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基于浓度–面积分形模型和模糊证据权的铜矿资源潜力评价:以江西九瑞地区为例

林俞亨, 王立立, 欧阳永棚, 李增华, 曾闰灵, 陈祺, 邓友国

林俞亨,王立立,欧阳永棚,等. 基于浓度–面积分形模型和模糊证据权的铜矿资源潜力评价:以江西九瑞地区为例[J]. 西北地质,2024,57(1):165−178. doi: 10.12401/j.nwg.2023199
引用本文: 林俞亨,王立立,欧阳永棚,等. 基于浓度–面积分形模型和模糊证据权的铜矿资源潜力评价:以江西九瑞地区为例[J]. 西北地质,2024,57(1):165−178. doi: 10.12401/j.nwg.2023199
LIN Yuheng,WANG Lili,OUYANG Yongpeng,et al. Evaluation of Copper Mineral Resource Potential Using Concentration–Area Fractal Model and Fuzzy Evidence Weighting: A Case Study of the Jiurui Region in Jiangxi[J]. Northwestern Geology,2024,57(1):165−178. doi: 10.12401/j.nwg.2023199
Citation: LIN Yuheng,WANG Lili,OUYANG Yongpeng,et al. Evaluation of Copper Mineral Resource Potential Using Concentration–Area Fractal Model and Fuzzy Evidence Weighting: A Case Study of the Jiurui Region in Jiangxi[J]. Northwestern Geology,2024,57(1):165−178. doi: 10.12401/j.nwg.2023199

基于浓度–面积分形模型和模糊证据权的铜矿资源潜力评价:以江西九瑞地区为例

基金项目: 江西省科技厅重点研发计划项目(20212BBG73045),江西省地质局青年科学技术带头人培养计划项目(2022JXDZKJRC02),鹰潭市科技计划项目(20233-185656)联合资助。
详细信息
    作者简介:

    林俞亨(1998−),男,硕士研究生,主要从事综合信息矿产预测研究。E−mail:1033425063@qq.com

    通讯作者:

    欧阳永棚(1988−),男,博士,高级工程师,主要从事勘查地质学和区域成矿学研究。E−mail:yongpeng0524@163.com

  • 中图分类号: P618.41

Evaluation of Copper Mineral Resource Potential Using Concentration–Area Fractal Model and Fuzzy Evidence Weighting: A Case Study of the Jiurui Region in Jiangxi

  • 摘要:

    中国江西省的九瑞地区是长江中下游成矿带中最重要的铜矿产地之一,其中花岗闪长斑岩与铜成矿关系密切。基于水系沉积物与矿化相关的信息,采用因子分析(FA)、浓度–面积分形法(C–A)和模糊证据权方法(FWofE)相结合建立成矿潜力预测模型。使用因子分析处理包含32个元素的255份水系沉积物样本数据,找到能够指示铜矿化的组合元素(即主因子)。采用多重分形反距离加权插值法(MIDW)创建主因子得分栅格图并用C–A分形模型提取与铜矿化相关的地化异常。将得到和铜矿化相关的地球化学异常图与地质、遥感解译数据相结合,应用模糊证据权方法建立预测模型。结果表明:已知铜矿床位于圈定预测概率高值区,且受花岗闪长斑岩和断裂的分布共同控制;除已知铜矿床区域外,圈定的3个一级远景区域内也具有较高的概率,值得进一步铜勘查找矿工作的进行。

    Abstract:

