1 引言

原国土资源部关于《全国地质找矿“358”行动纲要》明确指出要建立公益性地质工作拉动机制。为制定国家矿产资源规划，中国地质调查局以整装勘查区为对象，以潜力评价为手段，全面摸清整装勘查区矿产资源家底，为矿产地质调查和矿产勘查指明方向，为国家矿产资源的战略规划及保护利用，以及为生态文明建设提供基础数据和科学依据。甘肃崖湾—大桥地区金锑矿整装勘查区是西秦岭地区主要的金矿集中区，也是陕甘川“金三角”的重要组成部分。该地区处于这一特殊的成矿环境，也因此成为了近年来实现金、锑矿找矿突破的重点区域。随着对该区成矿特征认识程度的提高，找矿成果较为突出。但在找矿方向由矿床外围向全区及深部拓展的过程中，一些新的地质问题也逐渐显现，影响到勘探工作部署。因此在甘肃省崖湾—大桥地区设立整装勘查区矿产资源潜力评价示范项目，开展找矿预测，圈定找矿靶区，评价资源潜力，提出下一步找矿工作部署建议，同时，建立原始及成果资料数据集。

甘肃省崖湾—大桥地区金锑矿整装勘查区位于秦岭—大别新元古代—古生代造山带之白龙江隆起带与阿尼玛卿裂陷沉积区东段(图1)^①，岷县—宕昌—两当深大断裂和舟曲—成县—徽县区域断裂穿过本区，由这2条断裂将夏河—礼县、碌曲—成县和迭部—武都3个逆冲推覆构造带自北向南分割开，在武都—天水一线呈弧顶向南的弧形分布(图2；赵彦庆，2004)。整装勘查区东西横跨于该弧形构造带轴线位置，研究者通过弧形构造带对西秦岭金矿的控制作用研究，认为该弧形构造带对金矿的控制作用明显(殷先明，2009)。

区内的海–陆相沉积建造系统发育较齐全，其中以海相复理石沉积建造为主要建造类型。三叠系呈东西—北西西向展布于整装勘查区北部，整体为一套复理石建造，岩性组合为碎屑岩→砂岩和粉砂岩、泥灰岩→千枚岩和板岩及碳酸盐岩→泥灰岩、灰岩和白云岩，该套地层是区内层控–热液型金矿的重要含矿地层。南部发育古生代地层，为一套经历了低绿片岩相浅变质作用的海相复理石碎屑岩、碳酸盐岩和硅质岩沉积建造。白垩系、古近系、新近系零散分布于以北东向为主的陆相断陷构造盆地内，为一套红色磨拉石沉积建造（杜远生，1997）。

通过对整装勘查区进行地表的观测，岩浆岩呈小规模零星出露，但是本次工作通过化探、物探等手段推断了大量隐伏侵入岩。值得一提的是通过收集深部地震工作的研究成果（李清河，1991），笔者认为在宕昌—通渭—静宁—礼县范围内，存在着一系列近于平行的北北东向深部大断裂。是岩浆侵入的良好通道，可能也证明了该构造–岩浆岩带的存在。与成矿关系最为密切的岩浆岩属中酸性侵入体，主要为印支—燕山期岩体(张翔等，2017)。

区内矿产以金、锑为主，已发现的矿床呈带状规律性分布。其中比较重要的有大桥超大型金矿、崖湾大型锑矿、坪定中型金矿，小型矿床有羊里尾沟金矿、水眼头锑矿、安房坝金矿等。所有规模金、锑矿床均处于北东向或北西向隆起的边缘或区域性断裂一侧。

崖湾—大桥地区地区金锑矿整装勘查区 1∶50 000 矿产资源潜力评价数据集（张家瑞等，2020）基本信息简表如表1。

2 数据采集和处理方法 2.1 数据基础

甘肃省崖湾—大桥地区金锑矿整装勘查区1∶50 000矿产资源潜力评价系列图件以2018年由自然资源部矿产勘查技术指导中心组织编制的《整装勘查区1∶50 000矿产资源潜力评价技术指南(初稿)》为基本要求，以“三位一体”勘查区找矿预测理论为指导，以整装勘查区范围内的全国矿产资源潜力评价、矿产地质调查、矿产远景调查、区域地质调查原始资料为基础。采用坐标系统为：1954年北京坐标系，1985年国家高程基准，2000国家大地坐标系(CGCS 2000)。应用数字填图系统(DGSS)、MapGIS等计算机软件进行数据处理与图件编制。工作比例尺为1∶50 000。

2.2 资料收集情况

整装勘查区涉及22个1∶50 000标准地质图幅，工作面积约5613.84 km²，针对整装勘查区范围收集的资料，主要以1∶50 000矿产地质调查、矿产远景调查、区域地质调查资料为主(成果资料及所有原始资料)^②−⑧，用1∶100 000或1∶250 000资料补充，并在工作开展过程中及时进行资料更新，此外使用化探原始数据18209条，其中1∶50 000数据17831条，1∶200 000数据378条等。

基于上述资料，编制整装勘查区建造构造图、成矿要素图、预测要素图、预测成果图、成矿规律图、勘查工作部署建议图等系列图件。

2.3 地球物理和地球化学数据处理方法 2.3.1 1∶50 000航磁数据处理

该地区以往航磁数据网格大多为2 km × 2 km，本次收集到2015—2017年石家庄核工业航测遥感500 m × 500 m网格数据，因此有必要实现整装勘查区1∶50 000航磁数据的整理集成。

首先，对不同格式的航磁数据进行调平、拼接，采用Kriging法形成间距为500 m × 500 m的网格数据；然后，利用GeoIPAS 4.0软件对网格化文件进行分块变纬度化极、化极垂向一阶导数、解析延拓等位场转换处理，从而得到航磁ΔT异常图、航磁ΔT化极平面图、航磁ΔT化极垂向一阶导数图和航磁ΔT化极剩余异常图等图件。通过对比磁场平面特征与已知矿床分布的对应关系，结合基础地质、化探、遥感等资料，总结构成区域控矿的地质–地球物理标志，划分找矿远景区带。

2.3.2 1∶50 000地球化学数据处理

本次收集整理区内1∶50 000化探资料，源自18209个数据点。通过检查校正原始数据，计算浓集系数(Kk)与变异系数(Cv)2个参数，结合区内地质矿产背景，确定Au、Sb、As、Hg、Bi等元素成矿潜力大，为主要的成矿元素。

