan gold ore deposit is situated along the east of the shear zone extension−the Kushui–Yamansu ductile shear zone (see Fig. 1). The outcropping strata within the gold field present a simple structure, which except for Quaternary strata, are primarily the Lower Carboniferous Yamansu Formation. The lithology is predominantly conglomerate, sandstone and siliceous siltstone, interbedded with limestone and tuff (Fig. 2). There are developed structures within the region and the largest main fault is the Kushui–Yamansu Fault, which traverses the whole West Yemaquan Mine Area in the east, distributed in a NE direction, a north−dipping thrust fault with a strike of 60°~70° and at a dip angle of 70°~85°. On the south side of the fault there is a developed a set of strike-slip faults in a ductile shear zone encompassed in a nappe thrust which is strong in the south and weak in the north, under control of F1 and F2. Within this ductile shear zone, there are mainly three sets of secondary faults: the first is roughly in the same direction as the major fault, at an intersection angle of 10°~15° with the boundary of the shear zone; the second intersects with the shear zone at a larger angle of about 70°, primarily with NNE-strike fissures; the third is a compressional fracture mainly on a NS strike. At present, most gold orebodies are distributed within the first set of faults and no mineral (mineralized) body is found in the other two fault sets. There are developed magmatic rocks within the mine area, which are dominantly medium and later Hercynian intermediate-acid intrusive rocks. Granodiorite lies on the north side while diorite is in the south. In addition, there are developed intermediate-acid veins, which are mainly granite porphyry, quartz diorite, diorite vein and quartz vein❷.
Figure 1. Simplified geological map at Jueluotage, East Tianshan, Xinjiang (Han CM et al., revised in 2002)1−Mesozoic–Cenozoic sedimentary cover; 2- Permian continental volcano-sedimentary rock series; 3−Carboniferous volcano-sedimentary rocks; 4−Ordovician−Devonian volcano−sedimentary rocks; 5−Precambrian metamorphic rocks; 6−granitic rocks; 7−gold deposit; 8−copper deposit; 9−Cu−Ni−sulfide deposit; 10−iron deposit; 11−iron−copper deposit; 12−Pb−Zn deposit; 13−Ag multi−metal deposit; 14−multi−metal deposit; 15−fault; 16−shear zone; 17−the location of the gold field.
Figure 2. Simplified geological map of West Yemaquan Gold Field(Ren JW et al., 2017: Medium−scale Gold Deposit Found in West Yemaquan, East Tianshan, Xinjiang.New Letters of China Geological Survey, 3(14): 5-8)1−Quaternary alluvial-diluvium; 2−sandstone in Upper Yamansu Formation, Lower Carboniferous; 3−Yamansu Formation, Lower Carboniferous; 4−Lower Yamansu Formation, Lower Carboniferous; 5−medium Variscan diorite; 6−medium Variscan granodiorite; 7−medium Variscan moyite; 8−diorite vein; 9−quartz diorite vein; 10−granitic porphyry vein; 11− quartz porphyry vein; 12−regional major fault; 13−secondary fault; 14−ductile shear zone; 15−formation occurrence; 16−gold orebody and its number.Within the area, three groups of gold orebodies are delineated (Ⅰ, Ⅱ, and Ⅲ, as shown in Table 1) of which there are 12 strips of gold bodies and 23 mineralized gold bodies. The orebody shapes are mostly stratified, lentoid or vein-like. Orebody #1 is the main one within the mine area, which is generally along a strike of 70°; it is 160 m in length, 1.14~5.54 m in thickness and more than 400 m in depth along the direction of dip. The gold grade is 0.54~109.10 ×10-6. The ore origin and industrial type of the deposit belongs to the ductile shear zone type and the quartz vein type, respectively (source: as for Fig. 2). Survey and assessment of the deposit of resources not only allows provision of a valuable reference for assessment of resources of any deposits of the same type, but also sets an example for research into the distribution features of orebodies in the deposits of the same type within West Yemaquan (Liu HG et al., 2017).
Much research has been conducted to estimate the resources of metallic deposits, most of which uses traditional methods in combination with geo-statistics and information technology or geo−statistical methods (Bai RH et al., 2010; Guo HJ, 2010; Xiao YH et al., 2012; Cao JZ et al., 2015; Zhang PC et al., 2017). In traditional resource estimation methods, irregular geologic bodies are regarded roughly as regular geometries and then geometric methods are adopted to calculate the volumes of geometries, which are then considered as the volume of resources in the orebodies. For this purpose, there are two basic methods: the cross-section method and the geological ore block method (Zhang PC et al., 2017), the last of which was applied as a main method for this resource estimation.