    The Jiurui region in Jiangxi Province, China, is one of the most significant copper mining areas in the middle and lower reaches of the Yangtze River mineralization belt, with a close relationship between granodiorite porphyry and copper mineralization. In this study, a predictive model for mineralization potential was established by combining factor analysis (FA), concentration-area (C-A) fractal method, and fuzzy weight of evidence (FWofE) based on information related to stream sediment and mineralization. ϕfactor analysis was applied to a dataset of 255 stream sediment samples containing 32 elements to identify combinations of elements (principal factors) indicative of copper mineralization. κ the principal factor scores were interpolated using the multiple inverse distance weighted (MIDW) method to create a raster map, and the C-A fractal model was employed to extract geochemical anomalies associated with copper mineralization. λ the geochemical anomaly map related to copper mineralization was integrated with geological and remote sensing interpretation data, and a predictive model was established using the fuzzy weight of evidence method. The results indicated that: known copper deposits are located within high-probability zones defined by the model and are influenced by the distribution of granodiorite porphyry and faults; in addition to the known copper deposit areas, three primary prospective areas identified within the defined regions also exhibit a high probability, meriting further exploration efforts for copper prospecting.

  • 以苏里格气田为代表的鄂尔多斯盆地致密砂岩气的开发目前正处于快速发展阶段。目前,中国已有多位学者对研究区致密砂岩储层进行了深入的研究(白慧等,20152020董会等,2016田清华等,2022)。苏里格气田位于鄂尔多斯盆地伊陕斜坡的西北部,苏59井区位于苏里格气田的西部。而河道砂体是常规油气勘探开发的主要研究对象。对于这类砂岩储层的评价通常以单一岩性为主,岩相组合分析较少。岩相组合指的是沉积序列的垂向构成,包括岩石的岩性、成分、结构、构造、亚相(微相)等,例如,可以按照粒度特征分为向上变粗、向上变细和复合3种类型 (邱隆伟等,2012胡一然,2015张荣,2016孟德伟等,2016张洪洁,2020)。岩相组合分析能够反映一段沉积期内的沉积水动力条件、沉积原始物质组成,甚至后期成岩改造的程度(雷开强,2003陈俊亮等,2004陈克勇,2006白涛,2008张延庆,2008张广权等,2011李晓慧,2020)。不同的岩相组合具有特殊的测井曲线形态,分布在特定的沉积微相中,具有“易识别、可预测”的典型特征。然而,前人已经开展过单一岩相类型及其储层物性特征等方面研究(覃伟,2011叶爽清,2015印森林等,2016张荣,2016魏修平等,2019林建力等,2019Zhang et al.,2020),但岩相组合对储层物性的影响尚不明确。

    鄂尔多斯盆地苏里格气田上古生界石盒子组和山西组具有良好的开发前景。苏里格气田石盒子组和山西组沉积在海陆过渡沉积环境,广泛发育三角洲分流河道和水下分流河道砂体,以中–粗粒的岩屑砂岩以及岩屑石英砂岩为主。笔者拟通过岩心观察分析、薄片鉴定、图像分析对苏里格气田石盒子组和山西组开展岩石学特征研究,划分岩相类型和岩相组合,并从岩性、粒度、压实强度、溶蚀程度等特征进行分析,明确岩相组合对砂岩储层物性的控制作用。

    苏里格气田是中国陆上发现的最大的天然气田,位于长庆靖边气田西北侧的苏里格庙地区(图1a)。区域构造属于鄂尔多斯盆地陕北斜坡北部中带(图1),行政区属内蒙古自治区鄂尔多斯市的乌审旗和鄂托克旗所辖,勘探范围西起内蒙古鄂托克前旗、北抵鄂托克后旗的敖包加汗,勘探面积约20000 km(汪正江等,2002王光强,2010)。

    图  1  研究区位置及地层综合柱状图
    a.区域构造位置图; b.SU59-13-51B井地层综合柱状图
    Figure  1.  Comprehensive histogram of the location and stratigraphy of the study area

