Mineral search prediction based on Random Forest algorithm——A case study on porphyry-epithermal copper polymetallic deposits in the western Gangdise meatallogenic belt
-
摘要:研究目的
矿产资源定位预测的核心是矿产分布与控矿地质因素之间的非线性关系,大数据及机器学习技术在解决这类复杂非线性关系问题方面已经体现出巨大的优势。小比例尺地物化遥信息的预测数据集具有高维和极不平衡的特点,依靠传统的逻辑假设或统计分析很难适应。本文尝试将随机森林算法引入到小比例尺找矿预测领域来开展研究,探索大数据及机器学习技术在小比例尺找矿预测中的应用。
研究方法近年来,冈底斯成矿带西段新发现了鲁尔玛、拔拉扎、达若、红山和罗布真等多个斑岩型、浅成低温热液型铜金多金属矿床(点),证实冈底斯西段具有寻找斑岩型、浅成低温热液型铜金多金属矿的巨大潜力。本文以新发现的典型矿床为研究对象,在总结冈底斯成矿带西段斑岩铜矿成因模式的基础上,结合物化遥综合信息,构建地物化遥综合找矿模型,最后利用随机森林法开展研究区找矿预测。
研究结果本文结合典型矿床与区域地质、地球物理、地球化学及遥感综合信息,利用随机森林法在冈底斯成矿带西段开展斑岩型、浅成低温热液型铜金多金属矿的找矿预测,圈定出斑岩—浅成低温热液型铜多金属矿找矿远景区11个(包含Ⅰ级远景区2个,Ⅱ级远景区3个,Ⅲ级远景区6个),其中罗布真、打加错、达若、拔拉杂、尕尔穷和布东拉等远景区找矿潜力较大。
结论基于大数据机器学习的欠采样随机森林预测模型,有望适应综合地物化遥信息的预测数据高维和极不平衡特点,为成矿带尺度区域找矿预测提供方向。本次工作确定的远景区有望发现新的矿床(点),为冈底斯成矿带找矿勘查打开了新的视野。
创新点:(1)总结了冈底斯西段斑岩—浅成低温热液型铜多金属成矿作用的时空分布特征及区域找矿信息;(2)探索了基于大数据机器学习的欠采样随机森林预测模在找矿预测的应用;(3)圈定出了冈底斯西段斑岩—浅成低温热液型铜多金属矿找矿远景区。
Abstract:The paper is the result of geological survey engineering.
ObjectiveThe core problem of prospecting prediction is the nonlinear relationship between mineral distribution and mineral-controlling geological factors. Big data and machine learning technology have shown great advantages in solving such complex nonlinear relationship problems. The prediction dataset of small-scale geochemical remote information has the characteristics of high and extremely unbalanced, which is difficult to adapt by traditional logical assumptions or statistical analysis. Therefore, this paper attempts to introduce the random forest algorithm into the field of small-scale prospecting to explore the application of big data and machine learning technology in small-scale mineralization prediction.
MethodsIn recent years, several Porphyry-epithermal copper polymetallic deposits (such as Luerma, Bolazha, Daruo, Hongshan, and Luobuzhen, etc.) have been discovered in the western Gangdise mineralized belt, which proved that the western Gangdise belt has great prospecting potential for porphyry and epithermal Cu-Au polymetallic deposits. Combined with the comprehensive information of typical deposits, regional geology, geophysics, geochemistry, and remote sensing, this paper uses the random forest method to carry out the prospecting prediction of porphyry and epithermal Cu-Au polymetallic deposits in the western Gangdise belt.
ResultsThis work has delineated 11 porphyry copper polymetallic prospect areas (including 2 levels Ⅰ prospect areas, 3 level Ⅱ prospect areas, and 6 level Ⅲ prospect areas), of which Luobuzhen, Dajiacuo, Daruo, Balaza, Gaerqiong, and Budongla have great prospecting potential and are expected to find new ore deposits or points.
ConclusionsThe under-sampling random forest prediction model based on big data machine learning is expected to adapt to the high-dimensional and extremely unbalanced characteristics of prediction data of comprehensive geophysical and geochemical remote information and provide direction for regional prospecting prediction at the scale of the metallogenic belt. The prospective area determined in this work is expected to find new deposits (points), which opens a new vision for ore prospecting and exploration in the Gangdise metallogenic belt.
-
1. 引 言
塔里木盆地古生界碳酸盐岩储层分布广,厚度大,生储盖空间配置优越(翟光明等, 2004),围绕古隆起发育的塔北油田与塔中油田更是中国陆上碳酸盐岩油气勘探开发研究的重点区块(Yang et al., 2007; 何治亮等, 2016)。塔北油田的开发经历了自北部潜山区向南到顺层改造区的探索,形成了一套以浅层风化壳岩溶及层间岩溶为主控的缝洞体油藏的认识(沈安江等, 2019)。随着勘探开发逐步深入到台缘叠加区,已有油藏体系认知无法对低隆区油藏的开发进行有效指导,开发陷入瓶颈。随着顺北1号与顺北5号深层—超深层奥陶系碳酸盐岩储层取得重大突破(Jiao et al., 2018),受断裂控制的断溶体油气藏逐渐成为油田勘探开发的重点,对油气藏的认识也逐步转变为深大断裂控储、控藏、控富研究(王新新等, 2019; 丁志文等, 2020)。
塔里木盆地地质历史上构造运动强烈,经历多期构造运动,受区域应力场作用,稳定克拉通内部发育一系列陆内短滑距走滑断裂(Han et al., 2017; 邓尚等, 2021),最新三维地震勘探揭示,多期构造作用形成的走滑断裂继承性发育,形成多种构造样式,导致油气分布具有明显的区段性(邬光辉等, 2011)。同时,受断裂控制的断溶体油气藏特征表现出仅沿断裂带含油、且不均匀富集的特点(Wu et al., 2018; Jiao et al., 2018),表明走滑断裂是控制储层的重要因素(Wang et al., 2021),故进一步认识断裂对岩溶性储层的控制作用对碳酸盐岩油气的勘探具有重要意义。
2. 区域地质概况
跃满区块构造上位于塔里木盆地塔北隆起轮南低凸起的西部斜坡带(图1),轮南低凸起为一大型潜山背斜,面积15100 km2,主体在轮南油田至塔河油田一带,长轴在东部为北东向,西部为北东东向。跃满区块为向西倾没的哈拉哈塘大型鼻状构造一部分,北接轮台凸起,南衔北部坳陷,西邻英买力低凸起。研究区区域构造演化主要经历了中、晚加里东运动差异抬升期,晚海西—印支运动挤压抬升期,燕山—早喜山运动局部调整期,晚喜山运动至今构造反转期(马德波等, 2020)。
跃满区块地层发育完整,自上而下钻遇新生界第四系,新近系和古近系,中生界白垩系、侏罗系、三叠系,古生界二叠系、石炭系、志留系以及奥陶系。奥陶系可细分为上奥陶统桑塔木组(O3s)、良里塔格组(O3l)、吐木休克组(O3t);中奥陶统一间房组(O2y);中—下奥陶统鹰山组(O1-2y);下奥陶统蓬莱坝组(O1p)(朱光有等, 2011)。勘探开发目的层主要为奥陶系一间房组海相碳酸盐岩地层,上覆吐木休克组为一致密泥灰岩层,可以形成良好的油气封闭条件,有利于下伏一间房组油气成藏。
3. 储层特征
3.1 储层岩石学特征
岩心、薄片和测井资料表明,跃满地区中奥陶统一间房组储集岩以灰岩为主,岩性主要为生屑灰岩、砂屑灰岩、颗粒灰岩、泥晶灰岩(图2),为开阔台地相的台内砂屑、藻屑滩沉积岩类。岩心孔渗分析结果显示孔隙度平均值1.00%、渗透率平均值1.160×10−3 μm2,均为较低水平,且孔隙度与渗透率相关性不明显。
图 2 跃满地区奥陶系一间房组储层岩性(染色铸体薄片)a—跃满2井,井深:7211.8 m,亮晶生屑灰岩,构造缝;b—跃满2井,井深:7200.6 m,泥晶生屑灰岩;c—跃满2井,井深:7209.7 m,泥亮晶生屑灰岩,构造缝;d—跃满2井,井深:7206.7 m,泥粉晶生屑灰岩,构造缝;e—跃满2井,井深:7215.7 m,亮晶藻团块生屑灰岩,构造缝;f—跃满2井,井深:7209.9 m,泥亮晶生屑灰岩,构造缝与压溶缝;g—跃满2井,井深:7201.7 m,泥晶生屑灰岩,构造缝,压溶缝;h—跃满2井,井深:7210.7 m,方解石和沥青质半充填的构造缝;i—跃满2井,井深:7207.3 m,亮晶藻砂屑灰岩,构造缝,方解石全充填的溶蚀缝;j—跃满2井,井深:7216.7 m,亮晶生屑藻砂屑灰岩,粒内溶孔;k—跃满2井,井深:7217.6 m,泥亮晶生屑藻砂屑灰岩,粒内溶孔;l—跃满2井,井深:7212.6 m,亮晶颗粒灰岩,构造缝,压溶缝;m—跃满2井,井深:7213.7 m,亮晶颗粒灰岩,构造缝,压溶缝;n—跃满2井,井深:7214.5 m,粉晶颗粒灰岩,方解石半充填构造缝;o—跃满2井,井深:7196.5 m,生屑泥晶灰岩,构造缝;p—跃满2井,井深:7197.5 m,生屑泥晶灰岩,收缩缝Figure 2. Reservoir lithology of Ordovician Yijianfang Formation in Yueman area (dyed cast thin section)a−Well Yueman 2, depth: 7211.8 m, sparry bioclastic limestone, structural fracture; b−Well Yueman 2, depth: 7200.6 m, micrite bioclast limestone; c−Well Yueman 2, depth: 7209.7 m, micrite−sparry bioclast limestone, structural fracture; d−Well Yueman 2, depth: 7206.7 