How to determine the optimal balance for geochemical pattern recognition and anomaly mapping based on compositional balance analysis?

IF 1 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Geochemistry-Exploration Environment Analysis Pub Date : 2022-07-14 DOI:10.1144/geochem2022-009

Yue Liu

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引用次数: 1

Abstract

Balance analysis of two groups of parts within a whole has become an important method for compositional data analysis. A compositional balance is a particular orthonormal coordinate that is depicted by the log-ratio between two groups of components. Two available approaches to compositional balance analysis (CoBA) can be adopted to generate targeted balances for geochemical pattern analysis and anomaly identification, so-called data-driven CoBA and knowledge-driven CoBA. For the data-driven CoBA, the balance is produced strictly by the rules of sequential binary partition (SBP), while for the knowledge-driven CoBA, the first group within a balance is composed of the interesting parts of the whole and the second group is defined by the remaining parts of the whole. Commonly, it is difficult to conceptualize balances, particularly for high-dimensional data, because it will produce a large number of orthonormal bases or balances based on CoBA. For a certain geochemical pattern, it might be represented by multiple compositional balances generated by data-driven and knowledge-driven CoBA. Thus, how to determine an optimal balance for geochemical pattern analysis and anomaly identification needs to be further explored. In the present study, this question was thoroughly investigated based on a case study from the Chinese Western Tianshan (CWT) region. Fourteen compositional balances and three principal factors associated with different geochemical patterns including gold and copper mineralization, and particular lithological units were selected for comparative studies to illustrate how to determine the optimal balances from the perspective of CoBA and multivariate statistical analysis.Thematic collection: This article is part of the Applications of Innovations in Geochemical Data Analysis collection available at: https://www.lyellcollection.org/cc/applications-of-innovations-in-geochemical-data-analysisSupplementary material:https://doi.org/10.6084/m9.figshare.c.6083724

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如何确定基于成分平衡分析的地球化学模式识别和异常绘图的最佳平衡？

整体中两组部分的平衡分析已成为成分数据分析的重要方法。成分平衡是由两组成分之间的对数比描述的特定正交坐标。成分平衡分析（CoBA）的两种可用方法可用于生成用于地球化学模式分析和异常识别的目标平衡，即所谓的数据驱动CoBA和知识驱动CoBA。对于数据驱动的CoBA，平衡严格由顺序二进制划分（SBP）规则产生，而对于知识驱动的CoBA，平衡中的第一组由整体的感兴趣部分组成，第二组由整体剩余部分定义。通常，很难将平衡概念化，特别是对于高维数据，因为它会产生大量基于CoBA的正态碱基或平衡。对于某种地球化学模式，它可能由数据驱动和知识驱动的CoBA产生的多重成分平衡来表示。因此，如何确定地球化学模式分析和异常识别的最佳平衡还有待进一步探索。在本研究中，基于中国西天山地区的一个案例研究，对这个问题进行了深入的调查。选择了与不同地球化学模式（包括金和铜矿化）和特定岩性单元相关的14个成分平衡和3个主要因素进行比较研究，以说明如何从CoBA和多元统计分析的角度确定最佳平衡。专题汇编：本文是地球化学数据分析创新应用汇编的一部分，可在以下网站获取：https://www.lyellcollection.org/cc/applications-of-innovations-in-geochemical-data-analysisSupplementary材料：https://doi.org/10.6084/m9.figshare.c.6083724

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来源期刊

Geochemistry-Exploration Environment Analysis 地学-地球化学与地球物理

CiteScore

3.60

自引率

16.70%

发文量

审稿时长

1 months

期刊介绍： Geochemistry: Exploration, Environment, Analysis (GEEA) is a co-owned journal of the Geological Society of London and the Association of Applied Geochemists (AAG). GEEA focuses on mineral exploration using geochemistry; related fields also covered include geoanalysis, the development of methods and techniques used to analyse geochemical materials such as rocks, soils, sediments, waters and vegetation, and environmental issues associated with mining and source apportionment. GEEA is well-known for its thematic sets on hot topics and regularly publishes papers from the biennial International Applied Geochemistry Symposium (IAGS). Papers that seek to integrate geological, geochemical and geophysical methods of exploration are particularly welcome, as are those that concern geochemical mapping and those that comprise case histories. Given the many links between exploration and environmental geochemistry, the journal encourages the exchange of concepts and data; in particular, to differentiate various sources of elements. GEEA publishes research articles; discussion papers; book reviews; editorial content and thematic sets.