Literature DB >> 29320168

Linking Natural Oil Seeps from the Gulf of Mexico to Their Origin by Use of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry.

Logan C Krajewski1, Vladislav V Lobodin2, Caroline Johansen3, Tessa E Bartges1, Ekaterina V Maksimova4, Ian R MacDonald3, Alan G Marshall1,2.   

Abstract

We report chemical characterization of natural oil seeps from the Gulf of Mexico by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and Gas Chromatography/Atmospheric Pressure Chemical Ionization Mass Spectrometry (GC/APCI-MS), to highlight how FT-ICR MS can also be employed as a means to determine petroleum connectivity, in addition to traditional GC/MS techniques. The source of petroleum is the Green Canyon (GC) 600 lease block in the Gulf of Mexico. Within GC600, two natural oil seepage zones, Mega Plume and Birthday Candles, continuously release hydrocarbons and develop persistent oil slicks at the sea surface above them. We chemically trace the petroleum from the surface oil slicks to the Mega Plume seep itself, and further to a petroleum reservoir 5 km away in lease block GC645 (Holstein Reservoir). We establish the connectivity between oil samples and confirm a common geological origin for the oil slicks, oil seep, and reservoir oil. The ratios of seven common petroleum biomarkers detected by GC/APCI-MS display clear similarity between the GC600 and GC645 samples, as well as a distinct difference from another reservoir oil collected ∼300 km away (Macondo crude oil from MC252 lease block). FT-ICR MS and principal component analysis (PCA) demonstrate further similarities between the GC600 and GC645 samples that distinctly differ from MC252. A common geographical origin is postulated for the GC600/GC645 samples, with petroleum migrating from the GC645 reservoir to the oil seeps found in GC600 and up through the water column to the sea surface as an oil slick.

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Year:  2018        PMID: 29320168     DOI: 10.1021/acs.est.7b04445

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  ftmsRanalysis: An R package for exploratory data analysis and interactive visualization of FT-MS data.

Authors:  Lisa M Bramer; Amanda M White; Kelly G Stratton; Allison M Thompson; Daniel Claborne; Kirsten Hofmockel; Lee Ann McCue
Journal:  PLoS Comput Biol       Date:  2020-03-16       Impact factor: 4.475

  1 in total

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