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基于GEOROC大数据分析地壳厚度地球化学指标
引用本文:葛粲,汪方跃,李永东,李晓晖,李修钰,周宇章,袁峰,李建设,陆三明.基于GEOROC大数据分析地壳厚度地球化学指标[J].岩石学报,2018,34(11):3179-3188.
作者姓名:葛粲  汪方跃  李永东  李晓晖  李修钰  周宇章  袁峰  李建设  陆三明
作者单位:合肥工业大学资源与环境工程学院, 合肥 230009;合肥工业大学矿集区立体探测实验室, 合肥 230009;合肥工业大学矿床成因与勘察技术研究中心, 合肥 230009,合肥工业大学资源与环境工程学院, 合肥 230009;合肥工业大学矿集区立体探测实验室, 合肥 230009;合肥工业大学矿床成因与勘察技术研究中心, 合肥 230009,中国地质大学地球物理与空间信息学院, 武汉 430074,合肥工业大学资源与环境工程学院, 合肥 230009;合肥工业大学矿集区立体探测实验室, 合肥 230009;合肥工业大学矿床成因与勘察技术研究中心, 合肥 230009,安徽省地质调查院, 合肥 230091,安徽省公益性地质调查管理中心, 合肥 230091,合肥工业大学资源与环境工程学院, 合肥 230009;合肥工业大学矿集区立体探测实验室, 合肥 230009;合肥工业大学矿床成因与勘察技术研究中心, 合肥 230009,安徽省公益性地质调查管理中心, 合肥 230091,安徽省公益性地质调查管理中心, 合肥 230091
基金项目:本文受国家重点研发计划项目(2016YFC0600209)、国家自然科学基金重点国际合作研究项目(41820104007)、国家自然科学基金项目(41504042)和安徽省国土资源科技项目(2016-K-4)联合资助.
摘    要:前人研究认为,火山岩中部分地球化学指标与岩浆弧地壳厚度之间存在一定的相关性,并通过统计主量元素K2O、Ca O和Na2O指标及微量元素Ce/Y、Sm/Yb、Dy/Yb、Sr/Y、La/Yb指标与地壳厚度之间关系,约束地质史上某些区域的地壳厚度发展和变化。本文基于GEOROC数据库,以Si O2含量57%和火山岩年龄23Ma为界,将全球火山岩数据分成年轻-壳源( 57%,23Ma)、年轻-幔源(57%,23Ma)、古老-壳源( 57%, 23Ma)和古老-幔源(57%, 23Ma)四个数据集,并通过核函数估计方法获得了各个地球化学指标与地壳厚度的归一化联合概率密度分布图。本文统计结果表明,年轻-幔源火山岩中的K2O含量分布与壳源火山岩呈现指数正相关关系、Ca O含量分布于地壳厚度呈现线性负相关关系,年轻-壳源火山岩中Ce/Y、La/Yb和Sm/Yb与现今地壳厚度有指数正相关关系。由以上5种地化指标建立的回归方程确定系数R2均大于0. 7,可以认为相关关系显著。本文认为幔源岩浆在穿透地壳到达地表过程中,地壳厚度控制了富K壳源物质进入地幔熔体和富Ca矿物结晶分异过程,导致了火山岩中K2O和Ca O含量的相关变化;而下地壳部分熔融形成的壳源岩浆,不同深度压力控制了残留相矿物比例,导致Ce/Y、La/Yb和Sm/Yb体现出与地壳厚度的相关性。本文建立的回归函数是基于大量数据概率密度分布的统计分析得出的,由于离群数据普遍存在,回溯历史地壳厚度变化需要大量数据统计支撑,否则难以获得可靠的结果。

关 键 词:大数据  地壳厚度  地化指标  核函数估计  归一化联合概率密度分布
收稿时间:2018/4/5 0:00:00
修稿时间:2018/8/10 0:00:00

Analysis of geochemical indices of crustal thickness based on GEOROC big data
GE Can,WANG FangYue,LI YongDong,LI XiaoHui,LI XiuYu,ZHOU Yu Zhang,YUAN Feng,LI JianShe and LU SanMing.Analysis of geochemical indices of crustal thickness based on GEOROC big data[J].Acta Petrologica Sinica,2018,34(11):3179-3188.