The dataset for resources of the West Yemaquan gold ore deposit, Xinjiang, includes three Excel workbooks, namely “Work Registration.xls”, “Sample Testing Result.xls” and “Resource Estimation.xls”. The “Work Registration” workbook consists of two Excel sheets, i.e., the trenching work registration sheet and the drilling work registration sheet. The “Sample Testing Result” workbook contains three Excel sheets, i.e., the trenching sample testing sheet, the drill sample testing result sheet and the small-volume mass testing result sheet. The “Resource Estimation” workbook consists of five Excel sheets, i.e., the trenching work orebody horizontal thickness and weighted mean grade calculation sheet, the drill work orebody horizontal thickness and weighted mean grade calculation sheet, the orebody block area calculation sheet, the orebody block thickness and weighted grade calculation sheet and the resource estimation sheet. See Table 2 for Metadata.
2. Method for Data Acquisition and Processing
2.1 Sampling
270 samples were acquired for this survey from the trenching and drill cores. Samples acquired contain hornfelsic siltstone, metamorphic siltstone and quartz diorite porphyrite. Drill cores were sampled in the length of 0.8~1.5 m per sample continuously using the half-splitting method. In the surface orebody, samples with the size of 10 cm × 5 cm and 0.8~1.5 m long were taken continuously by grooving. Sample combinations are in the form of single work combination and sample combination generally consists of 2~7 samples depending on geological conditions.
Hornfelsic siltstone: dark grey−green, palimpsest silt texture and massive structure. This sample generally has finer debris with an even particle size < 0.03 mm, thus it belongs to fine silt. Metamorphic recrystallization of argillaceous matter in rocks has generated neogenic minerals, namely brownish−red biotite and a small amount of sericite. Metallic minerals are rare and sometimes appear in the form of an irregular stringer. A small amount of quartz in the form of irregular stringers or irregular blocks was found in the samples, which results from thermal metamorphism of the rock.
Metamorphic siltstone: grey−black or steel grey, palimpsest silt texture and palimpsest bedding-like structure. Debris feldspar is markedly clayey and quartz is subangular in shape. Since particle size of most debris is smaller than 0.1 mm, this sample belongs to the coarse silt−fine sand grade. Occasionally, the particle size of the coarse debris is around 0.25 mm, belonging to the fine-sand grade. Metamorphic crystallization has happened to the debris. Feldspar and quartz are closely bent and inlaid. Metamorphic recrystallization of argillaceous matter has generated neogenic minerals, such as fine scale-like sericite and biotite crystallites, with the crystal plane distributed in a direction consistent with the direction of micro-stratification in the rocks. Under certain action of later gas−liquid metasomatism, the rocks have turned into secondary quartzite. Quartz is in the allotriomorphic granular form with closely inlaid particles; it is unevenly distributed in the rocks, in the form of lumpy aggregations or connected intermittently in a line or in a stringer−like form, in a direction generally consistent with the direction of micro−stratification of the rocks. Occasionally it is found that a carbonate stringer cuts through the rocks.
Quartz diorite porphyrite: isabelline or brown, palimpsest porphyritic texture, micro−scale granular crystalloblastic texture for the matrix and directional structure. Light metamorphic recrystallization has occurred in the rocks. Phenocrysts and matrix are parallel in direction. Neogenic biotite is distributed in a pattern of parallel striae. Plagioclase, accounting for 90%, is inequigranular; most are anhedral in a granular matrix with particle size < 0.25mm. Palimpsest phenocryst, account for 35%, with a particle size of 0.73~1.7 mm ×1.2 mm and in a granular subhedral shape. Phenocryst plagioclase has been subjected to strong argillization from which bicrystals are visible, flattened, directional and closely distributed. Quartz accounts for 5% with a particle size typically of 0.03~0.18 mm, in anhedral granular form, sparsely distributed among the plagioclase particles. Micro-scale fine isabelline biotite accounts for 5%, and is distributed in a pattern of parallel striae among feldspar and quartz particles. Granular magnetite is occasionally seen, with a particle size < 0.05 mm, distributed in a star−like pattern.
2.2 Test Method
Gold samples were tested by the Testing Center of the Nonferrous Geological Survey of Xinjiang Uygur Autonomous Region. Weight samples were tested with the conventional wax−sealing method and assay analysis was done using atomic absorption spectrometry.
