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Modeling granulometric, mineralogical, and geochemical composition of sediments: A quantitative tool for predicting sediment composition and reconstructing sediment provenance

对沉积物的粒度、矿物学和地球化学成分进行建模：预测沉积物成分和重建沉积物来源的定量工具

基本信息

批准号：
26375345
负责人：
Professor Dr. Hilmar von Eynatten
金额：
--
依托单位：
Abteilung Sedimentologie und Umweltgeologie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2006
资助国家：
德国
起止时间：
2005-12-31 至 2013-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/26375345?language=en
关键词：
Modeling granulometric mineralogical geochemical composition

项目摘要

Numerical modeling has become a powerful tool in several fields of geosciences, but a comprehensive model to describe the composition of clastic sediments is still lacking. This study aims at developing a numerical-statistical model that allows for describing quantitatively the petrographic, chemical, and granulometric changes related to the overall transfer of material from the original source rock to the sediment at the final site of deposition. These relative changes of sediment composition (as compared to the initial source) are largely controlled by tectonics, physiography, climate, and transport energy. The model will be suited for both inductive and deductive approaches. Potential applications of the model are, for example, the prediction of sediment composition under well-known geologic conditions and the reconstruction of sediment provenance based on final composition. To achieve this general goal, it needs the successful execution of two subgoals: (1) the broadening of our theoretical understanding of so-called multi-way compositions (e.g., data sets reporting grain size, chemistry, and mineralogy of sediment samples) and (2) modeling of multi-way compositional change in several case studies comprising both literature data as well as new datasets obtained within the frame of this project.

数值模拟已成为地球科学研究的重要工具，但至今仍缺乏一个全面的碎屑沉积物组成模型。本研究的目的是开发一个数值统计模型，允许定量描述的岩相，化学和粒度的变化有关的整体转移的材料从原始源岩沉积在最终网站的沉积物。沉积物组成的这些相对变化（与初始来源相比）主要受构造、自然地理、气候和输送能量的控制。该模型将适用于归纳和演绎的方法。该模型的潜在应用包括，例如，预测已知地质条件下的沉积物成分，以及根据最终成分重建沉积物来源。为了实现这一总目标，它需要成功地执行两个子目标：（1）扩大我们对所谓的多路合成的理论理解（例如，报告沉积物样品的粒度、化学和矿物学的数据集）和（2）在包括文献数据以及在该项目框架内获得的新数据集的几个案例研究中的多途径成分变化的建模。