    苏里格气田上古生界自下而上发育石炭系本溪组、二叠系山西组、下石盒子组、上石盒子组和石千峰组,总厚度700 m左右。中二叠世下石盒子组初期伴随区域构造活动继续加剧,北部物源区持续抬升,丰富的物源碎屑导致河流沉积体系快速向南推移,致使冲积平原向南增大,湖泊相区缩小。该期岩相古地理面貌特征与山西期有一定的继承性,也发生了较大的变化,以多河道的辫状河与曲流河交替发育为主要特征,多心滩、边滩沉积,河道相互叠置,砂体厚度较山西组有较大增加。在山西组,早期的时候,发生强烈的构造活动,北部物源区迅速上升(汪正江等,2002陈昭佑等,2010谭晨曦,2010),使研究区在该时期形成大面积的砂体发育区。受古气候影响,山西组沉积期沼泽普遍发育,发育多套煤层。早二叠世山西期沉积在海陆过渡的三角洲环境,山西组下部发育三角洲前缘相,上部发育三角洲平原相(袁芳政,2008陈洪德,2011张广权,2011)。石盒子组和山西组三角洲平原相发育分流河道、分流间湾、天然堤、决口扇、泛滥洼地和泥炭沼泽微相;三角洲前缘发育水下分流河道、水下分流间湾和河口坝微相(王少鹏,2006郑婷,2015)。依据沉积旋回,研究区石盒子组由上而下分为盒8-3至盒8-4两个小层,盒8段上段以暗紫红色、紫红色泥岩、粉砂岩、泥岩为主,夹薄~中厚层状棕红色、浅棕红色细砂岩、中砂岩;中段以暗紫色、暗紫红色、深灰色、灰绿色泥岩为主夹浅灰色细砂岩;下段为中厚~厚层状浅灰色、灰白色细砂岩、中砂岩、含砾粗砂岩为主、薄层深灰色泥岩、粉砂质泥岩;底部为厚层状灰白色小砾岩;而山西组由下而上分为山1和山2段,并可进一步细分为S1-1至S2-2五个小层(图1)。山1段岩性为砾质砂岩、含砾粗砂岩、粗砂岩、中砂岩、细砂岩、泥岩和煤层,且煤层在山1段最为发育;山2段岩性与山1段基本一致,但煤层厚度较薄(罗东明等,2008万旸璐,2016)。

    通过苏里格气田西部的SU59-4-13、SU59-13-51B的岩心观察和薄片分析,石盒子组盒8和山西组12主要发育石英砂岩和岩屑石英砂岩,含少量岩屑砂岩。通过镜下对100余个薄片鉴定结果进行统计,储集层碎屑主要成分为石英,碎屑颗粒中石英含量为69%~88%,石英颗粒平均含量为80.3%;储集层碎屑次要为变质岩岩屑,变质砂岩含量较少,长石含量极低,胶结物以硅质胶结和铁方解石胶结为主,杂基以云母和高岭石为主,少见绿泥石(图2图3)。

    图  2  苏59井区石盒子组和山西组岩石中主要岩屑类型
    a、b岩屑石英砂岩SU59-4-13井 2 695.07 m S1-2;c、d 岩屑砂岩 SU59-13-51B井2 695.07 m S1-2
    Figure  2.  Major rock chip types in rocks of the Shibox Formation and Shanxi Formation in the Su59 well area
    图  3  苏59井区山西组岩石中主要岩屑类型
    a. 变质岩岩屑 变质石英岩SU59-4-13井 2660.33 m S2-1;b. 沉积岩岩屑 粉砂岩 SU59-4-13井 2600.76 m S1-2;c. 沉积岩岩屑 鲕粒灰岩SU59-4-13井 2660.33 m S2-1;d. 沉积岩岩屑 泥板岩 SU59-4-13井 2597.27 m S1-2; e. 变质岩岩屑 SU59-13-51B井 2621.82 m S1-1;f .变质岩岩屑SU59-13-51B井 2551.12 m S2-2
    Figure  3.  Main rock chip types in the rocks of Shanxi Formation in Su59 well area

