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

用于检测地球化学过程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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712328
• 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.

沉积有机物在地球的地下保存并修饰。该材料包含碳氢化合物的独特组合，并具有足够的地球化学信息，可以与曾经的生物体联系起来，从而促进了过去沉积环境的古生物学和地球化学重建。不幸的是，由于它嵌入的复杂矩阵，因此从未实现大部分信息。随着综合二维气相色谱法（GCGC）的发展，在挥发性内的空间分析物的能力，复杂的有机矩阵已通过数量级提高。已经开发出高级化学计量方法，以更完全捕获复杂流体组成之间和之间的结构差异。 这些技术和新方法的开发将在申请人的研究计划中使用，以跟踪已知的生物学标志物；但更重要的是，它们将能够研究自然发生的复杂有机混合物中的多分子变化，以更好地了解过去的生物系统，有机物保存途径，深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以及加利福尼亚海湾瓜伊马斯盆地沉积水热系统的独特条件，以整体解决碳氢化合物转化途径。这项工作将促进通过地质时间评估深层生物圈对沉积有机物组成的影响的第一步。从最终的进步中获得的知识将扩展到常规的石油生产盆地。作为对这些技术的测试，将研究斯科舍省利润和大银行内的岩石沥青和储层流体，以更好地定义有关有机物形成和保存的沉积控制，以及可以将可以与偶像西部伊比利亚人边缘相关的盆地流体产生历史。 该研究提出的跨越了6个不同的项目，该项目将创建HQP（4 MSC和2位PHD学生），具有有机地球化学，石油地球化学和区域石油地质学的能力。 HQP将能够为未来职业的新研究问题量身定制知识。该研究计划将提高我们对深层生物圈对碳循环的影响，并为大西洋地区提供一个强大的系统，用于整体询问在经过修改的常规和非常规地质环境中挥发性有机基质的分子组成。研究活动将提供经过修订的生成，石油源岩石特征和遗传石油家族模型，这些模型可以整合到未来的石油形成预测模型中。