2.3 Resource Estimation Methods
2.3.1 Industrial Indexes Used
In accordance with the Specifications for Hard Rock Gold Exploration (DZ/T 0205−2002) and in combination with phase analysis, an investigation was done to determine the mineralogical characteristics of the gold minerals in the samples, which are primarily natural gold and invisible gold as inclusions within sulfide. From this, the gold orebody #1 is deemed to be suitable for open mining for its high grade, large scale, shallow depth (outcrop over surface) (Fig. 3), flat landform and convenient transport condition. The established industrial indexes are:
Cutoff grade Au (10-6): 0.5;
Min. industrial grade Au (10-6): 1;
Min. minable thickness (m): 0.8;
Band rejected thickness (m): 4.
2.3.2 Selection of Resource Estimation Methods and Basis
Based on the form, occurrence and scale of orebodies, the geological ore block method was selected to estimate resources in the orebody vertical longitudinal projection map (Resource Department of Ministry of Land and Resources, 2000).
Formulas for resource estimation are as follows:
(1) Where, Q−mineral volume; d−orebody; S−block projection area; H−block mean horizontal thickness; P−metal volume; c−mineral mean grade.
2.3.3 Determination of Parameters for Resource Estimation
(1) Determination of block area: in the vertical longitudinal projection map for resource estimation, the block area is measured with the software MAPGIS based on the form of the delineated orebody blocks.
(2) Determination of the horizontal thickness: the horizontal thickness of a single-work orebody is the sum of the horizontal thicknesses of cutting continuous samples through the orebody within the single work. The following thickness calculation formulas are used for both trenching and drilling works:
(2) Where, Hv−orebody horizontal thickness (m); L−orebody apparent thickness (m); β−the slope angle at which the work cuts through the orebody (°); α−orebody dip (°); γ−the angle between the trench direction and the orebody strike (°), which is positive when the stratal dip is opposite to the slope direction and negative when they are in the same direction.
The orebody block horizontal thickness is the arithmetical mean value of the orebody horizontal thicknesses of all single works within the mineral block.
(3) Determination of mean grade: the mean grade of a single−work orebody is the weighted mean value of the sum of the products of the content of the metallogenic element and its length within the single work:
(3) Where, C−the mean grade of the single-work orebody; C1, C2, .... Cn−metallogenic element content in a single sample; andL1, L2…Ln−the length of a single sample (m).
The mean grade of the orebody is calculated from weighted mean grades of all single works.
2.3.4 Classification of Resources
Since the work control level is low within the goldfield and the control network is sparse, in this investigation, only the inferred resources of Category 333 and predicted resources of Category 334 in the deposit were estimated. Within the goldfield, the orebody was divided into four geological blocks, namely orebody #1: Categories 333 and 334 and orebody #38: categories 333 and 334.
2.4 Statistical Data Sheet from Testing within the Goldfield
Most samples involved in resource estimation were tested and analyzed through internal and external inspection. See Table 3 and 4 for details.
Table 3. Statistical Data Sheet from Testing within the Goldfield (comparison between internal inspection analysis and basic analysis)
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Table 4. Statistical Data Sheet from Testing within the Goldfield (comparison between results from external inspection analysis and basic analysis)
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3. Description of Data Samples
The “Trenching Work Registration Sheet” (Table 5) contains the following details: No., Work No., Work goal, Work start date, Work completion date, Geological record (Start date, End date and Recorder), Work result, Designed length (m), Actual length (m), Designed orientation (°), Actual orientation (°) and Coordinates of starting point (X, Y and Z) and Remarks.
The “Drilling Work Registration Sheet” (Table 6) includes: No., Work No., Work goal, Work start date, Work completion date, Geological record (Start date, End date and Recorder), Work result, Designed length (m), Actual length (m), Designed orientation (°), Actual orientation (°), Designed dip angle (°), Actual dip angle (°) and Coordinates of Starting point (X, Y and Z) and Remarks.
The “Trenching Sample Testing Result Sheet” (Table 7) includes: No., Work No., Sample No., Sampling location [from (m), to (m), Length (m)], Sampling line [Sample length (m), Orientation (°), and Gradient (°)], Orebody Occurrence [Dip (°), Dip angle (°)], Pb grade (%), Zn grade (%), Cu grade (%) and Au grade (×10-6).
The “Drill Sample Testing Result Sheet” is consistent with the “Trenching Sample Testing Result Sheet”, as shown in Table 7.
The “Small volume Mass Testing Result Sheet” (Table 8) includes: No., Sample No., Location of sampling work, Rock feature, Orebody No., Mineral grade (×10-6)(Au and Ag), Small volume mass (g/cm3) and Remarks.