    苏里格气田西区储集层物性总体表现为低孔隙度、低渗透率的特征。根据岩心物性资料统计,孔隙 度范围 4%~12%,平均为 7.24%;渗透率范围0.01×10−3~10×10−3 μm2 ,平均为 0.52×10−3 μm2 ;孔隙度与渗透 率之间具有明显的正相关关系,表明渗透率的变化主 要受控于孔隙度的发育程度(张春英等,1995)。其中渗透率大于0.5×10−3 μm2的砂岩可视为良好的储层,渗透率小于0.5×10−3 μm2的砂岩物性较差(赵靖舟,2012王少飞,2013)。

    石盒子组和山西组三角洲平原分流河道以及辫状河心滩微相砂岩的粒度普遍较粗,根据取心段岩心描述与统计的结果,中粒以上的砂岩占总砂岩厚度90%以上,平均厚度在2~5 m之间。根据粒度分析结果,山西组砂岩的粒度中值Φ为−1.08~3.98,平均为0.64,粒度较粗;标准偏差为0.28~1.05,分选好至中等;偏度普遍大于0,具有明显的正偏态。砂岩结构普遍具有颗粒支撑特征,局部含泥中砂岩具有杂基支撑结构。颗粒支撑砂岩的碎屑颗粒之间普遍呈线接触,仅部分样品可见点接触特征,指示了较强的压实作用。

    研究区三角洲平原分流河道和心滩微相砂岩的沉积构造特征明显,主要发育粒序层理、纹层层理、槽状交错层理、板状交错层理、和平行层理。根据研究区沉积构造和岩石粒度差异,可将盒8段主要划分为5类岩相(图4表1)。

    图  4  山西组不同粒度砂岩类型
    a.含砾粗砂岩相,发育交错层理,3 528.2 m,苏59井;b.灰黑色泥岩相,见碳质纹层,3 608.4 m,苏59-13-51B井;c.沙纹层理泥质粉砂岩相,可见明显的沙纹层理构造,3 532.6 m,苏59井;d.含砾粗砂岩相,3 531.05 m,苏59-13-51B井;e.细-中砂岩相,断面可见碳质,3 548.74 m,苏59-13-51B井
    Figure  4.  Types of sandstones with different grain sizes in the Shanxi Formation
    表  1  鄂尔多斯气田研究区主要岩相类型
    Table  1.  Main lithological types in the Ordos gas field study area
    粒度分级沉积构造岩相类型
    (含砾)粗砂岩板状交错层理板状交错层理粗砂岩
    中砂岩块状层理块状层理中砂岩
    平行层理平行层理中砂岩
    小型交错层理小型交错层理中砂岩
    细-中砂岩平行层理平行层理细-中砂岩
    细砂岩平行层理平行层理细砂岩
    粉砂岩小型交错层理小型交错层理细砂岩
    下载: 导出CSV 
    | 显示表格

    层理类型和粒度是沉积水动力条件的直接反映(刘忠群,2008李成等,2015),岩相类型能够反映一段时期内的水动力条件,而岩相组合能够反映河道沉积期内的水动力条件的变化特征。本研究根据纵向上岩石粒度变化,将岩相组合分为向上变细的正韵律组合和向上变粗的反韵律组合以及先变细再变粗的复合韵律组合(图5)。复合韵律组合为由多个正/反韵律相互叠置构成,表现为上部与下部粗-中砂岩与煤层互层,中部夹杂含泥中砂岩的复合韵律特征;复合韵律组合指示了河道水动力条件较强但不稳定,组合中部发育的含泥中砂岩具有密度流的特点。正韵律组合具有下粗上细的结构,下部发育中-粗砂岩,中部发育中砂岩、上部发育粉-细砂岩,具有河道沉积充填的典型特征;反韵律组合砂体垂向粒度变化表现为下细上粗的渐变,上部发育粗-中砂岩,下部发育粉-细砂岩,具有河口坝沉积充填的特征。

    图  5  研究区发育的岩相组合类型
    Figure  5.  The lithofacies assemblies of Formation in the study area