m, micrite−powder bioclast limestone, structural fracture; e−Well Yueman 2, depth: 7215.7 m, sparry clumpy alga bioclastic limestone, structural fracture; f−Well Yueman 2, depth: 7209.9 m, micrite−sparry bioclast limestone, structural fracture, pressolutional fracture; g−Well Yueman 2, depth: 7201.7 m, micrite bioclast limestone, structural fracture, pressolutional fracture; h−Well Yueman 2, depth: 7210.7 m, structural fracture, half−filled with calcite and asphalt; i−Well Yueman 2, depth: 7207.3 m, sparry algal arenaceous limestone, structural fracture, dissolution fracture, full−filled with calcite; j−Well Yueman 2, depth: 7216.7 m, Sparry bioclastic arenaceous limestone, intragranular dissolved pore; k−Well Yueman 2, depth: 7217.6 m, argillaceous sparry bioclastic arenaceous limestone, intragranular dissolved pore; l−Well Yueman 2, depth: 7212.6 m, sparry granular limestone, structural fracture, pressolutional fracture; m−Well Yueman 2, depth: 7213.7 m, sparry granular limestone, structural fracture, pressolutional fracture; n−Well Yueman 2, depth: 7214.5 m, silt−grained limestone, half−filled with calcite, structural fracture ; o−Well Yueman 2, depth: 7196.5 m, bioclastic micritic limestone, structural fracture; p−Well Yueman 2, depth: 7197.5 m, bioclastic micritic limestone, shrinkage fracture3.2 储层类型
薄片、岩心及钻测井资料揭示(图2,图3;表1),研究区奥陶系碳酸盐岩储集空间宏观上以大型溶蚀洞穴、溶蚀孔洞及构造裂缝为主,微观上以孔隙(粒间孔、粒内孔、晶间孔、晶间溶孔)与微裂缝(构造缝、压溶缝、溶蚀缝)为主。根据洞、孔、缝组合特征,储层类型可分为洞穴型储层、裂缝−孔洞型储层、裂缝型储层与孔洞型储层4类,其中洞穴型储层储集能力最强,裂缝孔洞型储层兼具良好的储集与运移能力,分别为区内重点开发的Ⅰ类、Ⅱ类储层发育段,而裂缝型与孔洞型储层储集能力一般但分布广,多为Ⅲ类储层发育段。
图 3 跃满地区奥陶系一间房组储层类型(岩心)a—跃满2井,1−58−35,生屑砂屑灰岩,溶蚀孔洞;b—跃满2井,2−54−6,生屑砂屑灰岩,溶蚀孔洞,方解石全充填、半充填;c—跃满703井,2−81−37,生屑灰岩,溶蚀孔洞;d—跃满2井,3−56−37,砂屑生屑灰岩,中高角度缝;e—跃满1井,1−51−1,砂屑灰岩,中高角度缝,沿缝发育溶蚀孔;f—跃满6井,1−64−42,砂屑灰岩,直立缝与水平缝近垂直共轭;g—跃满8井,1−64−46,砂屑灰岩,高角度裂缝,沿裂缝溶蚀孔洞发育,见油斑;h—跃满8井,2−63−25,砂屑灰岩,直立缝与水平缝交汇处溶孔扩大;i—跃满1井,1−51−42,砂屑灰岩,中高角度裂缝,沿裂缝溶蚀孔洞发育Figure 3. Reservoir type of the Yijianfang Formation of Ordovician in Yueman area (cores)a−Well Yueman 2, 1−58−35, bioclastic calcarenite, dissolved pore; b−Well Yueman 2, 2−54−6, bioclastic calcarenite, dissolved pore, full filled or half filled with calcite; c−Well Yueman 703, 2−81−37, bioclastic limestone, dissolved pore; d−Well Yueman 2, 3−56−37, sandy bioclastic limestone, middle−high angle fracture; e−Well Yueman 1, 1−51−1, calcarenite, middle−high angle fracture, dissolved pore; f−Well Yueman 6, 1−64−42, calcarenite, horizontal and vertical fractures; g−Well Yueman 8, 1−64−46, calcarenite, high Angle fracture, dissolved pore, oil patch; h−Well Yueman 8, 2−63−25, calcarenite, horizontal and vertical fractures, dissolved pore increase at fracture intersections; i−Well Yueman 1, 1−51−42, calcarenite, middle−high angle fracture, dissolved pore表 1 跃满区块漏失统计Table 1. Lost circulation statistics in Yueman area序号 井号 放空长/m 漏失量/m3 序号 井号 放空长/m 漏失量/m3 1 跃满1 1.92 355 18 跃满5−4X 6.39 659 2 跃满10 0 506.12 19 跃满5−5 1.85 148.4 3 跃满1−1 0 535.7 20 跃满601 0 373.7 4 跃满1−3 0.12 118.24 21 跃满6C 0 215.5 5 跃满1−5 0.76 0 22 跃满701 0 260.4 6 跃满2−2C 0 1200 23 跃满701−H1 1.11 1494.4 7 跃满2−4X 1.41 2049 24 跃满702 0 133.2 8 跃满3 0 253.4 25 跃满703 2.72 252.2 9 跃满3−1 1.49 307.1 26 跃满7−1X 0 1558.11 10 跃满3−2C 0 1063.2 27 跃满7−2X 0.34 1527.19 11 跃满3−3 0.93 348.5 28 跃满7JS 19.1 3231.33 12 跃满3−5 0.74 114.6 29 跃满8 4.02 773.5 13 跃满3−5C 8 1064.6 30 跃满801 2.79 1389.18 14 跃满3−6X 0.96 241.6 31 跃满801−H6 2.59 549.4 15 跃满3−7X 0 9.9 32 跃满802 1.45 329.7 16 跃满4 0 43.8 33 跃满8−1 6.34 286.2 17 跃满5−3 0 269.4 34 跃满9 9.25 811 孔洞型、裂缝型、裂缝−孔洞型储层在区内大量发育。其中孔洞型储层以一间房组开阔台地相台内滩和台地边缘相台缘礁滩体等高能相带为发育基础,层状发育且具有较好的孔隙度与渗透率,储层段岩心薄片可见微观粒间溶孔、铸膜孔、粒内溶孔等(图2e、k),可见部分孔洞被方解石充填,岩心可见不规则溶蚀孔洞发育,部分被方解石半充填、全充填(图3a~c)。裂缝型储层区内普遍发育,连通溶蚀洞穴、孔洞或成组发育的裂缝型储层更为有效,薄片可见沥青与泥质全充填的压溶缝,方解石全充填、半充填的溶蚀缝,未充填的构造缝等(图2f、h、i);岩心显示裂缝以中高角度—高角度构造缝为主,形态总体较规则,缝面较平坦,具成组发育特征(图3d~f)。裂缝−孔洞型储层主要分布于一间房组开阔台地相台内滩颗粒灰岩中,兼具良好的运移与储集能力,岩心显示,沿裂缝溶蚀孔洞发育,且多裂缝交汇处溶蚀孔洞发育更佳(图3g~i)。
洞穴型储层以大型溶蚀洞穴为主要储集空间,洞穴围岩裂缝及洞底碎石孔隙为次要储集空间,新三维地震资料显示,洞穴在地震剖面上表现出强串珠状反射特征,该类储层主要发育于一间房组上部,沿主干断层或断层两侧垂向发育(图4)。
钻井资料上洞穴型储层表现为放空和漏失,跃满区块已有钻井的放空漏失现象统计显示,区内共完钻51口井,放空21井,占比41.2%,平均放空3.537 m,最长放空跃满7JS井,放空长达19.1 m,最短放空跃满1−3井,仅放空0.12 m;同时总计33井有漏失现象,占比64.7%,平均漏失681.0 m3,最小漏失跃满3−7X井共9.9 m3,最大漏失跃满7JS井共3231 m3(表1),放空漏失现象普遍。
3.3 储层发育规律
综合钻、测井及三维地震资料,对比东西向与南北向相邻井所揭示的岩性、储层及沉积特征,对区内储层分布特征进行厘定,结果表明,在垂向上,储层主要分布于一间房组顶面以下0~120 m范围之内,少量钻井(跃满3、跃满7)揭示上覆吐木休克组与良里塔格组有少量Ⅱ类和Ⅲ类储层发育;在横向剖面上,储层表现出强非均质性以及低连续性:各井储层类型、储层厚度差异较大,东西向连井对比图显示各井储层连续性差,而在近南北断层走向上,连井对比图显示储层具有一定连续性(图5);在一间房组,洞穴型储层沿断裂孤立发育,孔洞型储层与裂缝型储层沿断裂带状发育,同时,不同断裂构造段内储层发育具有显著差异性,特别是洞穴型储层,往往集中于局部断裂大量发育,显示出强烈的断控特征(图6)。
4. 走滑断裂特征
塔里木盆地经历多期不同方向的斜向构造挤压作用,盆内发育多组走滑断裂系统,按形成的力学机制可分为纯剪机制和单剪机制(图7)。研究区受古昆仑洋及阿尔金板块俯冲消解作用,形成多组纯剪机制的“X”型共轭走滑断裂带(Tang et al., 2012; 孙东等, 2015),在此基础上,共轭断层相继滑动、切割调节,形成的不连续断层经过尾端扩张与连接生长,最终形成位移量极少的“小位移”长断裂带。通过断裂带碳酸盐胶结物U−Pb测年结合地震解析,确定塔里木盆地奥陶系碳酸盐岩走滑断裂活动始于距今约460 Ma的中奥陶世末期(Wu et al., 2021)。跃满区块位于塔北哈拉哈塘地区南部,为共轭走滑断裂发育区的边缘地带,区内主要发育一组北北西向与三组北北东向走滑断裂(图7)。
图 7 塔北至塔中地区(a,据Wu et al., 2021修改)跃满区块(b)走滑断裂体系纲要图Figure 7. Schematic diagram of strike−slip faults in Tabei−Tazhong area (a, modified from Wu et al., 2021) and Yueman area (b)4.1 走滑断裂分段特征
北北西向跃满1−3—跃满102断裂带位于跃满区块西北部,为北部金跃地区向南延伸的一号断裂的末端,具有强烈的应力发散特点,研究区可见有另一北北东向走滑断裂(跃满1−1井所在断裂)终止于该马尾断层。北北东向跃满601—跃满2−1断裂带与跃满704—跃满3−3断裂带位于研究区中部,是研究区油气开发的重点,两条断裂均延伸较长,跃满601—跃满2−1断裂带向南延伸至顺北区块后终止,向北穿过金跃、热普等区块,延伸至哈6区块被共轭北北西向断裂截断;跃满704—跃满3−3断裂带向南终止于北东东向的顺北1号断裂带,向北延伸至金跃区块后被截断。跃满801—跃满8走滑断裂仅在研究区发育,延伸较短、连续性差且前期勘探开发尚不完善,故暂不做分析研究。
在对区内沿断裂走向的高度差异表征断层应力特征研究的基础上,对断裂构造进行分段性研究,结果显示:跃满1−3—跃满102断裂带为一典型马尾段,平面上由主干断层与若干同向弯曲的短分支断层组成,分支断层向南散开形成典型的马尾状构造,最南端转变为扇形排布的雁列断层,地震剖面上,北部可见平行的主干断层与小的花状构造,中部可见半花状构造,南部多为深大半花状构造(图8)。
