Low-Temperature Oxidation of Oils in Terms of SARA Fractions: Why Simple Reaction Models Don't Work
Bibliographic record
Abstract
Abstract The low-temperature oxidation (LTO) reactions of the SARA fractions separated from two crude oils were studied in the presence of their reservoir sands at temperatures between 130 and 230 °?C. The results indicated that the usual approach to modelling LTO-the use of a very few single-step Arrhenius-rate equations-could not be made to reflect the observed reaction kinetics. Instead, this investigation found that the following reaction characteristics were needed for accurate reaction modelling:a change in the order of reaction with respect to oxygen concentration from ? to 1 as temperature rises;the repression of a saturates oxidation reaction by other fractions; and,a prominent induction period exhibited by the saturates fraction. The compositions and yields of the ultimate LTO reaction products were measured, and these included relatively stable residues with high oxygen contents. Because the LTO reactions play an important role in enhanced oil recovery by air injection methods, the above information is valuable for the simulation and prediction of these processes. Introduction Enhanced oil recovery processes need to be predictable before they can be seriously considered for widespread field application. One of the main problems limiting the development and application of new process variations for air injection or in situ combustion is that their field performance and consequently their technical success or failure can simply not be predicted with any reliability. The most serious questions frequently hinge upon the nature of stability of the combustion/oxidation zones. Many studies have provided valuable knowledge as to the nature of the related chemical reactions, but the usefulness of proposed reaction models for numerical simulation prediction is still limited. Three main types of reaction have been found to govern air-injection EOR processes: pyrolysis/coking, low-temperature oxidation, and high-temperature oxidation (combustion). This study was concentrated on the second category of reaction: low-temperature oxidation (LTO). The free-radical nature of low-temperature oxidation of hydrocarbons has long been known. In a 1958 review, Morton and Bell(1) confirmed that LTO occurs through a free-radical mechanism in which the production of hydroperoxides is an important first step. They also mentioned the role of inhibitors, discussed catalysis by metal surfaces and metallic salts, and described why long induction periods could occur before the onset of significant oxygen consumption was observed. Initially, most studies of the chemical mechanisms conducted both before and after Morton and Bell's review used pure compounds. The results varied between compounds, and could not be used directly to describe the oxidation of complex mixtures like crude oils in a petroleum reservoir. In 1968, Bousaid and Ramey(2), while investigating high-temperature oxidations, carried out three low-temperature oxidation tests on a heavy oil between 23 and 52 ° C. They reported very low values of oxygen consumption, with rates that were correlated with an activation energy of 53,200 J/ gmol. Later, Dabbous and Fulton(3) published much more extensive results for LTO of two whole oils on crushed Berea sand over the temperature range of 121 to 246 ° C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".