    根据对研究区对两口井取心井的分析,石盒子组砂体垂向上主要以正韵律、反韵律和符合韵律为主而山西组砂体垂向上主要以正韵律和复合韵律为主,粒度向上逐渐变细的正韵律最常见。通过对取心段的统计,3类岩相组合所发育的岩相类型存在较大差异(图6)。岩相组合和岩相组合II的岩相类型中粒度整体较粗,粗砂岩/中-粗砂岩所占比例较高,且以块状层理为主。岩相组合III的岩相类型的粒度偏细。

    图  6  研究区不同岩相组合所发育的单一岩相类型
    Figure  6.  The lithofacies type in the different lithofacies assemblies of Study area

    苏59井区山西组为海相–陆相沉积体系。在砂体垂向相主要以正韵律和复合韵律为主,从整体来看表现为粒度向上变细的正韵律。且正韵律往往在砂体下部分布于高孔渗的物性值,向上逐步过渡减小;复合韵律在单砂体内部渗透率变化规律并不显著,垂向表现出高低渗透率交替出现。

    通过对取心井76个柱塞样品孔渗数据分析,相比石盒子组山西组含砾粗砂岩、粗砂岩、中-粗砂岩的物性相对较好,孔隙度普遍大于4%,渗透率大于0.5×10−3 μm2。含泥中砂岩和中砂岩物性较差,排除微裂缝的样品,渗透率普遍低于0.5×10−3 μm2。山西组主要岩相类型的孔渗差异明显。据前人研究,苏里格气田低渗透致密砂岩储层可分为 4 种类型:①渗透率大于 1×10−3 µm2的砂岩储层。②渗透率介于 0.5×10−3 µm2~ 1×10−3 µm2的砂岩储层。③ 渗透率在0.1×10−3 µm2~0.5×10−3 µm2之间的砂岩储层。④渗透率小于 0.1×10−3 µm2砂岩储层。其中渗透率大于 0.5×10−3 µm2的砂岩储层可视为良好储层,渗透率小于0.5×10−3µm2的砂岩储层物性较差,在勘探开发过程中通常只将前两种砂岩储层作为开发对象(赵靖舟,2012王少飞,2013)。

    通过对平均孔隙度和平均渗透率的统计,物性最好的岩相为粒序层理含砾中砂岩、块状含砾粗砂岩、板状交错层理粗砂岩和块状粗砂岩,平均孔隙度大于8%,平均渗透率大于1×10−3 μm2图7图8)。根据对不同岩相组合中这4类相对高孔渗岩相发育程度的统计,在复合韵律组合I和正韵律组合II中相对高孔渗岩相更加发育,且组合II中最发育(图9)。由此可见,岩相组合之间存在物性差异主要与所发育的岩相类型有关。

    图  7  苏59井区组孔隙度与渗透率相关图
    Figure  7.  Porosity versus permeability correlation plot for the Su 59 well formation
    图  8  苏59井区不同岩相类型的平均孔隙度和渗透率
    Figure  8.  The average porosity and permeability of different lithofacies from the Study area
    图  9  苏59井区不同岩相组合中相对高孔渗岩相类型厚度百分比
    Figure  9.  Comparison of development frequency of relatively high porosity and permeability facies types in different lithofacies assemblages of Study area

    研究区山西组砂岩段岩石组合Ⅰ杂基含量较低且黏土以伊利石为主,石英含量高,胶结物含量较少;Ⅱ类岩石组合杂基含量较高,压实程度相对较高,高岭石含量较高,石英含量较低,溶蚀程度较强;Ⅲ类岩石组合,杂基含量高,压实程度高,高岭石含量低,溶蚀程度低(图10)。

    图  10  研究区山西组地区杂基含量直方图
    Figure  10.  Histogram of heterogeneous group content in Group area of Su59 well area