采用数理统计法确定异常下限(T)，T=X+2S，其中X和S分别为背景场的均值、标准离差，结果见表2。

圈定Ag、As、Au等15个元素的单元素异常597处，圈定综合异常59处，其中甲类异常9处(甲1类异常4处，甲2类异常5处)，乙类异常21处(乙2类异常3处，乙3类异常18处)，丙类异常29处(丙1类异常7处，丙2类异常7处，丙3类异常15处)。对每个综合异常编制剖析图并填写异常登记卡。同时依据组合异常图推测隐伏岩体2处。

2.3.3 遥感数据处理

遥感数据采用新收集的高分一号、高分二号数据源，较以往采用的ETM数据，数据时间更新、精度更高。为突出影像中有效信息，使用不同波段组合，并采用图像增强、融合、空间滤波等方法，制作与整装勘查区底图同比例尺真彩色合成影像与标准假彩色遥感影像图。

2.4 主要图件编制方法 2.4.1 综合建造构造图

利用所收集的区内最新矿产地质图进行初步拼接后，通过对资料分析筛选，结合区内现有的图切剖面及已查明的大桥金矿、崖湾锑矿、坪定金矿等典型矿床研究成果，系统划分出整装勘查区沉积岩建造、侵入岩建造等。对地质界线进行核实修正，并依据岩性组合及产状特征，填充岩性花纹。为确保预测工作的可靠性，选择穿过典型矿床、垂直地层的走向为剖面线方向编制剖面图。通过典型矿床建造构造及区域建造构造的分析梳理，确定大桥金矿的含矿建造为三叠系滑石关组薄层泥–粉砂质灰岩建造，崖湾锑矿的含矿建造为三叠系大河坝组泥灰岩建造，坪定金矿的含矿建造为泥盆系下吾那组碳酸盐岩夹泥砂岩建造。

2.4.2 成矿要素图 2.4.2.1 矿产预测类型的划分

通过区域成矿规律和典型矿床研究，确定研究区的主攻矿种为金、锑矿。崖湾—大桥整装勘查区矿产预测类型划分如表3。

2.4.2.2 成矿要素分析及成矿模式图的建立

全面收集整装勘查区典型矿床(大桥金矿、崖湾锑矿、坪定金矿)及区内其他矿床(点)的研究资料，运用叶天竺研究员提出的“三位一体”勘查区找矿预测理论(叶天竺等, 2014, 2017)，分析梳理出整装勘查区内3类典型矿床成矿地质体、成矿构造及成矿结构面和成矿作用特征标志等。同时，深大断裂严格控制建造的分布，矿床的分布又与建造有密切关系，因此深大断裂对成岩及成矿起到重要的控制作用，控制和影响了各类内生矿床的形成和时空分布。

由此建立整装勘查区成矿要素表(表4)及区域成矿模式图。

2.4.2.3 成矿要素图编制

以综合建造构造图为底图，以成矿要素分析成果为基础，保留必要、重要成矿要素，补充根据区域物探、化探、遥感资料推断的隐伏岩体(成矿地质体)和构造(成矿构造)；对与成矿无关的地层、岩浆岩等简要表达。同时，编图过程中使每个要素形成一个图层。

2.4.3 预测要素图 2.4.3.1 预测要素分析及区域预测模型的建立

成矿要素主要反映成矿的地质类信息，从成矿要素中提取出成矿作用形成的可识别的标志作为预测要素，利用地球物理、地球化学、遥感等手段，处理并筛选出与成矿有关的物探、化探、遥感预测要素，对地质类预测要素作以补充。其中，航磁、遥感解译成果指示成矿构造及隐伏岩体(成矿地质体)，Au、Sb、As等元素组合异常是该区热液型金、锑矿床地球化学异常的主要表现形式，同时，利用原生晕分带的理论，确定本区金、锑矿床前缘异常元素为Hg、Sb、As，尾晕元素为W、Mo、Bi，用以判定整装勘查区剥蚀程度，对矿床的定位有一定的指示意义。以此建立整装勘查区预测要素表(表5)。在预测要素分析的基础上，以成矿模式图为底图，叠加化探剖面，绘制区域预测模型图(图3)。

2.4.3.2 预测要素图编制

以成矿要素图为底图，为体现物探、化探、遥感预测要素，删除沉积建造、侵入岩建造区图层，仅保留岩性花纹并淡化表达。叠加物探预测要素：解译的中酸性岩体、构造；化探要素：Au–Hg–As–Sb组合异常及金、锑、砷单元素异常、解译的中酸性岩体；遥感解译的成矿构造。插入预测要素表图层及预测模型图图层。

2.4.4 预测成果图

区内典型矿床均为地质建造、变形构造、侵入岩浆作用综合因素时空定位的矿产，将矿产预测方法类型均划分为复合内生型。基于矿产预测GIS评价系统提取预测信息，提取结果的表现形式为区文件，提取的信息包括：成矿构造(根据不同预测类型成矿构造的产状、性质等分别提取，结合构造与矿点影响域频率，构建缓冲区)、成矿地质体(解译的印支晚期—燕山期中酸性侵入体，结合构造与矿点影响域频率，构建缓冲区)、含矿建造、地球化学异常(金、锑、砷单元素异常及金–汞–砷–锑组合异常)等，根据所建立的预测评价模型，采用要素叠加法，应用MRAS软件交互搜索模型建模器，进行预测要素之间交、并等运算，最终圈定最小预测区，采用人工选择模型单元法确定成矿概率。本次工作以剥蚀程度作为优选要素，优化最小预测区，最终确定金、锑最小预测区42个，占整装勘查区总面积的2.7%，进一步建立预测评价模型区，根据已查明资源量(333资源量以上)、矿脉聚集区面积、勘查最大深度等参数，计算预测深度、含矿地质体含矿系数等，采用含矿地质体体积法估算预测资源量。

在预测要素图的基础上，用横线填充A类最小预测区(成矿条件十分有利，且矿床所在最小预测区)，竖线填充B类最小预测区(成矿条件有利)，交叉线填充C类最小预测区(成矿条件一般)，并标注编号、名称、面积、深度、相似系数、预测资源量类别、最小预测区类别等。最终，叠加各类预测表格图层。

2.5 数据集属性数据赋值

本次数据集属性赋值依据中国地质调查局《地质信息元数据标准》(DD2006–05)，参照《数字地质图空间数据库建库标准》(DD2006–06)，数据库建库采用《矿产资源潜力评价数据模型方法技术体系》。按各类型图件及GeoMAG要求完成相应的数据库建设工作。