跃满601—跃满2−1断裂带自南向北可划分四段:D1线性段、D2叠覆段、D3斜列段、D4叠覆段。D1线性段为压扭性质,平面上为单条断层线性延伸,剖面上为单条直立断层;D2与D4左行右阶叠覆段均为张扭性质,平面上表现为主干断层错位发育,在断层之间形成条形叠覆区域,叠覆区内受拉张应力作用,发育多条与两主干断层大角度斜交的分支断层,D2段一大一小两个叠覆区连续发育,D4段叠覆区规模居中,剖面上主要表现为两条直立断层伴随半花状构造;D3斜列段中部为压扭性质,靠近叠覆段的两端为张扭性质,平面上由多条断层平行排列组成,剖面上主要表现为两条直立断层(图9)。
跃满704—跃满3−3断裂带自南向北可划分为四段:D5斜列段、D6线性段、D7斜列段、D8斜交段。D5斜列段为压扭性质,D7斜列段为张扭性质,平面上均为多条断层平行排列,与断层整体走向呈低角度交错,剖面上为两条直立断层;D6线性段为D5斜列段至D7斜列段间的过渡段,为张扭性质,平面上为单条主干断层,剖面上为单条陡直断层;D8斜交式断层应力性质表现为压扭与张扭交错,平面上为若干R剪切分支断层与主干断层组成,分支断层主要发育于主干断层以西,剖面上显示为发育在奥陶系内的半花状构造(图10)。
4.2 各构造段储层分布特征
根据三维地震资料揭示的洞穴及缝洞雕刻结果,区内布置并完成了30余口井的钻探工作,并对27口井进行了试采,在钻测井资料对储层的解析基础上,结合走滑断裂的分段特征对断裂不同构造段内储层发育情况进行统计分析(表2,表3,表4),结果表明:马尾段内,储层厚度普遍较厚,储层类型以裂缝型与孔洞型储层为主,裂缝孔洞型储层少量发育,未见洞穴型储层,储层发育整体较好;叠覆段与斜列段内,储层厚度普遍较厚,且各类储层均有发育,储层发育最佳;分支断层斜交段储层发育极不均匀,整体认为储层发育一般;线性段储层发育则普遍较差。
表 2 跃满区块钻井储层统计(跃满1−3—跃满102)Table 2. Reservoir statistics of drilling in Yueman area (Yueman 1−3−Yueman 102)分段 井号 顶深/m 底深/m 层厚/m 类型 顶深/m 底深/m 层厚/m 类型 马尾段 跃满1−3 7209 7224 15 Ⅲ 7282 7290 8 Ⅲ 7270 7276 6 Ⅲ 跃满1−1 7217 7223 6 Ⅱ 7227.5 7238 10.5 Ⅱ 7223 7227.5 4.5 Ⅱ 跃满1−5 7226 7232 6 Ⅲ 7287 7289.5 2.5 Ⅲ 7255 7261.5 6.5 Ⅲ 7295.5 7298.5 3 Ⅲ 7275.5 7278 2.5 Ⅲ 7301.5 7303.5 2 Ⅱ 7282.5 7285.5 3 Ⅲ 跃满1 7259.5 7265.5 6 Ⅲ 7268.5 7277 8.5 III 7265.5 7268.5 3 II 跃满1−4 7297 7301 4 Ⅱ 7303.5 7307 3.5 Ⅲ 跃满9 7586.8 7588.9 2.1 Ⅱ 7591 7598 7 Ⅱ 跃满1−8 7302.5 7305 2.5 Ⅲ 7343.5 7350 6.5 Ⅲ 7311 7317.5 6.5 Ⅱ 跃满102 7282 7297 15 Ⅲ 7300.5 7306 5.5 Ⅱ 7297 7300.5 3.5 Ⅲ 7306 7312.5 6.5 Ⅱ 表 4 跃满区块钻井储层统计(跃满704—跃满3−3)Table 4. Reservoir statistics of drilling in Yueman area (Yueman 704−Yueman 3−3)分段 井号 顶深/m 底深/m 层厚/m 类型 顶深/m 底深/m 层厚/m 类型 斜列段 跃满704 7307.5 7311 3.5 Ⅲ 7364 7370.5 6.5 Ⅲ 7338.5 7340 1.5 Ⅱ 7370.5 7378 7.5 Ⅱ 7340 7344.5 4.5 Ⅲ 跃满703 7277.9 7289.7 11.8 Ⅲ 7298 7300.92 2.92 Ⅰ 线性段 跃满701 7315.7 7321.5 5.8 Ⅰ 斜列段 跃满7 7234 7242.5 8.5 Ⅲ 7265.5 7270.5 5 Ⅲ 7242.5 7248.5 6 II 7270.5 7275 4.5 Ⅰ 7257 7263 6 Ⅲ 跃满3−1 7224 7229 5 Ⅲ 7244 7246.5 2.5 Ⅲ 7234.5 7242.5 8 Ⅲ 7246.5 7251 4.5 Ⅰ 7242.5 7244 1.5 Ⅱ 分支断层
斜交段跃满3 7189.5 7198.5 9 Ⅲ 7219.4 7223.2 3.8 Ⅰ 7209 7216 7 Ⅱ 跃满3−5 7167.7 7171 3.3 Ⅰ 7197.88 7206.96 9.08 Ⅱ 7173.8 7180.9 7.1 Ⅰ 7206.96 7212.04 5.08 Ⅰ 7184.04 7197.88 13.84 Ⅲ 7212.04 7220 7.96 Ⅲ 跃满3−3 7158.62 7159.55 0.93 Ⅰ 表 3 跃满区块钻井储层统计(跃满601—跃满2−1)Table 3. Reservoir statistics of drilling in Yueman area (Yueman 601−Yueman 2−1)分段 井号 顶深/m 底深/m 层厚/m 类型 顶深/m 底深/m 层厚/m 类型 线性段 跃满601 7313 7320 7 Ⅲ 7372.5 7379 6.5 Ⅱ 叠覆段 跃满6 7294 7296.28 2.28 Ⅱ 7302.04 7304 1.96 Ⅲ 7296.28 7300.6 4.32 Ⅲ 7304 7306 2 Ⅱ 7300.6 7302.04 1.44 Ⅱ 7308 7310.7 2.7 Ⅲ 跃满5−2 7277 7279 2 Ⅲ 7301.5 7304 2.5 Ⅲ 7284 7290.5 6.5 Ⅱ 7313 7315 2 Ⅲ 7290.5 7295 4.5 Ⅲ 7318 7319.5 1.5 Ⅲ 斜列段 跃满5 7272.5 7276.5 4 Ⅱ 7280 7281.5 1.5 Ⅱ 7276.5 7280 3.5 Ⅲ 7281.5 7289 7.5 Ⅲ 跃满5−3 7258.5 7271 12.5 Ⅲ 7279 7292 13 Ⅱ 跃满5−1 7248.5 7253 4.5 Ⅲ 7263 7269.5 6.5 Ⅱ 7253 7255 2 Ⅱ 7269.5 7277.5 8 Ⅲ 7255 7258.5 3.5 Ⅲ 7280.5 7282.5 2 Ⅲ 叠覆段 跃满2−3X 7274 7301.5 27.5 Ⅱ 7319 7323 4 Ⅱ 7313 7316 3 Ⅱ 7323 7326.5 3.5 Ⅲ 跃满2 7200.5 7212.5 12 Ⅲ 7245 7263 18 III 7221 7233.5 12.5 Ⅲ 7263 7273 10 Ⅲ 7233.5 7245 11.5 Ⅱ 跃满2−1 7304.5 7315.5 11 Ⅲ 7329.76 7334.44 4.68 Ⅰ 7315.5 7325 9.5 Ⅱ 7338 7341 3 Ⅱ 5. 分析讨论
5.1 断控岩溶作用对储层发育的控制
综上所述,跃满区块走滑断裂分段特征与储层的发育规模具有一定的耦合关系,前人研究认为:塔北哈拉哈塘地区岩溶作用对碳酸盐岩储层具有直接控制作用(Dan et al., 2016; 梁乘鹏等, 2019),岩溶体系又主要受控于低水位期海平面下降、先存断裂及裂缝、地表河流体系(Liang and Jones, 2014; 宁超众等, 2020)。塔北奥陶系碳酸盐岩储层发育可分为四个阶段:一间房组准同生阶段、良里塔格组台缘滩沉积阶段、志留系前潜山岩溶阶段与后期埋藏溶蚀阶段(张学丰等, 2012; 赵学钦等, 2015),而非暴露区跃满区块位于塔北隆起最南缘,隆升幅度最小(廖涛等, 2016),故该区奥陶系储层主要受早期准同生岩溶与后三期埋藏岩溶作用,埋藏岩溶作用主要表现为深部溶蚀性流体沿断裂向上运移,改造一间房组碳酸盐岩,形成有效储集体(郑剑等, 2015; 牛君等, 2017)。分析认为断裂主要通过控制岩溶作用间接控制储层的发育,结合钻井与走滑断裂相对位置关系发现:区内储层发育程度受控于走滑断裂的构造样式及应力特征,构造样式越复杂,应力作用越集中,则岩溶作用更强,相应储层发育更好(图11)。
马尾段是断裂端部应力发散的结果,多条拉张性质的雁列断层与分支断层成组发育,整体构造样式较复杂,中部短马尾分支断层间距小、下切浅,南部长雁列断层间距大、下切深。断层间距越小,单位面积溶蚀作用则越强,而下切越深越有利于溶蚀性流体的上侵,马尾段储层统计显示,整体储层发育较好,平均厚度19.45 m,储层类型多为裂缝型、孔洞型以及裂缝−孔洞型,未见洞穴型储层发育。
斜列段与叠覆段均为应力集中区,且区内构造样式复杂,斜列的主干断层以及连通主干断层的分支断层均可作为流体的运移通道,溶蚀区域面积增大且溶蚀作用强度大幅增强,以主干断层夹持区溶蚀效果最好。区内钻井揭示,区内斜列段与叠覆段储层发育最佳,储层厚度均较厚,各井平均厚度23.46 m,最厚储层38 m(跃满2−3X井),最薄储层14.7 m(跃满6井),储层类型以裂缝孔洞型为主,各井均有多类储层发育。
分支断层斜交段局部应力集中,密集程度不一,多条分支断层逆向发育于断层西侧,分支断层长度不一,与马尾段类似,长分支断层具有更长的流体运移通道,分支断层密集区单位面积溶蚀作用更强,储层统计显示长分支断层储层厚度异常厚,例如跃满3−5井,储层厚46.36 m,各类储层均发育,短分支断层上储层发育一般,且非密集分支断层上的跃满3−3井储层发育极差,整体认为储层发育一般。
线性段均无构造应力集中,且构造样式简单,断层仅作为流体的运移通道,岩溶作用对该段内碳酸盐岩改造作用较弱。线性段内储层发育较差,厚度较薄且储层类型单一。
5.2 断控高能相带对储层发育的控制
研究区一间房组整体为开阔台地相,加里东中期—晚奥陶纪早期(加里东中期Ⅰ幕),塔北发生了一次较大规模的海退,一间房组短暂暴露,准同生岩溶大面积发育(倪新锋等, 2009),中奥陶世末期,走滑断裂开始活动并控制着区内微地貌(Wu et al., 2021),断裂挤压段易形成正地貌,有利于高能礁滩体发育,该类礁滩体受准同生期岩溶作用及自身结构影响,具有更好的孔隙度、渗透率(Zeng et al., 2018; 高达等, 2022),也更易受埋藏岩溶作用溶蚀改造,从而形成有效储集体。
新三维地震资料上不同沉积相带具有不同的地震响应特征:开阔台地相地震反射时差横向变化稳定,成平行、亚平行结构,振幅较强、连续,能量稳定;台内滩地震反射时差增大,反射杂乱,具有下超、上隆的特征,振幅变弱(聂杞连等, 2015)。连井地震剖面显示,区内一间房组顶部发育不规则的高能相带(图12),主要覆盖了跃满601—跃满2−1断裂带北部D3斜列段与D4叠覆段,跃满704—跃满3−3断裂带中北部D6线性段与D7斜列段。对比高能相带叠合区与非叠合区发现,在断裂分段性控制储层发育的基础上,高能相带的叠加区储层发育更好,与高能相带叠加的D4叠覆段相较D2叠覆段储层厚度更厚,叠加高能相带的D3斜列段和D7斜列段储层厚度相近,且储层厚度均高于D5斜列段。
6. 结 论
(1)跃满区块奥陶系一间房组储层发育,储集岩以生屑灰岩、砂屑灰岩、颗粒灰岩、泥晶灰岩为主。根据储集空间组合特征储层可分为洞穴型储层、裂缝−孔洞型储层、裂缝型储层和孔洞型储层四类。各类储层集中发育于一间房组顶部,沿走滑断裂带状分布。
(2)跃满区块位于塔北南坡纯剪走滑区,发育一组北北西向与三组北北东向走滑断裂。区内断裂具有分段性,按平面构造样式可分为马尾段、斜列段、叠覆段、分支断层斜交段和线性段。断裂不同段内平面组合特征、剖面构造特征和应力特征均有区别,马尾段应力发散,构造样式复杂,斜列段与叠覆段应力集中、构造样式复杂,分支断层斜交段局部应力集中、构造样式单一,线性段无构造应力集中,构造样式最简单。
(3)走滑断裂分段性影响埋藏岩溶作用强度及规模,从而控制储层发育程度与分布情况。研究区内马尾段、斜列段和叠覆段储层发育最佳,分支断层斜交段储层发育受控于分支断层长度,整体发育一般,线性段储层发育较差。此外,在断裂分段性控制储层发育的基础上,高能相带叠加区储层更为发育。
致谢: 项目研究过程中,中国石油塔里木油田勘探开发研究院的张银涛高级工程师、康鹏飞工程师,以及西南石油大学地球科学与技术学院的赵星星、崔晓庆、宋玉婷等在前期资料收集、数据处理上提供了指导和帮助,审稿专家与编辑对稿件提出了宝贵的修改意见。在此一并致以诚挚谢意!