    由于不同岩相组合形成的沉积水动力条件不同,会导致岩石组成的不同,对储层物性产生明显影响。通过XRD全岩分析表明,研究区砂岩的碎屑颗粒都以石英为主,其次为岩屑,几乎未见长石。岩屑组分包括沉积岩岩屑、变质岩岩屑、火山岩岩屑、云母以及少量燧石,且以沉积岩岩屑为主。通过对研究区体薄片进行统计分析可知,在岩相组合Ⅰ和II中石英含量高于组合III,但岩屑含量低于组合III,而在岩石组合Ⅲ中石英含量相对较低而岩屑含量较高,特别是沉积岩岩屑分布较多(图11)。不同类型的岩屑的抗压实能力差异较大,沉积岩岩屑中碳酸盐岩岩屑抗压实能力最强,其次为粉砂岩岩屑,泥岩岩屑最易于压实。

    图  11  研究区不同岩相组合的砂岩岩石组成特征
    Figure  11.  Petrographic composition of sandstones developed in different lithofacies assemblages of the Study area

    通过对杂基含量与物性关系的分析,表明研究区山西组颗粒支撑的砂岩中杂基的含量与孔隙度和渗透率均存在明显的正相关性(图12)。通过对不同岩相组合中所发育砂岩的杂基含量的统计对比,发现组合III中的杂基含量明显高于组合I和组合II,是造成岩相组合III物性相对较差的主要原因。

    图  12  研究区砂岩中的杂基含量及其对储层物性的影响
    a.杂基含量与孔隙度相关性图;b.不同岩相组合中所发育的砂岩的平均杂基含量对比图
    Figure  12.  The matrix content of sandstone in the Study area and its influence on reservoir physical properties

    根据对研究区山西组成岩作用类型的分析,溶蚀作用的结果导致了砂岩中次生孔隙的形成。压实作用和溶蚀作用对储层的发育具有明显影响。压实作用的强度与颗粒粒径、塑性颗粒含量、埋藏深度等因素有关。压实相对较弱的砂岩能够保留较多连通性好的原生孔隙,形成相对高渗的储层。反之,在胶结作用较弱的砂岩中,原生孔较发育指示所经历的压实作用相对较弱。通过统计3类岩相组合的原生孔发育程度,岩相组合I和岩相组合II中的原生孔所占比例明显高于组合III(图13图14),表明在较高的石英含量和相对较少的沉积岩岩屑的岩石组成背景下岩相组合I和II砂岩所经历的岩石作用程度相对于组合III低。

    图  13  研究区储集空间类型
    a.粒内溶孔 SU59-4-13井2 668.9 m S2-1;b.粒内溶孔 SU59-4-13 井2 705.01 m S1-3;c.铸模孔SU59-4-13井2 702.7 m S1-3
    Figure  13.  Types of reservoir space in the study area
    图  14  山西组不同岩相组合的砂岩中原生孔和溶蚀孔发育程度对比图
    a.不同岩相组合的原生孔发育程度对比;b.不同岩相组合的溶蚀孔发育程度对比
    Figure  14.  Comparison of the degree of development of primary and dissolution pores in sandstones of different lithological assemblages of the Shanxi Formation

    研究区山西组颗粒支撑结构的砂岩中溶蚀作用普遍发育,但发育程度差异较大,局部甚至可见强烈溶蚀形成的矿物铸模孔。通过对研究区砂岩铸体薄片和扫描电镜观察,山西组砂岩溶孔大部分为岩屑溶蚀后形成,部分为长石溶蚀后形成,并在溶孔中残留较多蠕虫状自生高岭石(图15)。溶蚀作用的程度与压实程度密切相关,在压实相对较弱的砂岩中后期有机酸易于流动循环,促使溶蚀作用的进行。不同岩相组合的次生溶蚀孔隙的发育程度存在明显差异。岩相组合I和组合II溶蚀孔较为发育,并且在岩相组合II砂岩中发育一定铸模孔(图4图9)。这种溶蚀差异是由岩相组合的原始物质组成而产生的,由岩相组合I和组合II的较高的石英含量和较低的沉积岩岩屑含量导致在压实过程中仍然能够保留一定数量的原生孔,从而使溶蚀作用较强。

