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Record W2053175657 · doi:10.2118/09-09-12-tn

New Insights Into Oxidation Behaviours of Crude Oils

2009· article· en· W2053175657 on OpenAlexafffund
J. Li, S. A. Mehta, R.G. Moore, M.G. Ursenbach

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2009
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of CalgarySuncor Energy (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaSuncor Energy IncorporatedUniversity of Calgary
KeywordsLight crude oilChemistryAsphaltFlue gasSecondary air injectionCombustionFuel oilPetroleum engineeringChemical engineeringOrganic chemistryWaste managementMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract Systematic studies are performed to investigate oxidation behaviour of three different types of crude oils (light oil, medium oil and Athabasca bitumen) by using two thermal analysis techniques: Thermogravimetry and Pressurized Differential Scanning Calorimetry. This study is also to look at the effect of pressure on energy generation associated with oxidation reactions in different temperature ranges. It is observed that oxidation behaviours for light and medium oils are substantially different from those of Athabasca bitumen. The difference is seen in the temperature ranges where significant oxidation reactions occur. The experimental data in this work provide further evidence and addresses the difference in the oxidation behaviour of light oil and heavy oil. Introduction It is important to distinguish air injection applied to a light oil reservoir from the same process for heavy oil. Generally, the former is called air injection for light oil and the latter is termed in situ combustion. In both processes, various oxidation reactions take place(1). However, the main objective of air injection for light oil is to produce flue gas though oxidation reactions and to sweep the oil with the flue gas given that light oil is mobile under reservoir conditions(2), whereas in the heavy oil case, a thermal effect is desired for reducing the viscosity of heavy oil and to mobilize it. Moore et al. (2) reported that for both light oil and heavy oil, effective displacement requires the oxidation kinetics to be in the bond scission or combustion mode, i.e., effective displacement for both light and heavy oil needs a vigorous high temperature oxidation front to be maintained. There is some controversy about the application process for light oils. Some researchers state that light oil can be displaced without the need to generate higher temperatures. Ren et al.(3) point out that air injection in a light oil reservoir could be viewed as a conventional gasflooding process, as long as the oxygen in the injected air is removed in the oil bearing zones. Kisler and Shallcross(4), Moore et al.(2) and Ferguson(5) have addressed the different oxidation behaviours between light and heavy oils that might occur in the different temperature intervals. Because of the lack of a full understanding of light oil oxidation at reservoir conditions, people simply apply the concept of oxidation behaviour from heavy oil onto the case of light oil, which creates misleading information regarding the oxidation behaviour of light oils. Therefore, the principle objective of this study is to provide experimental information about the effect of pressure on the oxidation behaviour of crude oils and the difference between the oxidation behaviours of light oils and heavy oils. Instruments and Test Conditions Two different thermoanalyzers are used to conduct this study: Pressurized Differential Scanning Calorimeter (Q10P TA Instrument, US) and Thermogravimetry Differential Scanning Calorimeter (TG/DSC 111 Setaram, France). Pressurized Differential Scanning Calorimeter (PDSC) Experiment The test pressure is up to 7 MPa (1,000 psig) and the temperature range is from 20 to 650 °C.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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

Citations33
Published2009
Admission routes2
Has abstractyes

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