Authors:GE Can  WANG FangYue  LI YongDong  LI XiaoHui  LI XiuYu  ZHOU Yu Zhang  YUAN Feng  LI JianShe and LU SanMing
Institution:School of Resource and Environmental Engineer, Hefei University of Technology, Hefei 230009, China;Laboratory of Three-dimension Exploration for Mineral District, Hefei University of Technology, Hefei 230009, China;Ore Deposit and Exploration Centre, Hefei University of Technology, Hefei 230009, China,School of Resource and Environmental Engineer, Hefei University of Technology, Hefei 230009, China;Laboratory of Three-dimension Exploration for Mineral District, Hefei University of Technology, Hefei 230009, China;Ore Deposit and Exploration Centre, Hefei University of Technology, Hefei 230009, China,Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China,School of Resource and Environmental Engineer, Hefei University of Technology, Hefei 230009, China;Laboratory of Three-dimension Exploration for Mineral District, Hefei University of Technology, Hefei 230009, China;Ore Deposit and Exploration Centre, Hefei University of Technology, Hefei 230009, China,Geological Survey of Anhui Province, Hefei 230091, China,Public Geological Survey Management Center of Anhui Province, Hefei 230091, China,School of Resource and Environmental Engineer, Hefei University of Technology, Hefei 230009, China;Laboratory of Three-dimension Exploration for Mineral District, Hefei University of Technology, Hefei 230009, China;Ore Deposit and Exploration Centre, Hefei University of Technology, Hefei 230009, China,Public Geological Survey Management Center of Anhui Province, Hefei 230091, China and Public Geological Survey Management Center of Anhui Province, Hefei 230091, China
Abstract:Previous studies have shown that some geochemical indices in volcanic arc rocks are correlated with crustal thickness. The relationships between principal elements K2O, CaO and Na2O, trace elements ratios of Ce/Y, Sm/Yb, Dy/Yb, Sr/Y, La/Yb and crustal thickness have been statistically analyzed to restrict the development and variation of crustal thickness in some regions in geological history. Based on GEOROC database, the global volcanic rock data are divided into younger-crustal, younger-mantle, older-crustal and older-mantle data sets, and the normalized joint probability density distribution maps of geochemical indices and crustal thickness are obtained by Kernel Density Estimation method. The statistical results show that the distribution of K2O content in young-mantle-derived volcanic rocks has an exponential positive correlation with the present crustal thickness, the distribution of CaO content in young-mantle-derived volcanic rocks has a linear negative correlation with crustal thickness, Ce/Y, La/Yb and Sm/Yb ratios in young-crust-derived volcanic rocks have an exponential positive correlation with crustal thickness. The regression coefficients R2 of the above five geochemical indices are all greater than 0.7, and the correlation is significant. It is believed that the thickness of the crust controls K-rich crustal materials into mantle melts and the crystallization and differentiation of calcium-rich minerals during the ascent of mantle-derived magma to the earth''s surface, which results in the changes of K2O and CaO contents in volcanic rocks, and the stable regions of plagioclase, amphibole and garnet are controlled by the temperature and pressure conditions in the source region of crustal magma, resulting in the correlation between Ce/Y, La/Yb and Sm/Yb. The regression function established in this paper is based on the statistical analysis of the probability density distribution of massive data. Because of the existence of outlier data, tracing the historical variation of the crust thickness requires substantial data and statistical support. Otherwise, it is sometimes difficult to obtain reliable results.
Keywords:Big data  Crustal thickness  Geochemical indices  Kernel Density Estimation  Normalized joint probability density distribution
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