    图  15  研究区砂岩溶蚀孔发育特征
    a.粒内溶孔和残余粒间孔,SU59-13-51B井,H83;b.铸模孔,SU59-4-13B井,S1-2;c.岩屑溶蚀孔,SU59-4-13B井,S2-1;d.长石溶蚀孔被自生高岭石充填,SU59-13-51B井,S2-1
    Figure  15.  Characteristics of dissolved pores in sandstones of the Study area

    (1)苏里格气田盒8段岩屑石英砂岩和岩屑砂岩为主;山西组主要以石英砂岩和岩屑石英砂岩为主,分选程度中等至好,颗粒间以线接触为主。根据岩石粒度和沉积构造,研究区主要岩相类型可划分为5种。根据岩性的韵律变化特征,可将岩相组合划分为3种类型,分别为复合韵律组合、正韵律组合和反韵律组合,其中反韵律组合砂岩粒度偏细。

    (2)研究区不同岩相的物性差异明显,相对高孔渗岩相为粒序层理砾质砂岩、块状含砾粗砂岩、板状交错层理粗砂岩和块状粗砂岩,平均孔隙度大于8%,平均渗透率大于1×10−3 μm2。复合韵律和正韵律岩相组合中相对高孔渗岩相所占比例较高,是两类有利的岩相组合。

    (3)原始物质组成导致了不同岩相组合的物性差异。复合韵律和正韵律岩相组合相对于反韵律组合的石英含量较高,沉积岩岩屑含量较低,杂基含量较低,导致在压实过程中保留了一定原生孔,并且形成较多的溶蚀孔隙,使其孔隙度和渗透率相对较高。

  • 图  1   长江中下游成矿带简易地质图(据Pan et al.,1999修)

    Figure  1.   Simplified geological map of the Mid-Lower Yangtze metallogenic belt

    图  2   九瑞铜矿区地质图(据Yang et al.,2011修)

    Figure  2.   Geological map of the Jiurui region ore copper district

    图  3   ROC曲线示例图

    Figure  3.   Example plot of ROC curve

    图  4   水系沉积物样品采样点分布图

    Figure  4.   Steam sediment sample location map

    图  5   因子2得分的多重分形反距离权重插值结果图

    Figure  5.   Multifractal IDW result for the factor 2 scores

    图  6   浓度与面积的双对数图

    Figure  6.   Log-log plot of concentration versus area

    图  7   C–A分形模型识别的异常图

    Figure  7.   Anomaly map identified by the C–A fractal model

    图  8   用于九瑞地区成矿预测的证据图层

    Figure  8.   Evidence layers for mineral prediction in the Jiurui region

    图  9   MSF分类的证据图层

    Figure  9.   MSF for evidences

    图  10   九瑞地区找矿后验概率及远景区分级图

    Figure  10.   Map of posterior probability and hierarchical prospective in the Jiurui region

    图  11   正、负样本点空间分布图

    Figure  11.   Distribution map of positive and negative samples

    图  12   预测模型ROC曲线

    Figure  12.   ROC curve of the predictive model

    表  1   32种元素的检出限表

    Table  1   Detection limits of 32 elements

    序号元素检出限序号元素检出限
    1Ag0.0117Mo0.5
    2As2.8218Nb5
    3Au0.000319Ni5
    4B520P30
    5Ba1021Pb5.4
    6Be0.522Sb0.2
    7Bi0.1623Sn0.14
    8Cd0.124Sr5
    9Co125Th5.1
    10Cr7.226Ti30
    11Cu127U1
    12F1328V2
    13Hg0.0129W0.5
    14La1030Y10
    15Li531Zn10
    16Mn3032Zr10
     注:元素含量为10-6
    下载: 导出CSV

