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Abstract

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Petroleomics is a powerful tool for petroleum exploration and production, offering high-resolution insights into crude oil composition, depositional environments, and reservoir characteristics. This study applies ultra-high resolution mass spectrometry (UHRMS), chemometric techniques, and machine learning to systematically evaluate crude oils from eight Brazilian sedimentary basins. Advanced molecular characterization using APPI(+) FT-ICR MS enables precise classification of oils based on heteroatomic class distributions, thermal evolution, and depositional settings. Additionally, production allocation in the Búzios Field is optimized through compositional trends observed in PVT and TFR samples, revealing vertical connectivity and lateral geological barriers.

To expand petroleomics into reservoir geochemistry, Laser Ablation Electrospray Ionization Mass Spectrometry (LAESI-MS) was applied to Berea sandstone and carbonaceous rocks from the Araripe Basin. This method enables direct analysis of organic compound distributions on rock surfaces without extensive pretreatment, uncovering chemical heterogeneity at different depths and providing insights into rock-fluid interactions. These findings reinforce the potential of petroleomics for sample integrity checks, reservoir connectivity assessments, and improved hydrocarbon recovery strategies. The combined approach of fluid and rock characterization enhances geochemical modeling and supports sustainable resource management in petroleum systems.

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/content/papers/10.3997/2214-4609.202533236
2025-09-07
2026-02-13
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