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Record W7113512401

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

2007· article· en· W7113512401 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2007
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFourier transform ion cyclotron resonanceNaphthenic acidOil sandsMass spectrometryAsphaltAnalytical Chemistry (journal)PetroleumLight crude oilOil refineryHeteroatom
DOInot available

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.194
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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