3 数据样本描述

对综合建造构造图、磁测类、化探类和遥感类图件、成矿要素图、预测要素图、预测成果图、成矿规律图、勘查工作部署建议图等属性数据赋值，并建立了相应的数据库。部分数据库单元在各图件中具有继承性，仅对各图件特有数据库单元进行说明。

建造构造图有以下单元：沉积岩建造的编号，特征代码，图元编号，沉积岩建造大类，岩石组合，填图单位名称，填图单位代号，第四系成因类型，形成时代，建造，含矿层厚度，主要化石组合，沉积相；侵入岩建造的编号，特征代码，图元编号，岩性代码，地理位置经度，地理位置纬度，填图单位名称，填图单位代号，形成时代，特殊岩石，矿物成分，岩石颜色，岩石结构，岩石构造，侵入岩产状，岩墙，包体特征，侵位深度，侵位方式，剥蚀程度，重要岩石化学参数，岩石系列，岩石成因类型，岩石构造组合，大地构造环境；断裂的编号，名称，长度，类型，断裂面倾向(倾角)，断裂两侧及断裂带内岩石，构造层次，切割深度，运动方式，力学性质，形成时代，叠加运动；褶皱的编号，褶皱名称(类型、形态、程度)，枢纽倾伏角，褶皱倾伏向，轴面倾向(倾角)，卷入褶皱的地层，褶皱组合形式，褶皱成因，形成时代，叠加褶皱特征；产状的编号，产状类型，倾向，倾角，走向。

磁测类、化探类和遥感类图件主要单元：断裂编号，出露情况，断裂级别，断裂构造走向，断裂长度，断裂构造磁场标志，航磁ΔT等值线和航磁ΔT化极等值线中的等值线的编号、等值线值，等值线区的编号、起始值、终止值；单元素地球化学图中的等值线的编号，元素组分，含量值，等值线区的编号，元素组分，含量范围上限值，含量范围下限值；单元素地球化学异常图中地球化学异常边界线的异常编号，异常下限，地球化学异常范围面的编号，异常下限，极值点，异常编号，异常面积；地球化学异常图中综合异常范围的编号，面积，主要伴生元素，共生元素，主成矿元素范围的元素种类，异常下限，计量单位，异常面积。

成矿要素图数据库单元包括：矿产地的编号，特征代码，图元编号，名称，交通位置，地理经、纬度，赋矿岩石，控矿构造，主矿产，大地构造位置，成矿类型，主矿产规模，主矿产资源储量(单位)，主矿产平均品位(单位)，共、伴生矿产(储量、单位)，成矿区带，成矿系列，矿床式，成矿时代，成矿年龄，年龄误差，测定方法，矿体空间组合类型，主矿体编号，主矿体形状(规模、走向、倾向、倾角、长度、厚度)，矿石组分(品位、矿物成分、结构、构造)，蚀变带长度(宽度)，围岩蚀变组合，蚀变强度。

预测成果图有以下单元：最小预测区编号，名称，面积，比例尺，地理位置，成矿地质背景，矿产预测类型，预测区类别，已探明资源量，资源量估算方法；最小预测区储量数据表(EXCEL)。

成矿规律图单元有：成矿区带，矿集区和成矿远景区界线编号，名称，代表矿床名称。

勘查工作部署建议图相应的数据库单元有：部署建议区编号，名称，等级，矿种，中大比例尺填图工作，勘查工作建议，预期成果，勘查工作部署建议表(EXCEL)。

4 数据质量控制和评估

数据集是本次潜力评价成果的最终体现，项目的开展及数据集的建设收集了工作范围内前人丰富的数据资料，数据资料均真实可靠。仅两当幅，舟曲幅，沙湾幅以往未进行调查工作，因此采用1∶250 000岷县幅、天水幅、武都幅、略阳县幅区域地质调查资料，结合图切剖面进行综合建造构造图的编制；航磁数据由新收集500 m × 500 m网格数据集成处理；化探类数据由收集到的1∶50 000资料进行处理，上述资料严格按照2018年由自然资源部矿产勘查技术指导中心组织编制的《整装勘查区1∶50 000矿产资源潜力评价技术指南(初稿)》要求执行，数据来源可靠，数据库建设严格按照《矿产资源潜力评价数据模型方法技术体系》(中国地质调查局发展研究中心, 2016)规定执行，属性库建设完善。

在数据集制作过程中，严格执行质量三级检查制度，并受甘肃省地质调查院质量体系控制。2019年1月上旬，中国地质调查局发展研究中心(自然资源部矿产勘查技术指导中心)组织专家评审了甘肃崖湾—大桥地区金锑矿整装勘查区1∶50 000矿产资源潜力评价专题研究报告及数据库，专家组一致通过评审，等级为优秀。

5 数据价值

(1) 以“三位一体”找矿预测理论为指导，梳理出大桥金矿、坪定金矿、崖湾锑矿的预测要素，建立了预测模型。

(2) 在西秦岭地区成矿规律研究的基础上，对整装勘查区成矿规律进行了研究，在全国III级成矿区带的基础上，根据全国潜力评价成果划分了IV级成矿区2个，V级矿集区6个，根据本次矿产预测成果，划分了V级金锑成矿远景区8个。

(3) 在系统地收集和整理不同精度航磁资料的基础上，在整装勘查区利用500 m × 500 m网格数据，编制了整装勘查区1∶50 000航磁工作程度图、航磁ΔT等值线平面图、航磁ΔT化极等值线平面图、航磁ΔT化极垂向一阶导数等值线平面图，对解译岩体及构造做出了进一步的探索与数据更新，对预测工作起到了间接的指示作用。

(4) 集成整装勘查区各图幅1∶50 000地球化学数据，圈定了金等15种单元素异常597处、综合异常59处，解译出中酸性岩体2处。通过剥蚀程度研究成果，对本次预测起到了显著作用。

(5) 提交典型矿床深部及外围预测资源量，大桥金矿190 419 kg，坪定金矿7 492 kg，崖湾锑矿99 568 t；圈定大桥式层控–热液型金矿最小预测区17个，提交金矿预测资源量353 470.26 kg；圈定坪定式构造–热液型金矿最小预测区10个，提交金矿预测资源量107 171.85 kg；圈定崖湾式构造–热液型锑矿最小预测区15个，提交锑矿预测资源量587 889.43 t。