致谢: 感谢中国地质调查局成都地质调查中心王永华教授级高级工程师、张建龙教授级高级工程师、焦彦杰教授级高级工程师、张伟正高级工程师、李华正高级工程师、张志副研究员、梁维副研究员、曹华文副研究员、陈敏华高级工程师、李应栩副研究员和黄勇工程师,中国地质调查局应用地质调查中心黄勇研究员,成都理工大学杨武年教授、李佑国教授、何政伟教授,中国地质大学(武汉)刘文浩副教授、高顺宝副教授,中国地质大学(北京)张振杰副教授,以及多年来参加中国地质调查局青藏高原地质大调查项目的众多科技人员对本论文数据的支持和论文撰写的指导。 -
图 1 冈底斯成矿带地质简图(a据刘洪等, 2019a, b, 2020a; b据刘洪等, 2019c, 2020b)
GS—甘孜—松潘地块; JSS—金沙江缝合带; QT—羌塘地块;BNS—班公湖—怒江缝合带;LS—拉萨地块;YZS—印度河—雅鲁藏布江缝合带;HM—喜马拉雅地块;ABT—昂龙岗日—班戈—腾冲岩浆弧带;SSZ—狮泉河—纳木错蛇绿混杂岩带;CS—措勤—申扎岩浆弧带;LC—隆格尔—措麦断裂带;LG—隆格尔—工布江达复合岛弧带;LMF—洛巴堆—米拉山断裂带;LGX—拉达克—南冈底斯岩浆弧带
Figure 1. Mineral geological map of the Gangdise metallogenic belt (a, modified from Liu Hong et al., 2019a, b, 2020a; b, modified from Liu Hong et al., 2019c, 2020b)
GS-Ganzi-Songpan block; JSS-Jinshajiang suture zone; QT-Qiangtang block; BNS-Bangong-Nujiang suture zone; LS-Lhasa block; YZS-Indus-Yarlung Zangbo suture zone; HM-Himalayan Block; ABT-Anglonggangri-Bange Tengchong-magmatic arc zone; SSZ-Shiquanhe-Namtso suture zone; CS-Coqên-Xainza magmatic arc zone; LC-Lunggar-Comai fracture zone; LG-Lunggar-Gongbo'gyamda composite island arc zone; LMF-Lobadui-Milashan fracture zone; LGX-Ladakh-South Gangdise magmatic arc zone
图 4 冈底斯成矿带西段地质矿产图(据黄瀚霄等,2019修改)
1—新近纪花岗岩类;2—古近纪花岗岩类;3—白垩纪花岗岩类;4—侏罗纪花岗岩类;5—三叠纪花岗岩类;6—林子宗群火山岩;7—蛇绿岩;8—铜矿床(点);9—铜金矿床(点);10—铜钼矿床(点);11—金矿床(点);12—银金矿床(点);13—铁矿;14—铅锌矿床(点);15—构造边界;16—湖泊;17—研究区范围;构造单元代码同图 1
Figure 4. Mineral geological map of the western Gangdise metallogenic belt (modified from Huang Hanxiao et al., 2019)
1-Neogene granitoids; 2-Paleogene granitoids; 3-Cretaceous granitoids; 4-Jurassic granitoids; 5-Triassic granitoids; 6-Linzizong Group volcanic rocks; 7-Ophiolites; 8-Copper deposit (point); 9-Copper gold deposit (point); 10-Copper molybdenum deposit (point); 11-Gold deposit (point); 12-Silver gold deposit (point); 13-Iron deposit; 14-Lead zinc deposit (point); 15-Structural boundary; 16-Lake; 17-Scope of study area; The geotectonic elements code is the same as Fig. 1
图 5 冈底斯成矿带西段地质构造与成矿演化(据黄瀚霄等, 2019修改)
Figure 5. Summary of the geotectonic and metallogenic evolution of the western Gangdise metallogenic belt (modified from Huang Hanxiao et al., 2019)
图 7 冈底斯成矿带西段卫星重力小波分析细节图(据加州大学公开数据编制)
(a、b、c、d说明见正文;矿产图例同图 4)
Figure 7. The detail maps of satellite gravity wavelet analysis of the western Gangdise metallogenic (after the University of California public data)
(The description of Fig. 7 a, b, c, d is seen in the tex; The mineral legend is the same as Fig. 4)
图 9 冈底斯成矿带西段航磁△T化极小波分析细节图(据中国自然资源航空物探遥感中心公开数据编制)
(a、b、c、d说明见正文;矿产图例同图 4)
Figure 9. The detail maps of aeromagnetic △T pole wavelet analysis of the western Gangdise metallogenic belt (after the AGRS public data)
(The description of Fig. 9 a, b, c, d seen in the text; The mineral legend is the same as Fig. 4)
表 1 找矿预测分类结果混淆矩阵
Table 1 Confusion matrix of classification results of prospecting prediction
表 2 冈底斯西段地球化学元素相关系数矩阵
Table 2 The correlation coefficient matrix of geochemical elements in the western Gangdise metallgenic belt
表 3 冈底斯成矿带西段找矿预测基础变量
Table 3 Basic variables for prospecting prediction in the western Gangdise metallogenic belt
表 4 冈底斯成矿带西段预测模型结果评估表
Table 4 Evaluation table of prediction model results in the western Gangdise metallogenic belt
表 5 冈底斯西段与斑岩系统有关的铜多金属矿找矿远景区特征表
Table 5 Characteristics of prospecting areas for the copper polymetallic deposits related to porphyry system in the western Gangdise metallogenic belt
-
Andreoletti G, Lanata C M, Trupin L, Paranjpe I, Jain T S, Nititham J, Taylor K E, Combes A J, Maliskova L, Ye C J, Katz P, Dal E M, Yazdany J, Criswell L A, Sirota M. 2021. Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity-and disease-specific expression signatures[J]. Communications Biology, 488: 4838.
Asadi S, Roshan S E, Kattan M W. 2021. Random forest swarm optimization-based for heart diseases diagnosis[J]. Journal of biomedical informatics, 115(24): 103690.
Bonvalot S, Balmino G, Briais A, Kuhn M, Peyrefitte A, Vales N, Biancale R, Gabalda G, Reinquin F, Sarrailh M. 2012. World Gravity Map[M]. Commission for the Geological Map of the World. Eds. BGI-CGMW-CNES-IRD, Paris.
Cai Huihui, Zhu Wei, Li Muxuan, Liu Yuanyuan, Li Longbin, Liu Chang. 2019. Prediction method of tungsten-molybdenum prospecting target area based on deep learning[J]. Journal of Geo-Information Science, 21(6): 928-936.
Chen Jin, Mao Xiancheng, Liu Zhankun Deng Hao. 2020. Three-dimensional metallogenic prediction based on random forest classification algorithm for the Dayingezhuang gold deposit[J]. Geotectonica et Metallogenia, 44(2): 231-241 (in Chinese with English abstract).
Chen Xin, Zheng Youye, Gao Sunbao, Wu Song, Jiang Xiaojia, Jiang Junsheng, Cai Pengjie, Lin Cheng'gui. 2020. Ages and petrogenesis of the late Triassic andesitic rocks at the Luerma porphyry Cu deposit, western Gangdese, and implications for regional metallogeny[J]. Gondwana Research, 85: 103-123. doi: 10.1016/j.gr.2020.04.006
Cheng Qiuming. 2007. Singularity-generalized self-similarity-fractal spectrum (3S) models[J]. Earth Science——Journal of China University of Geosciences, 14(5): 1-10 (in Chinese with English abstract).
Cutler D R, Jr Edwards T C E., Beard K H, Hess K T. 2007. Random forests for classification in ecology[J]. Ecology, 88(11): 2783-2792. doi: 10.1890/07-0539.1
Dai Jingjing, Qu Xiaoming, Xin Hongbo, 2010. Extraction of alteration mineral information using ASTER remote sensing data in Duolong area, Tibet, China[J]. Geological Bulletin of China, 9(5): 752-759 (in Chinese with English abstract). doi: 10.3969/j.issn.1671-2552.2010.05.016
El B H, Rahouti M., El B M. 2021. Identification of SARS-CoV-2 origin: using Ngrams, Principal Component Analysis and Random Forest Algorithm[J]. Informatics in Medicine Unlocked, 24: 100577. doi: 10.1016/j.imu.2021.100577
Fang Kuangnan, Wu Jianbin, Zhu Jianping, Xie Bangchang. 2011. A review of technologies on random forests[J]. Statistics & Information Forum, 26(3): 32-38 (in Chinese With English abstract).
Fouedjio F. 2020. Exact conditioning of regression random forest for spatial prediction[J]. Artificial Intelligence in Geosciences, 1: 11-23. doi: 10.1016/j.aiig.2021.01.001
Gao Shunbao. 2015. Copper-iron Polymetal Metallogenic Regularity and Election of Targeet Areas in the Western of Gangdis Metallogenic Belt, Tibet[D]. Wuhan: China University of Geosciences (Wuhan), 1-110 (in Chinese with English abstract).
Geng Quanru, Li Wengchang, Wang Li, Zeng Xiangting, Peng Zhimin, Zhang Xiangfeng, Zhang Zhang, Cong Feng, Guan Junlei. 2021. Paleozoic tectonic framework and evolution of the central and western Tethys[J]. Sedimentary Geology and Tethyan Geology, 41(2): 297-315 (in Chinese with English abstract)
Han Shanchu, Jiang Yao, Pan Jiayong, Wan Hong, Huang Tianyu. 2021. Isotopic geochemical characteristics of Yuejingou copper deposit in Gangdise metallogenic belt, Tibet[J]. Journal of East China Institute of Technology (Natural Science Edition), 44(5): 423-432.
Hardeep S R, Naresh K, Prabha G. 2022. Machine learning-based modeling to predict inhibitors of acetylcholinesterase[J]. Molecular Diversity, 26(1): 331-340. doi: 10.1007/s11030-021-10223-5
Hou Zengqian, Cook N J. 2009. Metallogenesis of the Tibetan collisional orogen: A review and introduction to the special issue[J]. Ore Geology Reviews, 36: 2-24. doi: 10.1016/j.oregeorev.2009.05.001
Huang Faming, Ye Zhou, Yao Chi, Li Yuanyao, Yin Kunlong, Huang Jinsong, Jiang Qinghui. 2020. Uncertainties of landslide susceptibility prediction: Different attribute interval divisions of environmental factors and different data based models[J]. Earth Science, 45(12): 4535-4549 (in Chinese with English abstract).