The “Trenching Work Orebody Horizontal Thickness and Weighted Mean grade Calculation Sheet” (Table 9) includes: No., Work No., Sample No., Orebody No., Sampling location [from (m), to (m), Length (m)], Sampling line [Sample length (m), Orientation (°), and Gradient (°)], Exploration line, Orebody occurrence [Dip (°), Dip angle (°)], the Angle between work orientation and orebody dip (°), Sample real thickness (m), Sample horizontal thickness (m), Au grade (×10-6), Au orebody mean grade (×10-6), Au orebody real thickness (m), Au orebody horizontal thickness (m) and Remarks.
Table 9. Trenching Work Orebody Horizontal Thickness and Weighted Mean Grade Calculation Sheet
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The “Drilling Work Orebody Horizontal Thickness and Weighted Mean grade Calculation Sheet” is consistent with the “Trenching Work Orebody Horizontal Thickness and Weighted Mean grade Calculation Sheet”, as shown in Table 9.
The “Orebody Block Area Calculation Sheet” (Table 10) includes: Mine area, No., Orebody No., Resource volume classification, Block area (m2) and Remarks.
The “Orebody Block Thickness and Weighted Grade Calculation Sheet” (Table 11) includes: Mine area, No., Orebody No., Work No., Resource volume classification, Single−work orebody horizontal thickness (m), Single−work orebody mean grade (Au and Ag), Orebody block horizontal thickness (m) and Orebody block grade (Au and Ag).
The “Resource Estimation Sheet” (Table 12) includes: Mine area, Orebody No., Resource volume classification, Block horizontal thickness (m), Block grade (Au and Ag), Block area (m2), Mean volumetric mass (t/m3), Mineral mass (kt) (Au and Ag), Metal mass (kg) (Au and Ag) and Remarks.
4. Data Quality Control and Assessment
Based on existing known control points, the main engineering points within the mine area (drilled boreholes and trenches) were surveyed using a combination of TOPCON RTK satellite positioning survey and total station measurement, with the accuracy meeting requirements for resource estimation from general survey.
30 samples for external inspection were sent to the Urumqi Center for Mineral Resource Supervision and Testing and the Guilin Testing Center for Mineral Geology for Nonferrous Metals, both under the Ministry of Land and Resources, for external inspection analysis and comparison. 39 samples for internal inspection were sent to the Testing Center of the Nonferrous Geological Survey of Xinjiang Uygur Autonomous Region for self−inspection. Based on comparison between results from the basic analysis and from the internal and external inspections, the tested results are generally accurate and credible, with the external inspection qualified rate of 93% and the internal inspection qualified rate of 92%, basically meeting the requirements on resource estimation.
5. Conclusions
The resource dataset for the Lower Carboniferous West Yemaquan gold ore deposit, Xinjiang, contains three Excel workbooks consisting of 10 Excel sheets, created by calculating and collating data acquired in the field by using the geological ore block method. Complete parameters, and true and credible data are included in the various sheets. Within the dataset, there are 3537 samples acquired from surface trenches and 1471 samples from deep drilling. Samples containing minerals account for 12.4% of total samples. The mineral lithology is primarily siltstone, quartz vein and quartz diorite vein. The high−grade ore rate (rate of high grade samples) is 0.22% and high−grade orebodies are mainly distributed in quartz vein, which are valuable for mining and exploitation. Therefore, the dataset has important referential implications for further survey and development of the mine area as well as for estimation of resources of the surrounding deposits of the same kind.
Notes:
❶ Zhao Hengle, Guo Li, Liu Weiguo, Li Song, 1:50 000 Regional Geological Survey Results Report 2009 on Hancao Lake, Kumul, Xinjiang [R]. Xinjiang Uygur Autonomous Region Geological Survey.
❷ Ren Jinwu, Ye Lei, Qi Shuji et al., Geological Survey Results Report at West Yemaquan, Kumule, Xinjiang [R]. China Non−ferrous Metals Resource Geological Survey. 2016.
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Table 3. Statistical Data Sheet from Testing within the Goldfield (comparison between internal inspection analysis and basic analysis)
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Table 4. Statistical Data Sheet from Testing within the Goldfield (comparison between results from external inspection analysis and basic analysis)
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Table 9. Trenching Work Orebody Horizontal Thickness and Weighted Mean Grade Calculation Sheet
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白瑞和. 2010.固体矿产资源储量计算方法的探讨[J].中国非金属矿工业导刊, 6:59-61 http://d.old.wanfangdata.com.cn/Periodical/zgfjskgydk201006019
曹建洲, 赵远由, 谢环宇. 2015.地质块段法在固体矿产资源储量估算的应用探讨[J].矿产勘查, 6(4):144-148 http://d.old.wanfangdata.com.cn/Periodical/ytgcj201504019
董连慧, 冯京, 刘德权, 唐延龄, 屈迅, 王克卓, 杨在峰. 2010.新疆成矿单元划分方案研究[J].新疆地质, 28(1):1-15 doi: 10.3969/j.issn.1000-8845.2010.01.001
国土资源部储量司. 2000.矿产资源储量计算方法汇编[M].北京:地质出版社.