(6) 根据矿产预测工作，共部署了12个勘查区，其中I级勘查区3个，分别为查尔金—坪定勘查区、大桥勘查区、庙湾—牌儿坝勘查区；II级勘查区3个，分别为龙坝勘查区、安房坝勘查区、南家山勘查区；6个III级勘查区，具体部署了15个普查区、22个预查区，共计37个次级勘查区，预获金资源量460.67 t，锑资源量587 900 t。

6 结论

(1) 甘肃省崖湾—大桥地区金锑矿整装勘查区1∶50 000矿产资源潜力评价项目是中国地质调查局新一轮整装勘查区矿产地质调查与找矿预测项目的潜力评价示范项目，积极探索创新了一系列整装勘查区潜力评价工作方法及系列图件编制的方法，并建立潜力评价数据集，对全国整装勘查区1∶50 000潜力评价工作内容、工作流程、数据集的建立等起到了示范作用。

(2) 本次工作利用区内以往研究成果开展潜力评价工作，对前人成果和数据进行了梳理和整合。因此，本数据集的建立对数据的整理和集成具有重要意义。

(3) 利用整装勘查区内最新基础地质资料和科研资料，开展了整装勘查区沉积岩、侵入岩综合研究，编制整装勘查区综合建造构造图(1∶50 000)，为成矿规律研究和矿产预测提供了成矿地质背景基础资料，总结了切实可行的工作程序，提高了整装勘查区基础地质研究程度。依据此项目建立的数据集为该地区后续工作的开展提供了基础数据。

致谢：感谢甘肃省地质调查院李通国教授级高级工程师、余超教授级高级工程师、孙新春高级工程师、高永伟、牛鹏飞、李增、张万仁、张兴华、王鹤轩等付出的辛勤努力。感谢中国地质调查局发展研究中心副总工程师吕志成研究员给予的特别关心与指导。

注释：

① 甘肃省地质调查院. 2016. 甘肃省区域地质志[R].

② 张万仁，张有奎，欧春生，杨维刚，高永伟，马永东，冯备战，李通元，张琪. 2013. 甘肃成县—临潭地区铜钨金矿产远景调查成果报告[R].

③ 刘晓林，欧春生，刘海里，刘多朝，冯备战，甄红旭，王永宁，周斌. 2009. 甘肃宕昌—石桥镇地区矿产远景调查成果报告[R].

④ 杨维刚，任鹏飞，霍勤知，李通元，孔祥超，王海博，高志杰，李骁，王梅平，李亮，郭颂清，董雅清. 2016. 甘肃大桥金锑矿整装勘查区 1∶5 0 000芦家庄幅等六幅区域地质矿产调查[R].

⑤ 张勇，牛海平. 2013. 甘肃省迷坝–南康一带铜铁多金属矿远景调查成果报告[R].

⑥ 张万仁，万旭辉，陈刚. 2015. 甘肃省西和县崖湾一带金锑矿远景调查成果报告[R].

⑦ 甘肃省地质调查院. 2012. 甘肃省1∶250 000武都县区域地质调查成果幅报告[R].

⑧ 甘肃省地质调查院. 2013. 甘肃省矿产资源潜力评价报告[R].

1 Introduction

The former Ministry of Land and Resources of the People’s Republic of China proposed establishing relevant mechanisms to promote public-spirited geological work in the Guidelines of 358 National Geological Prospecting Action. To formulate national mineral resource plan, the China Geological Survey comprehensively figured out the mineral resources in integrated exploration areas through resource potential assessment. The purpose is to guide mineral geological surveys and mineral exploration, and to provide basic data and scientific bases for the planning, conservation, and utilization of national mineral resources and ecological civilization construction. The gold-antimony deposit integrated exploration area in Yawan−Daqiao area, Gansu Province (also referred to as the Yawan–Daqiao integrated exploration area) is a major concentration area of gold deposits in the West Qinling area and an important part of the Shanxi−Gansu−Sichuan Gold Triangle mineral area in China. This area has become a key region for prospecting breakthroughs of gold and antimony deposits in China in recent years owing to the special metallogenic environment. Furthermore, significant prospecting results have been obtained with the improvement in the understanding of its metallogenic characteristics. However, some new geological problems have gradually emerged when the prospecting in the integrated exploration area was transformed from deposit periphery to the whole area and deep strata. This has affected the deployment of mineral exploration. Therefore, a demonstration project for potential assessment of mineral resources in integrated exploration areas was set up in Yawan–Daqiao area, Gansu Province to carry out mineral prospection, delineate prospecting target areas, and assess resource potential. Meanwhile, it also aims to put forward suggestions on further prospecting deployment and develop a dataset of primary data and results.

The Yawan–Daqiao integrated exploration area lies in eastern part of the Bailongjiang uplift zone and Animaqen rift sedimentary zone of Qinling−Dabie Neoproterozoic−Paleozoic orogen (Fig. 1)^①. Two faults run through this area, namely Minxian−Tanchang−Liangdang deep fault and Zhouqu−Chengxian−Huixian regional fault, which separate the Xiahe−Lixian, Luqu−Chengxian, and Diebu−Wudu thrust nappe tectonic zones from north to south. As a result, the faults and thrust nappe zones are distributed in an arc shape along Wudu−Tianshui area, with the arc top facing southwards (Fig. 2; Zhao YQ, 2004). The integrated exploration area stretches across the axis of the arc-shaped structural belt from west to east. According to the study on the control of the arc-shaped structural belt over the gold deposits in west Qinling area, it can be argued that the gold deposits in the integrated exploration area are strongly controlled by the arc-shaped structural belt (Yin XM, 2009).

The Yawan–Daqiao integrated exploration area has the relatively developed sedimentary suite systems of marine-continental facies, which are dominated by the marine-facies flysch sedimentary suites. Triassic strata spread over the northern part of the integrated exploration area in the EW-NWW trending as a flysch suite in general, with the lithologic associations consisting of clastic rocks → sandstone, siltstone, and marl → phyllite, slate, and carbonate rock → marl, limestone, and dolomite. They serve as important ore-bearing strata of strata-bound−hydrothermal gold deposits. Paleozoic strata are developed in the southern part of the integrated exploration area as a sedimentary suite, which consists of marine-facies flysch clastic rocks, carbonate rocks, and siliceous rocks that have undergone low-grade metamorphism of lower greenschist facies. Cretaceous, Paleogene, and Neogene strata are scattered in the continental fault basins that are mainly in NE trending as a red molasse sedimentary suite. (Du YS, 1997)

According to the observation of the ground surface, magmatic rocks are sparsely exposed in the integrated exploration area. However, a large number of concealed intrusions were inferred from geochemical and geophysical exploration in this study. It is worthwhile to mention that a series of nearly parallel NNE-trending deep faults are believed to exist in the Tanchang−Tongwei−Jingning−Lixian area according to the deep seismic sounding results (Li QH, 1991) collected. These faults provide good pathways for magma intrusion and thus may prove the existence of structurally controlled magmatic rock belt in the area. The magmatic rocks most closely related to metallogenesis are intermediate-acid intrusive bodies, which mainly include Indosinian–Yanshanian plutons (Zhang X et al., 2017).