Huang Hanxiao, Li Guangming, Liu Hong, Zhang Hongming, Zhang Linkui, Yu Huai, Jiao Yanjie, Liang Wei. 2018. An low sulfide epithermal gold-silver polymetallic deposit newly discovered in the western section of the Gangdise metallogenic belt[J]. Geology in China, 45(3): 628-629 (in Chinese with English abstract).
Huang Hanxiao, Li Guangming, Liu Hong, Zhang Linkui, Cao Huawen, Zhou Qing, Wang Xinxin, Yan Guoqiang. 2019. Zircon U-Pb, molybdenite Re-Os and quartz vein Rb-Sr geochronology of the Luobuzhen Au-Ag and Hongshan Cu deposits, Tibet, China: Implications for the oligocene-miocene porphyry-epithermal metallogenic system[J]. Minerals, 9(8): 476-491. doi: 10.3390/min9080476
Huang Hanxiao, Zhang Linkui, Liu Hong, Li Guangming, Huang Yong, Lan Shuangshuang, Lü Menghong. 2019. Major types, mineralization and potential prospecting areas in western section of the Gangdise metallogenic belt, Tibet[J]. Earth Science, 44(6): 1876-1887 (in Chinese With English abstract).
Huang Yong, Li Guangming, Ding Jun, Dai Jie, Yan Guoqiang, Dong Suiliang, Huang Hanxiao. 2017. Origin of the newly discovered Zhunuo porphyry Cu-Mo-Au deposit in the western part of the Gangdese porphyry copper belt in the southern Tibetan plateau, SW China[J]. Acta Geologica Sinica (English edition), 91(1): 109-134. doi: 10.1111/1755-6724.13066
Huang Yong, Ren Minghua, Liang Wei, Li Guangming, Heilbronn K., Dai Zuowen, Wang Yiyun, Zhang Li. 2020. Origin of the oligocene Tuolangla porphyry-skarn Cu-W-Mo deposit in Lhasa terrane, southern Tibet[J]. China Geology, 3: 369-384.
Huang Yonggao, Han Fei, LI Yingxu, Jia Xiaochuan, Yang Xuejun, Li Guangming, Yang Qingsong. 2020. The discovery of Early Jurassic volcanism in the Nanmulin Basin, Tibet: Constraints from zircon U-Pb age[J]. Geology in China, 47(4): 1266-1267(in Chinese with English abstract).
Lang Xinghai, Guo Wenbo, Wang Xuhui, Deng Yulin, Yang Zongyao, Xie Fuwei, Li Zhuang, Zhang Zhong, Jiang Kai. 2019. Petrogenesis and tectonic implications of the ore-bearing porphyries in the Xiongcun district: Constraints from the geochronology and geochemistry[J]. Acta Petrologica Sinica, 35(7): 2105-2123 (in Chinese with English abstract). doi: 10.18654/1000-0569/2019.07.10
Lang Xinhai, Deng Yulin, Wang Xuhui, Tang Juxing, Xie Fuwei, Yang Zongyao, Yin Qing, Jiang Kai. 2020. Reduced fluids in porphyry copper-gold systems reflect the occurrence of the wall-rock thermogenic process: An example from the No. 1 deposit in the Xiongcun district, Tibet, China[J]. Ore Geology Reviews, 118: 103-212.
Langroodi A K, Vahdatikhaki F, Doree A. 2021. Activity recognition of construction equipment using fractional random forest[J]. Automation in Construction, 122: 103465. doi: 10.1016/j.autcon.2020.103465
Leo B. 2001. Random forests[J]. Mach Learn, 45(1): 5-32. doi: 10.1023/A:1010933404324
Li Cangbai, Xiao Keyan, Li Nan, Song Xianglong, Zhang Shuai, Wang Kai, Chu Wenkai, Cao R. 2020. Comparative study of support vector machine, random forest and artificial neural Network machine learning algorithms ingeochemical anomaly information extraction[J]. Acta Geoscientia Sinica, 41(2): 309-319.
Li Guangming, Pan Guitang, Wang Gaoming, Huang Zhiming, Gao Dafa. 2004. Evaluation and prospecting value of mineral resources in Gangdise metallogenic belt, Tibet, China[J]. Journal of Chengdu University of Technology (Science & Technology Edition), 31(1): 22-27 (in Chinese with English abstract). doi: 10.3969/j.issn.1671-9727.2004.01.004
Li Guangming, Zhang Linkui, Zhang Zhi, Xiao Xiangbiao, Liang Wei, Hou Chunqiu. 2021. New exploration progresses, resource potentials and prospecting targets of strategic minerals in the southern Qinghai-Tibet Plateau[J]. Sedimentary Geology and Tethyan Geology, 41(2): 351-360.
Li Jinghui. 2008. Metallogenic systems and regularity of porphyry-type molybdenum deposit in Dabieshan mountain[J]. Journal of East China Institute of Technology (Natural Science Edition), 31(1): 25-30.
Lin Jinxiang, Qin Kezhang, Lin Guangming, Lin Jindeng, Xiao Bo, Jiang Huazhai, Han Fengjie, Huang Shufeng, Chen Lei, Zhao Junxing. 2001. Zircon U-Pb geochronology and garnet composition of the Qiangdui Cu-Mo deposit in the eastern section of Gangdese and their significances[J]. Geology and Prospecting, 47(1): 11-19 (in Chinese with English abstract).
Liu Hong, Huang Hanxiao, Li Guangming, Li Wenchang, Li Youguo, Ma Dongfang, Huang Yong, Zhou Qing, and Fu Jiangang. 2022a. Petrogenesis of the Early Cretaceous Xiabie Co I-type granite in southern Qiangtang, Tibet (Xizang), China: Evidences from whole-rock geochemistry, Rb-Sr, Sm-Nd, and Pb isotopes, and LA-ICP-MS zircon U-Pb ages and Lu-Hf isotopes[J]. Acta Geologica Sinica (English edition), 96(3): 919-937. doi: 10.1111/1755-6724.14777
Liu Hong, Huang Hanxiao, Li Guangming, Li Wenchang, Zhang Linkui, Lan Shuangshuang, Lü Menghong, Song Wenjie. 2022b. Subduction-related Late Triassic Luerma porphyry copper deposit, western Gangdese, Tibet, China: Evidence from geology, geochemistry, and geochronology[J]. Ore Geology Reviews, 154: 105253. doi: 10.1016/j.oregeorev.2022.105253.
Liu Hong, Huang Hanxiao, Li Guangming, Xiao Wanfang, Zhang Zhilin, Liu Bo, Ma Dongfang, Dong Lei, Ma Dong. 2015. Factor analysis in geochemical survey of the Shangxu gold deposit, northern Tibet[J]. Geology in China, 42(4): 1126-1136 (in Chinese with English abstract). doi: 10.3969/j.issn.1000-3657.2015.04.026
Liu Hong, Huang Hanxiao, Ouyangyuan, Zhang Jinghua, Zhang Tengjiao, Li Fu, Xiao Qiliang, Zeng Jian, Hou Qian, Wen Dengkui, Duan Shengyi. 2020a. Soil's geologic investigation in Daliangshan, Xichang, Sichuan[J]. Sedimentary Geology and Tethyan Geology, 40(1): 91-105 (in Chinese with English abstract).
Liu Hong, Huang Hanxiao, Zhang Linkui, Li Guangming, Lü Menghong, Yan Guoqiang, Huang Yong, Lan Shuangshuang, Xie Hui. 2019b. Origin and evolution of ore-forming fluids in Luerma porphyry copper deposit from the western Gangdise[J]. Earth Science, 44(6): 1935-1956 (in Chinese With English abstract).
Liu Hong, Huang Hanxiao, Li Guangming, Zhang Linkui, Ouyang Yuan, Xiang Anping., Huang Yong, Lü Menghong, Lan Shuangshuang. 2021a. Luerma, a newly discovered Late Triassic porphyry copper-gold ore spot in the western Gangdise metallogenic belt, Tibet[J]. Sedimentary Geology and Tethyan Geology, 40(6): 569-581 (in Chinese with English abstract).
Liu Hong, Li Guangming, Huang Hanxiao, Zhang Linkui, Lü Menghong, Lan Shuangshuang, Xiehui. 2019a. The discovery of the Late Triassic porphyry type Cu deposit from Gangdise metallogenic belt, Tibet[J]. Geology in China, 46(5): 1238-1240 (in Chinese with English abstract).
Liu Hong, Li Guangming, Li Wenchang, Huang Hanxiao, Li, Youguo, Ouyang, Yuan, Zhang, Xiangfei, Zhou Qing. 2022. Petrogenesis and tectonic setting of the Late Early Cretaceous Kong Co A-type granite in the northern margin of Central Lhasa subterrane, Tibet[J]. Acta Petrologica Sinica, 38 (1): 230-252 (in Chinese with English abstract). doi: 10.18654/1000-0569/2022.01.15
Liu Hong, Li Guangming, Li Wenchang, Zhang Jinghua, Huang Hanxiao, Li Youguo, Zhang Zhilin, Zhang Tengjiao. 2021b. Epithermal mineralization at the Budongla gold deposit, in Zhongba, Tibet: Evidences from Fluid Inclusions and H-O Isotopes[J]. Mineral Deposits, 40(2): 311-328 (in Chinese With English abstract).
Liu Hong, Li Guangming, Zhang Zhilin, Huang Hanxiao, Xiao Wanfeng. 2014b. Geochemical analysis of rock debris in Muru Area, Gerze County, Tibet[J]. Metal Mine, 43(11): 105-108 (in Chinese with English abstract).
Liu Hong, Li Youguo, Li Wenchang, Li Guangming, Ma Dongfang, Ouyang Yuan, Huang Hanxiao, Zhang Zhilin, Li Tong, Wu Junyi, 2022c. Petrogenesis of the late Cretaceous Budongla Mg-rich monzodiorite pluton in the central Lhasa subterrane, Tibet, China: Wholerock geochemistry, zircon U-Pb dating, and zircon Lu-Hf isotopes[J]. Frontiers in Earth Science, 10: 927695. doi: 10.3389/feart.2022.927695
Liu Hong, Lü Xinbiao, Li Chuncheng, Liu Ge, Shang Shichao, Wang Lin, Zhang Wei, Mao Rongwei. 2013. Metallogenic conditions and ore-searching prospect at depth of the Jincheng gold ore deposit in Luoshan county, Henan province[J]. Geology and Prospecting, 49(2): 265-273 (in Chinese with English abstract).
Liu Hong, Lü Xinbiao, Yuan Qian, Ke Changshu, Zhu Qiaoqiao, Liu Xiao, Wang Yuqi, Zhang Shanming. 2014a. A study on geology and prospecting potential of Louziwan district of gaoliangdian Fe-Cu deposit, Xinyang area, Henan province, China[J]. Acta Mineralogica Sinica, 34(3): 337-342 (in Chinese with English abstract).
Liu Hong, Xia Xiangbiao, Huang Hanxiao, Zhang Linkui, Lan Shuangshuang, Lü Menghong, Ai Jinbiao, Xie Hui. 2019c. Geochemical statistics analysis of stream sediment and prospecting potential of Xuexiumaer area in western Gangdese metallogenic belt, Tibet[J]. Journal of Guilin University of Technology, 39(5): 847-855 (in Chinese with English abstract).
