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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=667718
• 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 (GC×GC), 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.**

沉积有机质在地球的地下被保存和改造。这种物质含有独特的碳氢化合物组合，具有足够的地球化学信息，可以与曾经的生物联系在一起，从而促进了过去沉积环境的古生态和地球化学重建。不幸的是，由于嵌入了复杂的矩阵，这些信息中的大部分从未实现。随着全二维气相色谱(GC×GC)的发展，在挥发性、复杂的有机基质中分离分析物的能力已经提高了一个数量级。必须开发先进的化学计量学方法来更全面地捕捉复杂流体组成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用于跟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、有机质保存途径、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的分析技术和加利福尼亚州海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。这一努力将有助于评估深部生物圈在地质时期对沉积有机质组成的影响的第一步。从这些进展中获得的知识将扩展到常规产油盆地。作为对这些技术的测试，将对斯科特边缘和大浅滩内的源岩沥青和储集层流体进行研究，以更好地确定有机质形成和保存的沉积控制以及与伊比利亚西部共轭边缘有关的盆地流体生成史。*这项研究提出了6个不同的项目，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名硕士和2名博士生)。HQP将能够针对未来职业生涯中的新研究问题量身定做他们的知识。该研究计划将提高我们对生物圈对碳循环的深层影响的理解，并为大西洋地区提供一个强大的系统，在改良的常规和非传统地质环境中全面询问挥发性有机底物的分子组成。研究活动将提供修订的生成、油源岩特征和成因油族模型，这些模型可以整合到未来的石油形成预测模型中。**