The minerals in the integrated exploration area mainly include gold and antimony, and the deposits discovered in the area are regularly distributed in a banded pattern. Among them, the major deposits include super-large Daqiao gold deposit, large Yawan antimony deposit, and medium-sized Pingding gold deposit. In addition, small-sized deposits in the area include Yangliweigou gold deposit, Shuiyantou antimony deposit, and Anfangba gold deposit. All these gold and antimony deposits lie on the margin of NE- or NW-trending uplifts or on the sides of regional faults.

The metadata table of the Dataset (Zhang JR et al., 2020) is shown in Table 1.

2 Methods for Data Acquisition and Processing 2.1 Data Bases

A series of 1∶50 000 mineral resource potential assessment maps of the Yawan–Daqiao integrated exploration area were prepared under the guidance of the afore-mentioned “trinity” prospecting predication theory according to the Technical Guidelines for1∶50 000 Mineral Resource Potential Assessment of Integrated Exploration Areas (Draft) developed by the Exploration Technical Guidance Center of the Ministry of Natural Resources of the People’s Republic of China in 2018. They were developed based on the primary data obtained from the national mineral resource potential assessment, mineral geological surveys, mineral prospect surveys, and regional geological surveys of the area. The coordinate systems adopted include the Beijing Geodetic Coordinate System 1954, National Height Datum 1985, and National Geodetic Coordinate System 2000 (CGCS2000). Data processing and map compilation were performed using the software such as Digital Geological Survey System (DGSS) and MapGIS, with the mapping scale of 1∶50 000.

2.2 Data Acquisition

The Yawan–Daqiao integrated exploration area involves twenty-two 1∶50 000 standard map sheets, covering an area of about 5 613.84 km². The data collected mainly include the results and primary data obtained from 1∶50 000 mineral geological surveys, mineral prospect surveys, and regional geological surveys^①-⑧. They were supplemented with 1∶100 000 or 1∶250 000 survey data and were timely updated during the building of the Dataset. In addition, 18 209 pieces of primary geochemical data were used, including 17 831 pieces obtained from 1∶50 000 geochemical exploration and 378 pieces from 1∶200 000 geochemical exploration.

Based on these data, a series of suite-structure maps, metallogenic factor maps, predictive factor maps, prediction result maps, metallogenic regularity maps, and exploration deployment suggestion maps were compiled.

2.3 Processing Methods of Geophysical and Geochemical Data 2.3.1 Processing of 1∶50 000 Aeromagnetic Data

Previous aeromagnetic data of the Yawan–Daqiao integrated exploration area mostly have a grid cell size of 2 km × 2 km. However, in this study, the aeromagnetic data with a grid cell size of 500 m ×500 m issued by the Shijiazhuang Nuclear Industry Aeromagnetic Survey and Remote Sensing Center in 2015−2017 was collected. Therefore, it is necessary to sort out and integrate the 1∶50 000 aeromagnetic data of the integrated exploration area. The details are as follows:

First, perform leveling and splicing of aeromagnetic data in different formats and form the grid data with a cell size of 500 m×500 m using the Kriging method. Second, conduct potential field transformations on the gridded data using the software GeoIPAS 4.0, including varying latitude-based reduction to the pole (RTP) by blocks, RTP-based vertical first derivative, and analytic continuation. As a result, a series of aeromagnetic maps can be obtained, such as the aeromagnetic (ΔT) anomaly maps, aeromagnetic (ΔT) RTP plans, aeromagnetic (ΔT) RTP-based vertical first-order derivative maps, and aeromagnetic (ΔT) residual RTP anomaly maps. Finally, summarize the regional ore-controlling geological−geophysical indicators and determine prospect areas according to basic geological, geochemical, and remote-sensing data along with the comparison between the plane characteristics of the magnetic field and the distribution of known deposits.

2.3.2 Processing of 1∶50 000 Geochemical Data

The 1∶50 000 geochemical data were collected from 18 209 data points in this study. After check and correction of primary data, the concentration coefficient (Kk) and the coefficient of variation (Cv) were calculated. Based on these parameters as well as the geological and mineral background of the Yawan–Daqiao integrated exploration area, it can be determined that the elements including Au, Sb, As, Hg, and Bi have great metallogenic potentiality and thus are major metallogenic elements in the area.

The anomaly thresholds (T) was determined using mathematical statistics according to the formula T=X+2S, where X and S are the mean and standard deviation of the geochemical background field. The results are listed in Table 2.

A total of 597 single-element anomalies of 15 elements such as Ag, As, and Au and 59 integrated anomalies were delineated in this study. The integrated anomalies consist of nine Class A anomalies (four Class A₁ and five Class A₂ anomalies), 21 Class B anomalies (three Class B₂ and 18 Class B₃ anomalies), 29 Class C anomalies (seven Class C₁, seven Class C₂, and 15 Class C₃ anomalies). An analytical map and a registration card were prepared for each integrated anomaly. Moreover, two concealed plutons were inferred from composite anomaly maps.

2.3.3 Processing of Remote Sensing Data

In this study, the remote sensing data were newly collected from the satellites Gaofen-1 and Gaofen-2. Compared with previous ETM data, they are newer and have higher precision. To highlight the effective information in the remote sensing images, true-color synthetic images and standard false-color remote sensing images on the same scale as the base map of the integrated exploration area were developed based on combination of different wavebands as well as image enhancement, fusion, and spatial filtering.