Liu Hong, Zhang Hui, Li Guangming, Huang Hanxiao, Xiao Wanfeng, You Qin, Ma Dongfang, Zhang Hai, Zhang Hong. 2016. Petrogenesis of the Early Cretaceous Qingcaoshan strongly peraluminous S-type granitic pluton, southern Qiangtang, northern Tibet: Constraints from whole-rock geochemistry and zircon U-Pb geochronology[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 52(5): 848-860 (in Chinese with English abstract).
Liu Hong, Zhang Linkui, Huang Hanxiao, Li Guangmin, Yu Huai, Huang Yong, Liang Wei, Yan Guoqiang, Zhang Hongming, Chen Xiaoping. 2020c. Evolution of ore-forming fluids in the Luobuzhen epithermal gold-silver deposit in western Gangdise: fluid inclusion and H-O isotope evidence[J]. Earth Science Frontiers, 27(4): 49-65 (in Chinese with English abstract).
Liu Hong, Zhang Linkui, Huang Hanxiao, Li Guangming, Ouyang Yuan, Lü Menghong, Liu Han, Lan Shuangshuang, Yan Guoqiang, 2019d. Petrogenesis of Late Triassic Luerma monzodiorite in western Gangdise, Tibet, China[J]. Earth Science, 44(7): 2339-2352 (in Chinese with English abstract).
Liu Weidong, Tang Zhipeng, Xiao Yan, Han Mengyao, Jiang Wanbei. 2019. Identifying the key factors influencing Chinese carbon intensity using machine learning, the random forest algorithm, and evolutionary analysis[J]. Acta Geographica Sinica, 74(12): 2592-2603 (in Chinese with English abstract). doi: 10.11821/dlxb201912012
Luciano A C D S, Picoli M C A, Duft D G, Rocha J V, Leal M R. L V, Le M G. 2021. Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm[J]. Computers and Electronics in Agriculture, 184: 106063. doi: 10.1016/j.compag.2021.106063
Makungwe M, Chabala L M, Chishala B H, Lark R M. 2021. Performance of linear mixed models and random forests for spatial prediction of soil pH[J]. Geoderma, 379(4): 115079.
Mao J W, Pirajno F, Lehmann B, Lehman B, Luo M C, Berzina A. 2014. Distribution of porphyry deposits in the eurasian continent and their corresponding tectonic settings[J]. Journal of Asian Earth Sciences, 79(2): 576-584.
Milanović S, Marković N, Pamučar D, Gigović L, Kostić P, Milanović S D. 2020. Forest fire probability mapping in eastern Serbia: Logistic Regression versus random forest method[J]. Forests, 12(1): 1-15. doi: 10.3390/f12010001
Mo Xuanxue, Niu Yaolin, Dong Guochen, Zhao Zhidan, Hou Zengqian, Zhou Su, Ke Shan. 2008. Contribution of syncollisional felsic magmatism to continental crust growth: A case study of the Paleogene Linzizong volcanic succession in southern Tibet[J]. Chemical Geology, 250(1): 49-67.
Mpanya D, Celik T, Klug E, Ntsinjana H. 2021. Predicting mortality and hospitalization in heart failure using machine learning: A systematic literature review[J]. IJC Heart & Vasculature, 34: 100773.
Naeini E Z, Prindle K. 2018. Machine learning and learning from machines[J]. The Leading Edge, 37(12): 886-893. doi: 10.1190/tle37120886.1
Ni Pei, Chui Zhe, Pan Junyi. 2020. An integrated investigation of ore-forming fluid evolution in porphyry and epithermal deposits and their implication on exploration[J]. Earth Science Frontiers, 27(2): 60-78 (in Chinese with English abstract).
Ouyang Yuan, Liu Hong, Huang Hanxiao, Li Guangming, Yang Wunian, Xiao Wanfeng, Zhang Zhilin, Ma Chengyi, Ma Buying. 2016. Study on geochemical multivariate statistics analysis and prospecting potential of Shangxu-Daze area in the northern Tibet[J]. Acta Mineralogica Sinica, 36(4): 586-594 (in Chinese with English abstract).
Ouyang Yuan, Yang Wunian, Huang, Huanxiao, Liu Hong, Zhang Jianlong, Zhang Jjinhua. 2017. Metallogenic dynamics background of Ga'erqiong Cu-Au deposit in Tibet, China[J]. Earth Sciences Research Journal, 21(2): 51-65.
Ouyang Yuan. 2020. Metallogenic Regularity and Metallogenic Prediction of Porphyry Copper Deposits in the Western of Gangdise Metallogenic Belt, Tibet[D]. Chengdu: Chengdu University of Technology, 1-110 (in Chinese with English abstract).
Pan Guitang, Mo Xuanxue, Hou Zengqian, Zhu Dicheng, Wang Liquan, Li Guangming, Zhao Zhidan, Geng Quanru, Liao Zhongli. 2006. Spatial-temporal framework of the Gangdese orogenic belt and its evolution[J]. Acta Petrologica Sinica, 22(3): 521-533 (in Chinese with English abstract).
Pan Guitang, Wang Liquan, Li Rongshe, Li Rongshe, Yuan Shihua, Ji Wenhua, Yin Fuguang, Zhang Wanping, Wang Baodi. 2012. Tectonic evolution of the Qinghai-Tibet plateau[J]. Journal of Asian Earth Sciences, 53: 3-14. doi: 10.1016/j.jseaes.2011.12.018
Pan Guitang, Wang Liquan, Geng Quanru, Yin Fuguang, Wang Baodi, Wang Dongbing, Peng Zhimin, Ren Fei. 2020. Space-time structure of the Bangonghu-Shuanghu-Nujiang-Changning-Menglian Mega-suture zone: A discussion on geology and evolution of the Tethys Ocean[J]. Sedimentary Geology and Tethyan Geology, 40(3): 1-19 (in Chinese with English abstract)
Pan Guitang, Wang Liquan, Li Xingzhen, Wang Jiemin, Xu Qiang. 2001. The tectonic framework and spatial allocation of the archipelagic arc-basin systems on the Qinghai-Xizang Plateau[J]. Sedimentary Geology and Tethyan Geology, 21(3): 1-26 (in Chinese with English abstract) doi: 10.3969/j.issn.1009-3850.2001.03.001
Panagiotis G. Asteris, Mohammadreza Koopialipoor, Danial J. Armaghani, Evgenios A. Kotsonis, Paulo B. Lourenço. 2021. Prediction of cement-based mortars compressive strength using machine learning techniques[J]. Neural Computing and Applications, 33: 13089-13121. doi: 10.1007/s00521-021-06004-8
Prasad A M, Iverson L R, Liaw A. 2006. Newer classification and regression tree techniques: Bagging and random forests for ecological prediction[J]. Ecosystems, 9(2): 181-199. doi: 10.1007/s10021-005-0054-1
Qin Yaozu, Wu Weicheng, Xie Lifeng, Ou Penghui, Huang Xiaolan. 2021. Applicayion of machine learning based mineral prospectivity mapping in the Yuexi antimony orefield, Hunan Province[J]. Journal of East China University of Technology (Natual Science), 44(1): 28-40 (in Chinese with English abstract).
Sillitoe R H. 2010. Porphyry copper systems[J]. Economic Geology, 105: 3-41. doi: 10.2113/gsecongeo.105.1.3
Song S H. 2021. Random forest approach in modeling the flow stress of 304 stainless steel during deformation at 700℃-900℃[J]. Materials, 14(7): 1812. doi: 10.3390/ma14071812
Song Shufang, He Ruysng. 2021. Importance measure index system based on random forest[J]. Journal of National University of Defense Technology, 43(2): 25-32(in Chinese with English abstract).
Song Yang, Tang Juxing, Qu Xiaoming, Wang Denghong, Xin Hongbo, Yang Chao, Lin Bin, Fan Shufang. 2014. Progress in the study of mineralization in the Bangongco-Nujiang metallogenic belt and some new recognition[J]. Advances in Earth Science, 29(7): 795-809 (in Chinese with English abstract).
Tang Juxing, Duo Ji, Liu Hongfei, Lang Xinghai, Zhang Jinshu, Zheng Wenbao, Ying Lijuan. 2012. Minerogenetic series of ore deposits in the east part of the Gangdise metallogenic belt[J]. Acta Geoscientia Sinica, 33(4): 393-410 (in Chinese with English abstract). doi: 10.3975/cagsb.2012.04.02
Tang Juxing, Yang Huanhuan, Song Yang, Wang Liqiang, Liu Zhibo, Li Baolong, Lin Bin, Peng Bo, Wang Genhou, Zeng Qinggao, Wang Qin, Chen Wei, Wang Nan, Li Zhijun, Li Yubin, Li Yanbo, Li Haifeng, Lei Chuanyang. 2021. The copper polymetallic deposits and resource potential in the Tibet Plateau[J]. China Geology, 4: 1-16.
Tang Juxing, Zhang Li, Li Zhijun, Chen Jianping, Huang Wei, Wang Qian. 2006. Porphyry copper deposit controlled by structural nose trap: Yulong porphyry copper deposit in eastern Tibet[J]. Mineral Deposits, 25(6): 652-662. doi: 10.3969/j.issn.0258-7106.2006.06.002
Tang Yuan, Liu Yuping, Wang Peng, Tang Wenqing, Qin Yadong, Gong Xiaodong, Wang Dongbing, Wang Baodi. 2021. A new understanding of Demala Group complex in Chayu area, southeastern Qinghai-Tibet Plateau: Evidence from zircon U-Pb and mica 40Ar/39Ar dating[J]. China Geology, 4: 77-94.
Wan C H, Lee L H, Rajkumar R, Isa D. 2012. A hybrid text classification approach with low dependency on parameter by integrating K-nearest neighbor and support vector machine[J]. Expert Systems with Applications, 39(15): 11880-11888. doi: 10.1016/j.eswa.2012.02.068
Wang Liquan, Wang Baodi, Li Guangming, Wang Dongbing, Peng Zhimin. 2021. Major progresses of geological survey and research in East Tethys: An overview[J]. Sedimentary Geology and Tethyan Geology, 41(2): 283-296 (in Chinese with English abstract).
Wu Huoxing, Fu Bin, Gao Ren, Fan Tao, Zha Zhiqiang, Tong Jizhong, Chen Tiandi. 2020. Characteristics analysis and prospecting potential prediction of newly discovered ore bodies in the Jiujiang Chengmenshan copper deposit[J]. Journal of East China Institute of Technology (Natural Science Edition), 43(2): 115-120.
Xiang Jie, Chen Jianping, Xiao Keyan, Li Shi, Zhang Zhiping, Zhang Ye. 2019. 3D metallogenic prediction based on machine learning: A case study of the Lala copper deposit in Sichuan Province[J]. Geological Bulletin of China, 38(12): 2010-2021. doi: 10.12097/j.issn.1671-2552.2019.12.009
Xiao Keyan, Lou Debo, Sun Li, Li Jingchao, Ye Tianzhu. 2013. Some progresses of mineral prediction theory and method in important mineral resource potential assessment of China[J]. Journal of Jilin University (Earth Science Edition), 43(3): 1053-1082.
