Barcoding Magmas: Applying Machine Learning In Zircon Geochemistry To Increase Provenance Accuracy

沉积物源使研究人员能够重建和解释沉积物从母岩（源）到沉积（汇）的历史。“源”是侵蚀山，“汇”是沉积盆地。沉积物源研究可以让我们重建过去的环境、气候和构造。它使我们能够评估沉积岩对资源勘探（碳氢化合物、地热、含水层）或碳捕获/储存（CCS）的适用性。造山活动（造山运动）的一个关键特征是大量熔融岩石（岩浆）的就位，这些岩浆冷却并结晶为火成岩，特别是花岗岩。花岗岩主要由石英、长石、角闪洞和/或云母组成。除此之外，还有一种常见的矿物，在岩浆侵位期间生长在岩浆中，这就是锆石。锆石是一种非凡的材料。使用铀铅（U-Pb）地质年代学可以很容易地确定它的年代，从而得出它形成的火成岩的年龄。它在物理和化学上都很坚固，可以承受侵蚀、运输和后期成岩作用（沉积物沉积后的物理和化学变化）期间的变化。传统上，物源研究是通过从沉积物中收集大量锆石，确定它们的年代（U-Pb地质年代学），并将获得的年龄与先前确定的地质区域进行比对来进行的。这对沉积物的来源提供了一个非常广泛的图像，但缺乏准确性。例如，中国黄土高原的锆石来源于青藏高原约250万平方公里的花岗岩。在更近的地方，西北爱尔兰石炭纪沉积盆地的物质来自多尼戈尔公司的加里东花岗岩。然而，这些花岗岩是在英国和爱尔兰约92,000平方公里的加里东山带发现的一套同时期花岗岩的一部分。因此，这些沉积物与多尼戈尔花岗岩之间的联系仍然是推测性的，现有的沉积物运输模型可能非常不准确。在岩浆室的结晶过程中，锆石中含有微量元素，这些元素以地球化学的方式记录了岩浆中变化的条件（很像树木的年轮记录了季节的流逝）。每一块锆石只记录了岩浆房在结晶时的部分地球化学历史。因此，为了重建更完整的岩浆地球化学历史，必须分析许多锆石。我们建议使用机器学习和模式匹配算法来分析构成多尼戈尔基的五个花岗岩体（每个体2000个）的10,000个锆石中的生长模式和微量元素分布。这一分析将创建一个地球化学条形码，代表相应岩浆房内条件的连续时间线。由于岩浆体是自然的动态系统，没有两个岩浆体具有相同的地球化学特征，因此生成的条形码对每个都是唯一的。来自爱尔兰西北部石炭纪砂岩沉积物的锆石被认为来自包含我们岩浆系统的造山带，将使用相同的技术进行地球化学分析。每一颗锆石都含有母岩浆体的部分条形码。使用定制的模式匹配算法，将这些部分条形码与附近花岗岩体的新条形码进行比较，以确定其确切来源并重建石炭世期间的区域沉积物运输路径。从本质上讲，这将类似于将沉积物中锆石的部分DNA序列与附近火成岩单元的完整DNA基因组相匹配。这项研究汇集了一个总部位于英国的国际科学家团队，邓普西博士和伯德博士（赫尔大学）以及埃因斯博士和尼尔博士（格拉斯哥大学）。我们的团队结合了丰富的加里东构造和岩浆作用，锆石地球化学和物源的经验，以及卓越的观察和分析技能。

Sedimentary provenance allows researchers to reconstruct and interpret the history of a sediment from its parent rock (source) to its deposition (sink). The "sources" are eroding mountains and the "sinks" are sedimentary basins. Sedimentary provenance studies can allow us to reconstruct past environments, climate and tectonics. It allows us to assess the suitability of sedimentary rocks for resource exploration (hydrocarbons, geothermal, aquifers) or carbon capture/storage (CCS). A key feature of mountain building events (orogenesis) is the emplacement of large bodies of molten rock (magma) which cools and crystallises as igneous rocks, in particular granite. Granites are primarily composed of quartz, feldspar, amphibole and/or mica. In addition to these, a common mineral, which grows within the magma during emplacement, is zircon.Zircon is a remarkable material. It's easily datable using Uranium-Lead (U-Pb) geochronology, yielding the age of the igneous body in which it formed. It is physically and chemically robust, withstanding alteration during erosion, transport and later diagenesis (physical and chemical changes in sediments after their deposition). Traditionally, provenance studies are conducted by collecting large suites of zircons from sediments, dating them (U-Pb geochronology) and matching the acquired ages to previously dated geological regions. This gives a very broad picture of the source of the sediment but lacks accuracy. For example, zircons from the Chinese Loess Plateau are sourced from granites in the ~2.5 million km2 Tibetan Plateau. Closer to home, the Carboniferous age sedimentary basin of North West Ireland sources material from Caledonian Granites in Co. Donegal. However, these granites are part of a suite of coeval granites found throughout the ~92,000 km2 Caledonian mountain belt in Britain and Ireland. As a result, links between these sediments and the Donegal granites remains speculative, and existing models of sediment transport may be highly inaccurate.During crystallisation in the magma chamber, zircons incorporate trace elements which geochemically record the changing conditions in the magma (much like tree rings record the passing of the seasons). Each individual zircon only records part of the geochemical history of that magma chamber from when it was crystalizing. Therefore, to reconstruct a more complete geochemical history of the magma many zircons must be analysed. We propose to use machine learning and pattern matching algorithms to analyse the growth patterns and trace element distribution within 10,000 individual zircons from the five granite bodies (2000 per body) making up the Donegal Batholith. This analysis will create a geochemical barcode, representing a continuous timeline of conditions within their corresponding magma chambers. Because magma bodies are natural and dynamic systems, no two bodies will have an identical geochemical signature, so the generated barcode will be unique to each. Zircons from sediment in the Carboniferous sandstones of NW Ireland believed to derive from the orogenic belt containing our magmatic systems will be geochemically analysed using the same techniques. Each of these zircons will contain a partial barcode of its parent magmatic body. Using bespoke pattern matching algorithms, these partial barcodes will be compared to new barcodes of the nearby granite bodies to ascertain their exact source & reconstruct the regional sediment transport pathways during the Carboniferous. In essence, this will be akin to matching a partial DNA sequence from the zircons in sediment to the complete DNA genomes of the nearby igneous units.This research brings together a UK-based team of international scientists, Dr Dempsey & Dr Bird (University of Hull) and, Dr Einsle & Dr Neill (University of Glasgow). Our team combines a wealth of experience of Caledonian tectonics & magmatism, zircon geochemistry & provenance, exceptional observational & analytical skills.