2.4 Methods for Preparation of Major Maps 2.4.1 Comprehensive Suite-tectonic Maps

Firstly, the latest mineral geological maps collected were preliminarily spliced. Secondly, based on existing cross-sections of the area and the research results of typical deposits such as Daqiao gold deposit, Yawan antimony deposit, and Pingding gold deposit, the sedimentary rock suites and intrusive rock suites in the integrated exploration area were systematically determined through data analysis and selection. Thirdly, geological boundaries were verified and corrected, and lithological patterns were filled in according to the characteristics of the lithologic associations and occurrence. In this way, the comprehensive suite-structure maps were formed. To ensure the reliability of mineral predication, section lines running across typical mineral deposits and perpendicular to the stratigraphic strike were selected to prepare the maps. According to the analysis and collation of the suites and structures of typical mineral deposits and regional suites and structures, the ore-bearing suites of the Daqiao gold deposit, Yawan antimony deposit, and Pingding gold deposit were determined to be thin-laminated carbonaceous-silty limestone suite of the Triassic Huashiguan Formation, the limestone suite of the Triassic Daheba Formation, and the suite of the Devonian Xiawuna Formation consisting of carbonate interbedded with sandstone, respectively.

2.4.2 Metallogenic Factor Maps 2.4.2.1 Division of Predicted Mineral Types

The main types of prospecting deposits in the Yawan–Daqiao integrated exploration area were determined to be gold and antimony deposits according to the study on regional metallogenic regularity and typical deposits in the area. The details are shown in Table 3.

2.4.2.2 Analysis of Metallogenic Factors and Establishment of Metallogenic Model Maps

The research data on typical mineral deposits (i.e., the Daqiao gold deposit, Yawan antimony deposit, and Pingding gold deposit) and other deposits (ore occurrences) in the Yawan–Daqiao integrated exploration area were completely collected. Based on this, the metallogenic geologic blocks, metallogenic structures, metallogenic structural planes, and metallogenic characteristics and indicators of three types of typical deposits in the area were analyzed and collated following the “trinity” prospecting prediction theory for exploration areas proposed by researcher Ye Tianzhu (Ye TZ et al., 2014, 2017). Meanwhile, deep faults strictly control the distribution of suites in the area, and the distribution of the deposits is closely related to the suites. Therefore, deep faults play a significant role in controlling the diagenesis and mineralization in the area and thus affect the formation and temporal and spatial distribution of various endogenous deposits in the area.

Based on this, the metallogenic factor table (Table 4) and regional metallogenic model maps of the integrated exploration area were established.

2.4.2.3 Preparation of Metallogenic Factor Maps

The metallogenic factor maps were prepared based on the analysis of the metallogenic factors, with comprehensive suite-structure maps serving as the base map. On these maps, necessary and major metallogenic factors were retained, concealed plutons (metallogenic geologic blocks) and structures (metallogenic structures) inferred from regional geophysical, geochemical, and remote-sensing data were supplemented, and the strata and magmatic rocks unrelated to mineralization are simply expressed. Moreover, a map layer was established for each metallogenic factor during mapping.

2.4.3 Predictive Factor Maps 2.4.3.1 Analysis of Predictive Factors and Establishment of Regional Prediction Models

The metallogenic factors mainly reflect the geological information related to metallogenesis, from which the identifiable indicators formed from metallogenesis were extracted as predictive factors. Meanwhile, geological predictive factors were supplemented with geophysical, geochemical, and remote-sensing predictive factors determined by geophysical exploration, geochemical exploration, and remote sensing. Among them, the aeromagnetic and remote-sensing interpretation results indicated metallogenic structures and concealed plutons (metallogenic geologic blocks). They also indicated that geochemical anomalies of hydrothermal gold-antimony deposits in the area mainly include the composite anomalies of the elements such as Au, Sb, and As. Meanwhile, according to the theory of primary halo zoning, the anomalous front halo elements of the gold-antimony deposits in the area include Hg, Sb, and As, and anomalous tail halo elements include W, Mo, and Bi. They are used to determine the denudation degree of the area and indicate the locations of mineral deposits to some extent. In this way, the predictive factor data table of the area was established (Table 5). Based on the analysis of predictive factors, the regional prediction model figure was prepared by superimposing geochemical profiles on the base map of the metallogenic model map (Fig. 3).

2.4.3.2 Preparation of Predictive Factor Maps

Predictive factor maps were prepared with the metallogenic factor map serving as the base map. To reflect the geophysical, geochemical, and remote-sensing predictive factors, the map layers of sedimentary suites and intrusive rock suites were deleted and only the lithological patterns were retained but faded. Meanwhile, the following factors were superimposed: (1) geophysical factors: the intermediate-acid plutons and structures interpreted; (2) chemical factors: Au-Hg-As-Sb composite anomalies, single element anomalies of Au, Sb, and As, and the intermediate-acid plutons interpreted; (3) metallogenic structures interpreted from remote sensing. In addition, the map layers of predictive factor data table and prediction models were inserted.

2.4.4 Prediction Result Maps

The typical deposits in Yawan–Daqiao integrated exploration area were determined temporally and spatially according to comprehensive factors of geological suites, deformed structures, and intrusive magmatism. Therefore, all mineral prediction methods used are of composite endogenous type. The prediction information was extracted based on the GIS assessment system for mineral prediction and presented in.wp files. It covers metallogenic structures (extracted according to the occurrence and properties of the metallogenic structures obtained from different prediction types; mitigation zones were built in combination with the frequency of the influence zones of metallogenic structures and ore occurrences), metallogenic geologic blocks (Late Indosinian–Yanshanian intermediate-acid intrusive bodies interpreted; mitigation zones were built in combination with the frequency of the influence zones of metallogenic structures and ore occurrences), ore-bearing suites, and geochemical anomalies (single element anomalies of Au, Sb, and As, and composite anomalies of Au-Hg-As-Sb). Afterwards, based on the prediction and assessment models, predicted minimum prospecting target areas (also referred to as the minimum predicted areas) were delineated by using the factor superposition method, applying the software MRAS to conduct interactive searches of modelers, and carrying out intersection and union operations of predictive factors. Then metallogenic probability was determined by manually selecting model units. In this study, the predicted minimum prospecting target areas were optimized in terms of denudation degree. As a result, 42 gold-antimony minimum predicted areas were determined, covering an area of 2.7% of the total area of the integrated exploration area. The areas for prediction assessment model were further established. The predicted depth and the ore-bearing coefficient of ore-bearing geologic blocks were calculated according to the parameters such as identified resources (above 333 resources), the area of ore vein concentration areas, and the maximum exploration depth. Moreover, the predicted resources was estimated according to the volume of ore-bearing geologic blocks.

The prediction result maps were compared based on predictive factor maps. On the prediction result maps, horizontal lines are used to fill in Class A predicted minimum areas (having very favorable metallogenic conditions and deposits), vertical lines are used to fill in Class B predicted minimum areas (having favorable metallogenic conditions), and cross lines are used to fill in Class C predicted minimum areas (having general metallogenic conditions). Meanwhile, annotations were made (including the nos., names, area, depth, similarity coefficient, predicted resource types, and categories of the predicted minimum areas). Finally, the map layers of various prediction tables were superimposed on the prediction result maps.