Xu Zhiqin, Dilek Y, Cao Hui, Yang Jingsui, Robinson Paul, Ma Changqian, Li Huaqi, Jolivet Marc, Roger Franoise, Chen Xijie. 2015. Paleo-Tethyan evolution of Tibet as recorded in the East Cimmerides and West Cathaysides[J]. Journal of Asian Earth Sciences, 105: 320-337. doi: 10.1016/j.jseaes.2015.01.021
Xu Zhiqin, Yang Jinsui, Li Wenchang, Li Huaqi, Cai Zhihui, Yan Zhen, Ma Changqian. 2013. Paleo-tethys system and accretionary orogen in the Tibet plateau[J]. Acta Petrologica Sinica, 29(6): 1847-1860 (in Chinese with English abstract).
Yang Jinsui, Xu Zhiqing, Li Tianfu, Li Huaqi, Li Zhaoli, Ren Yufeng, Xu Xiangzheng, Chen Songyong. 2007. Oceanic subduction-type eclogite in the Lhasa block, Tibet, China: Remains of the paleo-tethys ocean basin?[J]. Geological Bulletin of China, 26(10): 1277-1287 (in Chinese with English abstract). doi: 10.3969/j.issn.1671-2552.2007.10.006
Yang Zhiming, Hou Zengqian, Chang Zhaoshan, Li Qiuyun, Liu Yunfei, Qu Huanchun, Sun Maoyu, Xu Bo. 2016. Cospatial Eocene and Miocene granitoids from the Jiru Cu deposit in Tibet: Petrogenesis and implications for the formation of collisional and postcollisional porphyry Cu systems in continental collision zones[J]. Lithos, 245(3): 243-257.
Ye Tianzhu. 2013. Theoretical framework of methodology of deposit modeling and integrated geological information for mineral resource potential assessment[J]. Journal of Jilin University (Earth Science Edition), 43(4): 1053-1072.
Zadeh M H, Tangestani M H, Roldan F V, Yusta I. 2014. Spectral characteristics of minerals in alteration zones associated with porphyry copper deposits in the middle part of Kerman copper belt, SE Iran[J]. Ore Geology Reviews, 62(6): 191-198.
Zeng Yuanchuan, Chen Jianlin, Xu Jifeng, Lei Ming, Xiong Qiuwei. 2017. Origin of Miocene Cu-bearing porphyries in the Zhunuo region of the southern Lhasa subterrane: Constraints from geochronology and geochemistry[J]. Gondwana Research, 41: 51-64. doi: 10.1016/j.gr.2015.06.011
Zhang Shihong, Xiao Keyan. 2020. Random forest-based mineralization prediction of the Lala-type cu deposit in the Huili area, Sichuan Province[J]. Geology and Exploration, 56(2): 239-252 (in Chinese with English abstract).
Zhang Shizhen, Qin Yadong, Li Yong, Li Fengqi, Gong Xiaodong. 2021. U-Pb dating for detrital zircons from the Jiejunazhuo Formation in Xuru Co area and its geological significances[J]. Sedimentary Geology and Tethyan Geology, 41(1): 24-32.
Zhang Ye, Li Mingchao, Han Shuai, Ren Qiubing, Zhu Yueqin. 2020. Machine learning methods application in gold mineralization prediction based on gold unit data[J]. Geotectonica et Metallogenia, 44(2): 183-191.
Zhang Yujun, Zeng Chaoming, Chan Hui. 2003. The Methods for Extraction of alteration anomalies from the ETM+(TM) data and their application: Method selection and technological flow chart[J]. Remote Sensing for Land & Resources, 2: 44-50 (in Chinese with English abstract).
Zhang Zhenjie, Cheng Qiuming, Yang Jie, Wu Guopeng, Ge Yunzhao. 2021. Machine learning for mineral prospectivity: A case study of iron polymetallic mineral prospectivity in Southwestern Fujian[J]. Earth Science Frontiers 28(3): 281-215 (in Chinese with English abstract).
Zhao Jinxiang, Qin Kezhang, Li Guangming, Li Jinxiang, Xiao Bo, Chen Lei, Yang Yueheng, Li Chao, Liu Yongsheng. 2014. Collision-related genesis of the sharang porphyry molybdenum deposit, tibet: Evidence from zircon U-Pb ages, Re-Os ages and Lu-Hf isotopes[J]. Ore Geology Reviews, 56: 312-326. doi: 10.1016/j.oregeorev.2013.06.005
Zhao Pengda. 2007. Quantitative mineral prediction and deep mineral exploration[J]. Earth Science Frontiers, 14(5): 1-10 (in Chinese With English Abstract). doi: 10.3321/j.issn:1005-2321.2007.05.001
Zhao Xiliang, Gong Chen, He Jun, Peng Jianhua, Huang Shaochun, Yang Zhilong. 2013. Discovery of porphyry copper deposit and its significance of Dajiacuo in Cuoqin county, Tibet[J]. Journal of East China Institute of Technology (Natural Science Edition), 36(6): 13-20 (in Chinese with English abstract)
Zheng Youye, Sun Xiang, Gao Sunbao, Gao Shunbao, Wu Song, Xu Jing, Jiang Junsheng, Chen Xin, Zhao Zhongying, Liu Yan. 2015. Metallogenesis and the minerogenetic series in the Gangdese polymetallic copper belt[J]. Journal of Asian Earth Sciences, 103: 23-39. doi: 10.1016/j.jseaes.2014.11.036
Zhou Qing, Jiang Yaohui, Zhao Peng, Liao Shiyong, Jin Guodong, Liu Zheng, Jia Ruya. 2012. SHRIMP U-Pb dating on hydrothermal zircons: Evidence for an Early Cretaceous epithermal event in the Middle Jurassic Dexing porphyry copper deposit, southeast China[J]. Economic Geology, 107: 1507-1514. doi: 10.2113/econgeo.107.7.1507
Zhu Dicheng, Pan Guitang, Chung Shenlin, Liao Zhongli, Li Guangming. 2008. SHRIMP zircon age and geochemical constraints on the origin of lower Jurassic volcanic rocks from the Yeba fromation, southern Gangdese, south Tibet[J]. International Geology Review, 50(5): 442-471. doi: 10.2747/0020-6814.50.5.442
Zhu Yusheng, Xiao Keyan, Ma Yubo, Ding Jianhua. 2013. Review and status of mineralization belt study in China[J]. Journal of Geology, 37(3): 349-357. doi: 10.3969/j.issn.1674-3636.2013.03.349
蔡惠慧, 朱伟, 李孜轩, 刘园园, 李龙斌, 刘畅. 2019. 基于深度学习的钨钼找矿靶区预测方法研究[J]. 地球信息科学学报, 21(6): 928-936. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXX201906014.htm 陈进, 毛先成, 刘占坤. 邓浩. 2020. 基于随机森林算法的大尹格庄金矿床三维成矿预测. 大地构造与成矿学[J]. 44(2): 231-241. doi: 10.16539/j.ddgzyckx.2020.02.007 成秋明. 2006. 非线性成矿预测理论: 多重分形奇异性-广义自相似性-分形谱系模型与方法[J]. 地球科学, 31(3): 337-348. doi: 10.3321/j.issn:1000-2383.2006.03.009 代晶晶, 曲晓明, 辛洪波. 2010. 基于ASTER遥感数据的西藏多龙矿集区示矿信息的提取[J]. 地质通报, 9(5): 752-759. doi: 10.3969/j.issn.1671-2552.2010.05.016 方匡南, 吴见彬, 朱建平, 谢邦昌. 2011. 随机森林方法研究综述[J]. 统计与信息论坛, 26(3): 32-38. doi: 10.3969/j.issn.1007-3116.2011.03.006 高顺宝. 2015. 西藏冈底斯西段铜铁多金属成矿作用与找矿方向[D]. 武汉: 中国地质大学(武汉), 1-120. 耿全如, 李文昌, 王立全, 曾祥婷, 彭智敏, 张向飞, 张璋, 丛峰, 关俊雷. 2021. 特提斯中西段古生代洋陆格局与构造演化[J]. 沉积与特提斯地质, 41(2): 297-315. doi: 10.19826/j.cnki.1009-3850.2021.02012 韩善楚, 姜垚, 潘家永, 万弘, 黄天宇. 2021. 西藏冈底斯成矿带跃进沟铜矿床同位素地球化学特征研究[J]. 东华理工大学学报(自然科学版), 44(5): 423-432. doi: 10.3969/j.issn.1674-3504.2021.05.003 黄发明, 叶舟, 姚池, 李远耀, 殷坤龙, 黄劲松, 姜清辉. 2020. 滑坡易发性预测不确定性: 环境因子不同属性区间划分和不同数据驱动模型的影响[J]. 地球科学, 45(12): 4535-4549. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202012017.htm 黄瀚霄, 李光明, 刘洪, 张洪铭, 张林奎, 余槐, 焦彦杰, 陈小平, 梁维. 2020. 冈底斯西段罗布真浅成低温热液型银金矿的成矿流体演化: 来自流体包裹体、H-O同位素的证据[J]. 地学前缘, 27(4): 50-65. