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Enregistrement W7113512401

Petroleomics Applications of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: Crude Oil and Bitumen Analysis

2007· article· en· W7113512401 sur OpenAlexaboutno aff

Notice bibliographique

RevueDigiNole (Florida State University) · 2007
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFourier transform ion cyclotron resonanceNaphthenic acidOil sandsMass spectrometryAsphaltAnalytical Chemistry (journal)PetroleumLight crude oilOil refineryHeteroatom
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The ultra-high mass resolving power and high mass accuracy of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) have been shown to be well suited for the characterization of highly complex mixtures. Petroleum mixtures, arguably the most complex on the planet, have been extensively characterized by FT-ICR MS. This new field of "Petroleomics", spearheaded by the Ion Cyclotron Resonance group at the National High Magnetic Field Laboratory, presents the opportunity to address both fundamental aspects of petroleum chemistry as well as costly upstream and downstream processing issues. Field desorption ionization (FD) provides access to non-polar hydrocarbons and low-polarity sulfur constituents of petroleum not accessible by the more common electrospray ionization (ESI). Chapter 2 describes the complete automation of the NHMFL 9.4 Tesla FD FT-ICR mass spectrometer and the benefits thereof. Automation allows ensemble averaging for increased dynamic range, mass accuracy, S/N and unattended sample analysis. The decrease in light "sweet" crude oils has led to the use of heavier, more heteroatom rich feedstocks for the production of petroleum products. The oil sands bitumen deposits in Alberta, Canada represent a substantial reserve of recoverable crude oil. However, the high viscosity and high heteroatom content present production issues of this heavy oil. In particular, the high acid content (termed naphthenic acids) of Athabasca bitumen results in reduced market price due to the possibility of acid induced refinery corrosion (naphthenic acid corrosion). In Chapter 3 the characterization of organic acids in Athabasca bitumen and its heavy vacuum gas oil (HVGO) by negative-ion ESI FT-ICR MS are described. Advantages of acid isolation by ion-exchange chromatography are also discussed. In Chapter 4, eight distillation cuts of an Athabasca bitumen HVGO are characterized by negative-ion and positive-ion ESI, as well as automated LIFDI (discussed in Chapter 2) FT-ICR MS to investigate the evolution of acidic, basic and non-polar species under standard distillation conditions. All methods reveal an increase in double-bond equivalents (DBE, the number of rings plus double bonds) and carbon number with increased distillation temperature range. Estimation of carbon number and DBE distributions for individual distillation cuts from the high-resolution feed HVGO mass spectrum is discussed. The vacuum distillation tower has been shown to be highly susceptible to naphthenic acid corrosion, especially in the HVGO distillation temperature range of 220-400 degrees C. However, the thermal stability of petroleum acids in the temperature range is unknown. In Chapter 5, thermal treatment products of Athabasca bitumen are characterized by negative-ion ESI FT-ICR MS. Low-molecular weight organic acids are identified in the reactor inert sweep gas at higher treatment temperatures, suggesting boil-off. Self-association of petroleum molecules, such as asphaltenes, in solution is well known. Chapter 6 describes the self-association of organic acids in the gas phase for crude oil and bitumen characterized by low-resolution and high-resolution mass spectrometry. Multimer formation is found to be concentration, boiling point and chemical functionality dependent. The results discussed in Chapter 6 suggest molecular weight determination for petroleum products by mass spectrometry should be scrutinized closely. Asphaltenes are the most aromatic and most polar constituents of crude oil and are typically defined by their solubility. They are typically stable under reservoir conditions, but environmental changes in the production may disrupt their stability and cause costly deposition and precipitation problems. Chemical inhibitors are often added to the well to prevent asphaltene deposition. Chapter 7 discusses asphaltene inhibitor specificity related to detailed polar chemical composition for two geographically distinct crude oils derived from negative-ion and positive-ion ESI FT-ICR MS. Crude oils are commonly separated by their solubility in different solvents to simplify their characterization. Chapter 8 discusses the advantages and disadvantages of the saturate/aromatic/resin/asphaltene (SARA) chromatographic method for crude oil separation. FD and negative/positive-ion FT-ICR MS show compositional bleed between SARA fractions. Fractionation does facilitate identification of species not observed in the parent crude oil. The appendices include the description of three unpublished collaborations related to bitumen extraction and production. Appendix A discusses the effect of acidic species in Athabasca bitumen on oil sand ore processability. Bitumen recovered from "good" ore and "bad" ore are analyzed and the results suggest naphthenic acid composition does not effect processability. Appendix B discusses the effect of acid species in Athabasca bitumen on emulsion formation. A bitumen sample and the bitumen component of a water/oil emulsion are found to be similar. However, the water soluble organic acids may contribute to emulsion formation. Appendix C discusses issues related to the handling of petroleum samples prior to ESI mass spectral analysis. The results suggest minor compositional changes under certain storage conditions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,657
Score d'incertitude au seuil0,926

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,005
Tête enseignante GPT0,194
Écart entre enseignants0,190 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

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