2.5 Value Assignment for Attributes of the Dataset

The attribute values of the dataset in this study were assigned by referring to the Spatial Database Establishment Code of Digital Geological Maps (DD2006–06) according to the Code of Geological Information Metadata (DD2006–05) issued by the China Geological Survey. Databases were established for various types of maps according to the Method and Technology System of Data Models for Mineral Resources Potential Assessment and the requirements of GeoMAG.

3 Description of Data Samples

Attribute values were assigned and corresponding databases were established for comprehensive suite-structure maps, magnetic survey maps, geochemical maps, remote sensing maps, metallogenic factor maps, predictive factor maps, prediction results maps, metallogenic regularity maps, and maps of suggestions on mineral exploration deployment. Since partial database units of the maps are inherited from other maps, only the database units specific to each type of maps are described as follows.

Database units specific to the suite-structure maps: (1) the attributes of a sedimentary rock suite, including its no., characteristic code, primitive no., category, rock associations, names and codes of its mapping units, genetic type of the Quaternary, formation time, suite type, thickness of ore-bearing strata, major fossil assemblages, and sedimentary facies; (2) the attributes of an intrusive rock suite, including its no., characteristic code, primitive no., lithologic code, geographical longitude and geographical latitude, names and codes of its mapping units, formation time, special rocks, mineral composition, the colors, texture, and structure of its rocks, occurrence of intrusions, dikes, inclusion characteristics, the depth and pattern of its emplacement, denudation degree, important petrochemical parameters, the series, genetic types, and tectonic associations of its rocks, and geotectonic setting; (3) attributes of a fault, including its no., name, length, type, fault plane dip (dip angle), rocks on both sides of and within the fault, structural hierarchy, cutting depth, motion mode, mechanical properties, formation time, and superimposed motion; (4) attributes of a fold, including its no., name (type, morphology, and degree), hinge plunge angle, plunge direction, axial dip (dip angle), strata involved in the fold, fold association form, genesis, formation time, and characteristics of superimposed folds; (5) attributes of occurrence, including its no., type, dip, dip angle, and strike.

Database units specific to magnetic survey maps, geochemical maps, and remote-sensing maps: (1) attributes of a fault, including its no., outcrops, order, strike, length, and magnetic field indicators; nos. and values of its aeromagnetic ΔT isolines and aeromagnetic ΔT RTP isolines, and the no., initial value, and end value of its isoline area; (2) attributes of single-element geochemical maps, including the nos., element composition, and element content of isolines; the element composition, maximum element content, and minimum element content of an isoline area; (3) attributes of single-element geochemical anomaly maps, including the anomy no. and threshold of a geochemical anomaly boundary; the no., anomaly threshold, local maximum/minimum points, anomaly no., and anomaly area of a geochemical anomaly range area; (4) attributes of geochemical anomaly maps, including the no., area, major associated elements, and major paragenetic elements of an integrated anomaly range, and the element types, anomaly threshold, measurement units, and anomaly area of major metallogenic factor ranges.

The database units specific to the metallogenic factor maps: the attributes of a mineral deposit, including its no., characteristic code, primitive no., name, traffic location, geographical longitude and latitude, ore-hosting rocks, ore-controlling structures, major minerals, geotectonic location, metallogenic types, the scale, resource reserves (unit), and average grade (unit) of its major minerals, paragenetic and associated minerals (reserves, unit), metallogenic zones/belts, metallogenic series, deposit type, metallogenic time, metallogenic age, age error, dating methods, spatial combination type of its ore bodies, the no. and shape (scale, strike, dip, dip angle, length, and thickness) of its major ore body, ore composition (grade, mineral composition, structure, and texture), length (width) of its alteration zones, and the alteration assemblages and alteration intensity of its surrounding rocks.

The database units specific to the prediction result maps: the nos., names, area, scale, and geographic locations of predicted minimum areas; metallogenic geological setting; mineral prediction types; predicted area categories; identified resources; estimation method of resources; reserves data table of predicted minimum areas (EXCEL).

The database units specific to the metallogenic regularity maps: boundary nos. and names of metallogenic zone/belts, ore concentration areas, and metallogenic prospect areas; the names of typical deposits.

The database units specific to the maps of suggestions on mineral exploration deployment: the no., name, grade, and mineral types of suggested deployment area, suggestions on mapping and exploration on a medium-large scale, expected results, and the data table of suggestions on mineral exploration deployment (EXCEL).

4 Data Quality Control and Assessment

The results of the mineral resource potential assessment in this study were all integrated into a dataset. To implement the mineral resource potential assessment and build the dataset, rich true and reliable data obtained previously were collected. Among the map sheets in the Yawan–Daqiao integrated exploration area, only Liangdang, Zhouqu, and Shawan map sheets had not been surveyed before. Therefore, the 1:250 000 regional geological survey data of Minxian, Tianshui, Wudu, and Lueyang County map sheets along with cross-sections were adopted to prepare the comprehensive suite-structure maps. Meanwhile, the newly collected grid data with a cell size of 500 m ×500 m were integrated, and the 1∶50 000 geochemical data were processed. All data processing strictly followed the Technical Guidelines for 1∶50 000 Mineral Resource Potential Assessment of Integrated Exploration Areas (Draft) developed by the Exploration Technical Guidance Center of the Ministry of Natural Resources of the People's Republic of China in 2018. With reliable data sources, databases were constructed according to the Method and Technology System of Data Models for Mineral Resource Potential Assessment (Development and Research Center of China Geological Survey, 2016), achieving complete attributes.

The dataset was developed under the strict control of a three-level quality inspection system and the quality system of the Gansu Institute of Geological Survey. In early January 2019, the Development and Research Center of China Geological Survey (i.e., the Technical Guidance Center for Mineral Resources of Ministry of Natural Resources) organized experts to review the research report and database specific to the 1∶50 000 mineral resource potential assessment of the gold-antimony deposit integrated exploration area in Yawan–Daqiao area, Gansu Province. The expert panel unanimously approved the research report and database and rated them excellent.

5 Data Value

(1) Under the guidance of the “trinity” prospecting prediction theory, the predictive factors of the Daqiao gold deposit, Pingding gold deposit, and Yawan antimony deposit were sorted out and prediction models were built.

