基于无机地球化学数据的加州圣华金盆地白垩系-达尼安系莫雷诺组有机地球化学参数预测

IF 3.6 2区 地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS
Hunter C. Olson, Allegra Hosford Scheirer, Samantha R. Ritzer, Erik A. Sperling
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引用次数: 0

摘要

准确重建热成熟岩石中原始总有机碳(TOC)对于正确应用地球化学指标和了解有机碳埋藏时间至关重要。为了利用经验方法重建原始TOC,准确估计原始氢指数(HI)是至关重要的。两种最常用的方法是利用干酪根类型或利用盆地其他地方未成熟岩石的平均HI值来估计原始HI值。本研究以美国加利福尼亚州San Joaquin盆地上白垩统-古近系Moreno组为例,验证了利用无机地球化学数据重建原始HI的能力。该研究使用了来自Moreno组的岩心,这些岩心热成熟度不高,因此保留了原始HI值,并且在初始HI范围内。首先,对先前用于有机地球化学分析的样品进行无机地球化学数据(元素丰度和铁形态)的生成。这些数据表明,莫雷诺组沉积时期的底水条件为含铁(缺氧和非硫化物),没有持续的含氧(缺氧和硫化物)发育。接下来,采用随机森林机器学习分析方法,分析哪些无机地球化学变量最能预测莫雷诺组的HI。最重要的指标是碎屑输入(Ti, Th),海洋输出生产力(Cu, Ni)和缺氧条件下的氧化还原指标(Se, Cr,铁形态)。最后,利用随机森林框架预测了3个主要研究岩心的无机地球化学HI值。将这些预测结果与实测值、干酪根类型和平均HI方法进行了地层学和统计学比较,结果表明,新方法比基于单一值的方法具有更好的预测能力。这表明,利用无机地球化学这一相对不受热成熟影响的特征,可以重建埋藏和成岩过程中被改变的有机地球化学参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of organic geochemical parameters from inorganic geochemical data in the Cretaceous-Danian Moreno Formation, San Joaquin Basin, California
Accurately reconstructing original Total Organic Carbon (TOC) in thermally mature rocks is essential for the correct application of geochemical proxies and understanding organic carbon burial through time. To reconstruct original TOC using empirical methods, it is vital to have an accurate estimate of the original Hydrogen Index (HI). The two most common methods are estimating original HI using kerogen type or using average HI values from immature rocks elsewhere in the basin. This study tests the ability to use inorganic geochemical data to reconstruct original HI using the Upper Cretaceous-Paleogene Moreno Formation from the San Joaquin Basin, California, USA as a case study. The study utilized cores from the Moreno Formation that are thermally immature, thus preserving original HI values, and that span a range in initial HI. First, inorganic geochemical data were produced (elemental abundances and iron speciation) for samples previously analyzed for organic geochemistry. These data suggest that bottom water conditions during deposition of the Moreno Formation were ferruginous (anoxic and non-sulfidic), without development of sustained euxinia (anoxic and sulfidic). Next, a random forest machine learning analysis was implemented to analyze which inorganic geochemical variables best predict HI in the Moreno Formation. The most important proxies were those for detrital input (Ti, Th), marine export productivity (Cu, Ni), and redox proxies for suboxic conditions (Se, Cr, iron speciation). Finally, the random forest framework was used to predict HI values for three main study cores based on their inorganic geochemistry. These predictions were compared stratigraphically and statistically against the measured values and the kerogen type and average HI methods for reconstructing HI and show this new method has better predictive power than approaches based on single values. This indicates strong promise for using inorganic geochemistry, which is relatively immune to thermal maturation, to reconstruct organic geochemical parameters that are modified during burial and diagenetic process.
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来源期刊
Chemical Geology
Chemical Geology 地学-地球化学与地球物理
CiteScore
7.20
自引率
10.30%
发文量
374
审稿时长
3.6 months
期刊介绍: Chemical Geology is an international journal that publishes original research papers on isotopic and elemental geochemistry, geochronology and cosmochemistry. The Journal focuses on chemical processes in igneous, metamorphic, and sedimentary petrology, low- and high-temperature aqueous solutions, biogeochemistry, the environment and cosmochemistry. Papers that are field, experimentally, or computationally based are appropriate if they are of broad international interest. The Journal generally does not publish papers that are primarily of regional or local interest, or which are primarily focused on remediation and applied geochemistry. The Journal also welcomes innovative papers dealing with significant analytical advances that are of wide interest in the community and extend significantly beyond the scope of what would be included in the methods section of a standard research paper.
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