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY202004005.htm 黄瀚霄, 李光明, 刘洪, 张洪铭, 张林奎, 余槐, 焦彦杰, 梁维. 2018. 冈底斯成矿带西段首次发现低硫化型浅成低温热液型矿床——罗布真金银多金属矿床[J]. 中国地质, 45(3): 628-629. http://geochina.cgs.gov.cn/geochina/article/abstract/20180315?st=search 黄瀚霄, 张林奎, 刘洪, 李光明, 黄勇, 兰双双, 吕梦鸿. 2019. 西藏冈底斯成矿带西段矿床类型、成矿作用和找矿方向[J]. 地球科学, 44(6): 1876-1887. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201906010.htm 黄永高, 韩飞, 李应栩, 贾小川, 杨学俊, 李光明, 杨青松. 2020. 西藏南木林盆地发现早侏罗世火山作用——来自锆石U-Pb年龄的证据[J]. 中国地质, 47(4): 1266-1267. http://geochina.cgs.gov.cn/geochina/article/abstract/20200425?st=search 郎兴海, 郭文铂, 王旭辉, 邓煜霖, 杨宗耀, 谢富伟, 李壮, 张忠, 姜楷. 2019. 西藏雄村矿集区含矿斑岩成因及构造意义: 来自年代学及地球化学的约束[J]. 岩石学报, 35(7): 2105-2123. 李苍柏, 肖克炎, 李楠, 宋相龙, 张帅, 王凯, 楚文楷, 曹瑞. 2020. 支持向量机、随机森林和人工神经网络机器学习算法在地球化学异常信息提取中的对比研究[J]. 地球学报, 41(2): 309-319. 李光明, 潘桂棠, 王高明, 黄志英, 高大发. 2004. 西藏冈底斯成矿带矿产资源远景评价与展望[J]. 成都理工大学学报(自然科学版), 31(1): 22-27. doi: 10.3969/j.issn.1671-9727.2004.01.004 李光明, 张林奎, 张志, 夏祥标, 梁维, 侯春秋. 2021. 青藏高原南部的主要战略性矿产: 勘查进展、资源潜力与找矿方向[J]. 沉积与特提斯地质, 41(2): 351-360. https://www.cnki.com.cn/Article/CJFDTOTAL-TTSD202102019.htm 李金祥, 秦克章, 李光明, 林金灯, 肖波, 江化寨, 韩逢杰, 黄树峰, 陈雷, 赵俊兴. 2001. 冈底斯东段羌堆铜钼矿床年代学、矽卡岩石榴石成分及其意义[J]. 地质与勘探, 47(1): 11-19. 李靖辉. 2008. 大别山(北麓)斑岩型钼矿床成矿系列及成矿规律[J]. 东华理工大学学报(自然科学版), 31(1): 25-30. doi: 10.3969/j.issn.1674-3504.2008.01.005 刘洪, 黄瀚霄, 李光明, 肖万峰, 张智林, 刘波, 马东方, 董磊, 马东. 2015. 因子分析在藏北商旭金矿床地球化学勘查中的应用[J]. 中国地质, 42(4): 1126-1136. doi: 10.3969/j.issn.1000-3657.2015.04.026 刘洪, 黄瀚霄, 欧阳渊, 张景华, 张腾蛟, 李富, 肖启亮, 曾建, 侯谦, 文登奎, 段声义. 2020a. 基于地质建造的土壤地质调查及应用前景分析-以大凉山区西昌市为例[J]. 沉积与特提斯地质, 40(1): 91-105. https://www.cnki.com.cn/Article/CJFDTOTAL-TTSD202001011.htm 刘洪, 黄瀚霄, 张林奎, 李光明, 欧阳渊, 黄勇, 吕梦鸿, 兰双双. 2021a. 冈底斯西段打加错地区鲁尔玛晚三叠世斑岩型铜(金)矿点的地质特征及发现意义[J]. 沉积与特提斯地质, 41(6): 569-581. 刘洪, 李光明, 黄瀚霄, 张林奎, 吕梦鸿, 兰双双, 解惠. 2019a. 西藏冈底斯成矿带发现晚三叠世斑岩型铜矿[J]. 中国地质, 46(5): 1238-1240. http://geochina.cgs.gov.cn/geochina/article/abstract/20190524?st=search 刘洪, 李光明, 李文昌, 黄瀚霄, 李佑国, 欧阳渊, 张向飞, 周清. 2022. 西藏中拉萨地块北部早白垩世晚期控错A型花岗岩的成因及构造环境研究[J]. 岩石学报, 38(1): 230-252. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXB202201015.htm 刘洪, 李光明, 李文昌, 张景华, 李佑国, 张智林, 黄瀚霄, 欧阳渊, 张腾蛟. 2021b. 西藏仲巴县布东拉金矿床的浅成低温热液成矿作用: 来自流体包裹体和H-O同位素的证据[J]. 矿床地质, 40(2): 311-328. 刘洪, 李光明, 张智林, 黄瀚霄, 肖万峰. 2014b. 西藏改则县木如地区岩屑地球化学分析[J]. 金属矿山, 43(11): 105-108. https://www.cnki.com.cn/Article/CJFDTOTAL-JSKS201411025.htm 刘洪, 吕新彪, 李春诚, 刘阁, 尚世超, 王林, 张伟, 毛荣威. 2013. 河南罗山金城金矿床成矿条件与深部找矿前景分析[J]. 地质与勘探, 49(2): 265-273. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT201302011.htm 刘洪, 吕新彪, 袁迁, 柯长书, 朱乔乔, 柳潇, 王玉奇, 张善明. 2014a. 河南信阳高梁店铁铜矿床娄子湾矿段地质特征与找矿方向[J]. 矿物学报, 34(3): 337-342. 刘洪, 夏祥标, 黄瀚霄, 张林奎, 兰双双, 吕梦鸿, 艾金彪, 解惠. 2019b. 西藏冈底斯成矿带西段学修玛尔幅水系沉积物地球化学统计分析与找矿前景[J]. 桂林理工大学学报(自然科学版), 39(4): 847-855. 刘洪, 张晖, 李光明, 黄瀚霄, 肖万峰, 游钦, 马东方, 张海. 2016. 藏北羌塘南缘早白垩世青草山强过铝质S型花岗岩的成因: 地球化学和LA-ICP-MS锆石U-Pb年代学的约束[J]. 北京大学学报(自然科学版), 52(5): 848-860. 刘洪, 张林奎, 黄瀚霄李光明, 余槐, 黄勇, 梁维, 闫国强, 张洪铭, 陈小平. 2020b. 冈底斯西段罗布真浅成低温热液型银金矿的成矿流体演化: 来自流体包裹体、H-O同位素的证据[J]. 地学前缘, 27(4): 50-65. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY202004005.htm 刘洪, 张林奎, 黄瀚霄, 李光明, 吕梦鸿, 闫国强, 黄勇, 兰双双, 解惠. 2019c. 冈底斯西段鲁尔玛斑岩型铜(金)矿成矿流体性质及演化[J]. 地球科学, 44(6): 1935-1956. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201906014.htm 刘洪, 张林奎, 黄瀚霄, 李光明, 欧阳渊, 吕梦鸿, 刘函, 兰双双, 闫国强. 2019d. 西藏冈底斯西段鲁尔玛晚三叠世二长闪长岩的成因[J]. 地球科学, 44(7): 2339-2352. 刘卫东, 唐志鹏, 夏炎, 韩梦瑶, 姜宛贝. 2019. 中国碳强度关键影响因子的机器学习识别及其演进[J]. 地理学报, 74(12): 2592-2603. https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201912013.htm 倪培, 迟哲, 潘君屹. 2020. 斑岩型和浅成低温热液型矿床成矿流体与找矿预测研究: 以华南若干典型矿床为例[J]. 地学前缘, 27(2): 60-78. 欧阳渊, 刘洪, 黄瀚霄, 李光明, 杨武年, 肖万峰, 张智林, 马成义, 马步英. 2016. 藏北商旭-达则地区水系沉积物地球化学多元统计分析与找矿方向[J]. 矿物学报, 36(4): 586-594. https://www.cnki.com.cn/Article/CJFDTOTAL-KWXB201604019.htm 欧阳渊. 2020. 西藏冈底斯成矿带西段斑岩型铜矿成矿规律与成矿预测研究[D]. 成都: 成都理工大学, 1-110. 潘桂棠, 莫宣学, 侯增谦, 朱弟成, 王立全, 李光明, 赵志丹, 耿全如, 廖忠礼. 2006. 冈底斯造山带的时空结构及演化[J]. 岩石学报, 22(3): 521-533. 潘桂棠, 王立全, 耿全如, 尹福光, 王保弟, 王冬兵, 彭智敏, 任飞. 2020. 班公湖-双湖-怒江-昌宁-孟连对接带时空结构——特提斯大洋地质及演化问题[J]. 沉积与特提斯地质, 40(3): 1-19. 潘桂棠, 王立全, 李兴振, 王洁民, 徐强. 2001. 青藏高原区域构造格局及其多岛弧盆系的空间配置[J]. 沉积与特提斯地质, 21(3): 1-26. 秦耀祖, 吴伟成, 谢丽凤, 欧鹏辉, 黄小岚. 2021. 基于机器学习的找矿预测模型在湖南岳溪锑矿田的应用[J]. 东华理工大学学报(自然科学版), 44(1): 28-40. https://www.cnki.com.cn/Article/CJFDTOTAL-HDDZ202101004.htm 宋述芳, 何入洋. 2021. 基于随机森林的重要性测度指标体系[J]. 国防科技大学学报, 43(2): 25-32. 宋扬, 唐菊兴, 曲晓明, 王登红, 辛洪波, 杨超, 林彬, 范淑芳. 2014. 西藏班公湖-怒江成矿带研究进展及一些新认识[J]. 地球科学进展, 29(7): 795-809. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201407006.htm 唐菊兴, 多吉, 刘鸿飞, 郎兴海张金树郑文宝应立娟. 2012. 冈底斯成矿带东段矿床成矿系列及找矿突破的关键问题研究[J]. 地球学报, 33(4): 393-410. 唐菊兴, 张丽, 李志军, 陈建平, 黄炜, 王强. 2006. 西藏玉龙铜矿床——鼻状构造圈闭控制的特大型矿床[J]. 矿床地质, 25(6): 652-662. https://www.cnki.com.cn/Article/CJFDTOTAL-KCDZ200606001.htm 王立全, 王保弟, 李光明, 王冬兵, 彭智敏. 2021. 东特提斯地质调查研究进展综述[J]. 沉积与特提斯地质, 41(2): 283-296. https://www.cnki.com.cn/Article/CJFDTOTAL-TTSD202102014.htm 吴火星, 付斌, 高任, 樊涛, 查志强, 童继中, 陈天迪. 2020. 九江城门山铜矿新发现矿体特征分析及找矿潜力预测[J]. 东华理工大学学报(自然科学版), 43(2): 115-120. https://www.cnki.com.cn/Article/CJFDTOTAL-HDDZ202002003.htm 向杰, 陈建平, 肖克炎, 李诗, 张志平, 张烨. 2019. 基于机器学习的三维矿产定量预测——以四川拉拉铜矿为例[J]. 地质通报, 38(12): 2010-2021. https://www.cnki.com.cn/Article/CJFDTOTAL-ZQYD201912010.htm 肖克炎, 娄德波, 孙莉, 李景朝, 叶天竺. 2013. 全国重要矿产资源潜力评价一些基本预测理论方法的进展[J]. 吉林大学学报(地球科学版), 43(4): 1073-1082. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201304003.htm 许志琴, 杨经绥, 李文昌, 李化启, 蔡志慧. 闫臻, 马昌前. 2013. 青藏高原中的古特提斯体制与增生造山作用[J]. 岩石学报, 29(6): 1847-1860. 杨经绥, 许志琴, 李天福, 李化启, 李兆丽, 任玉峰, 徐向珍, 陈松永. 2007. 青藏高原拉萨地块中的大洋俯冲型榴辉岩: 古特提斯洋盆的残留?[J] 地质通报, 26(10): 1277-1287. https://www.cnki.com.cn/Article/CJFDTOTAL-ZQYD200710008.htm 叶天竺. 2013. 矿床模型综合地质信息预测技术方法理论框架[J]. 吉林大学学报(地球科学版), 43(4): 1053-1072. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201304002.htm 张士红, 肖克炎. 2020. 基于随机森林的四川省会理地区"拉拉式"铜矿成矿预测[J]. 地质与勘探, 56(2): 239-252. 张士贞, 秦雅东, 李勇, 李奋其, 巩小栋. 2021. 西藏许如错地区洁居纳卓组碎屑锆石U-Pb年龄及其地质意义[J]. 沉积与特提斯地质, 41(1): 24-32. 张野, 李明超, 韩帅, 任秋兵, 朱月琴. 2020. 基于金矿规格单元数据的机器学习方法在成矿建模分析中的应用[J]. 大地构造与成矿学, 44(2): 183-191. 张玉君, 曾朝铭, 陈薇. 2003. ETM+(TM)蚀变遥感异常提取方法研究与应用-方法选择和技术流程[J]. 国土资源遥感, 2: 44-50. 张振杰, 成秋明, 杨玠, 武国朋, 葛云钊. 2021. 机器学习与成矿预测: 以闽西南铁多金属矿预测为例[J]. 地学前缘, 28(3): 281-215. 赵鹏大. 2007. 成矿定量预测与深部找矿[J]. 地学前缘, 14(5): 1-10. 赵希良, 龚臣, 何俊, 彭建华, 黄韶春, 杨志龙. 2013. 西藏措勤县打加错地区斑岩型铜矿点发现及其意义[J]. 东华理工大学学报(自然科学版), 36(6): 13-20. https://www.cnki.com.cn/Article/CJFDTOTAL-HDDZ2013S2003.htm 朱裕生, 肖克炎, 马玉波, 丁建华. 2013. 中国成矿区带划分的历史与现状[J]. 地质学刊, 37(3): 349-357. https://www.cnki.com.cn/Article/CJFDTOTAL-JSDZ201303002.htm -
期刊类型引用(0)
其他类型引用(1)