(2) The metallogenic regularity of the Yawan–Daqiao integrated exploration area was researched based on the metallogenic regularity of west Qinling area. As a result, two Level-IV metallogenic zones and six Level-V ore concentration areas were determined according to the national mineral resource potential assessment results and the division of Level-III metallogenic zones/belts throughout China. Moreover, eight Grade-V gold-antimony metallogenic prospect areas were determined according to the mineral resource prediction results of this study.

(3) A series of aeromagnetic maps of the integrated exploration area were prepared through collecting and collating the aeromagnetic data with different precision, such as the grid data with a cell size of 500 m ×500 m. The aeromagnetic maps developed include 1∶50 000 aeromagnetic survey degree maps, aeromagnetic (ΔT) isoline plans, aeromagnetic (ΔT) RTP isoline plans, and aeromagnetic (ΔT) RTP-based vertical first-order derivative maps. Moreover, the interpretation of plutons and structures was further explored and updated in terms of data, which is indirectly indicative of mineral prediction.

(4) The 1∶50 000 geochemical data of the map sheets in the Yawan–Daqiao integrated exploration area were integrated into the dataset. Based on this, 597 single-elements anomalies and 59 integrated anomalies of 15 elements such as Au were delineated and two intermediate-acid plutons were interpreted. The research results of the denudation degree played a significant role in the mineral resource potential prediction of this study.

(5) The predicted resources in deep and peripheral areas of typical deposits in the integrated exploration area were delivered, including 190 419 kg in the Daqiao gold deposit, 7 492 kg in the Pingding gold deposit, and 99 568 tonnes in the Yawan antimony deposit. Meanwhile, 17 predicted minimum areas of Daqiao-type stratabound-hydrothermal gold deposits were delineated, with 353 470.26 kg of predicted gold resources being delivered; 10 predicted minimum areas of Pingding-type structural-hydrothermal gold deposits were delineated, with 107 171.85 kg of predicted gold resources being delivered; 15 predicted minimum areas of Yawan-type structural-hydrothermal antimony deposits were delineated, with 587 889.43 tonnes of predicted antimony resources being delivered.

(6) A total of 12 exploration areas were deployed according to the mineral resource prediction results in this study, including three Level I, three Level II, and six Level III exploration areas. Among them, the three Level I exploration areas are Chaerjin-Pingding exploration area, Daqiao exploration area, and Miaowan-Paierba exploration area, and the three Level II exploration areas are Longba exploration area, Anfangba exploration area, and Nanjiashan exploration area. Specially, 37 secondary exploration areas were deployed, including 15 reconnaissance survey areas and 22 pre-investigation areas. The predicted gold and antimony resources are 460.67 tonnes, and 587 900 tonnes, respectively.

6 Conclusions

(1) The 1∶50 000 mineral resource potential assessment of the gold-antimony deposit integrated exploration area in Yawan–Daqiao area, Gansu Province is a demonstration project of potential assessment in the new round of mineral geological survey and prospecting prediction projects of integrated exploration areas initiated by the China Geological Survey. In this study, the authors of this paper actively explored and innovated a series of working methods and map compilation methods for potential assessment of integrated exploration areas, and established a potential assessment dataset. All these provide an example for the 1∶50 000 potential assessment of integrated exploration areas throughout China in terms of working contents, working processes, and the establishment of datasets.

(2) To carry out the mineral resource potential assessment in this study, previous research results and data were sorted out and integrated. Therefore, the establishment of the dataset in this study is of significant for relevant data collation and integration.

(3) The sedimentary rocks and intrusive rocks in the Yawan–Daqiao integrated exploration area were comprehensively researched using the latest basic geological data and scientific research data of the area. Accordingly, comprehensive suite-structure maps (1∶50 000) of the area were prepared, providing basic information of the metallogenic geological setting for research on metallogenic regularity and mineral resource prediction. Meanwhile, practical and feasible working procedures were summarized. All these assist in improving the degree of basic geological research in the area. Meanwhile, the dataset established in this study will provide data bases for subsequent exploration in this area.

Acknowledgements: The authors would like to extend sincere gratitude to the leaders and colleagues from the Gansu Institute of Geological Survey for their hard work, including Professorate Senior Engineers Li Tongguo and Yu Chao, Senior Engineer Sun Xinchun, Gao Yongwei, Niu Pengfei, Li Zeng, Zhang Wanren, Zhang Xinghua, and Wang Hexuan. Thanks also go to Researcher Lyu Zhicheng, Deputy Chief Engineer from the Development and Research Center of China Geological Survey, for his special concern, guidance, and considerable assistance for the quality improvement of this study.

Notes:

① Gansu Institute of Geological Survey. 2016. Annals of Regional Geology in Gansu Province[R].

② Zhang Wanren, Zhang Youkui, Ou Chunsheng, Yang Weigang, Gao Yongwei, Ma Yongdong, Feng Beizhan, Li Tongyuan, Zhang Qi. 2013. Report on Prospect Survey Results of Copper, Tungsten and Gold Minerals in Chengxian-Lintan Area, Gansu Province[R].

③ Liu Xiaolin, Ou Chunsheng, Liu Haili, Liu Duochao, Feng Beizhan, Zhen Hongxu, Wang Yongning, Zhou Bin. 2009. Prospect Survey Report of Mineral Resources in Tanchang-Shiqiao Town Area, Gansu Province[R].

④ Yang Weigang, Ren Pengfei, Huo Qinzhi, Li Tongyuan, Kong Xiangchao, Wang Haibo, Gao Zhijie, Li Xiao, Wang Meiping, Li Liang, Guo Songqing, Dong Yaqing. 2016. 1∶50 000 Geological and Mineral Survey of Six Map Sheets Including Lujiazhuang in Daqiao Gold-Antimony Deposit Integrated Exploration Area, Gansu Province[R].

⑤ Zhang Yong, Niu Haiping. 2013. Report on Prospect Survey Results of Copper-Iron Polymetallic Deposits in Miba-Nankang Area, Gansu Province[R].

⑥ Zhang Wanren, Wan Xuhui, Chen Gang. 2015. Report on Prospect Survey Results of Gold-Antimony Deposits in Yawan Area, Xihe County, Gansu Province[R].

⑦ Gansu Institute of Geological Survey. 2012. Report on 1∶250 000 Regional Geological Survey Results of Wudu County Map Sheet, Gansu Province[R].

⑧ Gansu Institute of Geological Survey. 2013. Potential Assessment Report of Mineral Resources in Gansu Province[R].