Multi-Molecular Characterization of Complex Matrices for the Detection of Geochemical Processes

用于地球化学过程检测的复杂基质的多分子表征

• 批准号: RGPIN-2018-06147
• 负责人: Ventura, Gregory
• 金额: $ 1.82万
• 依托单位: Saint Mary's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=755043
• 关键词: Multi; Molecular; Characterization; Complex; Matrices

Sedimentary organic matter is preserved and modified in the Earth's subsurface. This material contains unique assemblages of hydrocarbons with enough geochemical information to be linked to once living organisms and thus facilitates paleoecological and geochemical reconstructions of past depositional environments. Unfortunately, much of this information is never realized due to the complex matrix with which it is embedded. With the development of comprehensive two-dimensional gas chromatography (GCGC), the ability to spatially separate analytes within volatile, complex organic matrices have improved by an order of magnitude. Advanced chemometric approaches have necessarily been developed to more completely capture the structural differences residing within and between complex fluid compositions.These technologies and the development of new methodologies will be used within the applicant's research program to track known and yet to be discovered biological markers; but more importantly, they will enable the investigation of multi-molecular changes within natural occurring complex organic mixtures to better understand past biotic systems, organic matter preservation pathways, the role of the deep biosphere, and factors leading to the formation of active petroleum systems. Targeted research projects will develop and utilize novel analytical techniques and the unique conditions of sedimented hydrothermal systems in the Guaymas Basin, Gulf of California to holistically resolve hydrocarbon transformation pathways. This effort will facilitate the first step in assessing the deep biosphere's impact on the composition of sedimentary organic matter through geologic time. The knowledge gained from the resulting advances will be extended to conventional petroleum producing basins. As a test of these techniques, source rock bitumens and reservoir fluids within the Scotian margin and Grand Banks will be studied to better define depositional controls on organic matter formation and preservation and basin fluid generation histories that can be linked to the conjugate western Iberian margin.The research proposed spans 6 distinct projects that will create HQP (4 MSc and 2 PhD students) with competency in organic geochemistry, petroleum geochemistry and regional petroleum geology. HQP will be able to tailor their knowledge toward new research problems in future careers. The research program will improve our understanding of the deep biosphere impact on the carbon cycle and provide the Atlantic region with a robust system for holistically interrogating the molecular compositions of volatile organic substrates in modified conventional and unconventional geological settings. The research activities will provide revised generation, oil-source rock characterization, and genetic oil family models that can be integrated into future predictive models of oil formation.

沉积有机质在地球地下得到保存和改变。这种材料包含独特的碳氢化合物组合，具有足够的地球化学信息，可与曾经存在的生物体联系起来，从而促进过去沉积环境的古生态和地球化学重建。不幸的是，由于嵌入的复杂矩阵，大部分信息从未被实现。随着综合二维气相色谱 (GCGC) 的发展，空间分离挥发性、复杂有机基质中分析物的能力已提高了一个数量级。必须开发先进的化学计量方法，以更完整地捕获复杂流体成分内部和之间的结构差异。这些技术和新方法的开发将在申请人的研究计划中使用，以追踪已知和尚未发现的生物标记；但更重要的是，它们将使研究天然存在的复杂有机混合物中的多分子变化成为可能，以更好地了解过去的生物系统、有机物保存途径、深层生物圈的作用以及导致活跃石油系统形成的因素。有针对性的研究项目将开发和利用新颖的分析技术和加利福尼亚湾瓜伊马斯盆地沉积热液系统的独特条件，以全面解决碳氢化合物转化途径。这项工作将有助于迈出评估地质时期深层生物圈对沉积有机质组成的影响的第一步。从由此产生的进步中获得的知识将扩展到常规石油生产盆地。作为对这些技术的测试，将研究斯科舍边缘和大浅滩内的烃源岩沥青和储层流体，以更好地确定对有机质形成和保存的沉积控制以及可与共轭西伊比利亚边缘联系起来的盆地流体生成历史。拟议的研究涵盖 6 个不同的项目，这些项目将创建具有有机地球化学、石油地球化学和区域石油地质学能力的 HQP（4 名硕士生和 2 名博士生）。 HQP 将能够针对未来职业中的新研究问题调整他们的知识。该研究计划将提高我们对深层生物圈对碳循环影响的理解，并为大西洋地区提供一个强大的系统，用于全面研究改良的常规和非常规地质环境中挥发性有机底物的分子组成。研究活动将提供修订后的生成、油源岩表征和成因油族模型，这些模型可以集成到未来的石油形成预测模型中。