    表  2   R型因子分析的正交旋转因子载荷矩阵表

    Table  2   Orthometric rotating factor loading matrix for R-factor analysis

    变量因子载荷
    F1F2F3F4F5F6F7
    Ag0.101−0.0310.954−0.0650.0300.039−0.062
    As0.0590.329−0.0990.854−0.039−0.027−0.203
    Au−0.0120.717−0.0410.007−0.0260.005−0.069
    B−0.303−0.072−0.021−0.0720.7160.163−0.104
    Ba0.101−0.0310.954−0.0650.0300.039−0.062
    Be0.910−0.0230.1750.0680.0150.170−0.016
    Bi−0.0250.941−0.0060.062−0.017−0.0320.007
    Cd0.0550.249−0.0980.917−0.099−0.0140.102
    Co0.767−0.0060.0930.4350.224−0.021−0.112
    Cr0.8310.0010.007−0.061−0.0130.0820.036
    Cu−0.0890.7860.0220.324−0.0220.0140.288
    F0.8350.043−0.057−0.051−0.0870.1020.123
    Hg0.0630.2210.0230.1960.1000.173−0.443
    La0.235−0.0930.068−0.1250.1530.7600.047
    Li0.890−0.0190.1240.0130.0590.177−0.038
    Mn0.4890.0050.0650.3280.1980.016−0.212
    Mo−0.0090.4890.0150.2290.0150.0440.679
    Nb0.2540.1040.118−0.0450.6110.1230.029
    Ni0.875−0.0690.049−0.070−0.0260.1810.052
    P0.464−0.0490.4170.025−0.226−0.2180.100
    Pb0.0750.918−0.0140.050−0.002−0.026−0.157
    Sb0.0480.926−0.0620.1690.022−0.059−0.053
    Sn0.2740.2870.0640.053−0.0940.5720.068
    Sr0.2090.0580.736−0.077−0.411−0.0930.068
    Th0.332−0.015−0.2410.0100.603−0.1160.094
    Ti0.5690.0110.5860.0060.252−0.002−0.110
    U0.170−0.022−0.193−0.0580.0730.0890.289
    V0.9310.0420.1460.0490.0360.1340.032
    W−0.0770.6570.1710.1440.064−0.0220.444
    Y0.108−0.216−0.1810.0310.1520.739−0.141
    Zn0.0260.049−0.0170.959−0.055−0.0230.041
    Zr−0.570−0.070−0.166−0.0980.5460.0970.007
     注:该因子分析采用的提取方法为主成分分析法,旋转方法为Kaiser标准化最大方差法,旋转在七次迭代后已经收敛。
    下载: 导出CSV

    表  3   各证据层隶属度表(MSF)及模糊证据权重计算表

    Table  3   Table of membership of each evidence layer (MSF) and calculation of fuzzy weights of evidence

    缓冲距离分类主要赋矿地层断裂花岗闪长斑岩绿泥石化蚀变地球化学异常分类C-A分形模型
    分类值缓冲
    距离(m)
    隶属度证据
    权重
    隶属度证据
    权重
    隶属度证据
    权重
    隶属度证据
    权重
    分类值C-A分形隶属度证据
    权重
    110010.6010.3714.0612.051高异常12.06
    220010.6010.370.673.4612.052异常0.672.00
    330010.6010.370.332.640.81.993弱异常0.331.83
    440010.6010.3700.690.61.914背景−0.37−0.37
    55000.80.580.860.3600.690.41.785
    66000.60.550.710.360.21.566
    77000.40.380.570.3501.037
    88000.2−0.030.430.3401.038
    99000−0.030.290.329
    10100000.140.3010
    11110000.2611
    12120000.2612
    13130000.2613
      注:“−”为空值。
    下载: 导出CSV
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  • 收稿日期:  2023-10-07
  • 修回日期:  2023-11-17
  • 录用日期:  2023-11-19
  • 网络出版日期:  2023-12-04
  • 刊出日期:  2024-01-07

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