郭慧锦. 2010.块段法与地质统计相结合的矿产储量计算方法研究——以武夷山上西坑钼矿床为例[D].北京: 中国地质大学.
韩春明, 毛景文, 杨建民, 王志良, 崔彬. 2002.东天山晚古生代内生金属矿床类型和成矿作用的动力学演化规律[J].地质学报, 76(2):222-234 doi: 10.3321/j.issn:0001-5717.2002.02.010
刘焕贵, 赖华福. 2017.江西省崇义聂都瓦窑坑白钨矿区资源储量数据集[J].中国地质, 44(S1):96-104 http://geochina.cgs.gov.cn/geochina/ch/reader/view_abstract.aspx?file_no=2017S112&flag=1
任经武, 刘增仁.新疆东天山野马泉西发现中型金矿床[J/OL].中国地质调查成果快讯, 2017, 3(14): 5-8. http://www.drc.cgs.gov.cn/maga/cgkx/201708/t20170821_437889.html.
肖玉华, 吴干华. 2010.固体矿产地质勘查资源/储量估算的几种方法[J].西部探矿工程, 24(5):117-118 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=xbtkgc201205045
张鹏川, 褚小东, 曾建平, 刘建兵. 2017.传统资源量估算方法在第三类矿产中的应用与对比研究:以宁夏某建筑用石灰岩矿山为例[J].中国矿业, 26(9):33-37 http://d.old.wanfangdata.com.cn/Periodical/zgky201709007
Bai Ruihe. 2010. Discussion on calculation method of solid mineral resources reserve[J]. China Nonmetallic Minerals Industry, 6:59-61(in Chinese) http://link.springer.com/article/10.1007/s00125-010-1681-4
Cao Jianzhou, Zhao Yuanyou, Xie Huanyu. 2015. Application of geological block method in the solid mineral reserve estimation[J]. Mineral Exploration, 6(4):144-148(in Chinese with English abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-YSJS201504020.htm
Dong Lianhui, Feng Jing, Liu Dequan, Tang Yanling, Qu Xun, Wang Kezhuo, Yang Zaifeng. 2010. Research for classification of metallogenic unit of Xinjiang[J]. Xinjiang Geology, 28(1):1-15(in Chinese with English abstract) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=xjdz201001001
Department of Reserves, Ministry of Land and Resources. 2000. Compilation of calculation methods for mineral resources reserves[M]. Beijing: Geological Publishing House(in Chinese).
Guo Huijin. 2010. Research on block method and geostatistical combined calculation of mineral reserves-the case of molybdenum deposit on Wu Yishan Shangxikeng[D]. Beijing: China University of Geosciences(in Chinese with English abstract).
Han Chunming, Mao Jingwen, Yang Jianming, Wang Zhiliang, Cui Bin. 2002. Types of late palaeozoic metal deposits and related geodynamical evolution in the east Tianshan[J]. Acta Geologica Sinica, 76(2):222-234(in Chinese with English abstract) doi: 10.3321/j.issn:0001-5717.2002.02.010
Liu Huangui, Lai Huafu. 2017. The Resource Reserves Dataset of the Wayaokeng Scheelite Mining Area, Niedu, Chongyi, Jiangxi Province[J]. Geology in China, 44(S1):118-127 (in Chinese and English) http://geochina.cgs.gov.cn/geochina/ch/reader/view_abstract.aspx?file_no=2017S112&flag=1
Ren Jingwu, Liu Zengren. 2017. Medium scale Gold Deposit Found in West Yemaquan, East Tianshan, Xinjiang[J/OL]. News Flash on CGS Results, 3(14): 5−8. http://www.drc.cgs.gov.cn/maga/cgkx/201708/t20170821_437889.html (in Chinese).
Xiao Yuhua, Wu Ganhua. 2010. Several methods for estimating the resources/reserves of solid mineral geological exploration[J]. West-China Exploratin Engineering, 24(5):117-118(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=xbtkgc201205045
Zhang Pengchuan, Chu Xiaodong, Zeng Jianping, Liu Jianbing. 2017. The application and comparison research of traditional resources estimation on the third kinds of minerals:a case study of limestone mine used in construction in Ningxia[J]. China Mining Magazine, 26(9):33-37(in Chinese with English abstract) http://d.old.wanfangdata.com.cn/Periodical/zgky201709007
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